@article{Capostagno2021,

title = {Deformable motion compensation for interventional cone-beam CT },

author = {Sarah Capostagno and Alejandro Sisniega and J. Webster Stayman and Tina Ehtiati and Clifford Weiss and Jeffrey H. Siewerdsen},

url = {https://pubmed.ncbi.nlm.nih.gov/33594993/},

doi = {10.1088/1361-6560/abb16e },

year  = {2021},

date = {2021-02-17},

journal = {Physics in Medicine and Biology},

volume = {66},

number = {5},

pages = {055010},

keywords = {CBCT, Image Guided Surgery, Motion Compensation},

pubstate = {published},

tppubtype = {article}

}

@article{Taguchi2020,

title = {Three-dimensional regions-of-interest-based intra-operative 4-dimensional soft tissue perfusion imaging using a standard x-ray system with no gantry rotation: A simulation study for a proof of concept},

author = {Katsuyuki Taguchi and Thomas J. Sauer and W. Paul Segars and Eric Frey and Jingyan Xu and Eleni Liapi and J. Webster Stayman and Kelvin Hong and Ferdinand Hui and Mathias Unberath and Yong Du},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7796930/},

doi = {10.1002/mp.14514},

year  = {2020},

date = {2020-12-01},

journal = {Medical Physics},

volume = {47},

number = {12},

pages = {6087-6102},

keywords = {Image Guided Surgery, System Design},

pubstate = {published},

tppubtype = {article}

}

@article{Zhang2019b,

title = {Known-component 3D image reconstruction for improved intraoperative imaging in spine surgery: A clinical pilot study},

author = {Xiaoxuan Zhang and Ali Uneri and J. Webster Stayman and C. C. Zygourakis and S. L. Lo and Nick Theodore and Jeffrey H. Siewerdsen},

url = {https://pubmed.ncbi.nlm.nih.gov/31180586/},

doi = {10.1002/mp.13652},

year  = {2019},

date = {2019-08-01},

journal = {Medical Physics},

volume = {46},

number = {8},

pages = {3483-95},

abstract = {Purpose: Intraoperative imaging plays an increased role in support of surgical guidance and quality assurance for interventional approaches. However, image quality sufficient to detect complications and provide quantitative assessment of the surgical product is often confounded by image noise and artifacts. In this work, we translated a three-dimensional model-based image reconstruction (referred to as "Known-Component Reconstruction," KC-Recon) for the first time to clinical studies with the aim of resolving both limitations.



Methods: KC-Recon builds upon a penalized weighted least-squares (PWLS) method by incorporating models of surgical instrumentation ("known components") within a joint image registration-reconstruction process to improve image quality. Under IRB approval, a clinical pilot study was conducted with 17 spine surgery patients imaged under informed consent using the O-arm cone-beam CT system (Medtronic, Littleton MA) before and after spinal instrumentation. Volumetric images were generated for each patient using KC-Recon in comparison to conventional filtered backprojection (FBP). Imaging performance prior to instrumentation ("preinstrumentation") was evaluated in terms of soft-tissue contrast-to-noise ratio (CNR) and spatial resolution. The quality of images obtained after the instrumentation ("postinstrumentation") was assessed by quantifying the magnitude of metal artifacts (blooming and streaks) arising from pedicle screws. The potential low-dose advantages of the algorithm were tested by simulating low-dose data (down to one-tenth of the dose of standard protocols) from images acquired at normal dose.



Results: Preinstrumentation images (at normal clinical dose and matched resolution) exhibited an average 24.0% increase in soft-tissue CNR with KC-Recon compared to FBP (N = 16, P = 0.02), improving visualization of paraspinal muscles, major vessels, and other soft-tissues about the spine and abdomen. For a total of 72 screws in postinstrumentation images, KC-Recon yielded a significant reduction in metal artifacts: 66.3% reduction in overestimation of screw shaft width due to blooming (P < 0.0001) and reduction in streaks at the screw tip (65.8% increase in attenuation accuracy, P < 0.0001), enabling clearer depiction of the screw within the pedicle and vertebral body for an assessment of breach. Depending on the imaging task, dose reduction up to an order of magnitude appeared feasible while maintaining soft-tissue visibility and metal artifact reduction.



