Patient-specific CFD simulation of intraventricular haemodynamics based on 3D ultrasound imaging

Background: The goal of this paper is to present a computational fluid dynamic (CFD) model with moving boundaries to study the intraventricular flows in a patient-specific framework. Starting from the segmentation of real-time transesophageal echocardiographic images, a CFD model including the complete left ventricle and the moving 3D mitral valve was realized. Their motion, known as a function of time from the segmented ultrasound images, was imposed as a boundary condition in an Arbitrary Lagrangian-Eulerian framework. Results: The model allowed for a realistic description of the displacement of the structures of interest and for an effective analysis of the intraventricular flows throughout the cardiac cycle. The model provides detailed intraventricular flow features, and highlights the importance of the 3D valve apparatus for the vortex dynamics and apical flow. Conclusions: The proposed method could describe the haemodynamics of the left ventricle during the cardiac cycle. The methodology might therefore be of particular importance in patient treatment planning to assess the impact of mitral valve treatment on intraventricular flow dynamics

Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction.

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome

Computational analysis of flow and stress patterns in thoracic aortic aneurysms : a patient specific study

Imperial Users onl

Novel strategies for mouse cardiac MRI : better, faster, stronger

Mouse models of cardiac disease are an important tool to gain understanding of the pathophysiological processes related to the heart, as well as for the development of new treatment strategies. In this respect, Magnetic Resonance Imaging (MRI) has become the gold standard imaging modality, because it combines high spatial resolution imaging with a large variety of soft tissue contrast weightings that can be related to the presence of diseased tissue. In addition, (targeted) MRI contrast agents can be employed to visualize different processes on the molecular level, for example in relation to myocardial infarction and the subsequent cardiac remodeling process. The specificity to discriminate healthy from diseased tissue as well as the sensitivity for detection of MR contrast agents is strongly affected by the specific MRI protocol design. Moreover, the challenging physiology of the mouse heart, especially with respect to its small size and high heart rate, often limits the direct translation of imaging protocols already available from clinical studies. Finally, the growing knowledge on cardiac pathology continuously pushes the development of sophisticated mouse cardiac MRI protocols that allow more detailed measurements of a variety of physiologically relevant cardiac parameters. The overall goal of this thesis was therefore to design and investigate novel imaging strategies in the field of mouse cardiac MRI and their application in models of cardiac disease. Chapter 2 of this thesis contains an extensive overview of currently available protocols for mouse cardiac MRI and more specifically those related to contrast enhanced imaging of myocardial infarction. The remainder of the thesis contains the experimental chapters describing all details on our newly developed mouse cardiac MRI techniques. This chapter shortly summarizes the aims and results with respect to each of these techniques, categorized based on the parameter of interest for which each measurement was specifically designed. Diastolic function Measurement of murine diastolic function requires Cine imaging with an extremely high frame rate ¿ more than 60 frames within a cardiac cycle of 100-120 ms ¿ to be able to discriminate between the two separate filling phases of the heart. In chapter 3, it was shown that using a retrospectively triggered MRI sequence, reconstruction of 80 Cine images was feasible, corresponding to a temporal resolution of around 1.5 ms. This was achieved without using any form of data interpolation. With retrospective triggering, the MRI measurements are not synchronized with the ECG, thereby in theory sampling an infinite number of time points during the cardiac cycle. Correct assignment of each k-line to a specific cardiac frame could be done retrospectively by measuring an additional navigator signal prior to image acquisition, whose signal amplitude varies with cardiac as well as respiratory movements. Because in this case, filling of k-space for each cardiac frame is a stochastic process, simulations were performed to investigate the efficiency of the method with respect to signal averaging, which was found to be almost equal compared to regular prospective triggering. Diabetic cardiomyopathy has a high prevalence in type 2 diabetes patients and is characterized by diastolic dysfunction. With the current technique, we were indeed able to measure a subtle reduction is several diastolic function parameters, which are the E/A-ratio and the E-contribution to total left ventricular filling. Therefore, this technique is a promising tool in experimental studies of diabetic cardiomyopathy and for evaluation of emerging treatment strategies for diastolic dysfunction. Myocardial perfusion Chapter 4 describes the application of first-pass perfusion measurements in a mouse model of myocardial infarction to allow the assessment of the myocardial perfusion status. A first-pass perfusion measurement is performed by venous injection of an MRI contrast agent and monitoring its passage through the left ventricle and myocardial wall. From the signal intensity changes upon passage of the contrast agent, myocardial perfusion values can be determined. The application of this technique in mice requires ultra-fast MRI sequences that can sample the signal intensity-time curves with sufficient temporal resolution. Because this concerns imaging of non-periodic signal changes this is a much different problem compared to the diastolic function experiments described in chapter 3. We showed