| 1. | Runze Han, Craig K. Jones, Junghoon Lee, Pengwei Wu, Prasad Vagdargi, Ali Uneri, Pratick A. Helm, Mark Luciano, William S. Anderson, Jeffrey H. Siewerdsen
Deformable MR-CT image registration using an unsupervised, dual-channel network for neurosurgical guidance Journal Article In: Medical Image Analysis, vol. 75, 2022, ISSN: 1361-8415. @article{Han2021c,
title = {Deformable MR-CT image registration using an unsupervised, dual-channel network for neurosurgical guidance},
author = {Runze Han and Craig K. Jones and Junghoon Lee and Pengwei Wu and Prasad Vagdargi and Ali Uneri and Pratick A. Helm and Mark Luciano and William S. Anderson and Jeffrey H. Siewerdsen
},
url = {https://doi.org/10.1016/j.media.2021.102292},
doi = {10.1016/j.media.2021.102292},
issn = {1361-8415},
year = {2022},
date = {2022-11-13},
urldate = {2022-11-13},
journal = {Medical Image Analysis},
volume = {75},
abstract = {Purpose
The accuracy of minimally invasive, intracranial neurosurgery can be challenged by deformation of brain tissue – e.g., up to 10 mm due to egress of cerebrospinal fluid during neuroendoscopic approach. We report an unsupervised, deep learning-based registration framework to resolve such deformations between preoperative MR and intraoperative CT with fast runtime for neurosurgical guidance.
Method
The framework incorporates subnetworks for MR and CT image synthesis with a dual-channel registration subnetwork (with synthesis uncertainty providing spatially varying weights on the dual-channel loss) to estimate a diffeomorphic deformation field from both the MR and CT channels. An end-to-end training is proposed that jointly optimizes both the synthesis and registration subnetworks. The proposed framework was investigated using three datasets: (1) paired MR/CT with simulated deformations; (2) paired MR/CT with real deformations; and (3) a neurosurgery dataset with real deformation. Two state-of-the-art methods (Symmetric Normalization and VoxelMorph) were implemented as a basis of comparison, and variations in the proposed dual-channel network were investigated, including single-channel registration, fusion without uncertainty weighting, and conventional sequential training of the synthesis and registration subnetworks.
Results
The proposed method achieved: (1) Dice coefficient = 0.82±0.07 and TRE = 1.2 ± 0.6 mm on paired MR/CT with simulated deformations; (2) Dice coefficient = 0.83 ± 0.07 and TRE = 1.4 ± 0.7 mm on paired MR/CT with real deformations; and (3) Dice = 0.79 ± 0.13 and TRE = 1.6 ± 1.0 mm on the neurosurgery dataset with real deformations. The dual-channel registration with uncertainty weighting demonstrated superior performance (e.g., TRE = 1.2 ± 0.6 mm) compared to single-channel registration (TRE = 1.6 ± 1.0 mm, p < 0.05 for CT channel and TRE = 1.3 ± 0.7 mm for MR channel) and dual-channel registration without uncertainty weighting (TRE = 1.4 ± 0.8 mm, p < 0.05). End-to-end training of the synthesis and registration subnetworks also improved performance compared to the conventional sequential training strategy (TRE = 1.3 ± 0.6 mm). Registration runtime with the proposed network was ∼3 s.
Conclusion
The deformable registration framework based on dual-channel MR/CT registration with spatially varying weights and end-to-end training achieved geometric accuracy and runtime that was superior to state-of-the-art baseline methods and various ablations of the proposed network. The accuracy and runtime of the method may be compatible with the requirements of high-precision neurosurgery.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose
The accuracy of minimally invasive, intracranial neurosurgery can be challenged by deformation of brain tissue – e.g., up to 10 mm due to egress of cerebrospinal fluid during neuroendoscopic approach. We report an unsupervised, deep learning-based registration framework to resolve such deformations between preoperative MR and intraoperative CT with fast runtime for neurosurgical guidance.
Method
The framework incorporates subnetworks for MR and CT image synthesis with a dual-channel registration subnetwork (with synthesis uncertainty providing spatially varying weights on the dual-channel loss) to estimate a diffeomorphic deformation field from both the MR and CT channels. An end-to-end training is proposed that jointly optimizes both the synthesis and registration subnetworks. The proposed framework was investigated using three datasets: (1) paired MR/CT with simulated deformations; (2) paired MR/CT with real deformations; and (3) a neurosurgery dataset with real deformation. Two state-of-the-art methods (Symmetric Normalization and VoxelMorph) were implemented as a basis of comparison, and variations in the proposed dual-channel network were investigated, including single-channel registration, fusion without uncertainty weighting, and conventional sequential training of the synthesis and registration subnetworks.
Results
The proposed method achieved: (1) Dice coefficient = 0.82±0.07 and TRE = 1.2 ± 0.6 mm on paired MR/CT with simulated deformations; (2) Dice coefficient = 0.83 ± 0.07 and TRE = 1.4 ± 0.7 mm on paired MR/CT with real deformations; and (3) Dice = 0.79 ± 0.13 and TRE = 1.6 ± 1.0 mm on the neurosurgery dataset with real deformations. The dual-channel registration with uncertainty weighting demonstrated superior performance (e.g., TRE = 1.2 ± 0.6 mm) compared to single-channel registration (TRE = 1.6 ± 1.0 mm, p < 0.05 for CT channel and TRE = 1.3 ± 0.7 mm for MR channel) and dual-channel registration without uncertainty weighting (TRE = 1.4 ± 0.8 mm, p < 0.05). End-to-end training of the synthesis and registration subnetworks also improved performance compared to the conventional sequential training strategy (TRE = 1.3 ± 0.6 mm). Registration runtime with the proposed network was ∼3 s.
Conclusion
The deformable registration framework based on dual-channel MR/CT registration with spatially varying weights and end-to-end training achieved geometric accuracy and runtime that was superior to state-of-the-art baseline methods and various ablations of the proposed network. The accuracy and runtime of the method may be compatible with the requirements of high-precision neurosurgery. |
| 2. | Ali Uneri, Pengwei Wu, Craig K Jones, Prasad Vagdargi, Runze Han, Patrick A Helm, Mark G Luciano, William S Anderson, and Jeffrey H Siewerdsen Deformable 3D-2D registration for high-precision guidance and verification of neuroelectrode placement Journal Article In: Physics in Medicine & Biology, vol. 66, no. 21, 2021. @article{Uneri2021,
title = {Deformable 3D-2D registration for high-precision guidance and verification of neuroelectrode placement},
author = {Ali Uneri and Pengwei Wu and Craig K Jones and Prasad Vagdargi and Runze Han and Patrick A Helm and Mark G Luciano and William S Anderson and and Jeffrey H Siewerdsen},
url = {https://iopscience.iop.org/article/10.1088/1361-6560/ac2f89},
doi = {10.1088/1361-6560/ac2f89},
year = {2021},
date = {2021-11-01},
journal = {Physics in Medicine & Biology},
volume = {66},
number = {21},
abstract = {Purpose. Accurate neuroelectrode placement is essential to effective monitoring or stimulation of neurosurgery targets. This work presents and evaluates a method that combines deep learning and model-based deformable 3D-2D registration to guide and verify neuroelectrode placement using intraoperative imaging. Methods. The registration method consists of three stages: (1) detection of neuroelectrodes in a pair of fluoroscopy images using a deep learning approach; (2) determination of correspondence and initial 3D localization among neuroelectrode detections in the two projection images; and (3) deformable 3D-2D registration of neuroelectrodes according to a physical device model. The method was evaluated in phantom, cadaver, and clinical studies in terms of (a) the accuracy of neuroelectrode registration and (b) the quality of metal artifact reduction (MAR) in cone-beam CT (CBCT) in which the deformably registered neuroelectrode models are taken as input to the MAR. Results. The combined deep learning and model-based deformable 3D-2D registration approach achieved 0.2 ± 0.1 mm accuracy in cadaver studies and 0.6 ± 0.3 mm accuracy in clinical studies. The detection network and 3D correspondence provided initialization of 3D-2D registration within 2 mm, which facilitated end-to-end registration runtime within 10 s. Metal artifacts, quantified as the standard deviation in voxel values in tissue adjacent to neuroelectrodes, were reduced by 72% in phantom studies and by 60% in first clinical studies. Conclusions. The method combines the speed and generalizability of deep learning (for initialization) with the precision and reliability of physical model-based registration to achieve accurate deformable 3D-2D registration and MAR in functional neurosurgery. Accurate 3D-2D guidance from fluoroscopy could overcome limitations associated with deformation in conventional navigation, and improved MAR could improve CBCT verification of neuroelectrode placement.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose. Accurate neuroelectrode placement is essential to effective monitoring or stimulation of neurosurgery targets. This work presents and evaluates a method that combines deep learning and model-based deformable 3D-2D registration to guide and verify neuroelectrode placement using intraoperative imaging. Methods. The registration method consists of three stages: (1) detection of neuroelectrodes in a pair of fluoroscopy images using a deep learning approach; (2) determination of correspondence and initial 3D localization among neuroelectrode detections in the two projection images; and (3) deformable 3D-2D registration of neuroelectrodes according to a physical device model. The method was evaluated in phantom, cadaver, and clinical studies in terms of (a) the accuracy of neuroelectrode registration and (b) the quality of metal artifact reduction (MAR) in cone-beam CT (CBCT) in which the deformably registered neuroelectrode models are taken as input to the MAR. Results. The combined deep learning and model-based deformable 3D-2D registration approach achieved 0.2 ± 0.1 mm accuracy in cadaver studies and 0.6 ± 0.3 mm accuracy in clinical studies. The detection network and 3D correspondence provided initialization of 3D-2D registration within 2 mm, which facilitated end-to-end registration runtime within 10 s. Metal artifacts, quantified as the standard deviation in voxel values in tissue adjacent to neuroelectrodes, were reduced by 72% in phantom studies and by 60% in first clinical studies. Conclusions. The method combines the speed and generalizability of deep learning (for initialization) with the precision and reliability of physical model-based registration to achieve accurate deformable 3D-2D registration and MAR in functional neurosurgery. Accurate 3D-2D guidance from fluoroscopy could overcome limitations associated with deformation in conventional navigation, and improved MAR could improve CBCT verification of neuroelectrode placement. |
| 3. | Chumin Zhao, Magdalena Herbst, Thomas Weber, Christoph Luckner, Sebastian Vogt, Ludwig Ritschl, Steffen Kappler, Wojciech Zbijewski, Jeffrey H. Siewerdsen Slot-scan dual-energy bone densitometry using motorized X-ray systems Journal Article In: Med Phys, vol. 48, iss. 11, pp. 6673– 6695, 2021. @article{Zhao2021,
title = {Slot-scan dual-energy bone densitometry using motorized X-ray systems},
author = {Chumin Zhao and Magdalena Herbst and Thomas Weber and Christoph Luckner and Sebastian Vogt and Ludwig Ritschl and Steffen Kappler and Wojciech Zbijewski and Jeffrey H. Siewerdsen},
url = {https://doi.org/10.1002/mp.15272},
doi = {10.1002/mp.15272},
year = {2021},
date = {2021-10-10},
urldate = {2021-10-10},
journal = {Med Phys},
volume = {48},
issue = {11},
pages = {6673– 6695},
abstract = {Purpose
We investigate the feasibility of slot-scan dual-energy (DE) bone densitometry on motorized radiographic equipment. This approach will enable fast quantitative measurements of areal bone mineral density (aBMD) for opportunistic evaluation of osteoporosis.
Methods
We investigated DE slot-scan protocols to obtain aBMD measurements at the lumbar spine (L-spine) and hip using a motorized x-ray platform capable of synchronized translation of the x-ray source and flat-panel detector (FPD). The slot dimension was 5 × 20 cm2. The DE slot views were processed as follows: (1) convolution kernel-based scatter correction, (2) unfiltered backprojection to tile the slots into long-length radiographs, and (3) projection-domain DE decomposition, consisting of an initial adipose–water decomposition in a bone-free region followed by water–CaHA decomposition with adjustment for adipose content. The accuracy and reproducibility of slot-scan aBMD measurements were investigated using a high-fidelity simulator of a robotic x-ray system (Siemens Multitom Rax) in a total of 48 body phantom realizations: four average bone density settings (cortical bone mass fraction: 10–40%), four body sizes (waist circumference, WC = 70–106 cm), and three lateral shifts of the body within the slot field of view (FOV) (centered and ±1 cm off-center). Experimental validations included: (1) x-ray test-bench feasibility study of adipose–water decomposition and (2) initial demonstration of slot-scan DE bone densitometry on the robotic x-ray system using the European Spine Phantom (ESP) with added attenuation (polymethyl methacrylate [PMMA] slabs) ranging 2 to 6 cm thick.