Conclusions: KC-Recon offers a promising means to improve visualization in the presence of surgical instrumentation and reduce patient dose in image-guided procedures. The improved soft-tissue visibility could facilitate the use of cone-beam CT to soft-tissue surgeries, and the ability to precisely quantify and visualize instrument placement could provide a valuable check against complications in the operating room (cf., postoperative CT).



Keywords: cone-beam CT; image-guided procedures; intraoperative imaging; model-based image reconstruction; patient safety.},

keywords = {CBCT, Image Guided Surgery, Known Components, MBIR, Metal Artifacts, Spine},

pubstate = {published},

tppubtype = {article}

}

@article{Stayman2019,

title = {Task-driven source–detector trajectories in cone-beam computed tomography: I. Theory and methods},

author = {J. Webster Stayman and Sarah Capostagno and Grace Gang and Jeffrey H. Siewerdsen },

url = {https://www.spiedigitallibrary.org/journals/Journal-of-Medical-Imaging/volume-6/issue-2/025002/Task-driven-sourcedetector-trajectories-in-cone-beam-computed-tomography/10.1117/1.JMI.6.2.025002.full},

doi = {10.1117/1.JMI.6.2.025002},

year  = {2019},

date = {2019-05-02},

journal = {Journal of Medical Imaging},

volume = {6},

number = {2},

pages = {025002},

keywords = {CBCT, Customized Acquisition, Image Guided Surgery, MBIR, Task-Driven Imaging},

pubstate = {published},

tppubtype = {article}

}

@article{Capostagno2019,

title = {Task-driven source–detector trajectories in cone-beam computed tomography: II. Application to neuroradiology},

author = {Sarah Capostagno and J. Webster Stayman and Matthew W. Jacobson and Tina Ehtiati and Clifford Weiss and Jeffrey H. Siewerdsen },

url = {https://www.spiedigitallibrary.org/journals/Journal-of-Medical-Imaging/volume-6/issue-2/025004/Task-driven-sourcedetector-trajectories-in-cone-beam-computed-tomography/10.1117/1.JMI.6.2.025004.full},

doi = {10.1117/1.JMI.6.2.025004},

year  = {2019},

date = {2019-03-09},

journal = {Journal of Medical Imaging},

volume = {6},

number = {2},

pages = {025004},

keywords = {CBCT, Customized Acquisition, Head/Neck, Image Guided Surgery, Task-Driven Imaging},

pubstate = {published},

tppubtype = {article}

}

@article{Jacobson2018,

title = {A line fiducial method for geometric calibration of cone-beam CT systems with diverse scan trajectories},

author = {Matthew W. Jacobson and Michael Ketcha and Sarah Capostagno and Andrew Martin and Ali Uneri and Joseph Goerres and Tharindu De Silva and Sureerat Reaungamornrat and Runze Han and Amir Manbachi and J. Webster Stayman and Sebastian Vogt and Gerhard Kleinszig and Jeffrey H. Siewerdsen},

url = {http://iopscience.iop.org/article/10.1088/1361-6560/aa9910/meta},

doi = {10.1088/1361-6560/aa9910},

year  = {2018},

date = {2018-01-15},

journal = {Physics in Medicine and Biology},

volume = {63},

number = {2},

pages = {025030},

keywords = {Customized Acquisition, Image Guided Surgery, Task-Driven Imaging},

pubstate = {published},

tppubtype = {article}

}

@article{Ouadah2017b,

title = {Correction of Patient Motion in Cone-Beam CT Using 3D-2D Registration},

author = {Sarah Ouadah and Matthew W. Jacobson and J. Webster Stayman and Tina Ehtiati and Clifford Weiss and J. Webster Stayman },

url = {http://iopscience.iop.org/article/10.1088/1361-6560/aa9254},

doi = {10.1088/1361-6560/aa9254},

year  = {2017},

date = {2017-12-01},

journal = {Physics in Medicine and Biology},

volume = {62},

number = {23},

pages = {8813},

keywords = {Image Guided Surgery, Image Registration, Motion Compensation},

pubstate = {published},

tppubtype = {article}

}

@article{dang2012robust,

title = {Robust methods for automatic image-to-world registration in cone-beam CT interventional guidance.},

