Accelerated Quantitative Mapping and Angiography for Cerebral and Cardiovascular Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) produces images with anatomical and functional information. These images can be obtained without the use of contrast agents, which generally require long scan times. This dissertation investigates existing techniques for accelerating such functional MRI methods, contributes novel fast acquisition and reconstruction techniques, and proposes new ways of analyzing real-time MRI data. First, we aim to determine an advantageous approach for accelerating high spatial resolution 3D cardiac T2 relaxometry data by comparing the performance of different data undersampling patterns and reconstruction methods over a range of acceleration rates. Quantitative results on healthy and edematous hearts reveal that the relaxometry maps are more sensitive to undersampling than anatomical images. The 3-fold variable density random undersampling with model-based or joint-sparsity sensitivity encoding (SENSE) is recommended. Second, we develop a rapid T2 mapping protocol using spiral acquisition and novel model-based approach joined with compressed sensing (CS) and model-based reconstruction. We also develop a sequence that suppresses cerebrospinal fluid (CSF). Quantitative evaluation on digital phantoms and healthy volunteers demonstrates the feasibility of T2 quantification with 3D high-resolution and whole-brain coverage in 2-3 min. Third, we propose a Golden Angle (GA) rotated Spiral Sparse Parallel imaging (GASSP) method for high spatial (0.8mm) and high temporal (<21ms) resolution for measuring coronary blood flow in a single breath-hold. We reduce k-space gaps using novel binning and triggered GA schemes. Velocity and flow metrics are validated against two existing methods and show high reproducibility. Fourth, we construct an abdominal non-contrast-enhanced magnetic resonance angiography (MRA) protocol with a large spatial coverage at 3.0T. The protocol uses advanced velocity-selective (VS) pulse trains. MRA with a large spatial coverage is slow and accelerated using CS. The VS-MRA sequences generate high-quality angiograms and arteriograms with high blood contrast. Finally, physiological changes in real-time (RT) MRI (30-100 frames/sec) are explored using Fourier transform (FT), principal component analyses (PCA), and perfusion modeling. We detect spectral patterns in pharyngeal images acquired during speaking and obtain T1-weighted, pulsation-weighted, and respiration-weighted images in healthy volunteers and heart patients with wall motion abnormalities with FT and PCA. RT perfusion maps are estimated from a proposed perfusion model in ongoing work in progress

MRI sequences for detection of acute pulmonary embolism

In recent years a range of imaging techniques have emerged to help diagnose patients with suspected acute Pulmonary Embolism (PE). This is particularly useful for those who are contraindicated (renal failure or allergies) to the contrast media that is needed to perform Computed Tomography Pulmonary Angiography (CTPA), which would be the usual diagnostic tool of choice. To aid the cohort of patients with this contraindication, we have investigated the option of using Magnetic Resonance Imaging (MRI) to diagnose PE. In this thesis, MRI sequences including gradient recall echo (more specifically balanced Steady State Free Precession [b-SSFP]) with different trajectories of data sampling, and diffusion weighted imaging (DWI) were assessed. None of the sequences investigated required the use of intravenous contrast media. In Study I, we investigated a group of positive PE patients (verified by CTPA) alongside a volunteer group, who provided a negative PE control cohort. A b-SSFP sequence was assessed, using repetitive sampling of each slice position, in three different orthogonal planes. No triggering or breath hold techniques were used during imaging. This technique produced a large number of slices at each location for evaluation by radiologist. An excellent specificity and a good sensitivity were achieved. In Study II, a group of positive PE patients (also verified by CTPA) and a control volunteer group were used to test the DWI technique, which is not used commonly for the investigation of thrombosis in the lungs. We compared DWI against the single