Results
For the L-spine, the mean aBMD error across all WC settings ranged from 0.08 g/cm2 for phantoms with average cortical bone fraction wcortical = 10% to ∼0.01 g/cm2 for phantoms with wcortical = 40%. The L-spine aBMD measurements were fairly robust to changes in body size and positioning, e.g., coefficient of variation (CV) for L1 with wcortical = 30% was ∼0.034 for various WC and ∼0.02 for an obese patient (WC = 106 cm) changing lateral shift. For the hip, the mean aBMD error across all phantom configurations was about 0.07 g/cm2 for a centered patient. The reproducibility of hip aBMD was slightly worse than in the L-spine (e.g., in the femoral neck, the CV with respect to changing WC was ∼0.13 for phantom realizations with wcortical = 30%) due to more challenging scatter estimation in the presence of an air–tissue interface within the slot FOV. The aBMD of the hip was therefore sensitive to lateral positioning of the patient, especially for obese patients: e.g., the CV with respect to patient lateral shift for femoral neck with WC = 106 cm and wcortical = 30% was 0.14. Empirical evaluations confirmed substantial reduction in aBMD errors with the proposed adipose estimation procedure and demonstrated robust aBMD measurements on the robotic x-ray system, with aBMD errors of ∼0.1 g/cm2 across all three simulated ESP vertebrae and all added PMMA attenuator settings.
Conclusions
We demonstrated that accurate aBMD measurements can be obtained on a motorized FPD-based x-ray system using DE slot-scans with kernel-based scatter correction, backprojection-based slot view tiling, and DE decomposition with adipose correction.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose
We investigate the feasibility of slot-scan dual-energy (DE) bone densitometry on motorized radiographic equipment. This approach will enable fast quantitative measurements of areal bone mineral density (aBMD) for opportunistic evaluation of osteoporosis.
Methods
We investigated DE slot-scan protocols to obtain aBMD measurements at the lumbar spine (L-spine) and hip using a motorized x-ray platform capable of synchronized translation of the x-ray source and flat-panel detector (FPD). The slot dimension was 5 × 20 cm2. The DE slot views were processed as follows: (1) convolution kernel-based scatter correction, (2) unfiltered backprojection to tile the slots into long-length radiographs, and (3) projection-domain DE decomposition, consisting of an initial adipose–water decomposition in a bone-free region followed by water–CaHA decomposition with adjustment for adipose content. The accuracy and reproducibility of slot-scan aBMD measurements were investigated using a high-fidelity simulator of a robotic x-ray system (Siemens Multitom Rax) in a total of 48 body phantom realizations: four average bone density settings (cortical bone mass fraction: 10–40%), four body sizes (waist circumference, WC = 70–106 cm), and three lateral shifts of the body within the slot field of view (FOV) (centered and ±1 cm off-center). Experimental validations included: (1) x-ray test-bench feasibility study of adipose–water decomposition and (2) initial demonstration of slot-scan DE bone densitometry on the robotic x-ray system using the European Spine Phantom (ESP) with added attenuation (polymethyl methacrylate [PMMA] slabs) ranging 2 to 6 cm thick.
Results
For the L-spine, the mean aBMD error across all WC settings ranged from 0.08 g/cm2 for phantoms with average cortical bone fraction wcortical = 10% to ∼0.01 g/cm2 for phantoms with wcortical = 40%. The L-spine aBMD measurements were fairly robust to changes in body size and positioning, e.g., coefficient of variation (CV) for L1 with wcortical = 30% was ∼0.034 for various WC and ∼0.02 for an obese patient (WC = 106 cm) changing lateral shift. For the hip, the mean aBMD error across all phantom configurations was about 0.07 g/cm2 for a centered patient. The reproducibility of hip aBMD was slightly worse than in the L-spine (e.g., in the femoral neck, the CV with respect to changing WC was ∼0.13 for phantom realizations with wcortical = 30%) due to more challenging scatter estimation in the presence of an air–tissue interface within the slot FOV. The aBMD of the hip was therefore sensitive to lateral positioning of the patient, especially for obese patients: e.g., the CV with respect to patient lateral shift for femoral neck with WC = 106 cm and wcortical = 30% was 0.14. Empirical evaluations confirmed substantial reduction in aBMD errors with the proposed adipose estimation procedure and demonstrated robust aBMD measurements on the robotic x-ray system, with aBMD errors of ∼0.1 g/cm2 across all three simulated ESP vertebrae and all added PMMA attenuator settings.
Conclusions
We demonstrated that accurate aBMD measurements can be obtained on a motorized FPD-based x-ray system using DE slot-scans with kernel-based scatter correction, backprojection-based slot view tiling, and DE decomposition with adipose correction.
|
| 4. | Xiaoxuan Zhang, Wojciech Zbijewski, Yixuan Huang, Ali Uneri, Craig K. Jones, Sheng-Fu L. Lo, Timothy F. Witham, Mark Luciano, William Stanley Anderson, Patrick A. Helm, Jeffrey H. Siewerdsen Intraoperative cone-beam and slot-beam CT: 3D image quality and dose with a slot collimator on the O-arm imaging system Journal Article In: Med Phys, vol. 48, iss. 11, pp. 6800– 6809, 2021. @article{Zhang2021b,
title = {Intraoperative cone-beam and slot-beam CT: 3D image quality and dose with a slot collimator on the O-arm imaging system},
author = {Xiaoxuan Zhang and Wojciech Zbijewski and Yixuan Huang and Ali Uneri, Craig K. Jones and Sheng-Fu L. Lo and Timothy F. Witham and Mark Luciano, William Stanley Anderson and Patrick A. Helm and Jeffrey H. Siewerdsen},
url = {https://doi.org/10.1002/mp.15221},
doi = {10.1002/mp.15221},
year = {2021},
date = {2021-09-14},
journal = { Med Phys},
volume = {48},
issue = {11},
pages = {6800– 6809},
abstract = {
Purpose
To characterize the 3D imaging performance and radiation dose for a prototype slot-beam configuration on an intraoperative O-arm™ Surgical Imaging System (Medtronic Inc., Littleton, MA) and identify potential improvements in soft-tissue image quality for surgical interventions.
Methods
A slot collimator was integrated with the O-arm™ system for slot-beam axial CT. The collimator can be automatically actuated to provide 1.2° slot-beam longitudinal collimation. Cone-beam and slot-beam configurations were investigated with and without an antiscatter grid (12:1 grid ratio, 60 lines/cm). Dose, scatter, image noise, and soft-tissue contrast resolution were evaluated in quantitative phantoms for head and body configurations over a range of exposure levels (beam energy and mAs), with reconstruction performed via filtered-backprojection. Qualitative imaging performance across various anatomical sites and imaging tasks was assessed with anthropomorphic head, abdomen, and pelvis phantoms.
Results
The dose for a slot-beam scan varied from 0.02–0.06 mGy/mAs for head protocols to 0.01–0.03 mGy/mAs for body protocols, yielding dose reduction by ∼1/5 to 1/3 compared to cone-beam, owing to beam collimation and reduced x-ray scatter. The slot-beam provided an ∼6–7× reduction in scatter-to-primary ratio (SPR) compared to the cone-beam, yielding SPR ∼20–80% for head and body without the grid and ∼7–30% with the grid. Compared to cone-beam scans at equivalent dose, slot-beam images exhibited an ∼2.5× increase in soft-tissue contrast-to-noise ratio (CNR) for both grid and gridless configurations. For slot-beam scans, a further ∼10–30% improvement in CNR was achieved when the grid was removed. Slot-beam imaging could benefit certain interventional scenarios in which improved visualization of soft tissues is required within a fairly narrow longitudinal region of interest (urn:x-wiley:00942405:media:mp15221:mp15221-math-00017 mm in urn:x-wiley:00942405:media:mp15221:mp15221-math-0002)––for example, checking the completeness of tumor resection, preservation of adjacent anatomy, or detection of complications (e.g., hemorrhage). While preserving existing capabilities for fluoroscopy and cone-beam CT, slot-beam scanning could enhance the utility of intraoperative imaging and provide a useful mode for safety and validation checks in image-guided surgery.
Conclusions
The 3D imaging performance and dose of a prototype slot-beam CT configuration on the O-arm™ system was investigated. Substantial improvements in soft-tissue image quality and reduction in radiation dose are evident with the slot-beam configuration due to reduced x-ray scatter.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose
To characterize the 3D imaging performance and radiation dose for a prototype slot-beam configuration on an intraoperative O-arm™ Surgical Imaging System (Medtronic Inc., Littleton, MA) and identify potential improvements in soft-tissue image quality for surgical interventions.
Methods
A slot collimator was integrated with the O-arm™ system for slot-beam axial CT. The collimator can be automatically actuated to provide 1.2° slot-beam longitudinal collimation. Cone-beam and slot-beam configurations were investigated with and without an antiscatter grid (12:1 grid ratio, 60 lines/cm). Dose, scatter, image noise, and soft-tissue contrast resolution were evaluated in quantitative phantoms for head and body configurations over a range of exposure levels (beam energy and mAs), with reconstruction performed via filtered-backprojection. Qualitative imaging performance across various anatomical sites and imaging tasks was assessed with anthropomorphic head, abdomen, and pelvis phantoms.
Results
The dose for a slot-beam scan varied from 0.02–0.06 mGy/mAs for head protocols to 0.01–0.03 mGy/mAs for body protocols, yielding dose reduction by ∼1/5 to 1/3 compared to cone-beam, owing to beam collimation and reduced x-ray scatter. The slot-beam provided an ∼6–7× reduction in scatter-to-primary ratio (SPR) compared to the cone-beam, yielding SPR ∼20–80% for head and body without the grid and ∼7–30% with the grid. Compared to cone-beam scans at equivalent dose, slot-beam images exhibited an ∼2.5× increase in soft-tissue contrast-to-noise ratio (CNR) for both grid and gridless configurations. For slot-beam scans, a further ∼10–30% improvement in CNR was achieved when the grid was removed. Slot-beam imaging could benefit certain interventional scenarios in which improved visualization of soft tissues is required within a fairly narrow longitudinal region of interest (urn:x-wiley:00942405:media:mp15221:mp15221-math-00017 mm in urn:x-wiley:00942405:media:mp15221:mp15221-math-0002)––for example, checking the completeness of tumor resection, preservation of adjacent anatomy, or detection of complications (e.g., hemorrhage). While preserving existing capabilities for fluoroscopy and cone-beam CT, slot-beam scanning could enhance the utility of intraoperative imaging and provide a useful mode for safety and validation checks in image-guided surgery.
Conclusions
The 3D imaging performance and dose of a prototype slot-beam CT configuration on the O-arm™ system was investigated. Substantial improvements in soft-tissue image quality and reduction in radiation dose are evident with the slot-beam configuration due to reduced x-ray scatter.
|
| 5. | Rohan C. Vijayan, Runze Han, Pengwei Wu, Niral M. Sheth, Michael D. Ketcha, Prasad Vagdargi, Sebastian Vogt, Gerhard Kleinszig, Greg M. Osgood, Ali Uneri, Jeffrey H. Siewerdsen Development of a fluoroscopically guided robotic assistant for instrument placement in pelvic trauma surgery Journal Article In: Journal of Medical Imaging, vol. 8, no. 3, 2021. @article{Vijayan2021b,
title = {Development of a fluoroscopically guided robotic assistant for instrument placement in pelvic trauma surgery},
author = {Rohan C. Vijayan and Runze Han and Pengwei Wu and Niral M. Sheth and Michael D. Ketcha and Prasad Vagdargi and Sebastian Vogt and Gerhard Kleinszig and Greg M. Osgood and Ali Uneri and Jeffrey H. Siewerdsen},
url = {https://doi.org/10.1117/1.JMI.8.3.035001},
doi = {10.1117/1.JMI.8.3.035001},
year = {2021},
date = {2021-06-09},
urldate = {2021-06-09},
journal = {Journal of Medical Imaging},
volume = {8},
number = {3},
abstract = { Purpose: A method for fluoroscopic guidance of a robotic assistant is presented for instrument placement in pelvic trauma surgery. The solution uses fluoroscopic images acquired in standard clinical workflow and helps avoid repeat fluoroscopy commonly performed during implant guidance.
Approach: Images acquired from a mobile C-arm are used to perform 3D–2D registration of both the patient (via patient CT) and the robot (via CAD model of a surgical instrument attached to its end effector, e.g; a drill guide), guiding the robot to target trajectories defined in the patient CT. The proposed approach avoids C-arm gantry motion, instead manipulating the robot to acquire disparate views of the instrument. Phantom and cadaver studies were performed to determine operating parameters and assess the accuracy of the proposed approach in aligning a standard drill guide instrument.