author = {Hao Dang and Yoshito Otake and Sebastian Schafer and J. Webster Stayman and Gerhard Kleinszig and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3477200},

doi = {10.1118/1.4754589},

issn = {0094-2405},

year  = {2012},

date = {2012-10-01},

journal = {Medical physics},

volume = {39},

number = {10},

pages = {6484--98},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE Real-time surgical navigation relies on accurate image-to-world registration to align the coordinate systems of the image and patient. Conventional manual registration can present a workflow bottleneck and is prone to manual error and intraoperator variability. This work reports alternative means of automatic image-to-world registration, each method involving an automatic registration marker (ARM) used in conjunction with C-arm cone-beam CT (CBCT). The first involves a Known-Model registration method in which the ARM is a predefined tool, and the second is a Free-Form method in which the ARM is freely configurable. METHODS Studies were performed using a prototype C-arm for CBCT and a surgical tracking system. A simple ARM was designed with markers comprising a tungsten sphere within infrared reflectors to permit detection of markers in both x-ray projections and by an infrared tracker. The Known-Model method exercised a predefined specification of the ARM in combination with 3D-2D registration to estimate the transformation that yields the optimal match between forward projection of the ARM and the measured projection images. The Free-Form method localizes markers individually in projection data by a robust Hough transform approach extended from previous work, backprojected to 3D image coordinates based on C-arm geometric calibration. Image-domain point sets were transformed to world coordinates by rigid-body point-based registration. The robustness and registration accuracy of each method was tested in comparison to manual registration across a range of body sites (head, thorax, and abdomen) of interest in CBCT-guided surgery, including cases with interventional tools in the radiographic scene. RESULTS The automatic methods exhibited similar target registration error (TRE) and were comparable or superior to manual registration for placement of the ARM within ∼200 mm of C-arm isocenter. Marker localization in projection data was robust across all anatomical sites, including challenging scenarios involving the presence of interventional tools. The reprojection error of marker localization was independent of the distance of the ARM from isocenter, and the overall TRE was dominated by the configuration of individual fiducials and distance from the target as predicted by theory. The median TRE increased with greater ARM-to-isocenter distance (e.g., for the Free-Form method, TRE increasing from 0.78 mm to 2.04 mm at distances of ∼75 mm and 370 mm, respectively). The median TRE within ∼200 mm distance was consistently lower than that of the manual method (TRE = 0.82 mm). Registration performance was independent of anatomical site (head, thorax, and abdomen). The Free-Form method demonstrated a statistically significant improvement (p = 0.0044) in reproducibility compared to manual registration (0.22 mm versus 0.30 mm, respectively). CONCLUSIONS Automatic image-to-world registration methods demonstrate the potential for improved accuracy, reproducibility, and workflow in CBCT-guided procedures. A Free-Form method was shown to exhibit robustness against anatomical site, with comparable or improved TRE compared to manual registration. It was also comparable or superior in performance to a Known-Model method in which the ARM configuration is specified as a predefined tool, thereby allowing configuration of fiducials on the fly or attachment to the patient.},

keywords = {CBCT, Image Guided Surgery},

pubstate = {published},

tppubtype = {article}

}

@article{reaungamornrat2012board,

title = {An on-board surgical tracking and video augmentation system for C-arm image guidance.},

author = {Sureerat Reaungamornrat and Yoshito Otake and Ali Uneri and Sebastian Schafer and Daniel J. Mirota and Sajendra Nithiananthan and J. Webster Stayman and Gerhard Kleinszig and A. Jay Khanna and Russell H. Taylor and Jeffrey H. Siewerdsen },

