@article {Singh2007b, title = {Simultaneous integrated boost of biopsy proven and MRI defined dominant intra-prostatic lesions to 95 Gray with IMRT: early results of a phase I NCI study}, journal = {Radiation Oncology}, volume = {2}, year = {2007}, pages = {36}, publisher = {Department of Radiation Medicine, Roswell Park Cancer Institute, Buffalo, USA singhanu@yahoo com}, abstract = {

BACKGROUND: To assess the feasibility, early toxicity of selective, IMRT-based dose escalation (simultaneous integrated boost) to biopsy proven dominant intra-prostatic lesions visible on MRI METHODS: Patients with localized prostate cancer, an abnormality within the prostate on endorectal coil MRI were eligible All patients underwent a MRI-guided transrectal biopsy at the location of the MRI abnormality Gold fiducial markers were also placed Several days later patients underwent another MRI scan for fusion with the treatment planning CT scan This fused MRI scan was used to delineate the region of the biopsy proven intra-prostatic lesion A 3 mm expansion was performed on the intra-prostatic lesions, defined as a separate volume within the prostate The lesion + 3 mm, the remainder of the prostate + 7 mm received 94 5/75 6 Gray (Gy) respectively in 42 fractions Daily seed position was verified to be within 3 mm RESULTS: Three patients were treated Follow-up was 18, 6, and 3 months respectively Two patients had a single intra-prostatic lesion One patient had 2 intra-prostatic lesions All four intra-prostatic lesions, with margin, were successfully targeted, treated to 94 5 Gy Two patients experienced acute RTOG grade 2 genitourinary (GU) toxicity One had grade 1 gastrointestinal (GI) toxicity All symptoms completely resolved by 3 months One patient had no acute toxicity CONCLUSION: These early results demonstrate the feasibility of using IMRT for simultaneous integrated boost to biopsy proven dominant intra-prostatic lesions visible on MRI The treatment was well tolerated

}, keywords = {adverse effects/methods, Biopsy, epidemiology, epidemiology/radiotherapy, Follow-Up Studies, Humans, Intensity-Modulated, Magnetic Resonance Imaging, Male, National Cancer Institute (U S ), Patient Selection, Prostatic Neoplasms, Questionnaires, Radiotherapy, Radiotherapy Dosage, United States}, doi = {10 1186/1748-717X-2-36}, url = {http://dx doi org/10 1186/1748-717X-2-36}, author = {Anurag K. Singh and Peter Guion and Nancy Sears-Crouse and Karen Ullman and Sharon Smith and Paul Albert and Gabor Fichtinger and Peter Choyke and Sheng Xu and Jochen Kruecker and Bradford Wood and Axel Krieger and Holly Ning} } @conference {Xu2006, title = {CT fluoroscopy-guided robotically-assisted lung biopsy}, booktitle = {Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display}, volume = {6141}, number = {1}, year = {2006}, pages = {61411L}, publisher = {SPIE}, organization = {SPIE}, doi = {10 1117/12 652882}, url = {http://link aip org/link/?PSI/6141/61411L/1}, author = {Sheng Xu and Gabor Fichtinger and Russell H. Taylor and Filip Banovac and Kevin Cleary}, editor = {Kevin Cleary and Robert L. Galloway, Jr.} } @article {Xu2006a, title = {Lung deformation estimation and four-dimensional CT lung reconstruction}, journal = {Journal of Academic Radiology}, volume = {13}, number = {9}, year = {2006}, month = {Sep}, pages = {1082{\textendash}1092}, publisher = {Philips Research North America, 345 Scarborough Road, Briarcliff Manor, NY 10510, USA sheng xu@philips com}, abstract = {

RATIONALE AND OBJECTIVES: Four-dimensional (4D) computed tomography (CT) can be used in radiation treatment planning to account for respiratory motion Current 4D CT techniques have limitations in either spatial or temporal resolution In addition, most of these techniques rely on auxiliary surrogates to relate the time of the CT scan to the patient{\textquoteright}s respiratory phase We propose a 4D CT method for lung applications to overcome these problems MATERIALS AND METHODS: A set of axial scans are taken at multiple table positions to obtain a series of two-dimensional images while the patient is breathing freely Each two-dimensional image is registered to a reference CT volume The deformation of the image with respect to the volume is used to synchronize the image with the respiratory cycle assuming that there is no phase variation along the craniocaudal direction The reconstructed 4D dataset is a series of deformable transformations of the reference volume RESULTS: A synthetic 4D dataset showed that the registration error is less than 5\% of the image deformation A swine study showed that the algorithm can generate better image quality than the image sorting method A respiratory-gated 4D dataset showed that the algorithm{\textquoteright}s result is consistent with the ground truth CONCLUSION: The algorithm can reconstruct good quality 4D images without external surrogates even if the CT scans are acquired under irregular respiratory motion The algorithm may allow for reduced radiation dose to the patient with a limited loss of image quality Although the phase variation exists along the craniocaudal direction, the 4D reconstruction is reasonably accurate

