Tools for improving high-dose-rate prostate cancer brachytherapy using three-dimensional ultrasound and magnetic resonance imaging

High-dose-rate brachytherapy (HDR-BT) is an interstitial technique for the treatment of intermediate and high-risk localized prostate cancer that involves placement of a radiation source directly inside the prostate using needles. Dose-escalated whole-gland treatments have led to improvements in survival, and tumour-targeted treatments may offer future improvements in therapeutic ratio. The efficacy of tumour-targeted HDR-BT depends on imaging tools to enable accurate dose delivery to prostate sub-volumes. This thesis is focused on implementing ultrasound tools to improve HDR-BT needle localization accuracy and efficiency, and evaluating dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) for tumour localization. First, we implemented a device enabling sagittally-reconstructed 3D (SR3D) ultrasound, which provides sub-millimeter resolution in the needle insertion direction. We acquired SR3D and routine clinical images in a cohort of 12 consecutive eligible HDR-BT patients, with a total of 194 needles. The SR3D technique provided needle insertion depth errors within 5 mm for 93\% of needles versus 76\% for the clinical imaging technique, leading to increased precision in dose delivered to the prostate. Second, we implemented an algorithm to automatically segment multiple HDR-BT needles in a SR3D image. The algorithm was applied to the SR3D images from the first patient cohort, demonstrating mean execution times of 11.0 s per patient and successfully segmenting 82\% of needles within 3 mm. Third, we augmented SR3D imaging with live-2D sagittal ultrasound for needle tip localization. This combined technique was applied to another cohort of 10 HDR-BT patients, reducing insertion depth errors compared to routine imaging from a range of [-8.1 mm, 7.7 mm] to [-6.2 mm, 5.9 mm]. Finally, we acquired DCE-MRI in 16 patients scheduled to undergo prostatectomy, using either high spatial resolution or high temporal resolution imaging, and compared the images to whole-mount histology. The high spatial resolution images demonstrated improved high-grade cancer classification compared to the high temporal resolution images, with areas under the receiver operating characteristic curve of 0.79 and 0.70, respectively. In conclusion, we have translated and evaluated specialized imaging tools for HDR-BT which are ready to be tested in a clinical trial investigating tumour-targeted treatment

Software and Hardware-based Tools for Improving Ultrasound Guided Prostate Brachytherapy

Minimally invasive procedures for prostate cancer diagnosis and treatment, including biopsy and brachytherapy, rely on medical imaging such as two-dimensional (2D) and three-dimensional (3D) transrectal ultrasound (TRUS) and magnetic resonance imaging (MRI) for critical tasks such as target definition and diagnosis, treatment guidance, and treatment planning. Use of these imaging modalities introduces challenges including time-consuming manual prostate segmentation, poor needle tip visualization, and variable MR-US cognitive fusion. The objective of this thesis was to develop, validate, and implement software- and hardware-based tools specifically designed for minimally invasive prostate cancer procedures to overcome these challenges. First, a deep learning-based automatic 3D TRUS prostate segmentation algorithm was developed and evaluated using a diverse dataset of clinical images acquired during prostate biopsy and brachytherapy procedures. The algorithm significantly outperformed state-of-the-art fully 3D CNNs trained using the same dataset while a segmentation time of 0.62 s demonstrated a significant reduction compared to manual segmentation. Next, the impact of dataset size, image quality, and image type on segmentation performance using this algorithm was examined. Using smaller training datasets, segmentation accuracy was shown to plateau with as little as 1000 training images, supporting the use of deep learning approaches even when data is scarce. The development of an image quality grading scale specific to 3D TRUS images will allow for easier comparison between algorithms trained using different datasets. Third, a power Doppler (PD) US-based needle tip localization method was developed and validated in both phantom and clinical cases, demonstrating reduced tip error and variation for obstructed needles compared to conventional US. Finally, a surface-based MRI-3D TRUS deformable image registration algorithm was developed and implemented clinically, demonstrating improved registration accuracy compared to manual rigid registration and reduced variation compared to the current clinical standard of physician cognitive fusion. These generalizable and easy-to-implement tools have the potential to improve workflow efficiency and accuracy for minimally invasive prostate procedures

