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spie Medical Imaging 50th anniversary: historical review of the image-guided procedures, robotic interventions, and modeling conference

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JOURNAL OF MEDICAL IMAGING 2022年第S1期9卷 012206页

作者： Siewerdsen, Jeffrey H. Linte, Cristian A. Johns Hopkins Univ Dept Biomed Engn Baltimore MD 21218 USA Univ Texas MD Anderson Canc Ctr Dept Imaging Phys Houston TX 77030 USA Inst Data Sci Oncol Houston TX USA Rochester Inst Technol Dept Biomed Engn Rochester NY 14623 USA

Purpose: Among the conferences comprising the Medical Imaging Symposium is the MI104 conference currently titled image-guided procedures, robotic interventions, and modeling, although its name has evolved through at least nine iterations over the last 30 years. Here, we discuss the important role that this forum has presented for researchers in the field during this time. Approach: The origins of the conference are traced from its roots in image Capture and Display in the late 1980s, and some of the major themes for which the conference and its proceedings have provided a valuable forum are highlighted. Results: These major themes include image display/visualization, surgical tracking/navigation, surgical robotics, interventional imaging, image registration, and modeling. Exceptional work from the conference is highlighted by summarizing keynote lectures, the top 50 most downloaded proceedings papers over the last 30 years, the most downloaded paper each year, and the papers earning student paper and young scientist awards. Conclusions: Looking forward and considering the burgeoning technologies, algorithms, and markets related to image-guided and robot-assisted interventions, we anticipate growth and ever increasing quality of the conference as well as increased interaction with sister conferences within the symposium. (C) 2022 Society of Photo-Optical Instrumentation Engineers (spie)

关键词： image-guided interventions medical robotics image registration image visualization image display interventional imaging

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Medical robotics and Computer-Integrated Interventional Medicine

Medical Robotics and Computer-Integrated Interventional Medi...

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conference on Medical Imaging - image-guided procedures, robotic interventions and modeling

作者： Taylor, Russell H. Johns Hopkins Univ 3400 N Charles St Baltimore MD 21218 USA

ISBN: (纸本)9780819489654

Computer-Integrated Interventional Medicine (CIIM) promises to have a profound impact on health care in the next 20 years, much as and for many of the same reasons that the marriage of computers and information processing methods with other technology have had on manufacturing, transportation, and other sectors of our society. Our basic premise is that the steps of creating patient-specific computational models, using these models for planning, registering the models and plans with the actual patient in the operating room, and using this information with appropriate technology to assist in carrying out and monitoring the intervention are best viewed as part of a complete patient-specific intervention process that occurs over many time scales. Further, the information generated in computer-integrated interventions can be captured and analyzed statistically to improve treatment processes. This paper will explore these themes briefly, using examples drawn from our work at the Engineering Research Center for Computer-Integrated Surgical Systems and Technology (CISST ERC).

关键词： Computer-Integrated Surgery Computer-Integrated interventions Medical robotics image-guided interventions Medical Imaging and modeling Experience Based Interventional Medicine

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image-guided procedures, robotic interventions, and modeling

Image-guided procedures, robotic interventions, and modeling

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Medical Imaging 2018: image-guided procedures, robotic interventions, and modeling

作者： Fei, Baowei Webster, Robert J.

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modeling and simulation of tumor-influenced high resolution real-time physics-based breast models for model-guided robotic interventions

Modeling and simulation of tumor-influenced high resolution ...

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conference on spie image-guided procedures, robotic interventions, and modeling

作者： Neylon, John Hasse, Katelyn Sheng, Ke Santhanam, Anand P. Univ Calif Los Angeles Dept Radiat Oncol Los Angeles CA 90024 USA

ISBN: (纸本)9781510600218

Breast radiation therapy is typically delivered to the patient in either supine or prone position. Each of these positioning systems has its limitations in terms of tumor localization, dose to the surrounding normal structures, and patient comfort. We envision developing a pneumatically controlled breast immobilization device that will enable the benefits of both supine and prone positioning. In this paper, we present a physics-based breast deformable model that aids in both the design of the breast immobilization device as well as a control module for the device during every day positioning. The model geometry is generated from a subject's CT scan acquired during the treatment planning stage. A GPU based deformable model is then generated for the breast. A mass-spring-damper approach is then employed for the deformable model, with the spring modeled to represent a hyperelastic tissue behavior. Each voxel of the CT scan is then associated with a mass element, which gives the model its high resolution nature. The subject specific elasticity is then estimated from a CT scan in prone position. Our results show that the model can deform at >60 deformations per second, which satisfies the real-time requirement for robotic positioning. The model interacts with a computer designed immobilization device to position the breast and tumor anatomy in a reproducible location. The design of the immobilization device was also systematically varied based on the breast geometry, tumor location, elasticity distribution and the reproducibility of the desired tumor location.

