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

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

Brachytherapy Seed and Applicator Localization via Iterative Forward Projection Matching Algorithm using Digital X-ray Projections

Interstitial and intracavitary brachytherapy plays an essential role in management of several malignancies. However, the achievable accuracy of brachytherapy treatment for prostate and cervical cancer is limited due to the lack of intraoperative planning and adaptive replanning. A major problem in implementing TRUS-based intraoperative planning is an inability of TRUS to accurately localize individual seed poses (positions and orientations) relative to the prostate volume during or after the implantation. For the locally advanced cervical cancer patient, manual drawing of the source positions on orthogonal films can not localize the full 3D intracavitary brachytherapy (ICB) applicator geometry. A new iterative forward projection matching (IFPM) algorithm can explicitly localize each individual seed/applicator by iteratively matching computed projections of the post-implant patient with the measured projections. This thesis describes adaptation and implementation of a novel IFPM algorithm that addresses hitherto unsolved problems in localization of brachytherapy seeds and applicators. The prototype implementation of 3-parameter point-seed IFPM algorithm was experimentally validated using a set of a few cone-beam CT (CBCT) projections of both the phantom and post-implant patient’s datasets. Geometric uncertainty due to gantry angle inaccuracy was incorporated. After this, IFPM algorithm was extended to 5-parameter elongated line-seed model which automatically reconstructs individual seed orientation as well as position. The accuracy of this algorithm was tested using both the synthetic-measured projections of clinically-realistic Model-6711 125I seed arrangements and measured projections of an in-house precision-machined prostate implant phantom that allows the orientations and locations of up to 100 seeds to be set to known values. The seed reconstruction error for simulation was less than 0.6 mm/3o. For the physical phantom experiments, IFPM absolute accuracy for position, polar angle, and azimuthal angel were (0.78 ± 0.57) mm, (5.8 ± 4.8)o, and (6.8 ± 4.0)o, respectively. It avoids the need to match corresponding seeds in each projection and accommodates incomplete data, overlapping seed clusters, and highly-migrated seeds. IFPM was further generalized from 5-parameter to 6-parameter model which was needed to reconstruct 3D pose of arbitrary-shape applicators. The voxelized 3D model of the applicator was obtained from external complex combinatorial geometric modeling. It is then integrated into the forward projection matching method for computing the 2D projections of the 3D ICB applicators, iteratively. The applicator reconstruction error for simulation was about 0.5 mm/2o. The residual 2D registration error (positional difference) between computed and actual measured applicator images was less than 1 mm for the intrauterine tandem and about 1.5 mm for the bilateral colpostats in each detector plane. By localizing the applicator’s internal structure and the sources, the effect of intra and inter-applicator attenuation can be included in the resultant dose distribution and CBCT metal streaking artifact mitigation. The localization accuracy of better than 1 mm and 6o has the potential to support more accurate Monte Carlo-based or 2D TG-43 dose calculations in clinical practice. It is hoped the clinical implementation of IFPM approach to localize elongated line-seed/applicator for intraoperative brachytherapy planning may have a positive impact on the treatment of prostate and cervical cancers