186 research outputs found

    Image fusion techniques in permanent seed implantation

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    Segmentation, separation and pose estimation of prostate brachytherapy seeds in CT images.

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    International audienceIn this paper, we address the development of an automatic approach for the computation of pose information (position + orientation) of prostate brachytherapy loose seeds from 3D CT images. From an initial detection of a set of seed candidates in CT images using a threshold and connected component method, the orientation of each individual seed is estimated by using the principal components analysis (PCA) method. The main originality of this approach is the ability to classify the detected objects based on a priori intensity and volume information and to separate groups of closely spaced seeds using three competing clustering methods: the standard and a modified k-means method and a Gaussian mixture model with an Expectation-Maximization algorithm. Experiments were carried out on a series of CT images of two phantoms and patients. The fourteen patients correspond to a total of 1063 implanted seeds. Detections are compared to manual segmentation and to related work in terms of detection performance and calculation time. This automatic method has proved to be accurate and fast including the ability to separate groups of seeds in a reliable way and to determine the orientation of each seed. Such a method is mandatory to be able to compute precisely the real dose delivered to the patient post-operatively instead of assuming the alignment of seeds along the theoretical insertion direction of the brachytherapy needles

    Deformable registration of X-ray and MRI for post-implant dosimetry in low-dose-rate prostate brachytherapy

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    Purpose Dosimetric assessment following permanent prostate brachytherapy (PPB) commonly involves seed localization using CT and prostate delineation using coregistered MRI. However, pelvic CT leads to additional imaging dose and requires significant resources to acquire and process both CT and MRI. In this study, we propose an automatic postimplant dosimetry approach that retains MRI for soft‐tissue contouring, but eliminates the need for CT and reduces imaging dose while overcoming the inconsistent appearance of seeds on MRI with three projection x rays acquired using a mobile C‐arm. Methods Implanted seeds are reconstructed using x rays by solving a combinatorial optimization problem and deformably registered to MRI. Candidate seeds are located in MR images using local hypointensity identification. X ray‐based seeds are registered to these candidate seeds in three steps: (a) rigid registration using a stochastic evolutionary optimizer, (b) affine registration using an iterative closest point optimizer, and (c) deformable registration using a local feature point search and nonrigid coherent point drift. The algorithm was evaluated using 20 PPB patients with x rays acquired immediately postimplant and T2‐weighted MR images acquired the next day at 1.5 T with mean 0.8 × 0.8 × 3.0 mmurn:x-wiley:00942405:media:mp13667:mp13667-math-0001 voxel dimensions. Target registration error (TRE) was computed based on the distance from algorithm results to manually identified seed locations using coregistered CT acquired the same day as the MRI. Dosimetric accuracy was determined by comparing prostate D90 determined using the algorithm and the ground truth CT‐based seed locations. Results The mean ± standard deviation TREs across 20 patients including 1774 seeds were 2.23 ± 0.52 mm (rigid), 1.99 ± 0.49 mm (rigid + affine), and 1.76 ± 0.43 mm (rigid + affine + deformable). The corresponding mean ± standard deviation D90 errors were 5.8 ± 4.8%, 3.4 ± 3.4%, and 2.3 ± 1.9%, respectively. The mean computation time of the registration algorithm was 6.1 s. Conclusion The registration algorithm accuracy and computation time are sufficient for clinical PPB postimplant dosimetry

    3D BrachyView System

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    Prostate cancer is quickly becoming the most common form of cancer across the globe, and is commonly treated with low dose rate brachytherapy due to its curative measures and highly conformal dose delivery. It is important to ensure there is a means of real time monitoring of the dose and seed placements when radioactive seeds are implanted in the prostate gland during a low dose rate brachytherapy treatment. The BrachyView system presents as a unique system that provides the capability of 3D seed reconstruction within an intraoperative setting. In this thesis the BrachyView system is tested for its suitability, accuracy and the system is further developed so that its application in real-time intraoperative dosime-try can become a reality. The system was tested with a clinically relevant number of seeds, 98, where previously the system had only been tested with a maximum number of 30 seeds. The BrachyView system was able to reconstruct 91.8% of implanted seeds from the 98 seed dataset with an average overall discrepancy of 3.65 mm without the application of the baseline subtraction algorithm, however with its application to the data the detection eïŹƒciency was improved to 100% and an overall positional accuracy of 11.5%, correlating to a reduced overall discrepancy of 3.23 mm, was noted. It was found that with seed numbers of 30 or lower that the addition of a background subtrac-tion algorithm was not necessary, whereas for datasets containing a clinically relevant number of seeds the application of a background subtraction algorithm was paramount to reducing the noise, scatter and means for identiïŹcation of newly implanted seeds that may be masked by those seed previously implanted