Results: The proposed approach achieved average drill guide tip placement accuracy of 1.57 ± 0.47 mm and angular alignment of 0.35 ± 0.32 deg in phantom studies. The errors remained within 2 mm and 1 deg in cadaver experiments, comparable to the margins of errors provided by surgical trackers (but operating without the need for external tracking).
Conclusions: By operating at a fixed fluoroscopic perspective and eliminating the need for encoded C-arm gantry movement, the proposed approach simplifies and expedites the registration of image-guided robotic assistants and can be used with simple, non-calibrated, non-encoded, and non-isocentric C-arm systems to accurately guide a robotic device in a manner that is compatible with the surgical workflow.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose: A method for fluoroscopic guidance of a robotic assistant is presented for instrument placement in pelvic trauma surgery. The solution uses fluoroscopic images acquired in standard clinical workflow and helps avoid repeat fluoroscopy commonly performed during implant guidance.
Approach: Images acquired from a mobile C-arm are used to perform 3D–2D registration of both the patient (via patient CT) and the robot (via CAD model of a surgical instrument attached to its end effector, e.g; a drill guide), guiding the robot to target trajectories defined in the patient CT. The proposed approach avoids C-arm gantry motion, instead manipulating the robot to acquire disparate views of the instrument. Phantom and cadaver studies were performed to determine operating parameters and assess the accuracy of the proposed approach in aligning a standard drill guide instrument.
Results: The proposed approach achieved average drill guide tip placement accuracy of 1.57 ± 0.47 mm and angular alignment of 0.35 ± 0.32 deg in phantom studies. The errors remained within 2 mm and 1 deg in cadaver experiments, comparable to the margins of errors provided by surgical trackers (but operating without the need for external tracking).
Conclusions: By operating at a fixed fluoroscopic perspective and eliminating the need for encoded C-arm gantry movement, the proposed approach simplifies and expedites the registration of image-guided robotic assistants and can be used with simple, non-calibrated, non-encoded, and non-isocentric C-arm systems to accurately guide a robotic device in a manner that is compatible with the surgical workflow. |
| 6. | Yixuan Huang, Ali Uneri, Craig K Jones, Xiaoxuan Zhang, Michael Daniel Ketcha, Nafi Aygun, Patrick A Helm, Jeffrey H Siewerdsen 3D vertebrae labeling in spine CT: an accurate, memory-efficient (Ortho2D) framework Journal Article In: Institute of Physics and Engineering in Medicine, 2021. @article{Huang2021,
title = {3D vertebrae labeling in spine CT: an accurate, memory-efficient (Ortho2D) framework},
author = {Yixuan Huang and Ali Uneri and Craig K Jones and Xiaoxuan Zhang and Michael Daniel Ketcha and Nafi Aygun and Patrick A Helm and Jeffrey H Siewerdsen},
url = {https://doi.org/10.1088/1361-6560/ac07c7},
doi = {10.1088/1361-6560/ac07c7},
year = {2021},
date = {2021-06-03},
journal = { Institute of Physics and Engineering in Medicine},
abstract = {Purpose: Accurate localization and labeling of vertebrae in computed tomography (CT) is an important step toward more quantitative, automated diagnostic analysis and surgical planning. In this paper, we present a framework (called Ortho2D) for vertebral labeling in CT in a manner that is accurate and memory-efficient. Methods: Ortho2D uses two independent Faster R-CNN networks to detect and classify vertebrae in orthogonal (sagittal and coronal) CT slices. The 2D detections are clustered in 3D to localize vertebrae centroids in the volumetric CT and classify the region (cervical, thoracic, lumbar, or sacral) and vertebral level. A post-process sorting method incorporates the confidence in network output to refine classifications and reduce outliers. Ortho2D was evaluated on a publicly available dataset containing 302 normal and pathological spine CT images with and without surgical instrumentation. Labeling accuracy and memory requirements were assessed in comparison to other recently reported methods. The memory efficiency of Ortho2D permitted extension to high-resolution CT to investigate the potential for further boosts to labeling performance. Results: Ortho2D achieved overall vertebrae detection accuracy of 97.1%, region identification accuracy of 94.3%, and individual vertebral level identification accuracy of 91.0%. The framework achieved 95.8% and 83.6% level identification accuracy in images without and with surgical instrumentation, respectively. Ortho2D met or exceeded the performance of previously reported 2D and 3D labeling methods and reduced memory consumption by a factor of ~50 (at 1 mm voxel size) compared to a 3D U-Net, allowing extension to higher resolution datasets than normally afforded. The accuracy of level identification increased from 80.1% (for standard / low resolution CT) to 95.1% (for high-resolution CT). Conclusions: The Ortho2D method achieved vertebrae labeling performance that is comparable to other recently reported methods with significant reduction in memory consumption, permitting further performance boosts via application to high-resolution CT.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose: Accurate localization and labeling of vertebrae in computed tomography (CT) is an important step toward more quantitative, automated diagnostic analysis and surgical planning. In this paper, we present a framework (called Ortho2D) for vertebral labeling in CT in a manner that is accurate and memory-efficient. Methods: Ortho2D uses two independent Faster R-CNN networks to detect and classify vertebrae in orthogonal (sagittal and coronal) CT slices. The 2D detections are clustered in 3D to localize vertebrae centroids in the volumetric CT and classify the region (cervical, thoracic, lumbar, or sacral) and vertebral level. A post-process sorting method incorporates the confidence in network output to refine classifications and reduce outliers. Ortho2D was evaluated on a publicly available dataset containing 302 normal and pathological spine CT images with and without surgical instrumentation. Labeling accuracy and memory requirements were assessed in comparison to other recently reported methods. The memory efficiency of Ortho2D permitted extension to high-resolution CT to investigate the potential for further boosts to labeling performance. Results: Ortho2D achieved overall vertebrae detection accuracy of 97.1%, region identification accuracy of 94.3%, and individual vertebral level identification accuracy of 91.0%. The framework achieved 95.8% and 83.6% level identification accuracy in images without and with surgical instrumentation, respectively. Ortho2D met or exceeded the performance of previously reported 2D and 3D labeling methods and reduced memory consumption by a factor of ~50 (at 1 mm voxel size) compared to a 3D U-Net, allowing extension to higher resolution datasets than normally afforded. The accuracy of level identification increased from 80.1% (for standard / low resolution CT) to 95.1% (for high-resolution CT). Conclusions: The Ortho2D method achieved vertebrae labeling performance that is comparable to other recently reported methods with significant reduction in memory consumption, permitting further performance boosts via application to high-resolution CT. |
| 7. | Matthew Hernandez, Pengwei Wu, Mahadevappa Mahesh, John M. Boone, Jeffrey H. Siewerdsen Location and direction dependence in the 3D MTF for a high-resolution CT system Journal Article In: Med. Phys, vol. 48, 2021, ISSN: 2760-2771. @article{Hernandex2021,
title = {Location and direction dependence in the 3D MTF for a high-resolution CT system},
author = {Matthew Hernandez and Pengwei Wu and Mahadevappa Mahesh and John M. Boone and Jeffrey H. Siewerdsen},
url = { https://doi.org/10.1002/mp.14789},
doi = {10.1002/mp.14789},
issn = {2760-2771},
year = {2021},
date = {2021-03-20},
journal = {Med. Phys},
volume = {48},
abstract = {
Purpose
The purpose of this study was to quantify location and direction-dependent variations in the 3D modulation transfer function (MTF) of a high-resolution CT scanner with selectable focal spot sizes and resolution modes.
Methods
The Aquilion Precision CT scanner (Canon Medical Systems) has selectable 0.25 mm or 0.5 mm detectors (by binning) in both the axial (x-y) and detector array width (z) directions. For the x-y and z orientations, detectors are configured (x–y) = 0.5 mm/(z) = 0.5 mm for normal resolution (NR), 0.25/0.5 mm for high resolution (HR), and 0.25/0.25 mm for super high resolution (SHR). Six focal spots (FS1-FS6) range in size from 0.4 (x-y) × 0.5 mm (z) for FS1 to 1.6 × 1.4 mm for FS6. Phantoms fabricated from spherical objects were positioned at radial distances of 0, 4.0, 7.5, 11.0, 14.5, and 18.5 cm. Axial and helical acquisitions were utilized and reconstructed using filtered back projection with the FC18 “Body,” FC30 “Bone,” and FC81 “Bone Sharp” kernels. The reconstructions were used to measure a 1D slice of the 3D MTF by oversampling the 3D ESF in the axial plane [MTF(fr); φ = 0°)], 45° out of the axial plane [MTF(fr); φ = 45°)], in the longitudinal direction [MTF(fr); φ = 80°)], and along the radial and azimuthal directions within the axial plane.
Results
The MTF(fr); φ = 45°) drops to 10% (f10) at 1.20, 1.45, and 2.06 mm−1 for NR, HR, and SHR, respectively, for a helical acquisition with FS1, FC30, and r = 4 cm from the isocenter. The MTF(fr); φ = 45°) includes contributions of both the axial-plane MTF (f10 = 1.10, 2.04, and 2.01 mm−1) and the longitudinal MTF (f10 = 1.17, 1.18, and 1.82 mm−1) for the NR, HR, and SHR modes, respectively. For SHR, the axial scan mode showed a 15–25% improvement over helical mode in the longitudinal resolution. Helical pitch, ranging from 0.569 to 1.381, did not appreciably affect the 3D resolution (<2%). The radial MTFs across the axial field of view (FOV) showed dependencies on the focal spot length in z; for example, for SHR with FS2 (0.6 × 0.6 mm), f10 at r = 11 cm was within 17% of the value at r = 4 cm, but for SHR with FS3 (0.6 × 1.3), the reduction in f10 was 46% from 4 to 11 cm from the isocenter. The azimuthal MTF also decreased as r increased but less so for longer gantry rotation times and smaller focal spot dimensions in the axial plane. The longitudinal MTF was minimally affected (<11%) by position in the FOV and was principally affected by the focal spot length in the z-dimension.
Conclusions
The 3D MTF was measured throughout the FOV of a high-resolution CT scanner, quantifying the advantages of different resolution modes and focal spot sizes on the axial-plane and longitudinal MTF. Reconstruction kernels were shown to impact axial-plane resolution, imparting non-isotropic 3D resolution characteristics. Focal spot size (both in x-y and in z) and gantry rotation time play important roles in preserving the high-resolution characteristics throughout the field of view for this new high-resolution CT scanner technology.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose
The purpose of this study was to quantify location and direction-dependent variations in the 3D modulation transfer function (MTF) of a high-resolution CT scanner with selectable focal spot sizes and resolution modes.
Methods
The Aquilion Precision CT scanner (Canon Medical Systems) has selectable 0.25 mm or 0.5 mm detectors (by binning) in both the axial (x-y) and detector array width (z) directions. For the x-y and z orientations, detectors are configured (x–y) = 0.5 mm/(z) = 0.5 mm for normal resolution (NR), 0.25/0.5 mm for high resolution (HR), and 0.25/0.25 mm for super high resolution (SHR). Six focal spots (FS1-FS6) range in size from 0.4 (x-y) × 0.5 mm (z) for FS1 to 1.6 × 1.4 mm for FS6. Phantoms fabricated from spherical objects were positioned at radial distances of 0, 4.0, 7.5, 11.0, 14.5, and 18.5 cm. Axial and helical acquisitions were utilized and reconstructed using filtered back projection with the FC18 “Body,” FC30 “Bone,” and FC81 “Bone Sharp” kernels. The reconstructions were used to measure a 1D slice of the 3D MTF by oversampling the 3D ESF in the axial plane [MTF(fr); φ = 0°)], 45° out of the axial plane [MTF(fr); φ = 45°)], in the longitudinal direction [MTF(fr); φ = 80°)], and along the radial and azimuthal directions within the axial plane.
Results
The MTF(fr); φ = 45°) drops to 10% (f10) at 1.20, 1.45, and 2.06 mm−1 for NR, HR, and SHR, respectively, for a helical acquisition with FS1, FC30, and r = 4 cm from the isocenter. The MTF(fr); φ = 45°) includes contributions of both the axial-plane MTF (f10 = 1.10, 2.04, and 2.01 mm−1) and the longitudinal MTF (f10 = 1.17, 1.18, and 1.82 mm−1) for the NR, HR, and SHR modes, respectively. For SHR, the axial scan mode showed a 15–25% improvement over helical mode in the longitudinal resolution. Helical pitch, ranging from 0.569 to 1.381, did not appreciably affect the 3D resolution (<2%). The radial MTFs across the axial field of view (FOV) showed dependencies on the focal spot length in z; for example, for SHR with FS2 (0.6 × 0.6 mm), f10 at r = 11 cm was within 17% of the value at r = 4 cm, but for SHR with FS3 (0.6 × 1.3), the reduction in f10 was 46% from 4 to 11 cm from the isocenter. The azimuthal MTF also decreased as r increased but less so for longer gantry rotation times and smaller focal spot dimensions in the axial plane. The longitudinal MTF was minimally affected (<11%) by position in the FOV and was principally affected by the focal spot length in the z-dimension.