url = {http://www.ncbi.nlm.nih.gov/pubmed/22539008},

doi = {10.1007/s11548-012-0682-9},

issn = {1861-6429},

year  = {2012},

date = {2012-09-01},

journal = {International journal of computer assisted radiology and surgery},

volume = {7},

number = {5},

pages = {647--65},

publisher = {Springer-Verlag},

abstract = {PURPOSE Conventional tracker configurations for surgical navigation carry a variety of limitations, including limited geometric accuracy, line-of-sight obstruction, and mismatch of the view angle with the surgeon's-eye view. This paper presents the development and characterization of a novel tracker configuration (referred to as "Tracker-on-C") intended to address such limitations by incorporating the tracker directly on the gantry of a mobile C-arm for fluoroscopy and cone-beam CT (CBCT). METHODS A video-based tracker (MicronTracker, Claron Technology Inc., Toronto, ON, Canada) was mounted on the gantry of a prototype mobile isocentric C-arm next to the flat-panel detector. To maintain registration within a dynamically moving reference frame (due to rotation of the C-arm), a reference marker consisting of 6 faces (referred to as a "hex-face marker") was developed to give visibility across the full range of C-arm rotation. Three primary functionalities were investigated: surgical tracking, generation of digitally reconstructed radiographs (DRRs) from the perspective of a tracked tool or the current C-arm angle, and augmentation of the tracker video scene with image, DRR, and planning data. Target registration error (TRE) was measured in comparison with the same tracker implemented in a conventional in-room configuration. Graphics processing unit (GPU)-accelerated DRRs were generated in real time as an assistant to C-arm positioning (i.e., positioning the C-arm such that target anatomy is in the field-of-view (FOV)), radiographic search (i.e., a virtual X-ray projection preview of target anatomy without X-ray exposure), and localization (i.e., visualizing the location of the surgical target or planning data). Video augmentation included superimposing tracker data, the X-ray FOV, DRRs, planning data, preoperative images, and/or intraoperative CBCT onto the video scene. Geometric accuracy was quantitatively evaluated in each case, and qualitative assessment of clinical feasibility was analyzed by an experienced and fellowship-trained orthopedic spine surgeon within a clinically realistic surgical setup of the Tracker-on-C. RESULTS The Tracker-on-C configuration demonstrated improved TRE (0.87 ± 0.25) mm in comparison with a conventional in-room tracker setup (1.92 ± 0.71) mm (p textless 0.0001) attributed primarily to improved depth resolution of the stereoscopic camera placed closer to the surgical field. The hex-face reference marker maintained registration across the 180° C-arm orbit (TRE = 0.70 ± 0.32 mm). DRRs generated from the perspective of the C-arm X-ray detector demonstrated sub- mm accuracy (0.37 ± 0.20 mm) in correspondence with the real X-ray image. Planning data and DRRs overlaid on the video scene exhibited accuracy of (0.59 ± 0.38) pixels and (0.66 ± 0.36) pixels, respectively. Preclinical assessment suggested potential utility of the Tracker-on-C in a spectrum of interventions, including improved line of sight, an assistant to C-arm positioning, and faster target localization, while reducing X-ray exposure time. CONCLUSIONS The proposed tracker configuration demonstrated sub- mm TRE from the dynamic reference frame of a rotational C-arm through the use of the multi-face reference marker. Real-time DRRs and video augmentation from a natural perspective over the operating table assisted C-arm setup, simplified radiographic search and localization, and reduced fluoroscopy time. Incorporation of the proposed tracker configuration with C-arm CBCT guidance has the potential to simplify intraoperative registration, improve geometric accuracy, enhance visualization, and reduce radiation exposure.},

keywords = {CBCT, Image Guided Surgery, Multimodality},

pubstate = {published},

tppubtype = {article}

}

@article{Nithiananthan2012,

title = {Extra-dimensional Demons: a method for incorporating missing tissue in deformable image registration.},

author = {Sajendra Nithiananthan and Sebastian Schafer and Daniel J. Mirota and J. Webster Stayman and Wojciech Zbijewski and Douglas D. Reh and Gary L. Gallia and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3443194},