slice per position approach of b-SSFP and CTPA, and demonstrated its capability to depict pulmonary embolism, finding a very high sensitivity but poor specificity for DWI. In Study III, we tested two different sampling techniques for b-SSFP, Cartesian standard and golden angle radial sampling trajectories, to image the pulmonary arteries in ten volunteers and in two patients who had PE. We demonstrated the improvement of image quality when using radial trajectory sampling in comparison to the Cartesian technique. We also demonstrated that the post-reconstruction ‘sliding window’ method could be applied to the golden angle radial sampling schema when a different temporal resolution is needed. In Study IV, we used the sequence tested in Study III (b-SSFP with golden angle radial and Cartesian sampling) in a clinical setting. The study included 64 patients who were suspected of having acute PE; all were examined while waiting for CTPA diagnostic testing. We compared radial sampling versus Cartesian, and also assessed post-reconstruction images of the radial sampling, with varying temporal resolution. The radial sampling with golden angle schema did not produce images of high enough quality to depict acute PE in patients. In study V, a retrospective overview of 57 patients (2012–2018) from our institution, with suspected acute PE was made. This group of patients was contraindicated to CTPA, and so were examined only using b-SSFP images. The clinical outcome of this cohort was obtained from the electronical medical record system up to twelve months after their MRI assessments. The MRI results allowed the clinicians to change or support their decision as to which treatment strategy they chose, in patients with or without PE

Integrated Structural And Functional Biomarkers For Neurodegeneration

Alzheimer\u27s Disease consists of a complex cascade of pathological processes, leading to the death of cortical neurons and development of dementia. Because it is impossible to regenerate neurons that have already died, a thorough understanding of the earlier stages of the disease, before significant neuronal death has occurred, is critical for developing disease-modifying therapies. The various components of Alzheimer\u27s Disease pathophysiology necessitate a variety of measurement techniques. Image-based measurements known as biomarkers can be used to assess cortical thinning and cerebral blood flow, but non-imaging characteristics such as performance on cognitive tests and age are also important determinants of risk of Alzheimer\u27s Disease. Incorporating the various imaging and non-imaging sources of information into a scientifically interpretable and statistically sound model is challenging. In this thesis, I present a method to include imaging data in standard regression analyses in a data-driven and anatomically interpretable manner. I also introduce a technique for disentangling the effect of cortical structure from blood flow, enabling a clearer picture of the signal carried by cerebral blood flow beyond the confounding effects of anatomical structure. In addition to these technical developments in multi-modal image analysis, I show the results of two clinically-oriented studies focusing on the relative importance of various biomarkers for predicting presence of Alzheimer\u27s Disease pathology in the earliest stages of disease. In the first, I present evidence that white matter hyperintensities, a marker of small vessel disease, are more highly associated with Alzheimer\u27s Disease pathology than current mainstream imaging biomarkers in elderly control patients. In the second, I show that once Alzheimer\u27s Disease has progressed to the point of noticeable cognitive decline, cognitive tests are as predictive of presence of Alzheimer\u27s pathology as standard imaging biomarkers. Taken together, these studies demonstrate that the relative importance of biomarkers and imaging modalities changes over the course of disease progression, and sophisticated data-driven methods for combining a variety of modalities is likely to lead to greater biological insight into the disease process than a single modality

Metabolic guided vascular analysis of brain tumors using MR/PET

Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Radiações em Diagnóstico e Terapia)Universidade de Lisboa, Faculdade de Ciências, 2016As técnicas de imagiologia são uma mais-valia para a compreensão do corpo humano, constituindo uma ferramenta relevante para a medicina moderna. Estas técnicas permitem não só o diagnóstico, como também a monitorização de doenças, sendo especialmente importantes na área neuro-oncológica. A ressonância magnética e a tomografia por emissão de positrões (MR e PET acrónimo inglês de Magnetic Ressonance e Positron Emission Tomography, respetivamente) são referidas como as técnicas de imagem mais importantes em neuro-oncologia devido à sua capacidade e eficácia na deteção de tumores cerebrais. Estas duas técnicas permitem obter informação relativa à localização, estado e atividade tumoral. No entanto, em ambas, a diferenciação precisa dos tecidos tumorais assim como o acesso a informação referente à heterogeneidade do tumor, através de alterações não especificas dos tecidos é limitada. Neste momento, a análise de imagens de MR em 3 dimensões (3D) é o procedimento mais utlizado no diagnóstico de tumores cerebrais, em particular de gliomas. Desta forma, e devido ao crescente interesse na aquisição de informação adicional relativa à biologia do tumor, técnicas mais avançadas de MR, em particular imagem ponderada por perfusão (PWI, acrónimo inglês de Perfusion-Weighted Imaging), têm vindo a revelar-se uma mais valia para a prática clínica. A dinâmica de contraste suscetível (DSC acrónimo inglês de Dynamic Susceptibility Contrast) é um dos métodos mais utilizados na medição da perfusão sanguínea em tumores cerebrais. O princípio de aquisição de DSC-MR baseia-se na injeção intravenosa de um agente de contraste paramagnético (ex. Gadolinium-Diethylenetriamine Penta-acetic acid (Gd-DTPA)) e na rápida medição das alterações do sinal transmitido durante a passagem do bolus através da circulação cerebral. O volume sanguíneo cerebral (CBV, acrónimo inglês de Cerebral Blood Volume) é um dos parâmetros mais relevantes obtidos por esta técnica. Nos tumores cerebrais, o CBV exibe uma elevada correlação com a densidade dos micro-vasos, pelo que o seu volume é tipicamente mais elevado nas regiões tumorais do que quando comparado com os tecidos saudáveis. Para além de PWI-MR, a introdução de radio-marcadores de aminoácidos na técnica de PET tem demonstrado um bom desempenho no diagnóstico de gliomas. Esta técnica tem por base a medição da magnitude do transporte de aminoácidos e a sua distribuição no tumor. Na região tumoral, a sua incorporação é aumentada quando comparada com o tecido normal, sendo essas diferenças traduzidas em imagem. De entre os radio-marcadores de aminoácidos disponíveis, O(2-[18F] FluoroEthyl)-L-Tyrosine (18F-FET) foi recentemente introduzido e o seu bom desempenho no diagnóstico de gliomas tem vindo a ser comprovado por diversos estudos. Desta forma, esta técnica de imagem permite não só uma delineação precisa da área tumoral como também a subsequente classificação de gliomas. Os principais problemas que afetam o planeamento do tratamento por terapia usando radiação ou biopsia são a precisa delineação do tecido tumoral vital e a falta de informação relativa à heterogeneidade dos vasos nos tecidos tumorais. Deste modo, foi proposta a combinação da informação proveniente da técnica de 18F-FET com a informação proveniente de PWI. Diversos estudos têm sido realizados de forma a comprovar as vantagens da combinação das referidas técnicas em gliomas. Uma boa correlação foi encontrada entre CBV medido através de perfusão e diferentes radio-marcadores de aminoácidos em PET. No entanto, um estudo recente realizado com o objetivo de comparar o desempenho de 18F-FET e CBV na delineação da área tumoral em gliomas, concluiu que a informação proveniente de 18F-FET permite uma delineação tumoral mais precisa. Para além disso, neste estudo foi ainda reportada uma reduzida correlação, fraca congruência espacial e diferentes localizações dos valores máximos na área do tumor entre 18F-FET e CBV. Em consequência destes resultados, bem como do fraco desempenho na delineação tumoral pelos parâmetros de perfusão conhecidos, fluxo sanguíneo cerebral (CBF acrónimo inglês de Cerebral Blood Flow) e CBV, nesta dissertação é proposta um melhoramento na computação dos parâmetros de perfusão e a sua subsequente comparação com a informação proveniente de 18F-FET. Para tal, neste trabalho