Biomechanical Modeling and Inverse Problem Based Elasticity Imaging for Prostate Cancer Diagnosis

Early detection of prostate cancer plays an important role in successful prostate cancer treatment. This requires screening the prostate periodically after the age of 50. If screening tests lead to prostate cancer suspicion, prostate needle biopsy is administered which is still considered as the clinical gold standard for prostate cancer diagnosis. Given that needle biopsy is invasive and is associated with issues including discomfort and infection, it is desirable to develop a prostate cancer diagnosis system that has high sensitivity and specificity for early detection with a potential to improve needle biopsy outcome. Given the complexity and variability of prostate cancer pathologies, many research groups have been pursuing multi-parametric imaging approach as no single modality imaging technique has proven to be adequate. While imaging additional tissue properties increases the chance of reliable prostate cancer detection and diagnosis, selecting an additional property needs to be done carefully by considering clinical acceptability and cost. Clinical acceptability entails ease with respect to both operating by the radiologist and patient comfort. In this work, effective tissue biomechanics based diagnostic techniques are proposed for prostate cancer assessment with the aim of early detection and minimizing the numbers of prostate biopsies. The techniques take advantage of the low cost, widely available and well established TRUS imaging method. The proposed techniques include novel elastography methods which were formulated based on an inverse finite element frame work. Conventional finite element analysis is known to have high computational complexity, hence computation time demanding. This renders the proposed elastography methods not suitable for real-time applications. To address this issue, an accelerated finite element method was proposed which proved to be suitable for prostate elasticity reconstruction. In this method, accurate finite element analysis of a large number of prostates undergoing TRUS probe loadings was performed. Geometry input and displacement and stress fields output obtained from the analysis were used to train a neural network mapping function to be used for elastopgraphy imaging of prostate cancer patients. The last part of the research presented in this thesis tackles an issue with the current 3D TRUS prostate needle biopsy. Current 3D TRUS prostate needle biopsy systems require registering preoperative 3D TRUS to intra-operative 2D TRUS images. Such image registration is time-consuming while its real-time implementation is yet to be developed. To bypass this registration step, concept of a robotic system was proposed which can reliably determine the preoperative TRUS probe position relative to the prostate to place at the same position relative to the prostate intra-operatively. For this purpose, a contact pressure feedback system is proposed to ensure similar prostate deformation during 3D and 2D image acquisition in order to bypass the registration step

Dual-camera infrared guidance for computed tomography biopsy procedures

A CT-guided biopsy is a specialised surgical procedure whereby a needle is used to withdraw tissue or fluid specimen from a lesion of interest. The needle is guided while being viewed by a clinician on a computed tomography (CT) scan. CT guided biopsies invariably expose patients and operators to high dosage of radiation and are lengthy procedures where the lack of spatial referencing while guiding the needle along the required entry path are some of the diffculties currently encountered. This research focuses on addressing two of the challenges clinicians currently face when performing CT-guided biopsy procedures. The first challenge is the lack of spatial referencing during a biopsy procedure, with the requirement for improved accuracy and reduction in the number of repeated scans. In order to achieve this an infrared navigation system was designed and implemented where an existing approach was subsequently extended to help guide the clinician in advancing the biopsy needle. This extended algorithm computed a scaled estimate of the needle endpoint and assists with navigating the biopsy needle through a dedicated and custom built graphical user interface. The second challenge was to design and implement a training environment where clinicians could practice different entry angles and scenarios. A prototype training module was designed and built to provide simulated biopsy procedures in order to help increase spatial referencing. Various experiments and different scenarios were designed and tested to demonstrate the correctness of the algorithm and provide real-life simulated scenarios where the operators had a chance to practice different entry angles and familiarise themselves with the equipment. A comprehensive survey was also undertaken to investigate the advantages and disadvantages of the system

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

Theoretical and Experimental Tools for Clinical Translation of Quantitative Tissue Optical Sensing.