doi = {10.1118/1.4747270},

issn = {0094-2405},

year  = {2012},

date = {2012-09-01},

journal = {Medical physics},

volume = {39},

number = {9},

pages = {5718--31},

abstract = {PURPOSE A deformable registration method capable of accounting for missing tissue (e.g., excision) is reported for application in cone-beam CT (CBCT)-guided surgical procedures. Excisions are identified by a segmentation step performed simultaneous to the registration process. Tissue excision is explicitly modeled by increasing the dimensionality of the deformation field to allow motion beyond the dimensionality of the image. The accuracy of the model is tested in phantom, simulations, and cadaver models. METHODS A variant of the Demons deformable registration algorithm is modified to include excision segmentation and modeling. Segmentation is performed iteratively during the registration process, with initial implementation using a threshold-based approach to identify voxels corresponding to "tissue" in the moving image and "air" in the fixed image. With each iteration of the Demons process, every voxel is assigned a probability of excision. Excisions are modeled explicitly during registration by increasing the dimensionality of the deformation field so that both deformations and excisions can be accounted for by in- and out-of-volume deformations, respectively. The out-of-volume (i.e., fourth) component of the deformation field at each voxel carries a magnitude proportional to the excision probability computed in the excision segmentation step. The registration accuracy of the proposed "extra-dimensional" Demons (XDD) and conventional Demons methods was tested in the presence of missing tissue in phantom models, simulations investigating the effect of excision size on registration accuracy, and cadaver studies emulating realistic deformations and tissue excisions imparted in CBCT-guided endoscopic skull base surgery. RESULTS Phantom experiments showed the normalized mutual information (NMI) in regions local to the excision to improve from 1.10 for the conventional Demons approach to 1.16 for XDD, and qualitative examination of the resulting images revealed major differences: the conventional Demons approach imparted unrealistic distortions in areas around tissue excision, whereas XDD provided accurate "ejection" of voxels within the excision site and maintained the registration accuracy throughout the rest of the image. Registration accuracy in areas far from the excision site (e.g., textgreater ∼5 mm) was identical for the two approaches. Quantitation of the effect was consistent in analysis of NMI, normalized cross-correlation (NCC), target registration error (TRE), and accuracy of voxels ejected from the volume (true-positive and false-positive analysis). The registration accuracy for conventional Demons was found to degrade steeply as a function of excision size, whereas XDD was robust in this regard. Cadaver studies involving realistic excision of the clivus, vidian canal, and ethmoid sinuses demonstrated similar results, with unrealistic distortion of anatomy imparted by conventional Demons and accurate ejection and deformation for XDD. CONCLUSIONS Adaptation of the Demons deformable registration process to include segmentation (i.e., identification of excised tissue) and an extra dimension in the deformation field provided a means to accurately accommodate missing tissue between image acquisitions. The extra-dimensional approach yielded accurate "ejection" of voxels local to the excision site while preserving the registration accuracy (typically subvoxel) of the conventional Demons approach throughout the rest of the image. The ability to accommodate missing tissue volumes is important to application of CBCT for surgical guidance (e.g., skull base drillout) and may have application in other areas of CBCT guidance.},

keywords = {CBCT, Image Guided Surgery, Image Registration},

pubstate = {published},

tppubtype = {article}

}

@article{otake2012automaticb,

title = {Automatic localization of vertebral levels in x-ray fluoroscopy using 3D-2D registration: a tool to reduce wrong-site surgery.},

author = {Yoshito Otake and Sebastian Schafer and J. Webster Stayman and Wojciech Zbijewski and Gerhard Kleinszig and Rainer Graumann and A. Jay Khanna and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3429949},

