19 research outputs found

    High-Resolution Quantitative Cone-Beam Computed Tomography: Systems, Modeling, and Analysis for Improved Musculoskeletal Imaging

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    This dissertation applies accurate models of imaging physics, new high-resolution imaging hardware, and novel image analysis techniques to benefit quantitative applications of x-ray CT in in vivo assessment of bone health. We pursue three Aims: 1. Characterization of macroscopic joint space morphology, 2. Estimation of bone mineral density (BMD), and 3. Visualization of bone microstructure. This work contributes to the development of extremity cone-beam CT (CBCT), a compact system for musculoskeletal (MSK) imaging. Joint space morphology is characterized by a model which draws an analogy between the bones of a joint and the plates of a capacitor. Virtual electric field lines connecting the two surfaces of the joint are computed as a surrogate measure of joint space width, creating a rich, non-degenerate, adaptive map of the joint space. We showed that by using such maps, a classifier can outperform radiologist measurements at identifying osteoarthritic patients in a set of CBCT scans. Quantitative BMD accuracy is achieved by combining a polyenergetic model-based iterative reconstruction (MBIR) method with fast Monte Carlo (MC) scatter estimation. On a benchtop system emulating extremity CBCT, we validated BMD accuracy and reproducibility via a series of phantom studies involving inserts of known mineral concentrations and a cadaver specimen. High-resolution imaging is achieved using a complementary metal-oxide semiconductor (CMOS)-based x-ray detector featuring small pixel size and low readout noise. A cascaded systems model was used to performed task-based optimization to determine optimal detector scintillator thickness in nominal extremity CBCT imaging conditions. We validated the performance of a prototype scanner incorporating our optimization result. Strong correlation was found between bone microstructure metrics obtained from the prototype scanner and µCT gold standard for trabecular bone samples from a cadaver ulna. Additionally, we devised a multiresolution reconstruction scheme allowing fast MBIR to be applied to large, high-resolution projection data. To model the full scanned volume in the reconstruction forward model, regions outside a finely sampled region-of-interest (ROI) are downsampled, reducing runtime and cutting memory requirements while maintaining image quality in the ROI

    Advances in the Role of Quantitative NMR in Medicine: Deep Learning applied to MR Fingerprinting and Trabecular Bone Volume Fraction Estimation through Single-Sided NMR

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    Nuclear Magnetic Resonance (NMR) has been a powerful and widespread tool since its birth thanks to its flexibility in assessing properties of physical systems without being invasive and without using ionizing radiations. Although applications of NMR for medical purposes have rapidly developed since the introduction of MR imaging (MRI), most of the clinical protocols retrieve qualitative information about biological tissues. Being able to retrieve also quantitative information with NMR may be beneficial to identify biomarkers for understanding and describing the pathophysiology of complex diseases in many tissues. However, established quantitative MRI (qMRI) methods require long scan times that not only can represent more exposure to image artifacts and more discomfort for the patient, but they also increase the costs of MRI protocols. To improve the clinical feasibility of quantitative NMR, one can focus on optimizing qMRI protocols to increase data acquisition efficiency, i.e. minimizing the acquisition times and maximising the number of retrieved information. Alternatively, one can focus on the application of low-cost, portable and low maintenance NMR devices in the medical field, such as single-sided devices. This Ph.D thesis presents studies that aim to advance the role of quantitative NMR in medicine using the two directions stated above. The first part of the thesis proposes a deep learning approach based on deep Fully Connected Networks (NN), for pixel-wise MR parameter prediction task in Magnetic Resonance Fingerprinting (MRF) as a solution to overcome the curse of dimensionality affecting the gold standard dictionary approach. The second part proposes a methodology to assess the trabecular bone-volume-to-total-volume (BV/TV) ratio using single-side NMR by means of NMR relaxometry measurements. Nowadays there are not well-established methodologies to assess trabecular BV/TV that are suitable for wide screening campaigns of the population at risk of bone fractures related to diseases such as osteoporosis

    Fundamentals and applications of Raman-based techniques for the design and development of active biomedical materials

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    Raman spectroscopy is an analytical method based on light–matter interactions that can interrogate the vibrational modes of matter and provide representative molecular fingerprints. Mediated by its label-free, non-invasive nature, and high molecular specificity, Raman-based techniques have become ubiquitous tools for in situ characterization of materials. This review comprehensively describes the theoretical and practical background of Raman spectroscopy and its advanced variants. The numerous facets of material characterization that Raman scattering can reveal, including biomolecular identification, solid-to-solid phase transitions, and spatial mapping of biomolecular species in bioactive materials, are highlighted. The review illustrates the potential of these techniques in the context of active biomedical material design and development by highlighting representative studies from the literature. These studies cover the use of Raman spectroscopy for the characterization of both natural and synthetic biomaterials, including engineered tissue constructs, biopolymer systems, ceramics, and nanoparticle formulations, among others. To increase the accessibility and adoption of these techniques, the present review also provides the reader with practical recommendations on the integration of Raman techniques into the experimental laboratory toolbox. Finally, perspectives on how recent developments in plasmon- and coherently-enhanced Raman spectroscopy can propel Raman from underutilized to critical for biomaterial development are provided

    Infective/inflammatory disorders

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    The radiological investigation of musculoskeletal tumours : chairperson's introduction

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