Errors in device localization in MRI using Z-frames.

The use of a passive MRI-visible tracking frame is a common method of localizing devices in MRI space for MRI-guided procedures. One of the most common tracking frame designs found in the literature is the z-frame, as it allows six degree-of-freedom pose estimation using only a single image slice. Despite the popularity of this design, it is susceptible to errors in pose estimation due to various image distortion mechanisms in MRI. In this paper, the absolute error in using a z-frame to localize a tool in MRI is quantified over various positions of the z-frame relative to the MRI isocenter, and for various levels of static magnetic field inhomogeneity. It was found that the error increases rapidly with distance from the isocenter in both the horizontal and vertical directions, but the error is much less sensitive to position when multiple contiguous slices are used with slice-select gradient nonlinearity correction enabled, as opposed to the more common approach of only using a single image slice. In addition, the error is found to increase rapidly with an increasing level of static field inhomogeneity, even with the z-frame placed within 10 cm of the isocenter

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

Deep Learning in Cardiology

The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving complicated medical tasks or for creating insights using big data. Deep learning has emerged as a more accurate and effective technology in a wide range of medical problems such as diagnosis, prediction and intervention. Deep learning is a representation learning method that consists of layers that transform the data non-linearly, thus, revealing hierarchical relationships and structures. In this review we survey deep learning application papers that use structured data, signal and imaging modalities from cardiology. We discuss the advantages and limitations of applying deep learning in cardiology that also apply in medicine in general, while proposing certain directions as the most viable for clinical use.Comment: 27 pages, 2 figures, 10 table

Towards Closed-loop, Robot Assisted Percutaneous Interventions under MRI Guidance

Image guided therapy procedures under MRI guidance has been a focused research area over past decade. Also, over the last decade, various MRI guided robotic devices have been developed and used clinically for percutaneous interventions, such as prostate biopsy, brachytherapy, and tissue ablation. Though MRI provides better soft tissue contrast compared to Computed Tomography and Ultrasound, it poses various challenges like constrained space, less ergonomic patient access and limited material choices due to its high magnetic field. Even after, advancements in MRI compatible actuation methods and robotic devices using them, most MRI guided interventions are still open-loop in nature and relies on preoperative or intraoperative images. In this thesis, an intraoperative MRI guided robotic system for prostate biopsy comprising of an MRI compatible 4-DOF robotic manipulator, robot controller and control application with Clinical User Interface (CUI) and surgical planning applications (3DSlicer and RadVision) is presented. This system utilizes intraoperative images acquired after each full or partial needle insertion for needle tip localization. Presented system was approved by Institutional Review Board at Brigham and Women\u27s Hospital(BWH) and has been used in 30 patient trials. Successful translation of such a system utilizing intraoperative MR images motivated towards the development of a system architecture for close-loop, real-time MRI guided percutaneous interventions. Robot assisted, close-loop intervention could help in accurate positioning and localization of the therapy delivery instrument, improve physician and patient comfort and allow real-time therapy monitoring. Also, utilizing real-time MR images could allow correction of surgical instrument trajectory and controlled therapy delivery. Two of the applications validating the presented architecture; closed-loop needle steering and MRI guided brain tumor ablation are demonstrated under real-time MRI guidance

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

Improving Radiotherapy Targeting for Cancer Treatment Through Space and Time

Radiotherapy is a common medical treatment in which lethal doses of ionizing radiation are preferentially delivered to cancerous tumors. In external beam radiotherapy, radiation is delivered by a remote source which sits several feet from the patient\u27s surface. Although great effort is taken in properly aligning the target to the path of the radiation beam, positional uncertainties and other errors can compromise targeting accuracy. Such errors can lead to a failure in treating the target, and inflict significant toxicity to healthy tissues which are inadvertently exposed high radiation doses. Tracking the movement of targeted anatomy between and during treatment fractions provides valuable localization information that allows for the reduction of these positional uncertainties. Inter- and intra-fraction anatomical localization data not only allows for more accurate treatment setup, but also potentially allows for 1) retrospective treatment evaluation, 2) margin reduction and modification of the dose distribution to accommodate daily anatomical changes (called `adaptive radiotherapy\u27), and 3) targeting interventions during treatment (for example, suspending radiation delivery while the target it outside the path of the beam). The research presented here investigates the use of inter- and intra-fraction localization technologies to improve radiotherapy to targets through enhanced spatial and temporal accuracy. These technologies provide significant advancements in cancer treatment compared to standard clinical technologies. Furthermore, work is presented for the use of localization data acquired from these technologies in adaptive treatment planning, an investigational technique in which the distribution of planned dose is modified during the course of treatment based on biological and/or geometrical changes of the patient\u27s anatomy. The focus of this research is directed at abdominal sites, which has historically been central to the problem of motion management in radiation therapy

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

Passive Resonant Coil Based Fast Registration And Tracking System For Real-Time Mri-Guided Minimally Invasive Surgery

This thesis presents a single-slice based fast stereotactic registration and tracking technique along with a corresponding modular system for guiding robotic mechanism or interventional instrument to perform needle-based interventions under live MRI guidance. The system can provide tracking of full 6 degree-of-freedom (DOF) in stereotactic interventional surgery based upon a single, rapidly acquired cross-sectional image. The whole system is constructed with a modular data transmission software framework and mechanical structure so that it supports remote supervision and manipulation between a 3D Matlab tracking user interface (UI) and an existing MRI robot controller by using the OpenIGTLink network communication protocol. It provides better closed-loop control by implementing a feedback output interface to the MRI-guided robot. A new compact fiducial frame design is presented, and the fiducial is wrapped with a passive resonant coil. The coil resonates at the Larmor frequency for 3T MRI to enhance signal strength and enable for rapid imaging. The fiducial can be attached near the distal end of the robot and coaxially with a needle so as to visualize target tissue and track the surgical tool synchronously. The MRI-compatible design of fiducial frame, robust tracking algorithm and modular interface allow this tracking system to be conveniently used on different robots or devices and in different size of MRI bores. Several iterations of the tracking fiducial and passive resonant coils were constructed and evaluated in a Phillips Achieva 3T MRI. To assess accuracy and robustness of the tracking algorithm, 25 groups of images with different poses were successively scanned along specific sequence in and MRI experiment. The translational RMS error along depth is 0.271mm with standard deviation of 0.277mm for totally 100 samples. The overall angular RMS error is less than 0.426 degree with standard deviation of 0.526 degree for totally 150 samples. The passive resonant coils were shown to significantly increase signal intensity in the fiducial relative to the surroundings and provide for rapid imaging with low flip angles