Intraoperative Photoacoustic Imaging of Breast Cancer

Breast cancer is one of the most common cancers to affect women, presenting a lifetime risk of 1 in 8. Treatment of stage 1 and 2 cancers usually involves breast conserving surgery (BCS). The goal of BCS is to remove the entire tumour with a surrounding envelope of healthy tissue, referred to as a negative margin. Unfortunately, up to 50% of surgeries fail to remove the whole tumour. To minimize the risk of cancer recurrence, a second surgery, must therefore be performed. Currently, there is no widely accepted intraoperative tool to significantly mitigate this problem. Employed systems are usually based on imaging, such as x-ray or ultrasonography. Unfortunately, sensitivity and specificity deficits, especially related to breast density, reduce the effectiveness of these methods. Photoacoustic tomography (PAT) is a relatively new imaging modality which uses safe near-infrared laser illumination to generate 3-D images of soft tissues to a depth of up to several cm. We used a custom designed and built intraoperative PAT system, called iPAT, to perform a 100 patient study on freshly excised breast lumpectomy specimens within the surgical setting. The system enabled the evaluation of tumour extent, shape, morphology and position within lumpectomy specimens measuring up to 11 cm in diameter. Scan results were used to compare iPAT-derived tumour size to the gold-standard pathologic examination, and when available, to x-ray, ultrasonography and DCE-MRI. Imaging results were also used to classify specimen margins as close or wide, and positive predictive values (PPV), negative predictive values (NPV), sensitivity and specificity were then calculated to estimate the effectiveness of the iPAT system at predicting lumpectomy margin status. With a close margin prevalence of 35%, the PPV, NPV, sensitivity and specificity of iPAT were found to be 71%, 83%, 69%, and 84%, respectively. Information provided by the iPAT system identified 9 out of the 12 positive specimens, potentially reducing the positive margin rate by 75%. . Contrary to expected photoacoustic contrast mechanisms, iPAT images of hemoglobin distribution correlated poorly with US and X-ray tumour imaging, while hypo-intense regions in lipid-weighted iPAT images were in excellent agreement

Analysis of Strain Relaxation, Ion Beam Damage and Instrument Imperfections for Quantitative STEM Characterizations

It is illustrated that the preparation of thin specimens from bulk materials can have significant influence on the interpretability of (S)TEM data. The results of the presented measurements show that and the elastic strain relaxation in low dimensional structures alters the overall strain state of the material – and hence affects strain measurements – as well as the contrast of STEM measurements and is generally needed to be incorporated in comparative simulation studies that involve strained structures. Furthermore, the ion beam thinning process itself can introduce – even with relatively low energies – a serious alteration of the surface which can affect the contrast of STEM measurements. Hence, the correlation to thickness measurements is complicated due to the distinct difference in scattering behaviour between (partially) amorphized surface layers in comparison with crystalline material. Although parts of these effects cannot be avoided the inclusion of amorphous pseudo-oxide layers in simulations has been shown to provide reasonable agreement with the experimental data. Furthermore, the impact of a finite electron source with limited coherence has been investigated. It can be shown that a reproduction of experimental contrast by simulation can only be achieved by the inclusion of an additional focus spread as well as a lateral point spread due to partial spatial coherence. Finally, the previous results are combined to reconstruct the three-dimensional shape of several antiphase domains within gallium phosphide grown on silicon-(001). At first the concept was demonstrated for a simple but highly strained interface and second for large structures with thousands of atomic columns. It is shown that although the contrast mechanism for annular dark-field imaging is in principle straight forward and mathematically simple, the details of atomic resolution microscopy are still very challenging. Realistic assumptions about the specimen properties and the electron optics have been shown to be of great relevance for data evaluation. It is clear that the research should be extended to the regime of low angular dark-field imaging where strain and inelastic scattering play a even more relevant role. Furthermore, it is of great importance to investigate the aforementioned practical aspects of damage layers and optical imperfections for other advanced imaging techniques like diffraction imaging. In addition, it is worth investigating in how far through focus depth section can be utilized to increase the reliability of structure restoration along the transmission direction. It is expected that the improvement of accuracy and robustness of atomic counting techniques will greatly increase the power of a (S)TEM by providing simultaneously lateral and depth information about arrangement and composition. Furthermore, it is clear that the role of high performance simulations will have an even more important role in the future