Conclusions
The 3D MTF was measured throughout the FOV of a high-resolution CT scanner, quantifying the advantages of different resolution modes and focal spot sizes on the axial-plane and longitudinal MTF. Reconstruction kernels were shown to impact axial-plane resolution, imparting non-isotropic 3D resolution characteristics. Focal spot size (both in x-y and in z) and gantry rotation time play important roles in preserving the high-resolution characteristics throughout the field of view for this new high-resolution CT scanner technology.
|
| 8. | Pengwei Wu, John M. Boone, Andrew M. Hernandez, Mahadevappa Mahesh, Jeffrey H. Siewerdsen Theory, method, and test tools for determination of 3D MTF characteristics in cone-beam CT Journal Article In: Med. Phys, vol. 48, no. 2772-2789, 2021. @article{Wu2021,
title = {Theory, method, and test tools for determination of 3D MTF characteristics in cone-beam CT},
author = {Pengwei Wu and John M. Boone and Andrew M. Hernandez and Mahadevappa Mahesh and Jeffrey H. Siewerdsen},
url = {https://doi.org/10.1002/mp.14820},
doi = {10.1002/mp.14820},
year = {2021},
date = {2021-03-03},
journal = {Med. Phys},
volume = {48},
number = {2772-2789},
abstract = {
Purpose
The modulation transfer function (MTF) is widely used as an objective metric of spatial resolution of medical imaging systems. Despite advances in capability for three-dimensional (3D) isotropic spatial resolution in computed tomography (CT) and cone-beam CT (CBCT), MTF evaluation for such systems is typically reported only in the axial plane, and practical methodology for assessment of fully 3D spatial resolution characteristics is lacking. This work reviews fundamental theoretical relationships of two-dimensional (2D) and 3D spread functions and reports practical methods and test tools for analysis of 3D MTF in CBCT.
Methods
Fundamental aspects of 2D and 3D MTF measurement are reviewed within a common notational framework, and three MTF test tools with analysis code are reported and made available online (https://istar.jhu.edu/downloads/): (a) a multi-wire tool for measurement of the axial plane MTF [denoted as urn:x-wiley:00942405:media:mp14820:mp14820-math-0001, where urn:x-wiley:00942405:media:mp14820:mp14820-math-0002is the measurement angle out of the axial plane] as a function of position in the axial plane; (b) a wedge tool for measurement of the MTF in any direction in the 3D Fourier domain [e.g., urn:x-wiley:00942405:media:mp14820:mp14820-math-0003 = 45°, denoted as urn:x-wiley:00942405:media:mp14820:mp14820-math-0004]; and (c) a sphere tool for measurement of the MTF in any or all directions in the 3D Fourier domain. Experiments were performed on a mobile C-arm with CBCT capability, showing that urn:x-wiley:00942405:media:mp14820:mp14820-math-0005 yields an informative one-dimensional (1D) representation of the overall 3D spatial resolution characteristics, capturing important characteristics of the 3D MTF that might be missed in conventional analysis. The effects of anisotropic filters and detector readout mode were investigated, and the extent to which a system can be said to provide “isotropic” resolution was evaluated by quantitative comparison of MTF at various urn:x-wiley:00942405:media:mp14820:mp14820-math-0006.
Results
All three test tools provided consistent measurement of urn:x-wiley:00942405:media:mp14820:mp14820-math-0007, and the wedge and sphere tools demonstrated how measurement of the MTF in directions outside the axial plane (urn:x-wiley:00942405:media:mp14820:mp14820-math-0008) can reveal spatial resolution characteristics to which conventional axial MTF measurement is blind. The wedge tool was shown to reduce statistical measurement error compared to the sphere tool due to improved sampling, and the sphere tool was shown to provide a basis for measurement of the MTF in any or all directions (outside the null cone) from a single scan. The C-arm system exhibited non-isotropic spatial resolution with conventional non-isotropic 1D apodization filters (i.e., frequency cutoff filters) — which is common in CBCT — and implementation of isotropic 2D apodization yielded quantifiably isotropic MTF. Asymmetric pixel binning modes were similarly shown to impart non-isotropic effects on the 3D MTF, and the overall 3D MTF characteristics were evident in each case with a single, 1D measurement of the 1D.
Conclusion
Three test tools and corresponding MTF analysis methods were presented within a consistent framework for analysis of 3D spatial resolution characteristics in a manner amenable to routine, practical measurements. Experiments on a CBCT C-arm validated many intuitive aspects of 3D spatial resolution and quantified the extent to which a CBCT system may be considered to have isotropic resolution. Measurement of urn:x-wiley:00942405:media:mp14820:mp14820-math-0010) provided a practical 1D measure of the underlying 3D MTF characteristics and is extensible to other CT or CBCT systems offering high, isotropic spatial resolution.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose
The modulation transfer function (MTF) is widely used as an objective metric of spatial resolution of medical imaging systems. Despite advances in capability for three-dimensional (3D) isotropic spatial resolution in computed tomography (CT) and cone-beam CT (CBCT), MTF evaluation for such systems is typically reported only in the axial plane, and practical methodology for assessment of fully 3D spatial resolution characteristics is lacking. This work reviews fundamental theoretical relationships of two-dimensional (2D) and 3D spread functions and reports practical methods and test tools for analysis of 3D MTF in CBCT.
Methods
Fundamental aspects of 2D and 3D MTF measurement are reviewed within a common notational framework, and three MTF test tools with analysis code are reported and made available online (https://istar.jhu.edu/downloads/): (a) a multi-wire tool for measurement of the axial plane MTF [denoted as urn:x-wiley:00942405:media:mp14820:mp14820-math-0001, where urn:x-wiley:00942405:media:mp14820:mp14820-math-0002is the measurement angle out of the axial plane] as a function of position in the axial plane; (b) a wedge tool for measurement of the MTF in any direction in the 3D Fourier domain [e.g., urn:x-wiley:00942405:media:mp14820:mp14820-math-0003 = 45°, denoted as urn:x-wiley:00942405:media:mp14820:mp14820-math-0004]; and (c) a sphere tool for measurement of the MTF in any or all directions in the 3D Fourier domain. Experiments were performed on a mobile C-arm with CBCT capability, showing that urn:x-wiley:00942405:media:mp14820:mp14820-math-0005 yields an informative one-dimensional (1D) representation of the overall 3D spatial resolution characteristics, capturing important characteristics of the 3D MTF that might be missed in conventional analysis. The effects of anisotropic filters and detector readout mode were investigated, and the extent to which a system can be said to provide “isotropic” resolution was evaluated by quantitative comparison of MTF at various urn:x-wiley:00942405:media:mp14820:mp14820-math-0006.
Results
All three test tools provided consistent measurement of urn:x-wiley:00942405:media:mp14820:mp14820-math-0007, and the wedge and sphere tools demonstrated how measurement of the MTF in directions outside the axial plane (urn:x-wiley:00942405:media:mp14820:mp14820-math-0008) can reveal spatial resolution characteristics to which conventional axial MTF measurement is blind. The wedge tool was shown to reduce statistical measurement error compared to the sphere tool due to improved sampling, and the sphere tool was shown to provide a basis for measurement of the MTF in any or all directions (outside the null cone) from a single scan. The C-arm system exhibited non-isotropic spatial resolution with conventional non-isotropic 1D apodization filters (i.e., frequency cutoff filters) — which is common in CBCT — and implementation of isotropic 2D apodization yielded quantifiably isotropic MTF. Asymmetric pixel binning modes were similarly shown to impart non-isotropic effects on the 3D MTF, and the overall 3D MTF characteristics were evident in each case with a single, 1D measurement of the 1D.
Conclusion
Three test tools and corresponding MTF analysis methods were presented within a consistent framework for analysis of 3D spatial resolution characteristics in a manner amenable to routine, practical measurements. Experiments on a CBCT C-arm validated many intuitive aspects of 3D spatial resolution and quantified the extent to which a CBCT system may be considered to have isotropic resolution. Measurement of urn:x-wiley:00942405:media:mp14820:mp14820-math-0010) provided a practical 1D measure of the underlying 3D MTF characteristics and is extensible to other CT or CBCT systems offering high, isotropic spatial resolution.
|
| 9. | Rohan C. Vijayan, Runze Han, Pengwei Wu, Niral M. Sheth, Michael D. Ketcha, Prasad Vagdargi, Sebastian Vogt, Gerhard Kleinszig, Greg M. Osgood, Ali Uneri, Jeffrey H. Siewerdsen Data-driven deformable 3D-2D registration for guiding neuroelectrode placement in deep brain stimulation Proceeding SPIE Medical Imaging, 2021 Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 11598, 2021. @proceedings{Vijayan2021,
title = {Data-driven deformable 3D-2D registration for guiding neuroelectrode placement in deep brain stimulation},
author = {Rohan C. Vijayan and Runze Han and Pengwei Wu and Niral M. Sheth and Michael D. Ketcha and Prasad Vagdargi and Sebastian Vogt and Gerhard Kleinszig and Greg M. Osgood and Ali Uneri and Jeffrey H. Siewerdsen},
url = {https://doi.org/10.1117/12.2582160},
doi = {10.1117/12.2582160},
year = {2021},
date = {2021-02-23},
volume = {11598},
publisher = {Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling},
organization = {SPIE Medical Imaging, 2021},
abstract = {Purpose. Deep brain stimulation is a neurosurgical procedure used in treatment of a growing spectrum of movement disorders. Inaccuracies in electrode placement, however, can result in poor symptom control or adverse effects and confound variability in clinical outcomes. A deformable 3D-2D registration method is presented for high-precision 3D guidance of neuroelectrodes. Methods. The approach employs a model-based, deformable algorithm for 3D-2D image registration. Variations in lead design are captured in a parametric 3D model based on a B-spline curve. The registration is solved through iterative optimization of 16 degrees-of-freedom that maximize image similarity between the 2 acquired radiographs and simulated forward projections of the neuroelectrode model. The approach was evaluated in phantom models with respect to pertinent imaging parameters, including view selection and imaging dose. Results. The results demonstrate an accuracy of (0.2 ± 0.2) mm in 3D localization of individual electrodes. The solution was observed to be robust to changes in pertinent imaging parameters, which demonstrate accurate localization with ≥20° view separation and at 1/10th the dose of a standard fluoroscopy frame. Conclusions. The presented approach provides the means for guiding neuroelectrode placement from 2 low-dose radiographic images in a manner that accommodates potential deformations at the target anatomical site. Future work will focus on improving runtime though learning-based initialization, application in reducing reconstruction metal artifacts for 3D verification of placement, and extensive evaluation in clinical data from an IRB study underway.},
keywords = {},
pubstate = {published},
tppubtype = {proceedings}
}
Purpose. Deep brain stimulation is a neurosurgical procedure used in treatment of a growing spectrum of movement disorders. Inaccuracies in electrode placement, however, can result in poor symptom control or adverse effects and confound variability in clinical outcomes. A deformable 3D-2D registration method is presented for high-precision 3D guidance of neuroelectrodes. Methods. The approach employs a model-based, deformable algorithm for 3D-2D image registration. Variations in lead design are captured in a parametric 3D model based on a B-spline curve. The registration is solved through iterative optimization of 16 degrees-of-freedom that maximize image similarity between the 2 acquired radiographs and simulated forward projections of the neuroelectrode model. The approach was evaluated in phantom models with respect to pertinent imaging parameters, including view selection and imaging dose. Results. The results demonstrate an accuracy of (0.2 ± 0.2) mm in 3D localization of individual electrodes. The solution was observed to be robust to changes in pertinent imaging parameters, which demonstrate accurate localization with ≥20° view separation and at 1/10th the dose of a standard fluoroscopy frame. Conclusions. The presented approach provides the means for guiding neuroelectrode placement from 2 low-dose radiographic images in a manner that accommodates potential deformations at the target anatomical site. Future work will focus on improving runtime though learning-based initialization, application in reducing reconstruction metal artifacts for 3D verification of placement, and extensive evaluation in clinical data from an IRB study underway. |
| 10. | Sarah Capostagno, Alex, Sisniega, J Webster. Stayman, Tina Ehtiati, Clifford Raabe Weiss, J H Siewerdsen Deformable motion compensation for interventional cone-beam CT Journal Article In: Phys. Med. Biol, vol. 66, no. 5, 2021. @article{Capostagno2021,
title = {Deformable motion compensation for interventional cone-beam CT},
author = {Sarah Capostagno and Alex and Sisniega and J Webster. Stayman and Tina Ehtiati and Clifford Raabe Weiss and J H Siewerdsen},
url = {https://iopscience.iop.org/article/10.1088/1361-6560/abb16e/meta},
doi = {10.1088/1361-6560/abb16e/meta},
year = {2021},
date = {2021-02-16},
journal = {Phys. Med. Biol},
volume = {66},
number = {5},