doi = {10.1088/0031-9155/57/17/5485},

issn = {1361-6560},

year  = {2012},

date = {2012-09-01},

journal = {Physics in medicine and biology},

volume = {57},

number = {17},

pages = {5485--508},

publisher = {IOP Publishing},

abstract = {Surgical targeting of the incorrect vertebral level (wrong-level surgery) is among the more common wrong-site surgical errors, attributed primarily to the lack of uniquely identifiable radiographic landmarks in the mid-thoracic spine. The conventional localization method involves manual counting of vertebral bodies under fluoroscopy, is prone to human error and carries additional time and dose. We propose an image registration and visualization system (referred to as LevelCheck), for decision support in spine surgery by automatically labeling vertebral levels in fluoroscopy using a GPU-accelerated, intensity-based 3D-2D (namely CT-to-fluoroscopy) registration. A gradient information (GI) similarity metric and a CMA-ES optimizer were chosen due to their robustness and inherent suitability for parallelization. Simulation studies involved ten patient CT datasets from which 50 000 simulated fluoroscopic images were generated from C-arm poses selected to approximate the C-arm operator and positioning variability. Physical experiments used an anthropomorphic chest phantom imaged under real fluoroscopy. The registration accuracy was evaluated as the mean projection distance (mPD) between the estimated and true center of vertebral levels. Trials were defined as successful if the estimated position was within the projection of the vertebral body (namely mPD textless5 mm). Simulation studies showed a success rate of 99.998% (1 failure in 50 000 trials) and computation time of 4.7 s on a midrange GPU. Analysis of failure modes identified cases of false local optima in the search space arising from longitudinal periodicity in vertebral structures. Physical experiments demonstrated the robustness of the algorithm against quantum noise and x-ray scatter. The ability to automatically localize target anatomy in fluoroscopy in near-real-time could be valuable in reducing the occurrence of wrong-site surgery while helping to reduce radiation exposure. The method is applicable beyond the specific case of vertebral labeling, since any structure defined in pre-operative (or intra-operative) CT or cone-beam CT can be automatically registered to the fluoroscopic scene.},

keywords = {CBCT, Image Guided Surgery, Image Registration, Multimodality, Spine},

pubstate = {published},

tppubtype = {article}

}

@article{lee2012intraoperative,

title = {Intraoperative C-arm cone-beam computed tomography: quantitative analysis of surgical performance in skull base surgery.},

author = {Stella Lee and Gary L. Gallia and Douglas D. Reh and Sebastian Schafer and Ali Uneri and Daniel J. Mirota and Sajendra Nithiananthan and Yoshito Otake and J. Webster Stayman and Wojciech Zbijewski and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3725328},

doi = {10.1002/lary.23374},

issn = {1531-4995},

year  = {2012},

date = {2012-09-01},

journal = {The Laryngoscope},

volume = {122},

number = {9},

pages = {1925--32},

publisher = {Wiley Subscription Services, Inc., A Wiley Company},

abstract = {OBJECTIVES/HYPOTHESIS To determine whether incorporation of intraoperative imaging via a new cone-beam computed tomography (CBCT) image-guidance system improves accuracy and facilitates resection in sinus and skull-base surgery through quantification of surgical performance. STUDY DESIGN Landmark identification and skull base ablation tasks were performed with a CBCT intraoperative image-guidance system in the experimental group and with image-guided surgery (IGS) alone based on preoperative computed tomography (CT) in the control group. METHODS Six cadaveric heads underwent preoperative CT imaging and surgical planning identifying surgical targets. Three types of surgical tasks were planned: landmark point identification, line contour identification, and volume drill-out. Key anatomic structures (carotid artery and optic nerve) were chosen for landmark identification and line contour tasks. Complete ethmoidectomy, vidian corridor drill-out, and clival resection were performed for volume ablation tasks. The CBCT guidance system was used in the experimental group and performance was assessed by metrics of target registration error, sensitivity, and specificity of excision. RESULTS Significant improvements were seen for point identification and line tracing tasks. Additional resection was performed in 67% of tasks in the CBCT group, and qualitative feedback indicated unequivocal improvement in confidence for all tasks. In review of tasks in the control group, additional resection would have been performed in 35% of tasks if an intraoperative image was available. CONCLUSIONS An experimental prototype C-arm CBCT guidance system was shown to improve surgical precision in the identification of skull base targets and increase accuracy in the ablation of surgical target volumes in comparison to using IGS alone.},

keywords = {CBCT, Head/Neck, Image Guided Surgery, System Assessment},

pubstate = {published},

tppubtype = {article}

}

@article{Lee2012,

title = {Volume-of-change cone-beam CT for image-guided surgery.},

author = {Junghoon Lee and J. Webster Stayman and Yoshito Otake and Sebastian Schafer and Wojciech Zbijewski and A. Jay Khanna and Jerry L. Prince and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3432954},