关键词： biomechanical modeling breast immobilization radiotherapy

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Intraoperative Brain Tumor Resection Cavity Characterization with Conoscopic Holography

Intraoperative Brain Tumor Resection Cavity Characterization...

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conference on Medical Imaging - image-guided procedures, robotic interventions and modeling

作者： Simpson, Amber L. Burgner, Jessica Chen, Ishita Pheiffer, Thomas S. Sun, Kay Thompson, Reid C. Webster, Robert J., III Miga, Michael I. Vanderbilt Univ Dept Biomed Engn Nashville TN 37235 USA

ISBN: (纸本)9780819489654

Brain shift compromises the accuracy of neurosurgical image-guided interventions if not corrected by either intraoperative imaging or computational modeling. The latter requires intraoperative sparse measurements for constraining and driving model-based compensation strategies. Conoscopic holography, an interferometric technique that measures the distance of a laser light illuminated surface point from a fixed laser source, was recently proposed for non-contact surface data acquisition in image-guided surgery and is used here for validation of our modeling strategies. In this contribution, we use this inexpensive, hand-held conoscopic holography device for intraoperative validation of our computational modeling approach to correcting for brain shift. Laser range scan, instrument swabbing, and conoscopic holography data sets were collected from two patients undergoing brain tumor resection therapy at Vanderbilt University Medical Center. The results of our study indicate that conoscopic holography is a promising method for surface acquisition since it requires no contact with delicate tissues and can characterize the extents of structures within confined spaces. We demonstrate that for two clinical cases, the acquired conoprobe points align with our model-updated images better than the uncorrected images lending further evidence that computational modeling approaches improve the accuracy of image-guided surgical interventions in the presence of soft tissue deformations.

关键词： Tumors Brain Holography Lawrencium Data acquisition 3D modeling Mathematical modeling Signal to noise ratio Neuroimaging Tissues

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Kernel-based modeling of pneumothorax deformation using intraoperative cone-beam CT images

Kernel-based modeling of pneumothorax deformation using intr...

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conference on Medical Imaging - image-guided procedures, robotic interventions, and modeling

作者： Maekawa, Hinako Nakao, Megumi Mineura, Katsutaka Chen-Yoshikawa, Toyofumi F. Matsuda, Tetsuya Kyoto Univ Grad Sch Informat Kyoto Japan Kyoto Univ Hosp Dept Thorac Surg Kyoto Japan Nagoya Univ Hosp Dept Thorac Surg Nagoya Aichi Japan

ISBN: (纸本)9781510640269

In this study, we introduce statistical modeling methods for pneumothorax deformation using paired cone-beam computed tomography (CT) images. We designed a deformable mesh registration framework for shape changes involving non-linear deformation and rotation of the lungs. The registered meshes with local correspondences are available for both surgical guidance in thoracoscopic surgery and building statistical deformation models with inter-patient variations. In addition, a kernel-based deformation learning framework is proposed to reconstruct intraoperative deflated states of the lung from the preoperative CT models. This paper reports the findings of pneumothorax deformation and evaluation results of the kernel-based deformation framework.

关键词： Pneumothorax deformation Registration Statistical modeling Cone-beam CT Thoracoscopic Surgery

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image Guidance Improves Localization of Sonographically Occult Colorectal Liver Metastases

Image Guidance Improves Localization of Sonographically Occu...

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conference on Medical Imaging - image-guided procedures, robotic interventions, and modeling

作者： Leung, Universe Simpson, Amber L. Adams, Lauryn B. Jarnagin, William R. Miga, Michael I. Kingham, T. Peter Mem Sloan Kettering Canc Ctr Dept Surg New York NY 10021 USA Vanderbilt Univ Dept Biomed Engn Nashville TN 37235 USA

ISBN: (纸本)9781628415056

Assessing the therapeutic benefit of surgical navigation systems is a challenging problem in image-guided surgery. The exact clinical indications for patients that may benefit from these systems is not always clear, particularly for abdominal surgery where image-guidance systems have failed to take hold in the same way as orthopedic and neurosurgical applications. We report interim analysis of a prospective clinical trial for localizing small colorectal liver metastases using the Explorer system (Pathfinder Technologies, Nashville, TN). Colorectal liver metastases are small lesions that can be difficult to identify with conventional intraoperative ultrasound due to echogeneity changes in the liver as a result of chemotherapy and other preoperative treatments. Interim analysis with eighteen patients shows that 9 of 15 (60%) of these occult lesions could be detected with image guidance. image guidance changed intraoperative management in 3 (17%) cases. These results suggest that image guidance is a promising tool for localization of small occult liver metastases and that the indications for image-guided surgery are expanding.

关键词： Liver Tumors Surgery image-guided intervention Ultrasonography 3D modeling Colorectal cancer Cancer Clinical trials Liver cancer

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modeling the Surgical Exposure of Anatomy in Robot-Assisted Laparoscopic Partial Nephrectomy

Modeling the Surgical Exposure of Anatomy in Robot-Assisted ...