    SEED LOCALIZATION IN IMAGE-GUIDED PROSTATE BRACHYTHERAPY INTRAOPERATIVE DOSIMETRY SYSTEMS

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    Prostate cancer is the most common cancer among men in the United States. Many treatments are available, but prostate brachytherapy is acknowledged as a standard treatment for patients with localized cancer. Prostate brachytherapy is a minimally invasive surgery involving the permanent implantation of approximately 100 grain-sized radioactive seeds into the prostate. While effective, contemporary practice of brachytherapy is suboptimal because it spreads the stages of planning, implant, and dosimetry over several weeks. Although brachytherapy is now moving towards intraoperative treatment planning (ITP) which integrates all three stages into a single day in the operating room,the American Brachytherapy Society states, “the major current limitation of ITP is the inability to localize the seeds in relation to the prostate.” While the procedure is traditionally guided by transrectal ultrasound (TRUS), poor image quality prevents TRUS from accurately localizing seeds to compute dosimetry intraoperatively. Alternative methods exist, but are generally impractical to implement in clinics worldwide. The subject of this dissertation is the development of two intraoperative dosimetry systems to practically solve the problem of seed localization in ITP. The first system fuses TRUS with X-ray fluoroscopy using the ubiquitous non-isocentric mobile C-arm.The primary contributions of this dissertation include an automatic fiducial and seed segmentation algorithm for fluoroscopic images, as well as a next generation intraoperative dosimetry system based on a fiducial with seed-like markers. Results from over 30 patients prove that both contributions are significant for localizing seeds with high accuracy and demonstrate the capability of detecting cold spots. The second intraoperative dosimetry system is based on photoacoustic imaging, and uses the already implemented TRUS probe to detect ultrasonic waves converted from electromagnetic waves generated by a laser. The primary contributions of this dissertation therefore also include a prototype benchtop photoacoustic system and an improved clinical version usable in the operating room. Results from gelatin phantoms, an ex vivo dog prostate, and an in vivo dog study reveal that multiple seeds are clearly visible with high contrast using photoacoustic imaging at clinically safe laser energies.Together, both systems significantly progress the latest technologies to provide optimal care to patients through ITP

    Automatic C-arm pose estimation via 2D/3D hybrid registration of a radiographic fiducial

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    ABSTRACT Motivation: In prostate brachytherapy, real-time dosimetry would be ideal to allow for rapid evaluation of the implant quality intra-operatively. However, such a mechanism requires an imaging system that is both real-time and which provides, via multiple C-arm fluoroscopy images, clear information describing the three-dimensional position of the seeds deposited within the prostate. Thus, accurate tracking of the C-arm poses proves to be of critical importance to the process. Methodology: We compute the pose of the C-arm relative to a stationary radiographic fiducial of known geometry by employing a hybrid registration framework. Firstly, by means of an ellipse segmentation algorithm and a 2D/3D feature based registration, we exploit known FTRAC geometry to recover an initial estimate of the C-arm pose. Using this estimate, we then initialize the intensity-based registration which serves to recover a refined and accurate estimation of the C-arm pose. Results: Ground-truth pose was established for each C-arm image through a published and clinically tested segmentation-based method. Using 169 clinical C-arm images and a ±10° and ±10 mm random perturbation of the ground-truth pose, the average rotation and translation errors were 0.68° (std = 0.06°) and 0.64 mm (std = 0.24 mm). Conclusion: Fully automated C-arm pose estimation using a 2D/3D hybrid registration scheme was found to be clinically robust based on human patient data

    Imaging in Radiation Oncology: A Perspective

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    This paper reviews the integration of imaging and radiation oncology, and discusses challenges and opportunities for improving the practice of radiation oncology with imaging

    CT and MRI fusion for postimplant prostate brachytherapy evaluation

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    Postoperative evaluation of prostate brachytherapy is typically performed using CT, which does not have sufficient soft tissue contrast for accurate anatomy delineation. MR-CT fusion enables more accurate localization of both anatomy and implanted radioactive seeds, and hence, improves the accuracy of postoperative dosimetry. We propose a method for automatic registration of MR and CT images without a need for manual initialization. Our registration method employs a point-to-volume registration scheme during which localized seeds in the CT images, produced by commercial treatment planning systems as part of the standard of care, are rigidly registered to preprocessed MRI images. We tested our algorithm on ten patient data sets and achieved an overall registration error of 1.6 ± 0.8 mm with a running time of less than 20s. With high registration accuracy and computational speed, and no need for manual intervention, our method has the potential to be employed in clinical applications

    Image-Fusion for Biopsy, Intervention, and Surgical Navigation in Urology

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