that using a saturation recovery MRI sequence with segmented k-space read-out in combination with parallel imaging acceleration techniques, a time-series of images could be acquired with a temporal resolution of 1 image for each 3 heart beats. The use of parallel imaging was crucial, since this requires less k-lines for image reconstruction compared to conventional imaging. Furthermore, the use of saturation pulses enhanced the contrast between contrast-enhanced and non-enhanced blood and myocardium. Using this technique, semi-quantitative perfusion values could be determined based on the upslope of the signal intensity-time curves. Experiments in mice with permanent occlusion of the LAD showed a significant decrease of perfusion values in the infarcted myocardium as compared to remote myocardium. In future experiments, this technique will be extended to provide quantitative perfusion values (in mg/l/min), requiring determination of the true arterial input function from a pre-bolus measurement with a smaller contrast agent bolus volume. T1 and T2 relaxation times Pathology is often accompanied by a change in the magnetic properties of the tissue, in particular the T1 and T2 relaxation times. This directly affects the signal intensity on the MR image. Diseased and healthy tissue can therefore be discriminated on MR images, which is one of the main applications of MRI in clinical diagnostics. However, there is much interest in quantitative assesment of T1 and T2 relaxation times, as this improves repeatibility of results in longitudinal studies and reproducibility between research groups. In this thesis, we aimed at developing protocols for both T1 and T2 mapping of the complete mouse heart for application in mouse models of myocardial infarction. Whole-heart coverage is important considering that a priori, the extent of the infarct is unknown. Currently available protocols for T1 mapping are relatvively time-consuming. In chapter 5, a 3D T1 mapping sequence is presented which allows myocardial T1 quantification of the mouse heart within 20 minutes. The retrospective triggering sequence used in chapter 3 proved also useful in this study, because it allows steady-state acqusition with very short repetition times, enabling whole heart coverage. T1 values were derived from measuring a variable flip angle data set and using available MRI signal models. Variable flip angle data showed excellent agreement in cardiac anatomy, allowing pixel-wise determination of T1. In healthy mice, no substantial differences in T1 were found for different heart regions in the 3D volume. Coefficents of repeatibility were determined from measurements at different days, which varied as function of the number of flip angles used in data analysis. In contrast to T1, T2 values could not be acquired using 3D acquisitons or retrospective triggering. Alternatively, chapter 6 describes a multi-slice T2 mapping protocol for the mouse heart based on a ECG-triggered T2 magnetization preparation module with variable TE. Because the preparation module consisted of many consecutive RF pulses, the effect of these pulses on T2 relxation had to be taken into account. Additionally, simulations were used to calculate the effect of T1 relaxation on T2 estimation, which was small as long as the repetition time was kept sufficiently long. Homogeneous T2 maps of healthy mouse heart were obtained, with no substantial differences between different heart regions or slices. In a ischemia/reperfusion model, elevated T2 values were found in the infarcted area, probably as result of edema formation. The extent of the infarction was also measured using late gadolinium enhanced imaging. The degree of correlation of T2 and LGE enhanced regions strongly depended on the signal intensity thresholds derived from remote tissue. Contrast agent accumulation Another application of quantitative T1 and T2¬ mapping is the assessment of the concentration of a contrast agent, which has been targeted to a specific disease site. This is especially valuable in molecular imaging applications where contrast agents report on the presence of specific disease markers related to various cardiac remodeling processes after myocardial infarction. Chapter 7 describes the application of the T1 mapping protocol from chapter 5 to quantify the accumulation of a Gd-based liposomal contrast agent in a model of myocardial infarction. Functional imaging and assessment of wall thickening values were used to determine which regions could be identified as being infarcted. Statistical analysis showed that before contrast agent administration, T¬1¬ values were already elevated in the infarcted regions as compared to remote myocardium, however, a more pronounced change in T1 values was found 24h post-contrast, with significantly lower T1 values in the infarcted areas. Pre-contrast T1 values in control mice were very similar to the study described in chapter 5, proving good reproducibility of T1 quantification using our methods. After the MRI measurement, the hearts were cut into slices, from which the Gd-content was determined in different sections of the heart using inductively coupled plasma mass spectrometry. T1 changes measured using in vivo MRI correlated well with ex vivo measurements of Gd concentration. These are promising results for quantification of contrast agent concentrations in contrast-enhanced MRI of mouse models of cardiac disease. More research has to be performed with regard to changes in contrast agent efficiency as a result of different cellular environments. Our results already indicate that the relaxivity values of liposomal contrast agents are significantly lower in vivo as compared to values obtained from measurements in phantom solutions. Conclusion This thesis has shown that mouse cardiac MRI is capable of assessing a large variety of parameters related to cardiac physiology in the in vivo mouse heart in a non-invasive way. This makes this technique an attractive platform for experimental studies on cardiac disease, as well as developing new treatment strategies