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

Transrectal ultrasound image processing for brachytherapy applications

In this thesis, we propose a novel algorithm for detecting needles and their corresponding implanted radioactive seed locations in the prostate. The seed localization process is carried out efficiently using separable Gaussian filters in a probabilistic Gibbs random field framework. An approximation of the needle path through the prostate volume is obtained using a polynomial fit. The seeds are then detected and assigned to their corresponding needles by calculating local maxima of the voronoi region around the needle position. In our experiments, we were able to successfully localize over 85% of the implanted seeds. Furthermore, as a regular part of a brachytherapy cancer treatment, patient’s prostate is scanned using a trans-rectal ultrasound probe, its boundary is manually outlined, and its volume is estimated for dosimetry purposes. In this thesis, we also propose a novel semi-automatic segmentation algorithm for prostate boundary detection that requires a reduced amount of radiologist’s input, and thus speeds up the surgical procedure. Saved time can be used to re-scan the prostate during the operation and accordingly adjust the treatment plan. The proposed segmentation algorithm utilizes texture differences between ultrasound images of the prostate tissue and the surrounding tissues. It is carried out in 5 the polar coordinate system and it uses three-dimensional data correlation to improve the smoothness and reliability of the segmentation. Test results show that the boundary segmentation obtained from the algorithm can reduce manual input by the factor of 3, without significantly affecting the accuracy of the segmentation (i.e. semi-automatically estimated prostate volume is within 90% of the original estimate)

Review of strategies for MRI based reconstruction of endocavitary and interstitial applicators in brachytherapy of cervical cancer

Brachytherapy plays an essential role in the curative intent management of locally advanced cervical cancer. The introduction of the magnetic resonance (MR) as a preferred image modality and the development of new type of applicators with interstitial components have further improved its benefits.The aim of this work is to review the current status of one important aspect in the cervix cancer brachytherapy procedure, namely catheter reconstruction.MR compatible intracavitary and interstitial applicators are described. Considerations about the use of MR imaging (MRI) regarding appropriate strategies for applicator reconstruction, technical requirements, MR sequences, patient preparation and applicator commissioning are included.It is recommendable to perform the reconstruction process in the same image study employed by the physician for contouring, that is, T2 weighted (T2W) sequences. Nevertheless, a clear identification of the source path inside the catheters and the applicators is a challenge when using exclusively T2W sequences. For the intracavitary component of the implant, sometimes the catheters may be filled with some substance that produces a high intensity signal on MRI. However, this strategy is not feasible for plastic tubes or titanium needles, which, moreover, induce magnetic susceptibility artifacts. In these situations, the use of applicator libraries available in the treatment planning system (TPS) is useful, since they not only include accurate geometrical models of the intracavitary applicators, but also recent developments have made possible the implementation of the interstitial component. Another strategy to improve the reconstruction process is based on the incorporation of MR markers, such as small pellets, to be used as anchor points.Many institutions employ computed tomography (CT) as a supporting image modality. The registration of CT and MR image sets should be carefully performed, and its uncertainty previously assessed. Besides, an important research work is being carried out regarding the use of ultrasound and electromagnetic tracking technologies

Image-based registration methods for quantification and compensation of prostate motion during trans-rectal ultrasound (TRUS)-guided biopsy

