Accelerated Cardiac Magnetic Resonance Imaging in the Mouse Using an Eight-Channel Array at 9.4 Tesla

MRI has become an important tool to noninvasively assess global and regional cardiac function, infarct size, or myocardial blood flow in surgically or genetically modified mouse models of human heart disease. Constraints on scan time due to sensitivity to general anesthesia in hemodynamically compromised mice frequently limit the number of parameters available in one imaging session. Parallel imaging techniques to reduce acquisition times require coil arrays, which are technically challenging to design at ultrahigh magnetic field strengths. This work validates the use of an eight-channel volume phased-array coil for cardiac MRI in mice at 9.4 T. Two- and three-dimensional sequences were combined with parallel imaging techniques and used to quantify global cardiac function, T1-relaxation times and infarct sizes. Furthermore, the rapid acquisition of functional cine-data allowed for the first time in mice measurement of left-ventricular peak filling and ejection rates under intravenous infusion of dobutamine. The results demonstrate that a threefold accelerated data acquisition is generally feasible without compromising the accuracy of the results. This strategy may eventually pave the way for routine, multiparametric phenotyping of mouse hearts in vivo within one imaging session of tolerable duration. Magn Reson Med, 2010. © 2010 Wiley-Liss, Inc

Coarse-Super-Resolution-Fine Network (CoSF-Net): A Unified End-to-End Neural Network for 4D-MRI with Simultaneous Motion Estimation and Super-Resolution

Four-dimensional magnetic resonance imaging (4D-MRI) is an emerging technique for tumor motion management in image-guided radiation therapy (IGRT). However, current 4D-MRI suffers from low spatial resolution and strong motion artifacts owing to the long acquisition time and patients' respiratory variations; these limitations, if not managed properly, can adversely affect treatment planning and delivery in IGRT. Herein, we developed a novel deep learning framework called the coarse-super-resolution-fine network (CoSF-Net) to achieve simultaneous motion estimation and super-resolution in a unified model. We designed CoSF-Net by fully excavating the inherent properties of 4D-MRI, with consideration of limited and imperfectly matched training datasets. We conducted extensive experiments on multiple real patient datasets to verify the feasibility and robustness of the developed network. Compared with existing networks and three state-of-the-art conventional algorithms, CoSF-Net not only accurately estimated the deformable vector fields between the respiratory phases of 4D-MRI but also simultaneously improved the spatial resolution of 4D-MRI with enhanced anatomic features, yielding 4D-MR images with high spatiotemporal resolution

Magnetic resonance imaging of the brain and vocal tract:Applications to the study of speech production and language learning

The human vocal system is highly plastic, allowing for the flexible expression of language, mood and intentions. However, this plasticity is not stable throughout the life span, and it is well documented that adult learners encounter greater difficulty than children in acquiring the sounds of foreign languages. Researchers have used magnetic resonance imaging (MRI) to interrogate the neural substrates of vocal imitation and learning, and the correlates of individual differences in phonetic “talent”. In parallel, a growing body of work using MR technology to directly image the vocal tract in real time during speech has offered primarily descriptive accounts of phonetic variation within and across languages. In this paper, we review the contribution of neural MRI to our understanding of vocal learning, and give an overview of vocal tract imaging and its potential to inform the field. We propose methods by which our understanding of speech production and learning could be advanced through the combined measurement of articulation and brain activity using MRI – specifically, we describe a novel paradigm, developed in our laboratory, that uses both MRI techniques to for the first time map directly between neural, articulatory and acoustic data in the investigation of vocalisation. This non-invasive, multimodal imaging method could be used to track central and peripheral correlates of spoken language learning, and speech recovery in clinical settings, as well as provide insights into potential sites for targeted neural interventions

Inverse problems in medical ultrasound images - applications to image deconvolution, segmentation and super-resolution