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Medical Imaging conference - image-guided procedures, robotic interventions, and modeling

作者： Kokko, Michael A. Seigne, John D. Van Citters, Douglas W. Halter, Ryan J. Dartmouth Coll Thayer Sch Engn 14 Engn Dr Hanover NH 03755 USA Dartmouth Coll Geisel Sch Med 1 Rope Ferry Rd Hanover NH 03755 USA Dartmouth Hitchcock Med Ctr Div Urol 1 Med Ctr Dr Lebanon NH 03756 USA

ISBN: (纸本)9781510633988

Although robotic instrumentation has revolutionized manipulation in oncologic laparoscopy, there remains a significant need for image guidance during the exposure portion of certain abdominal procedures. The high degree of mobility and potential for deformation associated with abdominal organs and related structures poses a significant challenge to implementing image based navigation for the initial phase of robot-assisted laparoscopic partial nephrectomy (RALPN). This work introduces two key elements of a RALPN exposure simulation framework: a model for laparoscopic exposure and a compact representation of anatomical geometry suitable for integration into a statistical estimation framework. Data to drive the exposure simulation were collected during a clinical RALPN case in which the robotic endoscope was tracked in six dimensions. An initial rigid registration was performed between a preoperative CT scan and the frame of the optical tracker, allowing the endoscope trajectory to be replayed over tomography to simulate anatomical observations with realistic kinematics. CT data from five study subjects were combined with four publicly available datasets to produce a mean kidney shape. This template kidney was fit back to each of the input models by optimally tuning a set of eight parameters, achieving an average RMSE of 2.18mm. These developments represent important steps toward a full, clinically-relevant framework for simulating organ exposure and testing navigation algorithms. In future work, a particle filter estimation scheme will be integrated into the simulation to incrementally optimize correspondences between parametric anatomical models and simulated or reconstructed endoscopic observations.

关键词： Surgical Navigation robotic Surgery Partial Nephrectomy Surgical Exposure Anatomical modeling

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Coronary Arteries Motion modeling on 2-D X-ray images

Coronary Arteries Motion Modeling on 2-D X-ray Images

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conference on Medical Imaging - image-guided procedures, robotic interventions and modeling

作者： Gao, Yang Sundar, Hari Siemens Corp Res Dept Imaging & Visualizat Princeton NJ 08540 USA

ISBN: (纸本)9780819489654

During interventional procedures, 3D imaging modalities like CT and MRI are not commonly used due to interference with the surgery and radiation exposure concerns. Therefore, real-time information is usually limited and building models of cardiac motion are difficult. In such case, vessel motion modeling based on 2-D angiography images become indispensable. Due to issues with existing vessel segmentation algorithms and the lack of contrast in occluded vessels, manual segmentation of certain branches is usually necessary. In addition, such occluded branches are the most important vessels during coronary interventions and obtaining motion models for these can greatly help in reducing the procedure time and radiation exposure. Segmenting different cardiac phases independently does not guarantee temporal consistency and is not efficient for occluded branches required manual segmentation. In this paper, we propose a coronary motion modeling system which extracts the coronary tree for every cardiac phase, maintaining the segmentation by tracking the coronary tree during the cardiac cycle. It is able to map every frame to the specific cardiac phase, thereby inferring the shape information of the coronary arteries using the model corresponding to its phase. Our experiments show that our motion modeling system can achieve promising results with real-time performance.

关键词： Cardiac Angiography Coronary motion modeling motion tracking

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Multi-body statistical shape representation of anatomy for navigation in Robot-Assisted Laparoscopic Partial Nephrectomy

Multi-body statistical shape representation of anatomy for n...

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conference on Medical Imaging - image-guided procedures, robotic interventions, and modeling

ISBN: (纸本)9781510640269

image guidance for abdominal procedures requires an anatomical model capable of representing significant displacement and deformation of relevant tissues in a computationally efficient manner. This work evaluates the suitability of statistical shape modeling to represent key structures in Robot Assisted Laparoscopic Partial Nephrectomy (RALPN) both individually, and also as a multi-body composite model. Tomography obtained from subjects in an ongoing RALPN study was used to produce surface model representations of the kidneys, abdominal aorta, and inferior vena cava. Each structure was resliced and remeshed in a standardized fashion to allow for extraction of the principal modes of variation. Reduced parameter representations of the example structures based on the strongest eigenmodes indicate that <5mm average RMSE modeling accuracy can be achieved with four parameters for the individual models and eight parameters for the four-body composite model. The magnitude of centroid displacements observed under the principal modes of variation is consistent with literature-reported values, suggesting that this approach may be suitable for image guidance in RALPN.

关键词： Statistical Shape modeling Partial Nephrectomy Anatomical modeling Tissue Displacement Tissue Deformation

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