@article {DiMaio2007b, title = {Challenges in image-guided therapy system design}, journal = {Neuroimage}, volume = {37 Suppl 1}, year = {2007}, pages = {S144{\textendash}S151}, publisher = {Brigham, Women{\textquoteright}s Hospital, 75 Francis St , Boston, MA 02115, USA simond@bwh harvard edu}, abstract = {

System development for image-guided therapy (IGT), or image-guided interventions (IGI), continues to be an area of active interest across academic, industry groups This is an emerging field that is growing rapidly: major academic institutions, medical device manufacturers have produced IGT technologies that are in routine clinical use, dozens of high-impact publications are published in well regarded journals each year, and several small companies have successfully commercialized sophisticated IGT systems In meetings between IGT investigators over the last two years, a consensus has emerged that several key areas must be addressed collaboratively by the community to reach the next level of impact, efficiency in IGT research, development to improve patient care These meetings culminated in a two-day workshop that brought together several academic, industrial leaders in the field today The goals of the workshop were to identify gaps in the engineering infrastructure available to IGT researchers, develop the role of research funding agencies, the recently established US-based National Center for Image Guided Therapy (NCIGT), and ultimately to facilitate the transfer of technology among research centers that are sponsored by the National Institutes of Health (NIH) Workshop discussions spanned many of the current challenges in the development, deployment of new IGT systems Key challenges were identified in a number of areas, including: validation standards; workflows, use-cases, and application requirements; component reusability;, device interface standards This report elaborates on these key points, proposes research challenges that are to be addressed by a joint effort between academic, industry, and NIH participants

}, keywords = {adverse effects/instrumentation/trends, Algorithms, Computational Biology, Computer Systems, Computer-Assisted, Humans, instrumentation/trends, Knowledge Bases, Models, National Institutes of Health (U S ), Neurosurgical Procedures, Organizational, Outcome Assessment (Health Care), Reproducibility of Results, Robotics, Software, Surgery, Treatment Outcome, United States}, doi = {10 1016/j neuroimage 2007 04 026}, url = {http://dx doi org/10 1016/j neuroimage 2007 04 026}, author = {Simon DiMaio and Tina Kapur and Kevin Cleary and Stephen Aylward and Peter Kazanzides and Kirby Vosburgh and Randy Ellis and James Duncan and Keyvan Farahani and Heinz Lemke and T. M. Peters and William Bill Lorensen and David Gobbi and John Haller and Laurence Larry Clarke and Stephen Pizer and Russell H. Taylor and Robert L. Galloway, Jr. and Gabor Fichtinger and Nobuhiko Hata and Kimberly Lawson and Clare M Tempany and Ron Kikinis and Ferenc Jolesz} } @article {Chowning2006, title = {A preliminary analysis and model of prostate injection distributions}, journal = {The Prostate}, volume = {66}, number = {4}, year = {2006}, month = {Mar}, pages = {344{\textendash}357}, publisher = {Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA schowning@mri jhu edu}, abstract = {

PURPOSE: Understanding the internal dynamics of prostate injections, particularly injection pattern distribution is a key step to developing new therapies for prostate disease that may be best served with a direct injection approach Due to excellent properties involving liquid contrast agents, MRI can be used for targeting, monitoring of injections into organs, tissues MATERIALS AND METHODS: Eleven intraprostatic injections were performed in vivo with canines using a custom transrectal guiding, imaging system for use in a standard 1 5 T MR scanner In addition, 25 injections were performed on excised cadaveric human prostates, using a MedRad Spectris injector system MRI was used to guide the injections, monitor intraparenchymal injection distribution RESULTS: T1, T2-weighted MR images were correlated with histology to produce three-dimensional data sets that can be used to analyze trends in injection patterns This analysis was used to develop strategies for injection prediction such as gadolinium pre-injections, diffusion-weighted imaging guidance In addition, a rough model of prostate injections is described, and a preliminary injection guide is developed that takes into account the individual clinician{\textquoteright}s goals for therapy CONCLUSIONS: MR visualization of injected therapeutic agents allows for prediction, monitoring of drug distributions, possibly improving efficacy, reducing side effects Injection analysis, modeling may be used to assist in optimizing clinical treatments that require or would benefit from focal parenchymal injections into the prostate

}, keywords = {Animals, Antineoplastic Agents, Dogs, drug therapy, Forecasting, Magnetic Resonance Imaging, Male, Models, pharmacokinetics/pharmacology, Prostate, Prostatic Neoplasms, Rectum, Theoretical}, doi = {10 1002/pros 20298}, url = {http://dx doi org/10 1002/pros 20298}, author = {Scott Chowning and Robert Susil and Axel Krieger and Gabor Fichtinger and Whitcomb, Louis L. and Ergin Atalar} } @article {Fichtinger2006, title = {Robotically assisted prostate brachytherapy with transrectal ultrasound guidance{\textendash}Phantom experiments}, journal = {Brachytherapy}, volume = {5}, number = {1}, year = {2006}, pages = {14{\textendash}26}, publisher = {Engineering Research Center, The Johns Hopkins University, Baltimore, MD 21218-2682, USA gabor@cs jhu edu}, abstract = {