doi = {10.1088/0031-9155/57/15/4969},

issn = {1361-6560},

year  = {2012},

date = {2012-08-01},

journal = {Physics in medicine and biology},

volume = {57},

number = {15},

pages = {4969--89},

abstract = {C-arm cone-beam CT (CBCT) can provide intraoperative 3D imaging capability for surgical guidance, but workflow and radiation dose are the significant barriers to broad utilization. One main reason is that each 3D image acquisition requires a complete scan with a full radiation dose to present a completely new 3D image every time. In this paper, we propose to utilize patient-specific CT or CBCT as prior knowledge to accurately reconstruct the aspects of the region that have changed by the surgical procedure from only a sparse set of x-rays. The proposed methods consist of a 3D-2D registration between the prior volume and a sparse set of intraoperative x-rays, creating digitally reconstructed radiographs (DRRs) from the registered prior volume, computing difference images by subtracting DRRs from the intraoperative x-rays, a penalized likelihood reconstruction of the volume of change (VOC) from the difference images, and finally a fusion of VOC reconstruction with the prior volume to visualize the entire surgical field. When the surgical changes are local and relatively small, the VOC reconstruction involves only a small volume size and a small number of projections, allowing less computation and lower radiation dose than is needed to reconstruct the entire surgical field. We applied this approach to sacroplasty phantom data obtained from a CBCT test bench and vertebroplasty data with a fresh cadaver acquired from a C-arm CBCT system with a flat-panel detector. The VOCs were reconstructed from a varying number of images (10-66 images) and compared to the CBCT ground truth using four different metrics (mean squared error, correlation coefficient, structural similarity index and perceptual difference model). The results show promising reconstruction quality with structural similarity to the ground truth close to 1 even when only 15-20 images were used, allowing dose reduction by the factor of 10-20.},

keywords = {CBCT, Image Guided Surgery, MBIR, Prior Images, Sparse Sampling, Spine},

pubstate = {published},

tppubtype = {article}

}

@article{schafer2011mobile,

title = {Mobile C-arm cone-beam CT for guidance of spine surgery: image quality, radiation dose, and integration with interventional guidance.},

author = {Sebastian Schafer and Sajendra Nithiananthan and Daniel J. Mirota and Ali Uneri and J. Webster Stayman and Wojciech Zbijewski and Christian Schmidgunst and Gerhard Kleinszig and A. Jay Khanna and Jeffrey H. Siewerdsen },

url = {http://www.ncbi.nlm.nih.gov/pubmed/21928628 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3161502},