foi adotada a sequência de PWI-MR desenvolvida no Forschungszentrum Jüllich. Esta sequência adquire múltiplos contrastes, denominado Gradient-Echo-Spin-Echo (GESE), explorando as vantagens da aquisição da técnica de imagem Echo-planar Imaging with keyhole (EPIK). Deste modo, e através da combinação de GE e SE, uma nova metodologia de PWI foi introduzida ,denominada imagiologia do tamanho dos vasos (VSI acrónimo inglês de Vessel Size Imaging). A técnica de VSI fornece informação acerca da vascularização tumoral, através da estimativa do caliber e densidade dos vasos, e da distribuição dos diferentes tipos de vasos (arteríolas, artérias, capilares, vénulas e veias) na área tumoral, o que não seria de outro modo acessível através dos conhecidos parâmetros de perfusão. Para além disso, sendo os tumores cerebrais caracterizados por uma anormal, desorganizada e heterogénea vascularização, alterações do calibre e densidade dos vasos assim como do volume sanguíneo, revelam ser informações importantes numa análise vascular, com particular interesse no diagnóstico de tumores, na sua monitorização e terapia. Assim sendo, e tendo em conta a boa performance mencionada pela técnica de 18F-FET na delineação da área tumoral, o principal objetivo deste trabalho é explorar a informação vascular adquirida através da técnica de VSI na região tumoral obtida pela informação proveniente de 18F-FET. Para este estudo foram recrutados vinte e cinco pacientes com gliomas. Cada paciente foi injetado com uma dose de 0.1 mmol/Kg de Gd-DTPA por peso corporal. As medições foram realizadas no scanner híbrido de MR/PET de 3T. As imagens de perfusão foram adquiridas usando a sequência 5-ecos GESE EPIK, simultaneamente com a aquisição das imagens de 18F-FET. Depois da conversão do sinal de MR na curva de concentração versus tempo (CTC acrónimo inglês de Concentration Time Curve), foi realizado um ajuste da curva na primeira passagem do bolus. As regiões de interesse foram selecionadas tendo em conta áreas saudáveis e tumorais delineadas com base na informação fornecida por 18F-FET. Desta forma, a área saudavél corresponde à região contra-lateral do tumor, respectivamente nos tecidos cerebrais de substância branca (WM acrónimo inglês de White Matter) e substância cinzenta (GM acrónimo inglês de Gray Matter) e a área tumoral, à região onde o rácio entre a região tumoral e a região cerebral saudável (TBR acrónimo do inglês Tumor To Brain Ratio), foi superior ou igual a 1.6. Para o acesso à informação vascular, os parâmetros de VSI: Índice do tamanho dos vasos (Vsi acrónimo inglês de Vessel Size Index), densidade média dos vasos (Q acrónimo inglês de Mean Vessel Density) e CBV foram analisados tanto em regiões saudáveis como tumorais. Subsequentemente, a informação de cada parâmetro foi comparada com a informação fornecida por 18F-FET através do cálculo da distância entre o voxel correspondente á máxima intensidade de 18F-FET e o voxel correspondente ao caliber máximo dos vasos, ao máximo volume sanguíneo e á mínima densidade dos vasos sanguíneos. Para Q foi considerado o mínimo, uma vez que ao contrário dos outros paramêtros é esperado a sua diminução na área tumoral. Por fim, e de forma a obter informação adicional relativa à heterogeneidade tumoral o parâmetro imagiologia da arquitetura dos vasos (VAI acrónimo inglês de Vessel Architecture Imaging) foi analisado na área tumoral delimitada por 18F-FET. A análise dos resultados relativos aos parâmetros de PW (Vsi, CBV e Q) revelou, para todos os pacientes, uma heterogénea variação no caliber e densidade dos vasos, assim como no volume cerebral na região do tumor em comparação com os tecidos cerebrais de aparência normal, WM e GM. Através da análise dos parâmetros de PW, vinte e quatro pacientes de um total de vinte e cinco apresentaram um aumento do caliber dos vasos, dezassete apresentaram um aumento do volume sanguíneo e dez uma redução da densidade dos vasos na área do tumor. Em todos os pacientes, foi verificado uma diferente localização dos parametros de PW nos vóxeis correspondestes ao valor máximo na área do tumor delineada por 18F-FET. Desta forma, como a distância entre o vóxeis de maior intensidade de 18F-FET e dos paramêtros de PW foi diferente de zero é possivél verificar que o voxel correspondente á máxima intensidade por 18F-FET não traduz o máximo de