A Kernel-based Approach to Diffusion Tensor and Fiber Clustering in the Human Skeletal Muscle

In this report, we present a kernel-based approach to the clustering of diffusion tensors in images of the human skeletal muscle. Based on the physical intuition of tensors as a means to represent the uncertainty of the position of water protons in the tissues, we propose a Mercer (i.e. positive definite) kernel over the tensor space where both spatial and diffusion information are taken into account. This kernel highlights implicitly the connectivity along fiber tracts. We show that using this kernel in a kernel-PCA setting compounded with a landmark-Isomap embedding and k-means clustering provides a tractable framework for tensor clustering. We extend this kernel to deal with fiber tracts as input using the multi-instance kernel by considering the fiber as set of tensors centered in the sampled points of the tract. The obtained kernel reflects not only interactions between points along fiber tracts, but also the interactions between diffusion tensors. We give an interpretation of the obtained kernel as a comparison of soft fiber representations and show that it amounts to a generalization of the Gaussian kernel Correlation. As in the tensor case, we use the kernel-PCA setting and k-means for grouping of fiber tracts. This unsupervised method is further extended by way of an atlas-based registration of diffusion-free images, followed by a classification of fibers based on non-linear kernel Support Vector Machines (SVMs) and kernel diffusion. The experimental results on a dataset of diffusion tensor images of the calf muscle of 25 patients (of which 5 affected by myopathies, i.e. neuromuscular diseases) show the potential of our method in segmenting the calf in anatomically relevant regions both at the tensor and fiber level

Estimation of tissue contractility from cardiac cine-MRI using a biomechanical heart model

International audienceThe objective of this paper is to propose and assess an estimation procedure - based on data assimilation principles - well-suited to obtain some regional values of key biophysical parameters in a beating heart model, using actual Cine-MR images. The motivation is twofold: (1) to provide an automatic tool for personalizing the characteristics of a cardiac model in order to achieve predictivity in patient-specific modeling, and (2) to obtain some useful information for diagnosis purposes in the estimated quantities themselves. In order to assess the global methodology we specifically devised an animal experiment in which a controlled infarct was produced and data acquired before and after infarction, with an estimation of regional tissue contractility - a key parameter directly affected by the pathology - performed for every measured stage. After performing a preliminary assessment of our proposed methodology using synthetic data, we then demonstrate a full-scale application by first estimating contractility values associated with 6 regions based on the AHA subdivision, before running a more detailed estimation using the actual AHA segments. The estimation results are assessed by comparison with the medical knowledge of the specific infarct, and with late enhancement MR images. We discuss their accuracy at the various subdivision levels, in the light of the inherent modeling limitations and of the intrinsic information contents featured in the data

Cognitive behaviour therapy plus aerobic exercise training to increase activity in patients with myotonic dystrophy type 1 (DM1) compared to usual care (OPTIMISTIC):Study protocol for randomised controlled trial

Peer reviewedPublisher PD

Cognitive behavioural therapy with optional graded exercise therapy in patients with severe fatigue with myotonic dystrophy type 1:a multicentre, single-blind, randomised trial