Identification and evaluation of biomarkers for Huntington’s disease

Huntington’s disease (HD) is a devastating, incurable inherited neurodegenerative disorder that commonly affects adults in mid-life. Despite encouraging results from in vitro and animal trials, disease-modifying therapeutic trials in HD are limited by a lack of tools to track disease progression. HD is clinically heterogeneous, and current clinical rating scales lack sensitivity and specificity, particularly over relatively short time periods. Improvements in the precision of objective measurement of disease progression in HD could lead to state markers (biomarkers) better able to predict onset, detect progression and measure the effects of therapeutic intervention. Biomarkers capable of detecting disease-related changes in premanifest gene carriers will be essential for clinical trials of treatments to delay onset. Imaging, clinical and cognitive assessment as well as laboratory markers have all been proposed as biomarkers, but few measures have been quantified over short time intervals or shown to be predictive of clinical change over longer periods. A robust panel of biomarkers from a number of modalities will be necessary to progress to interventional clinical trials of disease-modifying therapies in HD, using biomarkers to measure the success or failure of an intervention. Such cross-validation requires simultaneous multimodal biomarker evaluation within a suitable cohort of subjects studied longitudinally. This thesis describes a multi-modal approach to the discovery and evaluation of potential biomarkers for Huntington's disease in a large cohort of human volunteers. After reviewing the relevant features of Huntington's disease and current state of biomarker research in Huntington's disease, several approaches to, and outcomes from, biomarker discovery and evaluation are described, including proteomic profiling, targeted ELISA, multiplex inflammatory profiling and measurement of whole-brain atrophy by longitudinal magnetic resonance imaging. The thesis draws together these different approaches and summarises the contributions to both biomarker research and our understanding of the neurobiology of HD that the work has generated

Techniques for Analysis and Motion Correction of Arterial Spin Labelling (ASL) Data from Dementia Group Studies

This investigation examines how Arterial Spin Labelling (ASL) Magnetic Resonance Imaging can be optimised to assist in the early diagnosis of diseases which cause dementia, by considering group study analysis and control of motion artefacts. ASL can produce quantitative cerebral blood flow maps noninvasively - without a radioactive or paramagnetic contrast agent being injected. ASL studies have already shown perfusion changes which correlate with the metabolic changes measured by Positron Emission Tomography in the early stages of dementia, before structural changes are evident. But the clinical use of ASL for dementia diagnosis is not yet widespread, due to a combination of a lack of protocol consistency, lack of accepted biomarkers, and sensitivity to motion artefacts. Applying ASL to improve early diagnosis of dementia may allow emerging treatments to be administered earlier, thus with greater effect. In this project, ASL data acquired from two separate patient cohorts ( (i) Young Onset Alzheimer’s Disease (YOAD) study, acquired at Queen Square; and (ii) Incidence and RISk of dementia (IRIS) study, acquired in Rotterdam) were analysed using a pipeline optimised for each acquisition protocol, with several statistical approaches considered including support-vector machine learning. Machine learning was also applied to improve the compatibility of the two studies, and to demonstrate a novel method to disentangle perfusion changes measured by ASL from grey matter atrophy. Also in this project, retrospective motion correction techniques for specific ASL sequences were developed, based on autofocusing and exploiting parallel imaging algorithms. These were tested using a specially developed simulation of the 3D GRASE ASL protocol, which is capable of modelling motion. The parallel imaging based approach was verified by performing a specifically designed MRI experiment involving deliberate motion, then applying the algorithm to demonstrably reduce motion artefacts retrospectively

Free Breathing Real-Time Cardiac Cine Imaging With Improved Spatial Resolution at 3 T