PURPOSE: To report the preliminary experimental results obtained with a robot-assisted transrectal ultrasound (TRUS)-guided prostate brachytherapy system METHODS AND MATERIALS: The system consists of a TRUS unit, a spatially coregistered needle insertion robot, and an FDA-approved treatment planning, image-registered implant system The robot receives each entry/target coordinate pair of the implant plan, inserts a preloaded needle, and then the seeds are deposited The needles/sources are tracked in TRUS, thus allowing the plan to be updated as the procedure progresses RESULTS: The first insertion attempt was recorded for each needle, without adjustment All clinically relevant locations were reached in a prostate phantom Nonparallel, parallel needle trajectories were demonstrated Based on TRUS, the average transverse placement error was 2 mm (worst case 2 5 mm, 80\% less than 2 mm), and the average sagittal error was 2 5 mm (worst case 5 0 mm, 70\% less than 2 5 mm) CONCLUSIONS: The concept, technical viability of robot-assisted brachytherapy were demonstrated in phantoms The kinematically decoupled robotic assistant device is inherently safe Overall performance was promising, but further optimization is necessary to prove the possibility of improved dosimetry

}, keywords = {Anatomic, Brachytherapy, Endosonography, Equipment Design, Humans, instrumentation, Male, methods, Models, Prostatic Neoplasms, radiotherapy/ultrasonography, Rectum, Robotics}, doi = {10 1016/j brachy 2005 10 003}, url = {http://dx doi org/10 1016/j brachy 2005 10 003}, author = {Gabor Fichtinger and E. Clif Burdette and Attila Tanacs and Alexandru Patriciu and Dumitru Mazilu and Whitcomb, Louis L. and Dan Stoianovici} } @article {Boctor2006b, title = {Ultrasound monitoring of tissue ablation via deformation model and shape priors}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {9}, number = {Pt 2}, year = {2006}, pages = {405{\textendash}412}, abstract = {

A rapid approach to monitor ablative therapy through optimizing shape, elasticity parameters is introduced Our motivating clinical application is targeting, intraoperative monitoring of hepatic tumor thermal ablation, but the method translates to the generic problem of encapsulated stiff masses (solid organs, tumors, ablated lesions, etc ) in ultrasound imaging The approach involves the integration of the following components: a biomechanical computational model of the tissue, a correlation approach to estimate/track tissue deformation, and an optimization method to solve the inverse problem, recover the shape parameters in the volume of interest Successful convergence, reliability studies were conducted on simulated data Then ex-vivo studies were performed on 18 ex-vivo bovine liver samples previously ablated under ultrasound monitoring in controlled laboratory environment While B-mode ultrasound does not clearly identify the development of necrotic lesions, the proposed technique can potentially segment the ablation zone The same framework can also yield both partial, full elasticity reconstruction

}, keywords = {Algorithms, Animals, Automated, Biological, Cattle, Computer-Assisted, Elasticity, Hepatectomy, Image Enhancement, Image Interpretation, Imaging, Interventional, Liver, Mechanical, methods, Models, Pattern Recognition, physiology/surgery/ultrasonography, Reproducibility of Results, Sensitivity, Specificity, Statistical, Stress, Subtraction Technique, Surgery, Three-Dimensional, Ultrasonography}, author = {Emad Boctor and Michelle de Oliveira and Michael Choti and Roger Ghanem and Russell H. Taylor and Gregory D. Hager and Gabor Fichtinger} } @article {Xu2005b, title = {Lung deformation estimation and four-dimensional CT lung reconstruction}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {8}, number = {Pt 2}, year = {2005}, pages = {312{\textendash}319}, abstract = {

Four-dimensional (4D) computed tomography (CT) image acquisition is a useful technique in radiation treatment planning, interventional radiology in that it can account for respiratory motion of lungs Current 4D lung reconstruction techniques have limitations in either spatial or temporal resolution In addition, most of these techniques rely on auxiliary surrogates to relate the time of CT scan to the patient{\textquoteright}s respiratory phase In this paper, we propose a novel 4D CT lung reconstruction, deformation estimation algorithm Our algorithm is purely image based The algorithm can reconstruct high quality 4D images even if the original images are acquired under irregular respiratory motion The algorithm is validated using synthetic 4D lung data Experimental results from a swine study data are also presented