abstract = {Image-guided therapies in the abdomen and pelvis are often hindered by motion artifacts in cone-beam CT (CBCT) arising from complex, non-periodic, deformable organ motion during long scan times (5–30 s). We propose a deformable image-based motion compensation method to address these challenges and improve CBCT guidance. Motion compensation is achieved by selecting a set of small regions of interest in the uncompensated image to minimize a cost function consisting of an autofocus objective and spatiotemporal regularization penalties. Motion trajectories are estimated using an iterative optimization algorithm (CMA-ES) and used to interpolate a 4D spatiotemporal motion vector field. The motion-compensated image is reconstructed using a modified filtered backprojection approach. Being image-based, the method does not require additional input besides the raw CBCT projection data and system geometry that are used for image reconstruction. Experimental studies investigated: (1) various autofocus objective functions, analyzed using a digital phantom with a range of sinusoidal motion magnitude (4, 8, 12, 16, 20 mm); (2) spatiotemporal regularization, studied using a CT dataset from The Cancer Imaging Archive with deformable sinusoidal motion of variable magnitude (10, 15, 20, 25 mm); and (3) performance in complex anatomy, evaluated in cadavers undergoing simple and complex motion imaged on a CBCT-capable mobile C-arm system (Cios Spin 3D, Siemens Healthineers, Forchheim, Germany). Gradient entropy was found to be the best autofocus objective for soft-tissue CBCT, increasing structural similarity (SSIM) by 42%–92% over the range of motion magnitudes investigated. The optimal temporal regularization strength was found to vary widely (0.5–5 mm−2) over the range of motion magnitudes investigated, whereas optimal spatial regularization strength was relatively constant (0.1). In cadaver studies, deformable motion compensation was shown to improve local SSIM by ~17% for simple motion and ~21% for complex motion and provided strong visual improvement of motion artifacts (reduction of blurring and streaks and improved visibility of soft-tissue edges). The studies demonstrate the robustness of deformable motion compensation to a range of motion magnitudes, frequencies, and other factors (e.g. truncation and scatter).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Image-guided therapies in the abdomen and pelvis are often hindered by motion artifacts in cone-beam CT (CBCT) arising from complex, non-periodic, deformable organ motion during long scan times (5–30 s). We propose a deformable image-based motion compensation method to address these challenges and improve CBCT guidance. Motion compensation is achieved by selecting a set of small regions of interest in the uncompensated image to minimize a cost function consisting of an autofocus objective and spatiotemporal regularization penalties. Motion trajectories are estimated using an iterative optimization algorithm (CMA-ES) and used to interpolate a 4D spatiotemporal motion vector field. The motion-compensated image is reconstructed using a modified filtered backprojection approach. Being image-based, the method does not require additional input besides the raw CBCT projection data and system geometry that are used for image reconstruction. Experimental studies investigated: (1) various autofocus objective functions, analyzed using a digital phantom with a range of sinusoidal motion magnitude (4, 8, 12, 16, 20 mm); (2) spatiotemporal regularization, studied using a CT dataset from The Cancer Imaging Archive with deformable sinusoidal motion of variable magnitude (10, 15, 20, 25 mm); and (3) performance in complex anatomy, evaluated in cadavers undergoing simple and complex motion imaged on a CBCT-capable mobile C-arm system (Cios Spin 3D, Siemens Healthineers, Forchheim, Germany). Gradient entropy was found to be the best autofocus objective for soft-tissue CBCT, increasing structural similarity (SSIM) by 42%–92% over the range of motion magnitudes investigated. The optimal temporal regularization strength was found to vary widely (0.5–5 mm−2) over the range of motion magnitudes investigated, whereas optimal spatial regularization strength was relatively constant (0.1). In cadaver studies, deformable motion compensation was shown to improve local SSIM by ~17% for simple motion and ~21% for complex motion and provided strong visual improvement of motion artifacts (reduction of blurring and streaks and improved visibility of soft-tissue edges). The studies demonstrate the robustness of deformable motion compensation to a range of motion magnitudes, frequencies, and other factors (e.g. truncation and scatter). |
| 11. | Prasad Vagdargi, Niral M. Sheth, Alejandro Sisniega, Ali Uneri, Tharindu S. De Silva, Greg M. Osgood, Jeffrey H. Siewerdsen Drill-mounted video guidance for orthopaedic trauma surgery Journal Article In: J. of Medical Imaging, vol. 8, no. 015002 , 2021. @article{Vagdargi2021,
title = {Drill-mounted video guidance for orthopaedic trauma surgery},
author = {Prasad Vagdargi and Niral M. Sheth and Alejandro Sisniega and Ali Uneri and Tharindu S. De Silva and Greg M. Osgood and Jeffrey H. Siewerdsen},
url = {https://doi.org/10.1117/1.JMI.8.1.015002},
doi = {10.1117/1.JMI.8.1.015002},
year = {2021},
date = {2021-02-15},
journal = {J. of Medical Imaging},
volume = {8},
number = {015002 },
abstract = { Purpose: Percutaneous fracture fixation is a challenging procedure that requires accurate interpretation of fluoroscopic images to insert guidewires through narrow bone corridors. We present a guidance system with a video camera mounted onboard the surgical drill to achieve real-time augmentation of the drill trajectory in fluoroscopy and/or CT.
Approach: The camera was mounted on the drill and calibrated with respect to the drill axis. Markers identifiable in both video and fluoroscopy are placed about the surgical field and co-registered by feature correspondences. If available, a preoperative CT can also be co-registered by 3D–2D image registration. Real-time guidance is achieved by virtual overlay of the registered drill axis on fluoroscopy or in CT. Performance was evaluated in terms of target registration error (TRE), conformance within clinically relevant pelvic bone corridors, and runtime.
Results: Registration of the drill axis to fluoroscopy demonstrated median TRE of 0.9 mm and 2.0 deg when solved with two views (e.g., anteroposterior and lateral) and five markers visible in both video and fluoroscopy—more than sufficient to provide Kirschner wire (K-wire) conformance within common pelvic bone corridors. Registration accuracy was reduced when solved with a single fluoroscopic view (TRE = 3.4 mm and 2.7 deg) but was also sufficient for K-wire conformance within pelvic bone corridors. Registration was robust with as few as four markers visible within the field of view. Runtime of the initial implementation allowed fluoroscopy overlay and/or 3D CT navigation with freehand manipulation of the drill up to 10 frames / s.
Conclusions: A drill-mounted video guidance system was developed to assist with K-wire placement. Overall workflow is compatible with fluoroscopically guided orthopaedic trauma surgery and does not require markers to be placed in preoperative CT. The initial prototype demonstrates accuracy and runtime that could improve the accuracy of K-wire placement, motivating future work for translation to clinical studies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose: Percutaneous fracture fixation is a challenging procedure that requires accurate interpretation of fluoroscopic images to insert guidewires through narrow bone corridors. We present a guidance system with a video camera mounted onboard the surgical drill to achieve real-time augmentation of the drill trajectory in fluoroscopy and/or CT.
Approach: The camera was mounted on the drill and calibrated with respect to the drill axis. Markers identifiable in both video and fluoroscopy are placed about the surgical field and co-registered by feature correspondences. If available, a preoperative CT can also be co-registered by 3D–2D image registration. Real-time guidance is achieved by virtual overlay of the registered drill axis on fluoroscopy or in CT. Performance was evaluated in terms of target registration error (TRE), conformance within clinically relevant pelvic bone corridors, and runtime.
Results: Registration of the drill axis to fluoroscopy demonstrated median TRE of 0.9 mm and 2.0 deg when solved with two views (e.g., anteroposterior and lateral) and five markers visible in both video and fluoroscopy—more than sufficient to provide Kirschner wire (K-wire) conformance within common pelvic bone corridors. Registration accuracy was reduced when solved with a single fluoroscopic view (TRE = 3.4 mm and 2.7 deg) but was also sufficient for K-wire conformance within pelvic bone corridors. Registration was robust with as few as four markers visible within the field of view. Runtime of the initial implementation allowed fluoroscopy overlay and/or 3D CT navigation with freehand manipulation of the drill up to 10 frames / s.
Conclusions: A drill-mounted video guidance system was developed to assist with K-wire placement. Overall workflow is compatible with fluoroscopically guided orthopaedic trauma surgery and does not require markers to be placed in preoperative CT. The initial prototype demonstrates accuracy and runtime that could improve the accuracy of K-wire placement, motivating future work for translation to clinical studies. |
| 12. | Runze Han, Ali Uneri, Rohan Vijayan, Pengwei Wu, Pasad Vagdargi, Niral Sheth Sebastian Vogt, Gerhard Kleinszig, Greg Osgood, Jeffrey H. Siewerdsen, Fracture reduction planning and guidance in orthopaedic trauma surgery via multi-body image registration Journal Article In: Medical Image Analysis, vol. 68, no. 101917, 2021, ISSN: 1361-8415. @article{Han2021b,
title = {Fracture reduction planning and guidance in orthopaedic trauma surgery via multi-body image registration},
author = {Runze Han and Ali Uneri and Rohan Vijayan and Pengwei Wu and Pasad Vagdargi and Niral Sheth Sebastian Vogt and Gerhard Kleinszig and Greg Osgood and Jeffrey H. Siewerdsen,},
url = {https://www.sciencedirect.com/science/article/pii/S1361841520302814},
doi = {10.1016/j.media.2020.101917},
issn = {1361-8415},
year = {2021},
date = {2021-02-01},
journal = {Medical Image Analysis},
volume = {68},
number = {101917},
abstract = {Purposes
Surgical reduction of pelvic fracture is a challenging procedure, and accurate restoration of natural morphology is essential to obtaining positive functional outcome. The procedure often requires extensive preoperative planning, long fluoroscopic exposure time, and trial-and-error to achieve accurate reduction. We report a multi-body registration framework for reduction planning using preoperative CT and intraoperative guidance using routine 2D fluoroscopy that could help address such challenges.
Method
The framework starts with semi-automatic segmentation of fractured bone fragments in preoperative CT using continuous max-flow. For reduction planning, a multi-to-one registration is performed to register bone fragments to an adaptive template that adjusts to patient-specific bone shapes and poses. The framework further registers bone fragments to intraoperative fluoroscopy to provide 2D fluoroscopy guidance and/or 3D navigation relative to the reduction plan. The framework was investigated in three studies: (1) a simulation study of 40 CT images simulating three fracture categories (unilateral two-body, unilateral three-body, and bilateral two-body); (2) a proof-of-concept cadaver study to mimic clinical scenario; and (3) a retrospective clinical study investigating feasibility in three cases of increasing severity and accuracy requirement.
Results
Segmentation of simulated pelvic fracture demonstrated Dice coefficient of
. Reduction planning using the adaptive template achieved 2-3 mm and 2-3° error for the three fracture categories, significantly better than planning based on mirroring of contralateral anatomy. 3D-2D registration yielded ~2 mm and 0.5° accuracy, providing accurate guidance with respect to the preoperative reduction plan. The cadaver study and retrospective clinical study demonstrated comparable accuracy: ~0.90 Dice coefficient in segmentation, ~3 mm accuracy in reduction planning, and ~2 mm accuracy in 3D-2D registration.
Conclusion
The registration framework demonstrated planning and guidance accuracy within clinical requirements in both simulation and clinical feasibility studies for a broad range of fracture-dislocation patterns. Using routinely acquired preoperative CT and intraoperative fluoroscopy, the framework could improve the accuracy of pelvic fracture reduction, reduce radiation dose, and could integrate well with common clinical workflow without the need for additional navigation systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purposes
Surgical reduction of pelvic fracture is a challenging procedure, and accurate restoration of natural morphology is essential to obtaining positive functional outcome. The procedure often requires extensive preoperative planning, long fluoroscopic exposure time, and trial-and-error to achieve accurate reduction. We report a multi-body registration framework for reduction planning using preoperative CT and intraoperative guidance using routine 2D fluoroscopy that could help address such challenges.
Method
The framework starts with semi-automatic segmentation of fractured bone fragments in preoperative CT using continuous max-flow. For reduction planning, a multi-to-one registration is performed to register bone fragments to an adaptive template that adjusts to patient-specific bone shapes and poses. The framework further registers bone fragments to intraoperative fluoroscopy to provide 2D fluoroscopy guidance and/or 3D navigation relative to the reduction plan. The framework was investigated in three studies: (1) a simulation study of 40 CT images simulating three fracture categories (unilateral two-body, unilateral three-body, and bilateral two-body); (2) a proof-of-concept cadaver study to mimic clinical scenario; and (3) a retrospective clinical study investigating feasibility in three cases of increasing severity and accuracy requirement.