CBV e Vsi e o mínimo de Q. Para além disso, diferentes distâncias foram encontradas para cada um dos parâmetros de PW em cada paciente. Através da combinação dos parâmetros de perfusão, diferente informação relativa á vasculatura cerebral pode ser fornecida a cada paciente e uma variação de sinal foi encontrada entre WM e GM. Ainda, da análise do parâmetro VAI foi possível distinguir os diferentes tipos de vasos (ex. artérias, capilares e veias) no tumor. Em conclusão, a análise metabólica da vasculatura cerebral pela técnica de VSI proporciona novas perspetivas sobre a complexa natureza da vascularização e heterogeneidade tumoral. Adicionalmente, dada a diferente informação encontrada entre a captação de aminoácidos através da técnica de 18F-FET e VSI, a combinação de ambas as informações pode ser bastante importante para os radiologistas, abrindo a possibilidade à obtenção de nova informação, até então disponível apenas aos patologistas e provenientes por biópsia.Introduction: Assessment of vascular information using the Dynamic Susceptibility Contrast Perfusion-Weighted Imaging Magnetic Resonance technique (DSC PWI-MR) has potential benefits in the diagnosis and treatment monitoring of brain tumors. Beyond MR techniques, amino acid Positron Emission Tomography (PET) tracers, particularly O-(2-[18F] FluoroEthyl)-L-Tyrosine (18F-FET), have been demonstrating a good performance in brain tumor diagnosis and treatment monitoring. Previous publications have shown a mismatch between the Cerebral Blood Volume (CBV) defined in PWI and metabolic information from 18F-FET. PWI also allows measuring Vessel Size Imaging (VSI) by combining Gradient-Echo (GE) and Spin-Echo (SE) information with diffusion data. VSI enables the assessment of vessel caliber, density and architecture information, which is not directly accessible using others PWI parameters. The main goal of this work is to explore the tumor vascular information from VSI guided by the metabolic information from 18F-FET. Materials and methods: Twenty-five patients with gliomas were recruited for the study. For each patient, Gd-DTPA was injected with a dose of 0.1 mmol/Kg of body weight. The measurements were performed on a 3T MR-BrainPET scanner. PWI images were acquired using the combined 5-echo GESE echo planar imaging with keyhole (EPIK) sequence simultaneously with 18F-FET PET acquisition. After the conversion of the MR signal to Concentration Time Curve (CTC), the first–bolus passage was fitted using a Gamma Variate Function (GVF). The Regions of Interest (ROIs), in normal and tumor areas were delineated based on 18F-FET information. For the assessment of vascular information VSI parameters (e.g. Vessel Size Index (Vsi), Mean Vessel Density (Q) and Vessel Architecture Imaging (VAI)) and CBV were evaluated. In addition, distance between local hot spots related to 18F-FET PET was also computed. Results: For all the patients, Vsi, CBV and Q revealed a heterogeneous variation in tumor region comparing to brain tissues of normal appearance. Lower values were found in white matter (WM) comparing to grey matter (GM). From the evaluation of Vsi, CBV and Q in tumor area, twenty-four out of twenty-five patients exhibited an increased Vsi, seventeen patients an increased CBV and ten patients a decreased Q. For all the patients, the locations of the local hot spots differed considerably between 18F-FET and PWI metrics. From the evaluation of VAI, different types of vessels were distinguished (arteries, veins and capillaries) in the tumor. Conclusion: VSI metrics present different information when compared to 18F-FET. The metabolic guided analysis of VSI data provides further insights into the complex nature of the tumor vascularity and heterogeneity

Learning-based Algorithms for Inverse Problems in MR Image Reconstruction and Quantitative Perfusion Imaging