Objectives: The aim of this study was to evaluate free-breathing single-shot real-time cine imaging for functional cardiac imaging at 3 +/- with increased spatial resolution. Special emphasis of this study was placed on the influence of parallel imaging techniques. Materials and Methods: Gradient echo phantom images were acquired with GRAPPA and modified SENSE reconstruction using both integrated and separate reference scans as well as TGRAPPA and TSENSE. In vivo measurements were performed for GRAPPA reconstruction with an integrated and a separate reference scan, as well as TGRAPPA using balanced steady-state free precession protocols. Three clinical protocols, rtLRInt (T-res = 51.3 milliseconds; voxel, 2.5 x 5.0 x 10 mm(3)), rtMRSep (T-res = 48.8 milliseconds; voxel, 1.9 x 3.1 x 10 mm(3)), and rtHRSep ((Tres) = 48.3 milliseconds; voxel, 1.6 x 2.6 x 10 mm(3)), were investigated on 20 volunteers using GRAPPA reconstruction with internal as well as separate reference scans. End-diastolic volume, end-systolic volume, ejection fraction, peak ejection rate, peak filling rate, and myocardial mass were evaluated for the left ventricle and compared with an electrocardiogram-triggered segmented readout cine protocol used as standard of reference. All studies were performed at 3 T. Results: Phantom and in vivo data demonstrate that the combination of GRAPPA reconstruction with a separate reference scan provides an optimal compromise of image quality as well as spatial and temporal resolution. Functional values (P values) for the standard of reference, rtLRInt, rtMRSep, and rtHRSep end-diastolic volume were 141 +/- 24 mL, 138 +/- 21 mL, 138 +/- 19 mL, and 128 +/- 33 mL, respectively (P = 0.7, 0.7, 0.4); end-systolic volume, 55 +/- 15 mL, 61 +/- 14 mL, 58 +/- 12 mL, and 55 +/- 20 mL, respectively (P = 0.23, 0.43, 0.62); ejection fraction, 61% +/- 5%, 57% +/- 5%, 58% +/- 4%, and 56% +/- 8%, respectively (P = 0.01, 0.11, 0.06); peak ejection rate, 481 +/- 73 mL/s, 425 +/- 62 mL/s, 434 +/- 67 mL/s, and 381 +/- 86 mL/s, respectively (P = 0.03, 0.04, 0.01); peak filling rate, 555 +/- 80 mL/s, 480 +/- 70 mL/s, 500 +/- 70 mL/s, and 438 +/- 108 mL/s, respectively (P = 0.007, 0.05, 0.004); and myocardial mass, 137 +/- 26 g, 141 T 25 g, 141 +/- 23 g, and 130 +/- 31 g, respectively (P = 0.62, 0.54, 0.99). Conclusions: Using a separate reference scan and high acceleration factors up to R = 6, single-shot real-time cardiac imaging offers adequate temporal and spatial resolution for accurate assessment of global left ventricular function in free breathing with short examination times

Methods and algorithms for quantitative analysis of metallomic images to assess traumatic brain injury

The primary aim of this thesis is to develop image processing algorithms to quantitatively determine the link between traumatic brain injury (TBI) severity and chronic traumatic encephalopathy (CTE) neuropathology, specifically looking into the role of blood-brain barrier disruption following TBI. In order to causally investigate the relationship between the tau protein neurodegenerative disease CTE and TBI, mouse models of blast neurotrauma (BNT) and impact neurotrauma (INT) are investigated. First, a high-speed video tracking algorithm is developed based on K-means clustering, active contours and Kalman filtering to comparatively study the head kinematics in blast and impact experiments. Then, to compare BNT and INT neuropathology, methods for quantitative analysis of macroscopic optical images and fluorescent images are described. The secondary aim of this thesis focuses on developing methods for a novel application of metallomic imaging mass spectrometry (MIMS) to biological tissue. Unlike traditional modalities used to assess neuropathology, that suffer from limited sensitivity and analytical capacity, MIMS uses a mass spectrometer -- an analytical instrument for measuring elements and isotopes with high dynamic range, sensitivity and specificity -- as the imaging sensor to generate spatial maps with spectral (vector-valued) data per pixel. Given the vector nature of MIMS data, a unique end-to-end processing pipeline is designed to support data acquisition, visualization and interpretation. A novel multi-modal and multi-channel image registration (MMMCIR) method using multi-variate mutual information as a similarity metric is developed in order to establish correspondence between two images of arbitrary modality. The MMMCIR method is then used to automatically segment MIMS images of the mouse brain and systematically evaluate the levels of relevant elements and isotopes after experimental closed-head impact injury on the impact side (ipsilateral) and opposing side (contralateral) of the brain. This method quantifiably confirms observed differences in gadolinium levels for a cohort of images. Finally, MIMS images of human lacrimal sac biopsy samples are used for preliminary clinicopathological assessments, supporting the utility of the unique insights MIMS provides by correlating areas of inflammation to areas of elevated toxic metals. The image processing methods developed in this work demonstrate the significant capabilities of MIMS and its role in enhancing our understanding of the underlying pathological mechanisms of TBI and other medical conditions.2019-07-09T00:00:00

Recommended Implementation of Quantitative Susceptibility Mapping for Clinical Research in The Brain: A Consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group

This article provides recommendations for implementing quantitative susceptibility mapping (QSM) for clinical brain research. It is a consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available give rise to the need in the neuroimaging community for guidelines on implementation. This article describes relevant considerations and provides specific implementation recommendations for all steps in QSM data acquisition, processing, analysis, and presentation in scientific publications. We recommend that data be acquired using a monopolar 3D multi-echo GRE sequence, that phase images be saved and exported in DICOM format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields should be removed within the brain mask using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of whole brain as a region of interest in the analysis, and QSM results should be reported with - as a minimum - the acquisition and processing specifications listed in the last section of the article. These recommendations should facilitate clinical QSM research and lead to increased harmonization in data acquisition, analysis, and reporting