Results
Segmentation of simulated pelvic fracture demonstrated Dice coefficient of
. Reduction planning using the adaptive template achieved 2-3 mm and 2-3° error for the three fracture categories, significantly better than planning based on mirroring of contralateral anatomy. 3D-2D registration yielded ~2 mm and 0.5° accuracy, providing accurate guidance with respect to the preoperative reduction plan. The cadaver study and retrospective clinical study demonstrated comparable accuracy: ~0.90 Dice coefficient in segmentation, ~3 mm accuracy in reduction planning, and ~2 mm accuracy in 3D-2D registration.
Conclusion
The registration framework demonstrated planning and guidance accuracy within clinical requirements in both simulation and clinical feasibility studies for a broad range of fracture-dislocation patterns. Using routinely acquired preoperative CT and intraoperative fluoroscopy, the framework could improve the accuracy of pelvic fracture reduction, reduce radiation dose, and could integrate well with common clinical workflow without the need for additional navigation systems. |
| 13. | Xiaoxuan Zhang, Ali Uneri, Pengwei Wu, Michael Daniel Ketcha, Craig Jones, Yixuan Huang, Sheng-fu L Lo, Patrick A Helm, Jeffrey H Siewerdsen Long-length tomosynthesis and 3D-2D registration for intraoperative assessment of spine instrumentation Journal Article In: Institute of Physics and Engineering in Medicine, 2021. @article{Zhang2021,
title = {Long-length tomosynthesis and 3D-2D registration for intraoperative assessment of spine instrumentation},
author = {Xiaoxuan Zhang and Ali Uneri and Pengwei Wu and Michael Daniel Ketcha and Craig Jones and Yixuan Huang and Sheng-fu L Lo and Patrick A Helm and Jeffrey H Siewerdsen},
url = {https://iopscience.iop.org/article/10.1088/1361-6560/abde96/meta},
doi = {10.1088/1361-6560/abde96},
year = {2021},
date = {2021-01-21},
journal = {Institute of Physics and Engineering in Medicine},
abstract = {Purpose: A system for long-length intraoperative imaging is reported based on longitudinal motion of an O-arm gantry featuring a multi-slot collimator. We assess the utility of long-length tomosynthesis and the geometric accuracy of 3D image registration for surgical guidance and evaluation of long spinal constructs. Methods: A multi-slot collimator with tilted apertures was integrated into an O-arm system for long-length imaging. The multi-slot projective geometry leads to slight view disparity in both long-length projection images (referred to as "line scans") and tomosynthesis "slot reconstructions" produced using a weighted-backprojection method. The radiation dose for long-length imaging was measured, and the utility of long-length, intraoperative tomosynthesis was evaluated in phantom and cadaver studies. Leveraging the depth resolution provided by parallax views, an algorithm for 3D-2D registration of the patient and surgical devices was adapted for registration with line scans and slot reconstructions. Registration performance using single-plane or dual-plane long-length images was evaluated and compared to registration accuracy achieved using standard biplane radiographs. Results: Longitudinal coverage of ~50–64 cm was achieved with a single long-length slot scan, providing a field-of-view up to (40 × 64) cm2, depending on patient positioning. The dose-area product (reference point air kerma × x-ray field area) for a slot scan ranged from ~702–1757 mGy ⋅ cm2, equivalent to ~2.5 s of fluoroscopy and comparable to other long-length imaging systems. Long-length scanning produced high-resolution tomosynthesis reconstructions, covering ~12–16 vertebral levels. 3D image registration using dual-plane slot reconstructions achieved median target registration error (TRE) of 1.2 mm and 0.6° in cadaver studies, outperforming registration to line scans (TRE = 2.8 mm and 2.2°) and biplane radiographs (TRE = 2.5 mm and 1.1°). 3D registration using single-plane slot reconstructions leveraged the ~7–14° angular separation between slots to achieve median TRE ~2 mm and < 2° from a single scan. Conclusion: The multi-slot configuration provided intraoperative visualization of long spine segments, facilitating target localization, assessment of global spinal alignment, and evaluation of long surgical constructs. 3D-2D registration to long-length tomosynthesis reconstructions yielded a promising means of guidance and verification with accuracy exceeding that of 3D-2D registration to conventional radiographs. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose: A system for long-length intraoperative imaging is reported based on longitudinal motion of an O-arm gantry featuring a multi-slot collimator. We assess the utility of long-length tomosynthesis and the geometric accuracy of 3D image registration for surgical guidance and evaluation of long spinal constructs. Methods: A multi-slot collimator with tilted apertures was integrated into an O-arm system for long-length imaging. The multi-slot projective geometry leads to slight view disparity in both long-length projection images (referred to as "line scans") and tomosynthesis "slot reconstructions" produced using a weighted-backprojection method. The radiation dose for long-length imaging was measured, and the utility of long-length, intraoperative tomosynthesis was evaluated in phantom and cadaver studies. Leveraging the depth resolution provided by parallax views, an algorithm for 3D-2D registration of the patient and surgical devices was adapted for registration with line scans and slot reconstructions. Registration performance using single-plane or dual-plane long-length images was evaluated and compared to registration accuracy achieved using standard biplane radiographs. Results: Longitudinal coverage of ~50–64 cm was achieved with a single long-length slot scan, providing a field-of-view up to (40 × 64) cm2, depending on patient positioning. The dose-area product (reference point air kerma × x-ray field area) for a slot scan ranged from ~702–1757 mGy ⋅ cm2, equivalent to ~2.5 s of fluoroscopy and comparable to other long-length imaging systems. Long-length scanning produced high-resolution tomosynthesis reconstructions, covering ~12–16 vertebral levels. 3D image registration using dual-plane slot reconstructions achieved median target registration error (TRE) of 1.2 mm and 0.6° in cadaver studies, outperforming registration to line scans (TRE = 2.8 mm and 2.2°) and biplane radiographs (TRE = 2.5 mm and 1.1°). 3D registration using single-plane slot reconstructions leveraged the ~7–14° angular separation between slots to achieve median TRE ~2 mm and < 2° from a single scan. Conclusion: The multi-slot configuration provided intraoperative visualization of long spine segments, facilitating target localization, assessment of global spinal alignment, and evaluation of long surgical constructs. 3D-2D registration to long-length tomosynthesis reconstructions yielded a promising means of guidance and verification with accuracy exceeding that of 3D-2D registration to conventional radiographs. |
| 14. | Alejandro Sisniega, Joseph Webster Stayman, Sarah Capostagno, Clifford Raabe Weiss, Tina Ehtiati, Jeffrey H Siewerdsen Accelerated 3D image reconstruction with a morphological pyramid and noise-power convergence criterion Journal Article In: Institute of Physics and Engineering in Medicine, 2021. @article{Sisniega2021,
title = {Accelerated 3D image reconstruction with a morphological pyramid and noise-power convergence criterion},
author = {Alejandro Sisniega and Joseph Webster Stayman and Sarah Capostagno and Clifford Raabe Weiss and Tina Ehtiati and Jeffrey H Siewerdsen},
url = {https://doi.org/10.1088/1361-6560/abde97},
doi = {10.1088/1361-6560/abde97},
year = {2021},
date = {2021-01-21},
journal = { Institute of Physics and Engineering in Medicine},
abstract = {Model-based iterative reconstruction (MBIR) for cone-beam CT (CBCT) offers better noise-resolution tradeoff and image quality than analytical methods for acquisition protocols with low x-ray dose or limited data, but with increased computational burden that poses a drawback to routine application in clinical scenarios. This work develops a comprehensive framework for acceleration of MBIR in the form of penalized weighted least squares (PWLS) optimized with ordered subsets separable quadratic surrogates. The optimization was scheduled on a set of stages forming a morphological pyramid varying in voxel size. Transition between stages was controlled with a convergence criterion based on the deviation between the mid-band noise power spectrum (NPS) measured on a homogeneous region of the evolving reconstruction and that expected for the converged image, computed with an analytical model that used projection data and the reconstruction parameters. An stochastic backprojector (SBP) was developed by introducing a random perturbation to the sampling position of each voxel for each ray in the reconstruction within a voxel-based backprojector, breaking the deterministic pattern of sampling artifacts when combined with an unmatched Siddon forward projector. This fast, forward and backprojector pair were included into a multi-resolution reconstruction strategy to provide support for objects partially outside of the field of view. Acceleration from ordered subsets was combined with momentum accumulation stabilized with an adaptive technique that automatically resets the accumulated momentum when it diverges noticeably from the current iteration update. The framework was evaluated with CBCT data of a realistic abdomen phantom acquired on an imaging x-ray bench and with clinical CBCT data from an angiography robotic C-arm (Artis Zeego, Siemens Healthineers, Forchheim, Germany) acquired during a liver embolization procedure. Image fidelity was assessed with the structural similarity index (SSIM) computed with a converged reconstruction. The accelerated framework provided accurate reconstructions in 60 s (SSIM = 0.97) and as little as 27 s (SSIM = 0.94) for soft-tissue evaluation. The use of simple forward and backprojectors resulted in 9.3x acceleration. Accumulation of momentum provided extra ~3.5x acceleration with stable convergence for 6 to 30 subsets. The NPS-driven morphological pyramid resulted in initial faster convergence, achieving similar SSIM with 1.5x lower runtime than the single-stage optimization. Acceleration of MBIR to provide reconstruction time compatible with clinical applications is feasible via architectures that integrate algorithmic acceleration with approaches to provide stable convergence, and optimization schedules that maximize convergence speed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Model-based iterative reconstruction (MBIR) for cone-beam CT (CBCT) offers better noise-resolution tradeoff and image quality than analytical methods for acquisition protocols with low x-ray dose or limited data, but with increased computational burden that poses a drawback to routine application in clinical scenarios. This work develops a comprehensive framework for acceleration of MBIR in the form of penalized weighted least squares (PWLS) optimized with ordered subsets separable quadratic surrogates. The optimization was scheduled on a set of stages forming a morphological pyramid varying in voxel size. Transition between stages was controlled with a convergence criterion based on the deviation between the mid-band noise power spectrum (NPS) measured on a homogeneous region of the evolving reconstruction and that expected for the converged image, computed with an analytical model that used projection data and the reconstruction parameters. An stochastic backprojector (SBP) was developed by introducing a random perturbation to the sampling position of each voxel for each ray in the reconstruction within a voxel-based backprojector, breaking the deterministic pattern of sampling artifacts when combined with an unmatched Siddon forward projector. This fast, forward and backprojector pair were included into a multi-resolution reconstruction strategy to provide support for objects partially outside of the field of view. Acceleration from ordered subsets was combined with momentum accumulation stabilized with an adaptive technique that automatically resets the accumulated momentum when it diverges noticeably from the current iteration update. The framework was evaluated with CBCT data of a realistic abdomen phantom acquired on an imaging x-ray bench and with clinical CBCT data from an angiography robotic C-arm (Artis Zeego, Siemens Healthineers, Forchheim, Germany) acquired during a liver embolization procedure. Image fidelity was assessed with the structural similarity index (SSIM) computed with a converged reconstruction. The accelerated framework provided accurate reconstructions in 60 s (SSIM = 0.97) and as little as 27 s (SSIM = 0.94) for soft-tissue evaluation. The use of simple forward and backprojectors resulted in 9.3x acceleration. Accumulation of momentum provided extra ~3.5x acceleration with stable convergence for 6 to 30 subsets. The NPS-driven morphological pyramid resulted in initial faster convergence, achieving similar SSIM with 1.5x lower runtime than the single-stage optimization. Acceleration of MBIR to provide reconstruction time compatible with clinical applications is feasible via architectures that integrate algorithmic acceleration with approaches to provide stable convergence, and optimization schedules that maximize convergence speed. |
| 15. | Runze Han, Ali Uneria, Rohan Vijayana Pengwei Wu, Prasad Vagdargi, Niral Sheth, Sebastian Vogt, Gerhard Kleinszig, Greg Michael Osgood, Jeffrey H. Siewerdsen Fracture reduction planning and guidance in orthopaedic trauma surgery via multi-body image registration Journal Article In: Medical Image Analysis, vol. 68, no. 101917, 2020, ISBN: 1361-8415. @article{Han2021,
title = {Fracture reduction planning and guidance in orthopaedic trauma surgery via multi-body image registration},
author = {Runze Han and Ali Uneria and Rohan Vijayana Pengwei Wu and Prasad Vagdargi and Niral Sheth and Sebastian Vogt and Gerhard Kleinszig and Greg Michael Osgood and Jeffrey H. Siewerdsen},
url = {https://doi.org/10.1016/j.media.2020.101917},
doi = {10.1016/j.media.2020.101917},
isbn = {1361-8415},
year = {2020},
date = {2020-11-30},
journal = {Medical Image Analysis},
volume = {68},
number = {101917},
abstract = {Purposes
Surgical reduction of pelvic fracture is a challenging procedure, and accurate restoration of natural morphology is essential to obtaining positive functional outcome. The procedure often requires extensive preoperative planning, long fluoroscopic exposure time, and trial-and-error to achieve accurate reduction. We report a multi-body registration framework for reduction planning using preoperative CT and intraoperative guidance using routine 2D fluoroscopy that could help address such challenges.