doi = {10.1118/1.3597566},

issn = {0094-2405},

year  = {2011},

date = {2011-08-01},

journal = {Medical physics},

volume = {38},

number = {8},

pages = {4563--74},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE A flat-panel detector based mobile isocentric C-arm for cone-beam CT (CBCT) has been developed to allow intraoperative 3D imaging with sub-millimeter spatial resolution and soft-tissue visibility. Image quality and radiation dose were evaluated in spinal surgery, commonly relying on lower-performance image intensifier based mobile C-arms. Scan protocols were developed for task-specific imaging at minimum dose, in-room exposure was evaluated, and integration of the imaging system with a surgical guidance system was demonstrated in preclinical studies of minimally invasive spine surgery. METHODS Radiation dose was assessed as a function of kilovolt (peak) (80-120 kVp) and milliampere second using thoracic and lumbar spine dosimetry phantoms. In-room radiation exposure was measured throughout the operating room for various CBCT scan protocols. Image quality was assessed using tissue-equivalent inserts in chest and abdomen phantoms to evaluate bone and soft-tissue contrast-to-noise ratio as a function of dose, and task-specific protocols (i.e., visualization of bone or soft-tissues) were defined. Results were applied in preclinical studies using a cadaveric torso simulating minimally invasive, transpedicular surgery. RESULTS Task-specific CBCT protocols identified include: thoracic bone visualization (100 kVp; 60 mAs; 1.8 mGy); lumbar bone visualization (100 kVp; 130 mAs; 3.2 mGy); thoracic soft-tissue visualization (100 kVp; 230 mAs; 4.3 mGy); and lumbar soft-tissue visualization (120 kVp; 460 mAs; 10.6 mGy)--each at (0.3 x 0.3 x 0.9 mm3) voxel size. Alternative lower-dose, lower-resolution soft-tissue visualization protocols were identified (100 kVp; 230 mAs; 5.1 mGy) for the lumbar region at (0.3 x 0.3 x 1.5 mm3) voxel size. Half-scan orbit of the C-arm (x-ray tube traversing under the table) was dosimetrically advantageous (prepatient attenuation) with a nonuniform dose distribution (-2 x higher at the entrance side than at isocenter, and -3-4 lower at the exit side). The in-room dose (microsievert) per unit scan dose (milligray) ranged from -21 microSv/mGy on average at tableside to -0.1 microSv/mGy at 2.0 m distance to isocenter. All protocols involve surgical staff stepping behind a shield wall for each CBCT scan, therefore imparting -zero dose to staff. Protocol implementation in preclinical cadaveric studies demonstrate integration of the C-arm with a navigation system for spine surgery guidance-specifically, minimally invasive vertebroplasty in which the system provided accurate guidance and visualization of needle placement and bone cement distribution. Cumulative dose including multiple intraoperative scans was -11.5 mGy for CBCT-guided thoracic vertebroplasty and -23.2 mGy for lumbar vertebroplasty, with dose to staff at tableside reduced to -1 min of fluoroscopy time (-4(0-60 microSv), compared to 5-11 min for the conventional approach. CONCLUSIONS Intraoperative CBCT using a high-performance mobile C-arm prototype demonstrates image quality suitable to guidance of spine surgery, with task-specific protocols providing an important basis for minimizing radiation dose, while maintaining image quality sufficient for surgical guidance. Images demonstrate a significant advance in spatial resolution and soft-tissue visibility, and CBCT guidance offers the potential to reduce fluoroscopy reliance, reducing cumulative dose to patient and staff. Integration with a surgical guidance system demonstrates precise tracking and visualization in up-to-date images (alleviating reliance on preoperative images only), including detection of errors or suboptimal surgical outcomes in the operating room.},

keywords = {CBCT, Image Guided Surgery, Spine, System Assessment},

pubstate = {published},

tppubtype = {article}

}

@article{reaungamornrat2011tracker,

title = {Tracker-on-C: A novel tracker configuration for image-guided therapy using a mobile C-arm},

author = {Sureerat Reaungamornrat and Yoshito Otake and Ali Uneri and Sebastian Schafer and J. Webster Stayman and Wojciech Zbijewski and Daniel J. Mirota and Jongheun Yoo and Sajendra Nithiananthan and A. Jay Khanna and Russell H. Taylor and Jeffrey H. Siewerdsen },

year  = {2011},

date = {2011-01-01},

journal = {Computer Assisted Radiology and Surgery, Berlin, Germany},

pages = {22--25},

keywords = {CBCT, Image Guided Surgery},

pubstate = {published},

tppubtype = {article}

}

@article{lee2011cone,

title = {Cone Beam CT-Assisted Endoscopic Sinus and Skull Base Surgery: Quantitative Analysis of Surgical Performance Using a Next-Generation C-Arm Prototype},

author = {Stella Lee and Gary L. Gallia and Douglas D. Reh and Sebastian Schafer and Ali Uneri and Daniel J. Mirota and Sajendra Nithiananthan and Yoshito Otake and J. Webster Stayman and Wojciech Zbijewski and Jeffrey H. Siewerdsen},

url = {http://www.thieme-connect.de/DOI/DOI?10.1055/s-2011-1274205},

doi = {10.1055/s-2011-1274205},

issn = {1531-5010},

year  = {2011},

date = {2011-01-01},

journal = {Skull Base},

volume = {21},

number = {S 01},

pages = {A030},

keywords = {CBCT, Head/Neck, Image Guided Surgery, System Assessment},

pubstate = {published},

tppubtype = {article}

}