}, keywords = {Algorithms, Artifacts, Computer-Assisted, Humans, Imaging, Information Storage, Lung, methods, Movement, Phantoms, Radiographic Image Enhancement, Radiographic Image Interpretation, Radiography, Reproducibility of Results, Respiratory Mechanics, Retrieval, Sensitivity, Specificity, Three-Dimensional, Tomography, X-Ray Computed}, doi = {10 1016/j acra 2006 05 004}, url = {http://dx doi org/10 1016/j acra 2006 05 004}, author = {Sheng Xu and Russell H. Taylor and Gabor Fichtinger and Kevin Cleary} } @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 {Cleary2005, title = {Precision placement of instruments for minimally invasive procedures using a "needle driver" robot}, journal = {international journal of medical robotics computer assisted surgery MRCAS}, volume = {1}, number = {2}, year = {2005}, month = {Jan}, pages = {40{\textendash}47}, abstract = {

Medical practice continues to move toward less invasive procedures Many of these procedures require the precision placement of a needle in the anatomy Over the past several years, our research team has been investigating the use of a robotic needle driver to assist the physician in this task This paper summarizes our work in this area The robotic system is briefly described, followed by a description of a clinical trial in spinal nerve blockade The robot was used under joystick control to place a 22 gauge needle in the spines of 10 patients using fluoroscopic imaging The results were equivalent to the current manual procedure We next describe our follow-up clinical application in lung biopsy for lung cancer screening under CT fluoroscopy The system concept is discussed, the results of a phantom study are presented A start-up company named ImageGuide has recently been formed to commercialize the robot Their revised robot design is presented, along with plans to install a ceiling-mounted version of the robot in the CT fluoroscopy suite at Georgetown University

}, keywords = {Biopsy, Cadaver, Equipment Design, Fluoroscopy, Humans, Imaging, instrumentation, instrumentation/methods, Lung, Lung Neoplasms, methods, Minimally Invasive, Needles, Nerve Block, pathology, pathology/radiography, Phantoms, Randomized Controlled Trials as Topic, Robotics, Spinal Nerves, Surgical Procedures, Tomography, X-Ray Computed}, doi = {10 1002/rcs 40}, url = {http://dx doi org/10 1002/rcs 40}, author = {Kevin Cleary and Vance Watson and David Lindisch and Russell H. Taylor and Gabor Fichtinger and Sheng Xu and Charles White and John Donlon and Michael Taylor and Alexandru Patriciu and Dumitru Mazilu and Dan Stoianovici} } @conference {Xu2005a, title = {Registration and motion compensation of a needle placement robot for CT-guided spinal procedures}, booktitle = {Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display}, volume = {5744}, number = {1}, year = {2005}, pages = {661-669}, publisher = {SPIE}, organization = {SPIE}, doi = {10 1117/12 594731}, url = {http://link aip org/link/?PSI/5744/661/1}, author = {Sheng Xu and Kevin Cleary and Dan Stoianovici and Gabor Fichtinger}, editor = {Robert L. Galloway, Jr. and Kevin Cleary} } @conference {Xu2005, title = {Validation of 3D motion tracking of pulmonary lesions using CT fluoroscopy images for robotically assisted lung biopsy}, booktitle = {Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display}, volume = {5744}, number = {1}, year = {2005}, pages = {60-68}, publisher = {SPIE}, organization = {SPIE}, doi = {10 1117/12 594910}, url = {http://link aip org/link/?PSI/5744/60/1}, author = {Sheng Xu and Gabor Fichtinger and Russell H. Taylor and Kevin Cleary}, editor = {Robert L. Galloway, Jr. and Kevin Cleary} } @conference {Xu2004, title = {3D motion tracking of pulmonary lesions using CT fluoroscopy images for robotically assisted lung biopsy}, booktitle = {Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display}, volume = {5367}, number = {1}, year = {2004}, pages = {394-402}, publisher = {SPIE}, organization = {SPIE}, doi = {10 1117/12 534056}, url = {http://link aip org/link/?PSI/5367/394/1}, author = {Sheng Xu and Gabor Fichtinger and Russell H. Taylor and Kevin Cleary}, editor = {Robert L. Galloway, Jr.} } @article {Fichtinger2001a, title = {Approximate Volumetric Reconstruction from Projected Images}, journal = {Lecture Notes in Computer Science Medical Image Computing and Computer-Assisted Intervention (MICCAI)}, volume = {2208}, year = {2001}, pages = {416-424}, author = {Gabor Fichtinger and Sheng Xu and Attila Tanacs and Kieran P Murphy and Lee Myers and Jeffery Williams} } @article {Cleary2001, title = {Automatic registration for percutaneous vertebral body tracking}, journal = {International Congress Series}, volume = {1230}, year = {2001}, pages = {1215 - 1216}, issn = {0531-5131}, doi = {DOI: 10 1016/S0531-5131(01)00045-0 }, url = {http://www sciencedirect com/science/article/B7581-47V9SDF-8B/2/b4387cef8e19f8c7dbc5d52fa97414de}, author = {Kevin Cleary and Sheng Xu and Gabor Fichtinger and Neil Glossop} }