Method
The framework starts with semi-automatic segmentation of fractured bone fragments in preoperative CT using continuous max-flow. For reduction planning, a multi-to-one registration is performed to register bone fragments to an adaptive template that adjusts to patient-specific bone shapes and poses. The framework further registers bone fragments to intraoperative fluoroscopy to provide 2D fluoroscopy guidance and/or 3D navigation relative to the reduction plan. The framework was investigated in three studies: (1) a simulation study of 40 CT images simulating three fracture categories (unilateral two-body, unilateral three-body, and bilateral two-body); (2) a proof-of-concept cadaver study to mimic clinical scenario; and (3) a retrospective clinical study investigating feasibility in three cases of increasing severity and accuracy requirement.
Results
Segmentation of simulated pelvic fracture demonstrated Dice coefficient of
. Reduction planning using the adaptive template achieved 2-3 mm and 2-3° error for the three fracture categories, significantly better than planning based on mirroring of contralateral anatomy. 3D-2D registration yielded ~2 mm and 0.5° accuracy, providing accurate guidance with respect to the preoperative reduction plan. The cadaver study and retrospective clinical study demonstrated comparable accuracy: ~0.90 Dice coefficient in segmentation, ~3 mm accuracy in reduction planning, and ~2 mm accuracy in 3D-2D registration.
Conclusion
The registration framework demonstrated planning and guidance accuracy within clinical requirements in both simulation and clinical feasibility studies for a broad range of fracture-dislocation patterns. Using routinely acquired preoperative CT and intraoperative fluoroscopy, the framework could improve the accuracy of pelvic fracture reduction, reduce radiation dose, and could integrate well with common clinical workflow without the need for additional navigation systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purposes
Surgical reduction of pelvic fracture is a challenging procedure, and accurate restoration of natural morphology is essential to obtaining positive functional outcome. The procedure often requires extensive preoperative planning, long fluoroscopic exposure time, and trial-and-error to achieve accurate reduction. We report a multi-body registration framework for reduction planning using preoperative CT and intraoperative guidance using routine 2D fluoroscopy that could help address such challenges.
Method
The framework starts with semi-automatic segmentation of fractured bone fragments in preoperative CT using continuous max-flow. For reduction planning, a multi-to-one registration is performed to register bone fragments to an adaptive template that adjusts to patient-specific bone shapes and poses. The framework further registers bone fragments to intraoperative fluoroscopy to provide 2D fluoroscopy guidance and/or 3D navigation relative to the reduction plan. The framework was investigated in three studies: (1) a simulation study of 40 CT images simulating three fracture categories (unilateral two-body, unilateral three-body, and bilateral two-body); (2) a proof-of-concept cadaver study to mimic clinical scenario; and (3) a retrospective clinical study investigating feasibility in three cases of increasing severity and accuracy requirement.
Results
Segmentation of simulated pelvic fracture demonstrated Dice coefficient of
. Reduction planning using the adaptive template achieved 2-3 mm and 2-3° error for the three fracture categories, significantly better than planning based on mirroring of contralateral anatomy. 3D-2D registration yielded ~2 mm and 0.5° accuracy, providing accurate guidance with respect to the preoperative reduction plan. The cadaver study and retrospective clinical study demonstrated comparable accuracy: ~0.90 Dice coefficient in segmentation, ~3 mm accuracy in reduction planning, and ~2 mm accuracy in 3D-2D registration.
Conclusion
The registration framework demonstrated planning and guidance accuracy within clinical requirements in both simulation and clinical feasibility studies for a broad range of fracture-dislocation patterns. Using routinely acquired preoperative CT and intraoperative fluoroscopy, the framework could improve the accuracy of pelvic fracture reduction, reduce radiation dose, and could integrate well with common clinical workflow without the need for additional navigation systems. |
| 16. | Grace J. Gang, Tom Russ, Yiqun Ma, Christian Toennes, Lothar R. Schad, J. Webster Stayman, Jeffrey H. Siewerdsen Metal-Tolerant Noncircular Orbit Design and Implementation on Robotic C-Arm Systems Journal Article In: Conference proceedings. International Conference on Image Formation in X-Ray Computed Tomography, pp. 400-403, 2020. @article{Gang2020b,
title = {Metal-Tolerant Noncircular Orbit Design and Implementation on Robotic C-Arm Systems},
author = {Grace J. Gang and Tom Russ and Yiqun Ma and Christian Toennes and Lothar R. Schad and J. Webster Stayman and Jeffrey H. Siewerdsen},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7643882/},
year = {2020},
date = {2020-11-05},
journal = {Conference proceedings. International Conference on Image Formation in X-Ray Computed Tomography},
pages = {400-403},
abstract = {Metal artifacts are a major confounding factor for image quality in CT, especially in image-guided surgery scenarios where surgical tools and implants frequently occur in the field-of-view. Traditional metal artifact correction methods typically use algorithmic solutions to interpolate over the highly attenuated projection measurements where metal is present but cannot recover the missing information obstructed by the metal. In this work, we treat metal artifacts as a missing data problem and employ noncircular orbits to maximize data completeness in the presence of metal. We first implement a local data completeness metric based on Tuy’s condition as the percentage of great circles sampled by a particular orbit and accounted for the presence of metal by discounting any rays that pass through metal. We then compute the metric over many locations and many possible metal locations to reflect data completeness for arbitrary metal placements within a volume of interest. We used this metric to evaluate the effectiveness of sinusoidal orbits of different magnitudes and frequencies in metal artifact reduction. We also evaluated noncircular orbits in two imaging systems for phantoms with different metal objects and metal arrangements. Among a circular, tilted circular, and a sinusoidal orbit of two cycles per rotation, the latter is shown to most effectively remove metal artifacts. The noncircular orbit not only reduce the extent of streaks, but allows better visualization of spatial frequencies that cannot be recovered by metal artifact correction algorithms. These results illustrate the potential of relatively simple noncircular orbits to be robust against metal implants which ordinarily present significant challenges in interventional imaging.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Metal artifacts are a major confounding factor for image quality in CT, especially in image-guided surgery scenarios where surgical tools and implants frequently occur in the field-of-view. Traditional metal artifact correction methods typically use algorithmic solutions to interpolate over the highly attenuated projection measurements where metal is present but cannot recover the missing information obstructed by the metal. In this work, we treat metal artifacts as a missing data problem and employ noncircular orbits to maximize data completeness in the presence of metal. We first implement a local data completeness metric based on Tuy’s condition as the percentage of great circles sampled by a particular orbit and accounted for the presence of metal by discounting any rays that pass through metal. We then compute the metric over many locations and many possible metal locations to reflect data completeness for arbitrary metal placements within a volume of interest. We used this metric to evaluate the effectiveness of sinusoidal orbits of different magnitudes and frequencies in metal artifact reduction. We also evaluated noncircular orbits in two imaging systems for phantoms with different metal objects and metal arrangements. Among a circular, tilted circular, and a sinusoidal orbit of two cycles per rotation, the latter is shown to most effectively remove metal artifacts. The noncircular orbit not only reduce the extent of streaks, but allows better visualization of spatial frequencies that cannot be recovered by metal artifact correction algorithms. These results illustrate the potential of relatively simple noncircular orbits to be robust against metal implants which ordinarily present significant challenges in interventional imaging. |
| 17. | Stephen Z Liu, Qian Cao, Matthew Tivnan, Steven Wayne Tilley II, Joseph Webster Stayman, Wojciech Zbijewski, Jeffrey H Siewerdsen Model-based dual-energy tomographic image reconstruction of objects containing known metal components Journal Article In: Institute of Physics and Engineering in Medicine, 2020. @article{Liu2020,
title = {Model-based dual-energy tomographic image reconstruction of objects containing known metal components},
author = {Stephen Z Liu and Qian Cao and Matthew Tivnan and Steven Wayne Tilley II and Joseph Webster Stayman and Wojciech Zbijewski and Jeffrey H Siewerdsen },
url = {https://iopscience.iop.org/article/10.1088/1361-6560/abc5a9},
doi = {10.1088/1361-6560/abc5a9},
year = {2020},
date = {2020-10-28},
journal = {Institute of Physics and Engineering in Medicine},
abstract = {Dual-energy (DE) decomposition has been adopted in orthopedic imaging to measure bone composition and visualize intraarticular contrast enhancement. One of the potential applications involves monitoring of callus mineralization for longitudinal assessment of fracture healing. However, fracture repair usually involves internal fixation hardware that can generate significant artifacts in reconstructed images. To address this challenge, we develop a novel algorithm that combines simultaneous reconstruction-decomposition using a previously reported method for Model-Based Material Decomposition (MBMD) augmented by the Known-Component (KC) reconstruction framework to mitigate metal artifacts. We apply the proposed algorithm to simulated DE data representative of a dedicated extremity cone-beam CT (CBCT) employing an x-ray unit with three vertically arranged sources. The scanner generates DE data with non-coinciding high- and low-energy projection rays when the central source is operated at high tube potential and the peripheral sources at low potential. The proposed algorithm was validated using a digital extremity phantom containing varying concentrations of Ca-water mixtures and Ti implants. Decomposition accuracy was compared to MBMD without the KC model. The proposed method suppressed metal artifacts and yielded estimated Ca concentrations that approached the reconstructions of an implant-free phantom for most mixture regions. In the vicinity of simple components, the errors of Ca density estimates obtained by incorporating KC in MBMD were ~1.5 – 5x lower than the errors of conventional MBMD; for cases with complex implants, the errors were ~3 – 5x lower. In conclusion, the proposed method can achieve accurate bone mineral density measurements in the presence of metal implants using non-coinciding DE projections acquired on a multisource CBCT system.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Dual-energy (DE) decomposition has been adopted in orthopedic imaging to measure bone composition and visualize intraarticular contrast enhancement. One of the potential applications involves monitoring of callus mineralization for longitudinal assessment of fracture healing. However, fracture repair usually involves internal fixation hardware that can generate significant artifacts in reconstructed images. To address this challenge, we develop a novel algorithm that combines simultaneous reconstruction-decomposition using a previously reported method for Model-Based Material Decomposition (MBMD) augmented by the Known-Component (KC) reconstruction framework to mitigate metal artifacts. We apply the proposed algorithm to simulated DE data representative of a dedicated extremity cone-beam CT (CBCT) employing an x-ray unit with three vertically arranged sources. The scanner generates DE data with non-coinciding high- and low-energy projection rays when the central source is operated at high tube potential and the peripheral sources at low potential. The proposed algorithm was validated using a digital extremity phantom containing varying concentrations of Ca-water mixtures and Ti implants. Decomposition accuracy was compared to MBMD without the KC model. The proposed method suppressed metal artifacts and yielded estimated Ca concentrations that approached the reconstructions of an implant-free phantom for most mixture regions. In the vicinity of simple components, the errors of Ca density estimates obtained by incorporating KC in MBMD were ~1.5 – 5x lower than the errors of conventional MBMD; for cases with complex implants, the errors were ~3 – 5x lower. In conclusion, the proposed method can achieve accurate bone mineral density measurements in the presence of metal implants using non-coinciding DE projections acquired on a multisource CBCT system. |
| 18. | Sarah Capostagno, Alejandro Sisniega, Joseph Webster Stayman, Tina Ehtiati, Clifford Raabe Weiss, Jeffrey H Siewerdsen Deformable motion compensation for interventional cone-beam CT Journal Article In: Institute of Physics and Engineering in Medicine, 2020. @article{2020Capostagno,
title = {Deformable motion compensation for interventional cone-beam CT},
author = {Sarah Capostagno and Alejandro Sisniega and Joseph Webster Stayman and Tina Ehtiati and Clifford Raabe Weiss and Jeffrey H Siewerdsen},
url = {https://doi.org/10.1088/1361-6560/abb16e},
doi = {10.1088/1361-6560/abb16e},
year = {2020},
date = {2020-08-21},
journal = {Institute of Physics and Engineering in Medicine},