In the field of medical image analysis, ultrasound is a core imaging modality employed due to its real time and easy-to-use nature, its non-ionizing and low cost characteristics. Ultrasound imaging is used in numerous clinical applications, such as fetus monitoring, diagnosis of cardiac diseases, flow estimation, etc. Classical applications in ultrasound imaging involve tissue characterization, tissue motion estimation or image quality enhancement (contrast, resolution, signal to noise ratio). However, one of the major problems with ultrasound images, is the presence of noise, having the form of a granular pattern, called speckle. The speckle noise in ultrasound images leads to the relative poor image qualities compared with other medical image modalities, which limits the applications of medical ultrasound imaging. In order to better understand and analyze ultrasound images, several device-based techniques have been developed during last 20 years. The object of this PhD thesis is to propose new image processing methods allowing us to improve ultrasound image quality using postprocessing techniques. First, we propose a Bayesian method for joint deconvolution and segmentation of ultrasound images based on their tight relationship. The problem is formulated as an inverse problem that is solved within a Bayesian framework. Due to the intractability of the posterior distribution associated with the proposed Bayesian model, we investigate a Markov chain Monte Carlo (MCMC) technique which generates samples distributed according to the posterior and use these samples to build estimators of the ultrasound image. In a second step, we propose a fast single image super-resolution framework using a new analytical solution to the l2-l2 problems (i.e., $\ell_2$-norm regularized quadratic problems), which is applicable for both medical ultrasound images and piecewise/ natural images. In a third step, blind deconvolution of ultrasound images is studied by considering the following two strategies: i) A Gaussian prior for the PSF is proposed in a Bayesian framework. ii) An alternating optimization method is explored for blind deconvolution of ultrasound

Développement et évaluation des paramètres quantitatifs de l’IRM de la prostate

The purpose of this thesis is to develop and evaluate the quantitative methods of multiparametric MRI of prostate in discriminating Gleason score (GS) ≥7 cancers. We suppose that the quantitative parameter of MRI could help standardizer the diagnostic, reduce the inter-lecture and/ or inter-institution variation in diagnostic of prostate cancer. This thesis is divided into three chapters. The firs chapter, entilted « Quantitative T2 MRI of prostate » is a retrospective study on a database of prostate cancer patients before radical prostatectomy. The second chapter, entilted « Multi-parametric Quantitative MRI of prostate » is also a retrospective study before radical prostatectomy. The third chapter, entitled « MR elastography of prostate by transperineal approach », is an experimental study. Our first study shows that T2 value is robust between machines of different constructors. T2 value is significant predictor, but of weak performance, of aggressively cancer of prostate at 3T. Our second study shows that the combination of ADC_10th percentile with Time-to-peak (TTP) improved the diagnosis performance, and this model is also robust between two machines of different constructors. Our third study shows the initial results on elasticity of the prostate. These results show that MRI elastography of prostate at high excitation frequency (>100 Hz) by trans-perineale approach was feasible. The elastography may, in the future, be integrated in quantitative multi-parametric MRI to improve the diagnosis performanceL'objectif de cette thèse est de développer et d'évaluer des paramètres quantitatifs de l'IRM de la prostate en discriminant les cancers de score de Gleason (GS) ≥7. Nous supposons que les paramètres quantitatifs de l'IRM pourraient aider à standardiser le diagnostic, et à diminuer la variation inter-lecteur et/ou inter-institution du diagnostic du cancer de la prostate. Cette thèse est divisée en trois chapitres. Le premier chapitre, intitulé « IRM T2 quantitatif de la prostate », est une étude rétrospective sur une base de données des patients avant prostatectomie radicale. Le deuxième chapitre, intitulé « IRM multiparamétrique quantitative de la prostate », est aussi une étude rétrospective avant prostatectomie radicale. Le troisième chapitre, intitulé « Élastographie IRM de la prostate par voie trans-périnéale» est une étude expérimentale. Notre première étude montre que le T2 est robuste sur les machines de constructeurs différents. Le T2 est un prédicteur significatif, mais de faible performance, d'agressivité du cancer de la prostate à 3T. Notre deuxième étude montre que la combinaison du 10ème centile de l'ADC avec le Time-topeak (TTP) améliore la performance du diagnostic, et ce modèle est lui aussi robuste entre des machines de constructeurs différents. Notre troisième étude montre les résultats préliminaires sur l'élasticité de la prostate. Ces résultats montrent que l'élastographie IRM de la prostate en haute fréquence d'excitation (>100 Hz) par voie trans-périnéale est faisable. L'élastographie pourrait à l'avenir être intégrée à l'IRM multiparamétrique quantitative pour améliorer la performance de diagnosti