Medical imaging has become an integral part of the clinical pipeline through its widespread use in the diagnosis, prognosis and treatment planning of several diseases. Magnetic Resonance Imaging (MRI) is particularly useful because it is free from ionizing radiation and is able to provide excellent soft tissue contrast. However, MRI suffers from drawbacks like long scanning durations that increase the cost of imaging and render the acquired images vulnerable to artifacts like motion. In modalities like Arterial Spin Labeling (ASL), which is used for non-invasive and quantitative perfusion imaging, low signal-to-noise ratio and lack of precision in parameter estimates also present significant problems. In this thesis, we develop and present algorithms whose focus can be divided into two broad categories. First, we investigate the reconstruction of MR images from fewer measurements, using data-driven machine learning to fill in the gaps in acquisition, thereby reducing the scan duration. Specifically, we first combine a supervised and an unsupervised (blind) learned dictionary in a residual fashion as a spatial prior in MR image reconstruction, and then extend this framework to include deep supervised learning. The latter, called blind primed supervised (BLIPS) learning, proposes that there exists synergy between features learned using shallower dictionary-based methods or traditional prior-based image reconstruction and those learned using newer deep supervised learning-based approaches. We show that this synergy can be exploited to yield reconstructions that are approx. 0.5-1 dB better in PSNR (in avg. across undersampling patterns). We also observe that the BLIPS algorithm is more robust to a scarcity of available training data, yielding reconstructions that are approx. 0.8 dB better (in terms of avg. PSNR) compared to strict supervised learning reconstruction when training data is very limited. Secondly, we aim to provide more precise estimates for multiple physiological parameters and tissue properties from ASL scans by estimation-theory-based optimization of ASL scan design, and combination with MR Fingerprinting. For this purpose, we use the Cramer-Rao Lower Bound (CRLB) for optimizing the scan design, and deep learning for regression-based estimation. We also show that regardless of the estimator used, optimization improves the precision in parameter estimates, and enables us to increase the available ‘useful’ information obtained in a fixed scanning duration. Specifically, we successfully improve the theoretical precision of perfusion estimates by 4.6% compared to a scan design where the repetition times are randomly chosen (a popular choice in literature) thereby yielding a 35.2% improvement in the corresponding RMSE in our in-silico experiments. This improvement is also visually evident in our in-vivo studies on healthy human subjects.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169819/1/anishl_1.pd

Time-encoded pseudo-continuous arterial spin labeling: Increasing SNR in ASL dynamic angiography

Purpose: Dynamic angiography using arterial spin labeling (ASL) can provide detailed hemodynamic information. However, the long time-resolved readouts require small flip angles to preserve ASL signal for later timepoints, limiting SNR. By using time-encoded ASL to generate temporal information, the readout can be shortened. Here, the SNR improvements from using larger flip angles, made possible by the shorter readout, are quantitatively investigated. Methods: The SNR of a conventional protocol with nine Look-Locker readouts and a 4 (Formula presented.) 3 time-encoded protocol with three Look-Locker readouts (giving nine matched timepoints) were compared using simulations and in vivo data. Both protocols were compared using readouts with constant flip angles (CFAs) and variable flip angles (VFAs), where the VFA scheme was designed to produce a consistent ASL signal across readouts. Optimization of the background suppression to minimize physiological noise across readouts was also explored. Results: The time-encoded protocol increased in vivo SNR by 103% and 96% when using CFAs or VFAs, respectively. Use of VFAs improved SNR compared with CFAs by 25% and 21% for the conventional and time-encoded protocols, respectively. The VFA scheme also removed signal discontinuities in the time-encoded data. Preliminary data suggest that optimizing the background suppression could improve in vivo SNR by a further 16%. Conclusions: Time encoding can be used to generate additional temporal information in ASL angiography. This enables the use of larger flip angles, which can double the SNR compared with a non-time-encoded protocol. The shortened time-encoded readout can also lead to improved background suppression, reducing physiological noise and further improving SNR