Prostate biopsy is the clinical standard for cancer diagnosis and is typically performed under two-dimensional (2D) transrectal ultrasound (TRUS) for needle guidance. Unfortunately, most early stage prostate cancers are not visible on ultrasound and the procedure suffers from high false negative rates due to the lack of visible targets. Fusion of pre-biopsy MRI to 3D TRUS for targeted biopsy could improve cancer detection rates and volume of tumor sampled. In MRI-TRUS fusion biopsy systems, patient or prostate motion during the procedure causes misalignments in the MR targets mapped to the live 2D TRUS images, limiting the targeting accuracy of the biopsy system. In order to sample smallest clinically significant tumours of 0.5 cm3with 95% confidence, the root mean square (RMS) error of the biopsy system needs to be The target misalignments due to intermittent prostate motion during the procedure can be compensated by registering the live 2D TRUS images acquired during the biopsy procedure to the pre-acquired baseline 3D TRUS image. The registration must be performed both accurately and quickly in order to be useful during the clinical procedure. We developed an intensity-based 2D-3D rigid registration algorithm and validated it by calculating the target registration error (TRE) using manually identified fiducials within the prostate. We discuss two different approaches that can be used to improve the robustness of this registration to meet the clinical requirements. Firstly, we evaluated the impact of intra-procedural 3D TRUS imaging on motion compensation accuracy since the limited anatomical context available in live 2D TRUS images could limit the robustness of the 2D-3D registration. The results indicated that TRE improved when intra-procedural 3D TRUS images were used in registration, with larger improvements in the base and apex regions as compared with the mid-gland region. Secondly, we developed and evaluated a registration algorithm whose optimization is based on learned prostate motion characteristics. Compared to our initial approach, the updated optimization improved the robustness during 2D-3D registration by reducing the number of registrations with a TRE \u3e 5 mm from 9.2% to 1.2% with an overall RMS TRE of 2.3 mm. The methods developed in this work were intended to improve the needle targeting accuracy of 3D TRUS-guided biopsy systems. The successful integration of the techniques into current 3D TRUS-guided systems could improve the overall cancer detection rate during the biopsy and help to achieve earlier diagnosis and fewer repeat biopsy procedures in prostate cancer diagnosis

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

A Novel System and Image Processing for Improving 3D Ultrasound-guided Interventional Cancer Procedures

Image-guided medical interventions are diagnostic and therapeutic procedures that focus on minimizing surgical incisions for improving disease management and reducing patient burden relative to conventional techniques. Interventional approaches, such as biopsy, brachytherapy, and ablation procedures, have been used in the management of cancer for many anatomical regions, including the prostate and liver. Needles and needle-like tools are often used for achieving planned clinical outcomes, but the increased dependency on accurate targeting, guidance, and verification can limit the widespread adoption and clinical scope of these procedures. Image-guided interventions that incorporate 3D information intraoperatively have been shown to improve the accuracy and feasibility of these procedures, but clinical needs still exist for improving workflow and reducing physician variability with widely applicable cost-conscience approaches. The objective of this thesis was to incorporate 3D ultrasound (US) imaging and image processing methods during image-guided cancer interventions in the prostate and liver to provide accessible, fast, and accurate approaches for clinical improvements. An automatic 2D-3D transrectal ultrasound (TRUS) registration algorithm was optimized and implemented in a 3D TRUS-guided system to provide continuous prostate motion corrections with sub-millimeter and sub-degree error in 36 ± 4 ms. An automatic and generalizable 3D TRUS prostate segmentation method was developed on a diverse clinical dataset of patient images from biopsy and brachytherapy procedures, resulting in errors at gold standard accuracy with a computation time of 0.62 s. After validation of mechanical and image reconstruction accuracy, a novel 3D US system for focal liver tumor therapy was developed to guide therapy applicators with 4.27 ± 2.47 mm error. The verification of applicators post-insertion motivated the development of a 3D US applicator segmentation approach, which was demonstrated to provide clinically feasible assessments in 0.246 ± 0.007 s. Lastly, a general needle and applicator tool segmentation algorithm was developed to provide accurate intraoperative and real-time insertion feedback for multiple anatomical locations during a variety of clinical interventional procedures. Clinical translation of these developed approaches has the potential to extend the overall patient quality of life and outcomes by improving detection rates and reducing local cancer recurrence in patients with prostate and liver cancer