Optical techniques for non-destructive detection of flaws in ceramic components

No abstract availableThis thesis primarily concerns development of a non-destructive inspection method for 3mol% Yttria-Stabilised Zirconia Polycrystal (3Y-TZP) ceramics used for dental applications and a scoping study on applying the technique to other ceramic materials applied in thermal barrier coatings and other fields. Zirconia ceramics are materials of great interest for various engineering applications, primarily due to their stiffness, hardness and wear resistance. These factors in combination with the complex manufacturing processes may reduce the material strength and durability due to induced cracking. Knowledge of the extent of this cracking must be obtained and often, if each part is unique as in biomedicine, the assessment must be carried out for every part non-destructively so the part can be subsequently used. Only a few techniques are known for inspection of Zirconia ceramics, however these techniques are not able to detect flaws in thick (above 500 μm) parts. The main limitation for optical inspection of 3Y-TZP is the highly scattering nature of the material due to its multicrystalline grain structure (grains size of 500 nm) which, particularly in the visible region, reduces imaging capabilities. However, a transmission window in the mid-infrared (between 3 and 8 μm) exists opening up the potential for inspection at these wavelengths. Mid-Infrared Transmission Imaging (MIR-TI) and Confocal Mid-Infrared Transmission Imaging (CMIR-TI) techniques were developed for inspection of 3Y-TZP parts which allow for detecting sub mm scale cracks. The measured imaging resolution for the MIR-TI is 42 ± 5 μm, whereas for the CMIR-TI it is below 38.5 ± 5 μm. The maximum sample thickness inspected with the MIR-TI and CMIR-TI is 6 mm and 3.5 mm respectively, considerably more than currently available inspection methods. The MIRTI technique provides fast inspection of the part due to the large field of view (11 by 7 mm), however the high cost and limited imaging resolution make this technique less attractive. The CMIR-TI technique on the other hand is more cost effective due to reduced cost of the infrared sensor and it provides an enhanced imaging capabilities. The promising results achieved with the MIR-TI and CMIR-TI techniques led to the development of reflection equivalents (Camera-MIRI and Confocal-MIRI) for ceramic coating measurements, however further in-depth experiments to determine and quantify the capabilities of both techniques are required

Development and validation of a psychological screening tool to assess pre-enlistment psychological factors likely to impact on military well-being and performance in the context of the Sri Lankan military

Military personnel who are directly involved in war face its most harmful consequences. However, research suggests that personality differences and characteristics might mitigate or exacerbate the impact on individual responses to war-related experiences. These characteristics could be either risk or protective factors.The current study aimed to develop and validate a psychological screening tool to assess pre-enlistment personality factors which can contribute to the well-being of military personnel and determine whether this tool can predict variables related to military well-being and performance.Two main studies were conducted to achieve these aims. Firstly, a cross-sectional descriptive survey was conducted with 960 junior military officers representing triforces in Sri Lanka for scale development and validation. A tool was developed combining Resilience Scale (RS25), Dispositional Resilience Scale (DRS15), and Mental Toughness Questionnaire (MTQ48). This tool was validated through EFA and CFA processes adopting a split sample cross validation method and resulting a scale with 42 items which was named as the “Resilience Inventory for Military (RIM)”. These 42 items comprised two factors. One consisted of 20 resilience items, the other consisted of 22 mental toughness items. Both subscales in this scale demonstated good validity and reliability levels.Secondly, a longitudinal study was carried out with 92 Cadet trainees to determine whether this scale can predict the turnover intention of the trainees, newcomer adjustment of trainees, training satisfaction,training performance and their general mental health condition. The results demonstrated that those who score high on the RIM scale have a greater adjustment, good level of mental health, are less likely to exibhit turnover intention and more satisfied with the training.The findings can help Sri Lankan military forces identify the most resilient candidates for military service and minimise negative behaviour outcomes among military personnel. Also, this research suggests how mental toughness, hardiness and resilience relate together.This approach might also be of use elsewhere in South Asia