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

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

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

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

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

New Technology and Techniques for Needle-Based Magnetic Resonance Image-Guided Prostate Focal Therapy

The most common diagnosis of prostate cancer is that of localized disease, and unfortunately the optimal type of treatment for these men is not yet certain. Magnetic resonance image (MRI)-guided focal laser ablation (FLA) therapy is a promising potential treatment option for select men with localized prostate cancer, and may result in fewer side effects than whole-gland therapies, while still achieving oncologic control. The objective of this thesis was to develop methods of accurately guiding needles to the prostate within the bore of a clinical MRI scanner for MRI-guided FLA therapy. To achieve this goal, a mechatronic needle guidance system was developed. The system enables precise targeting of prostate tumours through angulated trajectories and insertion of needles with the patient in the bore of a clinical MRI scanner. After confirming sufficient accuracy in phantoms, and good MRI-compatibility, the system was used to guide needles for MRI-guided FLA therapy in eight patients. Results from this case series demonstrated an improvement in needle guidance time and ease of needle delivery compared to conventional approaches. Methods of more reliable treatment planning were sought, leading to the development of a systematic treatment planning method, and Monte Carlo simulations of needle placement uncertainty. The result was an estimate of the maximum size of focal target that can be confidently ablated using the mechatronic needle guidance system, leading to better guidelines for patient eligibility. These results also quantified the benefit that could be gained with improved techniques for needle guidance

SEED LOCALIZATION IN IMAGE-GUIDED PROSTATE BRACHYTHERAPY INTRAOPERATIVE DOSIMETRY SYSTEMS

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

A 3D US Guidance System for Permanent Breast Seed Implantation: Development and Validation

Permanent breast seed implantation (PBSI) is a promising breast radiotherapy technique that suffers from operator dependence. We propose and have developed an intraoperative 3D ultrasound (US) guidance system for PBSI. A tracking arm mounted to a 3D US scanner registers a needle template to the image. Images were validated for linear and volumetric accuracy, and image quality in a volunteer. The tracking arm was calibrated, and the 3D image registered to the scanner. Tracked and imaged needle positions were compared to assess accuracy and a patient-specific phantom procedure guided with the system. Median/mean linear and volumetric error was ±1.1% and ±4.1%, respectively, with clinically suitable volunteer scans. Mean tracking arm error was 0.43mm and 3D US target registration error ≤0.87mm. Mean needle tip/trajectory error was 2.46mm/1.55°. Modelled mean phantom procedure seed displacement was 2.50mm. To our knowledge, this is the first reported PBSI phantom procedure with intraoperative 3D image guidance

A Study of Image-based C-arm Tracking Using Minimal Fiducials

Image-based tracking of the c-arm continues to be a critical and challenging problem for many clinical applications due to its widespread use in many computer-assisted procedures that rely upon its accuracy for further planning, registration, and reconstruction tasks. In this thesis, a variety of approaches are presented to improve current c-arm tracking methods and devices for intra-operative procedures. The first approach presents a novel two-dimensional fiducial comprising a set of coplanar conics and an improved single-image pose estimation algorithm that addresses segmentation errors using a mathematical equilibration approach. Simulation results show an improvement in the mean rotation and translation errors by factors of 4 and 1.75, respectively, as a result of using the proposed algorithm. Experiments using real data obtained by imaging a simple precisely machined model consisting of three coplanar ellipses retrieve pose estimates that are in good agreement with those obtained by a ground truth optical tracker. This two-dimensional fiducial can be easily placed under the patient allowing a wide field of view for the motion of the c-arm. The second approach employs learning-based techniques to two-view geometrical theories. A demonstrative algorithm is used to simultaneously tackle matching and segmentation issues of features segmented from pairs of acquired images. The corrected features can then be used to retrieve the epipolar geometry which can ultimately provide pose parameters using a one-dimensional fiducial. The problem of match refinement for epipolar geometry estimation is formulated in a reinforcement-learning framework. Experiments demonstrate the ability to both reject false matches and fix small localization errors in the segmentation of true noisy matches in a minimal number of steps. The third approach presents a feasibility study for an approach that entirely eliminates the use of tracking fiducials. It relies only on preoperative data to initialize a point-based model that is subsequently used to iteratively estimate the pose and the structure of the point-like intraoperative implant using three to six images simultaneously. This method is tested in the framework of prostate brachytherapy in which preoperative data including planned 3-D locations for a large number of point-like implants called seeds is usually available. Simultaneous pose estimation for the c-arm for each image and localization of the seeds is studied in a simulation environment. Results indicate mean reconstruction errors that are less than 1.2 mm for noisy plans of 84 seeds or fewer. These are attained when the 3D mean error introduced to the plan as a result of adding Gaussian noise is less than 3.2 mm

New Mechatronic Systems for the Diagnosis and Treatment of Cancer

Both two dimensional (2D) and three dimensional (3D) imaging modalities are useful tools for viewing the internal anatomy. Three dimensional imaging techniques are required for accurate targeting of needles. This improves the efficiency and control over the intervention as the high temporal resolution of medical images can be used to validate the location of needle and target in real time. Relying on imaging alone, however, means the intervention is still operator dependent because of the difficulty of controlling the location of the needle within the image. The objective of this thesis is to improve the accuracy and repeatability of needle-based interventions over conventional techniques: both manual and automated techniques. This includes increasing the accuracy and repeatability of these procedures in order to minimize the invasiveness of the procedure. In this thesis, I propose that by combining the remote center of motion concept using spherical linkage components into a passive or semi-automated device, the physician will have a useful tracking and guidance system at their disposal in a package, which is less threatening than a robot to both the patient and physician. This design concept offers both the manipulative transparency of a freehand system, and tremor reduction through scaling currently offered in automated systems. In addressing each objective of this thesis, a number of novel mechanical designs incorporating an remote center of motion architecture with varying degrees of freedom have been presented. Each of these designs can be deployed in a variety of imaging modalities and clinical applications, ranging from preclinical to human interventions, with an accuracy of control in the millimeter to sub-millimeter range

Image Guided Robots for Urology

This dissertation addresses the development of medical image-guided robots and their applications in urology. Image-guided robots integrate medical image information with robotic precision to assist the planning and execution of the image-guided interventions. Robots guided by two different image modalities, ultrasound and MR image, were developed. Ultrasound image-guided robots manipulate an ultrasound probe and a needle-guide that are calibrated with respect to the robot for image-guided targeting. A method for calibration was developed and verified through the image-guided targeting experiments. Robotic manipulation of the calibrated probe allows acquisition of image slices at precise location, which can be combined to generate a 3D ultrasound image. Software for 3D ultrasound image acquisition, processing, and segmentation was developed as a part of the image-guided robot system. The feasibility of several image-guided intervention procedures using the ultrasound image-guided robot system was tested. The robot was used in a clinical trial of intraoperative transrectal ultrasound (TRUS) guided prostatectomy. The accuracy of TRUS-guided prostate biopsy using the robot was evaluated in a comparative study versus the classic human operation of the probe. Robot controlled palpation and image processing methods were developed for ultrasound elastography imaging of the prostate. An ultrasound to CT image-fusion method using the robot as a common reference was developed for percutaneous access of the kidney. MRI-guided robots were developed for transrectal and transperineal prostate biopsy. Extensive in-vitro tests were performed to ensure MRI compatibility and image-guided accuracy of the robots. The transrectal robot was evaluated in an animal study and the transperineal robot is undergoing a clinical trial. The collection of methods and algorithms presented in this dissertation can contribute to the development of image-guided robots that may provide less invasive and more precise interventions in urology, interventional radiology, and other fields