}, keywords = {Algorithms, Animals, Artificial Intelligence, Biological, Computer Simulation, Computer-Assisted, Elasticity, Humans, Imaging, Lung, methods, Models, physiology/radiography, Radiographic Image Enhancement, Radiographic Image Interpretation, Reproducibility of Results, Respiratory Mechanics, Sensitivity, Specificity, Swine, Three-Dimensional, Tomography, X-Ray Computed}, author = {Sheng Xu and Russell H. Taylor and Gabor Fichtinger and Kevin Cleary} } @article {Jain2005e, title = {Matching and reconstruction of brachytherapy seeds using the Hungarian algorithm (MARSHAL)}, journal = {Journal of Medical Physics}, volume = {32}, number = {11}, year = {2005}, month = {Nov}, pages = {3475{\textendash}3492}, abstract = {

Intraoperative dosimetric quality assurance in prostate brachytherapy critically depends on discerning the three-dimensional (3D) locations of implanted seeds The ability to reconstruct the implanted seeds intraoperatively will allow us to make immediate provisions for dosimetric deviations from the optimal implant plan A method for seed reconstruction from segmented C-arm fluoroscopy images is proposed The 3D coordinates of the implanted seeds can be calculated upon resolving the correspondence of seeds in multiple x-ray images We formalize seed-matching as a combinatorial optimization problem, which has salient features: (a) extensively studied solutions by the computer science community; (b) proof for the nonexistence of any polynomial time exact algorithm;, (c) a practical pseudo-polynomial algorithm that mostly runs in O(N3) time using any number of images We prove that two images are insufficient to correctly match the seeds, while a third image renders the matching problem to be of nonpolynomial complexity We utilize the special structure of the problem, propose a pseudopolynomial time algorithm Using three presegmented images, matching, reconstruction of brachytherapy seeds using the Hungarian algorithm achieved complete matching in simulation experiments;, 98 5\% in phantom experiments 3D reconstruction error for correctly matched seeds has a mean of 0 63 mm, and 0 9 mm for incorrectly matched seeds The maximum seed reconstruction error in each implant was typically around 1 32 mm Both on synthetic data, in phantom experiments, matching rate, reconstruction error achieved using presegmented images was found to be sufficient for prostate brachytherapy The algorithm is extendable to deal with arbitrary number of images without any loss in speed or accuracy The algorithm is sufficiently generic to provide a practical solution to any correspondence problem, across different imaging modalities, features

}, keywords = {Algorithms, Automated, Brachytherapy, Calibration, Computer Simulation, Computer-Assisted, Humans, Image Interpretation, Imaging, Male, methods, Models, Numerical Analysis, Pattern Recognition, Phantoms, Prostatic Neoplasms, Radiographic Image Enhancement, Radiographic Image Interpretation, Radiometry, Radiotherapy, Radiotherapy Dosage, Radiotherapy Planning, Reproducibility of Results, Statistical, Theoretical, Three-Dimensional, Time Factors, Ultrasonography}, author = {Ameet K. Jain and Yu Zhou and Tabish Mustufa and E. Clif Burdette and Gregory Chirikjian and Gabor Fichtinger} } @article {Shen2004a, title = {Optimized prostate biopsy via a statistical atlas of cancer spatial distribution}, journal = {Medical image analysis}, volume = {8}, number = {2}, year = {2004}, month = {Jun}, pages = {139{\textendash}150}, abstract = {

A methodology is presented for constructing a statistical atlas of spatial distribution of prostate cancer from a large patient cohort, and it is used for optimizing needle biopsy An adaptive-focus deformable model is used for the spatial normalization, registration of 100 prostate histological samples, which were provided by the Center for Prostate Disease Research of the US Department of Defense, resulting in a statistical atlas of spatial distribution of prostate cancer Based on this atlas, a statistical predictive model was developed to optimize the needle biopsy sites, by maximizing the probability of detecting cancer Experimental results using cross-validation show that the proposed method can detect cancer with a 99\% success rate using seven needles, in these samples

}, keywords = {Algorithms, Biological, Biopsy, Cohort Studies, Computer Simulation, Computer-Assisted, Forecasting, Humans, Image Processing, Imaging, Male, Models, Needle, pathology, Probability, Prostate, Prostatic Neoplasms, Reproducibility of Results, Statistical, statistics /\&/ numerical data, Three-Dimensional}, doi = {10 1016/j media 2003 11 002}, url = {http://dx doi org/10 1016/j media 2003 11 002}, author = {Dinggang Shen and Zhiqiang Lao and Jianchao Zeng and Wei Zhang and Isabel Sesterhenn and Leon Sun and Judd Moul and Edward Herskovits and Gabor Fichtinger and Christos Davatzikos} }