Quantitative tissue optical spectroscopy has been considered as a promising method for clinical diagnosis, owing to its ability to non-invasively give an objective assessment of biological tissues at cellular and sub-cellular levels. In spite of recent advances in optics and the computational power, not many quantitative tissue optical sensing technologies have been translated into clinical practice. In order to translate this technology in the clinics, we need to further improve the technology. To name a few, we need accurate and rapid quantification method for a real-time diagnostic feedback. Next, we need computational methods for complex tissue-optics problems. Also, we need a novel approach in probe design for the inaccessible organs. This dissertation focuses on the development, verification and validation of theoretical (mathematical and computational) and experimental (instrumental) tool set to promote the translation of quantitative tissue optical spectroscopy into clinical diagnostic applications. For the mathematical tool, a direct-fit photon tissue interaction (DF-PTI) model that could rapidly and accurately extract the parameters associated biophysical features was developed and validated to characterize the precursor lesions of pancreatic cancer. A rapid scattering model on pancreatic tissue reflectance based on principal components analysis (PCA) results was also developed. The diagnostic capability of scattering properties obtained was demonstrated on an 18-patient data set using a rigorous statistical method, which implied the potential of reflectance spectroscopy for real-time detection of pancreatic cancer. For the computational tool, a ray-traced Monte Carlo (RTMC) simulation for the design of fluorescence spectroscopy or imaging system utilizing complex optics to probe turbid biological tissues was devised. This new method was verified computationally with epithelial tissue models and experimentally using tissue-simulating optical phantoms. For the instrumental tool, the design and development of minimally-invasive diagnostic technologies employing optoelectronic components were discussed. In this dissertation, we focused on detection of pancreatic cancer, which has the worst prognosis among other major cancers. Pancreatic tissues were employed as our model system to validate our developed tools. The developed technology and tools can be applied to a variety of other human tissue sites to help in the translation of quantitative tissue optical sensing in a clinical setting.PhDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111401/1/paulslee_1.pd

Sensorisation of a novel biologically inspired flexible needle

Percutaneous interventions are commonly performed during minimally invasive brain surgery, where a straight rigid instrument is inserted through a small incision to access a deep lesion in the brain. Puncturing a vessel during this procedure can be a life-threatening complication. Embedding a forward-looking sensor in a rigid needle has been proposed to tackle this problem; however, using a rigid needle, the procedure needs to be interrupted if a vessel is detected. Steerable needle technology could be used to avoid obstacles, such as blood vessels, due to its ability to follow curvilinear paths, but research to date was lacking in this respect. This thesis aims to investigate the deployment of forward-looking sensors for vessel detection in a steerable needle. The needle itself is based on a bioinspired programmable bevel-tip needle (PBN), a multi-segment design featuring four hollow working channels. In this thesis, laser Doppler flowmetry (LDF) is initially characterised to ensure that the sensor fulfils the minimum requirements for it to be used in conjunction with the needle. Subsequently, vessel reconstruction algorithms are proposed. To determine the axial and off-axis position of the vessel with respect to the probe, successive measurements of the LDF sensor are used. Ideally, full knowledge of the vessel orientation is required to execute an avoidance strategy. Using two LDF probes and a novel signal processing method described in this thesis, the predicted possible vessel orientations can be reduced to four, a setup which is explored here to demonstrate viable obstacle detection with only partial sensor information. Relative measurements from four LDF sensors are also explored to classify possible vessel orientations in full and without ambiguity, but under the assumption that the vessel is perpendicular to the needle insertion axis. Experimental results on a synthetic grey matter phantom are presented, which confirm these findings. To release the perpendicularity assumption, the thesis concludes with the description of a machine learning technique based on a Long Short-term memory network, which enables a vessel's spatial position, cross-sectional diameter and full pose to be predicted with sub-millimetre accuracy. Simulated and in-vitro examinations of vessel detection with this approach are used to demonstrate effective predictive ability. Collectively, these results demonstrate that the proposed steerable needle sensorisation is viable and could lead to improved safety during robotic assisted needle steering interventions.Open Acces

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