abstract = {Image-guided therapies in the abdomen and pelvis are often hindered by motion artifacts in cone-beam CT (CBCT) arising from complex, non-periodic, deformable organ motion during long scan times (5–30 sec). We propose a deformable image-based motion compensation method to address these challenges and improve CBCT guidance. Motion compensation is achieved by selecting a set of small regions of interest in the uncompensated image to minimize a cost function consisting of an autofocus objective and spatiotemporal regularization penalties. Motion trajectories are estimated using an iterative optimization algorithm (CMA-ES) and used to interpolate a 4D spatiotemporal motion vector field. The motion-compensated image is reconstructed using a modified filtered backprojection approach. Being image-based, the method does not require additional input besides the raw CBCT projection data and system geometry that are used for image reconstruction. Experimental studies investigated: (1) various autofocus objective functions, analyzed using a digital phantom with a range of sinusoidal motion magnitude (4, 8, 12, 16, 20 mm); (2) spatiotemporal regularization, studied using a CT dataset from The Cancer Imaging Archive with deformable sinusoidal motion of variable magnitude (10, 15, 20, 25 mm); and (3) performance in complex anatomy, evaluated in cadavers undergoing simple and complex motion imaged on a CBCT-capable mobile C-arm system (Cios Spin 3D, Siemens Healthineers, Forchheim, Germany). Gradient entropy was found to be the best autofocus objective for soft-tissue CBCT, increasing structural similarity (SSIM) by 42–92% over the range of motion magnitudes investigated. The optimal temporal regularization strength was found to vary widely (0.5–5 mm-2) over the range of motion magnitudes investigated, whereas optimal spatial regularization strength was relatively constant (0.1). In cadaver studies, deformable motion compensation was shown to improve local SSIM by ~17% for simple motion and ~21% for complex motion and provided strong visual improvement of motion artifacts (reduction of blurring and streaks and improved visibility of soft-tissue edges). The studies demonstrate the robustness of deformable motion compensation to a range of motion magnitudes, frequencies, and other factors (e.g., truncation and scatter).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Image-guided therapies in the abdomen and pelvis are often hindered by motion artifacts in cone-beam CT (CBCT) arising from complex, non-periodic, deformable organ motion during long scan times (5–30 sec). We propose a deformable image-based motion compensation method to address these challenges and improve CBCT guidance. Motion compensation is achieved by selecting a set of small regions of interest in the uncompensated image to minimize a cost function consisting of an autofocus objective and spatiotemporal regularization penalties. Motion trajectories are estimated using an iterative optimization algorithm (CMA-ES) and used to interpolate a 4D spatiotemporal motion vector field. The motion-compensated image is reconstructed using a modified filtered backprojection approach. Being image-based, the method does not require additional input besides the raw CBCT projection data and system geometry that are used for image reconstruction. Experimental studies investigated: (1) various autofocus objective functions, analyzed using a digital phantom with a range of sinusoidal motion magnitude (4, 8, 12, 16, 20 mm); (2) spatiotemporal regularization, studied using a CT dataset from The Cancer Imaging Archive with deformable sinusoidal motion of variable magnitude (10, 15, 20, 25 mm); and (3) performance in complex anatomy, evaluated in cadavers undergoing simple and complex motion imaged on a CBCT-capable mobile C-arm system (Cios Spin 3D, Siemens Healthineers, Forchheim, Germany). Gradient entropy was found to be the best autofocus objective for soft-tissue CBCT, increasing structural similarity (SSIM) by 42–92% over the range of motion magnitudes investigated. The optimal temporal regularization strength was found to vary widely (0.5–5 mm-2) over the range of motion magnitudes investigated, whereas optimal spatial regularization strength was relatively constant (0.1). In cadaver studies, deformable motion compensation was shown to improve local SSIM by ~17% for simple motion and ~21% for complex motion and provided strong visual improvement of motion artifacts (reduction of blurring and streaks and improved visibility of soft-tissue edges). The studies demonstrate the robustness of deformable motion compensation to a range of motion magnitudes, frequencies, and other factors (e.g., truncation and scatter). |
| 19. | Pengwe Wu, Niral Sheth, Alejandro Sisniega, Ali Uneri, Runze Han, Rohan Vijayan, Prasad Vagdargi, B. Kreher, Holger Kunze, Gerhard Kleinszig, Sebastian Vogt, Sheng-Fu Lo, Nicolas Theodore, Jeffrey H. Siewerdsen C-arm orbits for metal artifact avoidance (MAA) in cone-beam CT Journal Article In: Physics in Medicine & Biology, vol. 65, no. 16m, 2020. @article{Wu2020d,
title = {C-arm orbits for metal artifact avoidance (MAA) in cone-beam CT},
author = {Pengwe Wu and Niral Sheth and Alejandro Sisniega and Ali Uneri and Runze Han and Rohan Vijayan and Prasad Vagdargi and B. Kreher and Holger Kunze and Gerhard Kleinszig and Sebastian Vogt and Sheng-Fu Lo and Nicolas Theodore and Jeffrey H. Siewerdsen},
url = {https://doi.org/10.1088/1361-6560/ab9454},
doi = {10.1088/1361-6560/ab9454},
year = {2020},
date = {2020-08-14},
journal = {Physics in Medicine & Biology},
volume = {65},
number = {16m},
abstract = {Metal artifacts present a challenge to cone-beam CT (CBCT) image-guided surgery, obscuring visualization of metal instruments and adjacent anatomy—often in the very region of interest pertinent to the imaging/surgical tasks. We present a method to reduce the influence of metal artifacts by prospectively defining an image acquisition protocol—viz., the C-arm source-detector orbit—that mitigates metal-induced biases in the projection data. The metal artifact avoidance (MAA) method is compatible with simple mobile C-arms, does not require exact prior information on the patient or metal implants, and is consistent with 3D filtered backprojection (FBP), more advanced (e.g. polyenergetic) model-based image reconstruction (MBIR), and metal artifact reduction (MAR) post-processing methods. The MAA method consists of: (i) coarse localization of metal objects in the field-of-view (FOV) via two or more low-dose scout projection views and segmentation (e.g. a simple U-Net) in coarse backprojection; (ii) model-based prediction of metal-induced x-ray spectral shift for all source-detector vertices accessible by the imaging system (e.g. gantry rotation and tilt angles); and (iii) identification of a circular or non-circular orbit that reduces the variation in spectral shift. The method was developed, tested, and evaluated in a series of studies presenting increasing levels of complexity and realism, including digital simulations, phantom experiment, and cadaver experiment in the context of image-guided spine surgery (pedicle screw implants). The MAA method accurately predicted tilted circular and non-circular orbits that reduced the magnitude of metal artifacts in CBCT reconstructions. Realistic distributions of metal instrumentation were successfully localized (0.71 median Dice coefficient) from 2–6 low-dose scout views even in complex anatomical scenes. The MAA-predicted tilted circular orbits reduced root-mean-square error (RMSE) in 3D image reconstructions by 46%–70% and 'blooming' artifacts (apparent width of the screw shaft) by 20–45%. Non-circular orbits defined by MAA achieved a further ~46% reduction in RMSE compared to the best (tilted) circular orbit. The MAA method presents a practical means to predict C-arm orbits that minimize spectral bias from metal instrumentation. Resulting orbits—either simple tilted circular orbits or more complex non-circular orbits that can be executed with a motorized multi-axis C-arm—exhibited substantial reduction of metal artifacts in raw CBCT reconstructions by virtue of higher fidelity projection data, which are in turn compatible with subsequent MAR post-processing and/or polyenergetic MBIR to further reduce artifacts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Metal artifacts present a challenge to cone-beam CT (CBCT) image-guided surgery, obscuring visualization of metal instruments and adjacent anatomy—often in the very region of interest pertinent to the imaging/surgical tasks. We present a method to reduce the influence of metal artifacts by prospectively defining an image acquisition protocol—viz., the C-arm source-detector orbit—that mitigates metal-induced biases in the projection data. The metal artifact avoidance (MAA) method is compatible with simple mobile C-arms, does not require exact prior information on the patient or metal implants, and is consistent with 3D filtered backprojection (FBP), more advanced (e.g. polyenergetic) model-based image reconstruction (MBIR), and metal artifact reduction (MAR) post-processing methods. The MAA method consists of: (i) coarse localization of metal objects in the field-of-view (FOV) via two or more low-dose scout projection views and segmentation (e.g. a simple U-Net) in coarse backprojection; (ii) model-based prediction of metal-induced x-ray spectral shift for all source-detector vertices accessible by the imaging system (e.g. gantry rotation and tilt angles); and (iii) identification of a circular or non-circular orbit that reduces the variation in spectral shift. The method was developed, tested, and evaluated in a series of studies presenting increasing levels of complexity and realism, including digital simulations, phantom experiment, and cadaver experiment in the context of image-guided spine surgery (pedicle screw implants). The MAA method accurately predicted tilted circular and non-circular orbits that reduced the magnitude of metal artifacts in CBCT reconstructions. Realistic distributions of metal instrumentation were successfully localized (0.71 median Dice coefficient) from 2–6 low-dose scout views even in complex anatomical scenes. The MAA-predicted tilted circular orbits reduced root-mean-square error (RMSE) in 3D image reconstructions by 46%–70% and 'blooming' artifacts (apparent width of the screw shaft) by 20–45%. Non-circular orbits defined by MAA achieved a further ~46% reduction in RMSE compared to the best (tilted) circular orbit. The MAA method presents a practical means to predict C-arm orbits that minimize spectral bias from metal instrumentation. Resulting orbits—either simple tilted circular orbits or more complex non-circular orbits that can be executed with a motorized multi-axis C-arm—exhibited substantial reduction of metal artifacts in raw CBCT reconstructions by virtue of higher fidelity projection data, which are in turn compatible with subsequent MAR post-processing and/or polyenergetic MBIR to further reduce artifacts. |
| 20. |
Sophia A Doerr, Tharindu De Silva, Rohan Vijayan, Runze Han, Ali Uneri, Michael D Ketcha, Xiaoxuan Zhang, Nishanth Khanna, Erick Westbroek, Bowen Jiang, Corinna Zygourakis, Nafi Aygun, Nicholas Theodore, Jeffrey H Siewerdsen
Automatic Analysis of Global Spinal Alignment From Simple Annotation of Vertebral Bodies Journal Article In: Journal of Medical Imaging , pp. 16 PAGES, 2020. @article{Doerr2020,
title = {Automatic Analysis of Global Spinal Alignment From Simple Annotation of Vertebral Bodies },
author = {
Sophia A Doerr and Tharindu De Silva and Rohan Vijayan and Runze Han and Ali Uneri and Michael D Ketcha and Xiaoxuan Zhang and Nishanth Khanna and Erick Westbroek and Bowen Jiang and Corinna Zygourakis and Nafi Aygun and Nicholas Theodore and Jeffrey H Siewerdsen
},
url = {https://doi.org/10.1117/1.JMI.7.3.035001},
doi = {10.1117/1.JMI.7.3.035001},
year = {2020},
date = {2020-05-13},
journal = {Journal of Medical Imaging },
pages = {16 PAGES},
abstract = { Purpose: Measurement of global spinal alignment (GSA) is an important aspect of diagnosis and treatment evaluation for spinal deformity but is subject to a high level of inter-reader variability.
Approach: Two methods for automatic GSA measurement are proposed to mitigate such variability and reduce the burden of manual measurements. Both approaches use vertebral labels in spine computed tomography (CT) as input: the first (EndSeg) segments vertebral endplates using input labels as seed points; and the second (SpNorm) computes a two-dimensional curvilinear fit to the input labels. Studies were performed to characterize the performance of EndSeg and SpNorm in comparison to manual GSA measurement by five clinicians, including measurements of proximal thoracic kyphosis, main thoracic kyphosis, and lumbar lordosis.
Results: For the automatic methods, 93.8% of endplate angle estimates were within the inter-reader 95% confidence interval (CI95). All GSA measurements for the automatic methods were within the inter-reader CI95, and there was no statistically significant difference between automatic and manual methods. The SpNorm method appears particularly robust as it operates without segmentation.
Conclusions: Such methods could improve the reproducibility and reliability of GSA measurements and are potentially suitable to applications in large datasets—e.g., for outcome assessment in surgical data science.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose: Measurement of global spinal alignment (GSA) is an important aspect of diagnosis and treatment evaluation for spinal deformity but is subject to a high level of inter-reader variability.
Approach: Two methods for automatic GSA measurement are proposed to mitigate such variability and reduce the burden of manual measurements. Both approaches use vertebral labels in spine computed tomography (CT) as input: the first (EndSeg) segments vertebral endplates using input labels as seed points; and the second (SpNorm) computes a two-dimensional curvilinear fit to the input labels. Studies were performed to characterize the performance of EndSeg and SpNorm in comparison to manual GSA measurement by five clinicians, including measurements of proximal thoracic kyphosis, main thoracic kyphosis, and lumbar lordosis.
Results: For the automatic methods, 93.8% of endplate angle estimates were within the inter-reader 95% confidence interval (CI95). All GSA measurements for the automatic methods were within the inter-reader CI95, and there was no statistically significant difference between automatic and manual methods. The SpNorm method appears particularly robust as it operates without segmentation.
Conclusions: Such methods could improve the reproducibility and reliability of GSA measurements and are potentially suitable to applications in large datasets—e.g., for outcome assessment in surgical data science. |