Variational learning for inverse problems

Machine learning methods for solving inverse problems require uncertainty estimation to be reliable in real settings. While deep variational models offer a computationally tractable way of recovering complex uncertainties, they need large supervised data volumes to be trained, which in many practical applications requires prohibitively expensive collections with specific instruments. This thesis introduces two novel frameworks to train variational inference models for inverse problems, in semi-supervised and unsupervised settings respectively. In the former, a realistic scenario is considered, where few experimentally collected supervised data are available, and analytical models from domain expertise and existing unsupervised data sets are leveraged in addition to solve inverse problems in a semi-supervised fashion. This minimises the supervised data collection requirements and allows the training of effective probabilistic recovery models relatively inexpensively. This novel method is first evaluated in quantitative simulated experiments, testing performance in various controlled settings and compared to alternative techniques. The framework is then implemented in several real world applications, spanning imaging, astronomy and human-computer interaction. In each real world setting, the novel technique makes use of all available information for training, whether this is simulations, data or both, depending on the task. In each experimental scenario, state of the art recovery and uncertainty estimation were demonstrated with reasonably limited experimental collection efforts for training. The second framework presented in this thesis approaches instead the challenging unsupervised situation, where no examples of ground-truths are available. This type of inverse problem is commonly encountered in data pre-processing and information retrieval. A variational framework is designed to capture the solution space of inverse problem by using solely an estimate of the observation process and large ensembles of observations examples. The unsupervised framework is tested on data recovery tasks under the common setting of missing values and noise, demonstrating superior performance to existing variational methods for imputation and de-noising with different real data sets. Furthermore, higher classification accuracy after imputation are shown, proving the advantage of propagating uncertainty to downstream tasks with the new model

Improving Material Mapping in Glenohumeral Finite Element Models: A Multi-Level Evaluation

An improved understanding of glenohumeral bone mechanics can be elucidated using computational models derived from computed tomography data. Although computational tools, such as finite element analysis, provide a powerful quantitative technique to evaluate and answer a variety of biomechanical and clinical questions, glenohumeral finite element models (FEMs) have not kept pace with improvements in modeling techniques or model validation methods seen in other anatomic locations. The present work describes the use of multi-level computational modeling to compare, develop and validate FEMs of the glenohumeral joint. Common density-modulus relationships within the literature were evaluated using a multi-level comparative testing methodology to determine if relationships from alternate anatomic locations can accurately replicate the apparent-level properties of glenoid trabecular bone. Two different relationships were able to replicate the micro-level loading to within 1.4%, compared to microFEMs when accounting for homogeneous or heterogeneous tissue moduli. The multi-level comparative methodology was then used to develop a glenoid-specific trabecular density-modulus relationship. This allowed for controlled and consistent development of the relationship that was adapted for use in whole-bone scapular FEMs. The density-modulus relationship developed was able to simulate micro-level apparent loading to within 1.3%, using a QCT-density specific relationship. Micro-level FEM characteristics were then compared to determine the optimal parameters for microFEMs and the effect of down-sampled images as FEM input. This was accomplished by creating glenoid trabecular microFEMs from microCT images at 32 micron, 64 micron or down-sampled 64 micron, spatial resolution. It was found that microFEMs accounting for material heterogeneity at the highest spatial resolution were the most accurate. MicroFEMs generated from down-sampled images at 64 microns were found to differ from those generated from scanned 64 micron images, indicating that caution should be used with down-sampled images as input for microFEMs. The optimal QCT-FEM parameters and material mapping strategies (elemental or nodal) were then explored using the same multi-level computational methodology. Little difference was found when comparing elemental or nodal material mapping strategies for all element types; however, QCT-FEMs generated with hexahedral elements and mapped with elemental material mapping, most accurately replicated micro-level apparent loading. Comparisons by material mapping strategy are also presented for linear and quadratic tetrahedral elements. Experimental validation of whole-bone scapular models was then explored by loading cadaveric scapulae within a microCT and using digital volume correlation (DVC) and a 6-degree of freedom load cell to compare full-field displacements and reaction loads to whole-bone scapular QCT-FEMs generated with different material mapping strategies and density-modulus relationships from the literature. It was found that elemental and nodal material mapping strategies were able to accurately replicate experimental DVC displacement field results. There was only minimal variation between elemental or nodal material mapping, and although percentage errors in reaction forces varied from -46% to 965%, QCT-FEMs mapped with density-modulus relationships from the literature were able to replicate experimental reaction loads to within 3%. Finally, morphometric parameters and apparent modulus between non-pathologic normal and end-stage osteoarthritic humeral trabecular bone was compared. It was found that morphometric differences compared to normal bone only occurred in the most medial aspects of end-stage OA bone, within the subchondral region. Moving distally from the articular surface showed near identical morphometric parameters. The end-stage OA group also exhibited a more linear bone-volume-modulus relationship compared to non-pathologic normal bone. The largest differences were seen at bone volume fractions greater than 0.25. This indicates that if high bone volume OA bone is being modeled, then a linear bone-volume-fraction-modulus (or density-modulus) relationship may more accurately replicate bone loading; however, if the high bone-volume-fraction bone is removed (such as with humeral joint replacement surgery), a power-law relationship similar to normal non-pathologic bone may accurately replicate bone loading