Background: Myotonic dystrophy type 1 is the most common form of muscular dystrophy in adults and leads to severe fatigue, substantial physical functional impairment, and restricted social participation. In this study, we aimed to determine whether cognitive behavioural therapy optionally combined with graded exercise compared with standard care alone improved the health status of patients with myotonic dystrophy type 1. Methods: We did a multicentre, single-blind, randomised trial, at four neuromuscular referral centres with experience in treating patients with myotonic dystrophy type 1 located in Paris (France), Munich (Germany), Nijmegen (Netherlands), and Newcastle (UK). Eligible participants were patients aged 18 years and older with a confirmed genetic diagnosis of myotonic dystrophy type 1, who were severely fatigued (ie, a score of ≥35 on the checklist-individual strength, subscale fatigue). We randomly assigned participants (1:1) to either cognitive behavioural therapy plus standard care and optional graded exercise or standard care alone. Randomisation was done via a central web-based system, stratified by study site. Cognitive behavioural therapy focused on addressing reduced patient initiative, increasing physical activity, optimising social interaction, regulating sleep–wake patterns, coping with pain, and addressing beliefs about fatigue and myotonic dystrophy type 1. Cognitive behavioural therapy was delivered over a 10-month period in 10–14 sessions. A graded exercise module could be added to cognitive behavioural therapy in Nijmegen and Newcastle. The primary outcome was the 10-month change from baseline in scores on the DM1-Activ-c scale, a measure of capacity for activity and social participation (score range 0–100). Statistical analysis of the primary outcome included all participants for whom data were available, using mixed-effects linear regression models with baseline scores as a covariate. Safety data were presented as descriptives. This trial is registered with ClinicalTrials.gov, number NCT02118779. Findings: Between April 2, 2014, and May 29, 2015, we randomly assigned 255 patients to treatment: 128 to cognitive behavioural therapy plus standard care and 127 to standard care alone. 33 (26%) of 128 assigned to cognitive behavioural therapy also received the graded exercise module. Follow-up continued until Oct 17, 2016. The DM1-Activ-c score increased from a mean (SD) of 61·22 (17·35) points at baseline to 63·92 (17·41) at month 10 in the cognitive behavioural therapy group (adjusted mean difference 1·53, 95% CI −0·14 to 3·20), and decreased from 63·00 (17·35) to 60·79 (18·49) in the standard care group (−2·02, −4·02 to −0·01), with a mean difference between groups of 3·27 points (95% CI 0·93 to 5·62, p=0·007). 244 adverse events occurred in 65 (51%) patients in the cognitive behavioural therapy group and 155 in 63 (50%) patients in the standard care alone group, the most common of which were falls (155 events in 40 [31%] patients in the cognitive behavioural therapy group and 71 in 33 [26%] patients in the standard care alone group). 24 serious adverse events were recorded in 19 (15%) patients in the cognitive behavioural therapy group and 23 in 15 (12%) patients in the standard care alone group, the most common of which were gastrointestinal and cardiac. Interpretation: Cognitive behavioural therapy increased the capacity for activity and social participation in patients with myotonic dystrophy type 1 at 10 months. With no curative treatment and few symptomatic treatments, cognitive behavioural therapy could be considered for use in severely fatigued patients with myotonic dystrophy type 1. Funding: The European Union Seventh Framework Programme

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Quantitative assessment of myocardial perfusion in MRI. From registration to clinical measurements

International audienceThis paper presents a novel methodology for the non-rigid registration of cardiac perfusion MRI exams. The target medical application is the automated quantitative assessment of myocardial perfusion for clinical diagnosis and longitudinal study of ischemic pathologies. Specifically, an original variational method for the groupwise registration of p-MRI exams based on high-dimensional feature distribution matching using (normalized) mutual information, is developed. The hard issue of estimating information in high-dimensional spaces is solved using state-of-the-art kth-nearest neighbor (kNN) entropy estimators. Combined with mean-shift approximation, the latter allow to efficiently optimize (normalized) mutual information over finite- and infinite-dimensional motion spaces. This framework is applied to the groupwise alignment of cardiac p-MRI exams using local contrast enhancement curves as a feature set, and a B-spline model for cardio-thoracic motions. Preliminary experimental assessment suggests that the technique allows for accurately aligning up to 34 p-MRI images simultaneously, and for further reliably computing perfusion parameters whose joint analysis strongly correlates with expert-based visual diagnosis

Validation of a biomechanical heart model using animal data with acute myocardial infarction

International audienceIn this paper, we validate a biomechanical heart model with animal data providing a controlled infarct condition with a follow-up over several weeks. First, we set up the personalized model using data coming from the healthy animal, and we show that the simulations compare accurately with the measured data, both for the tissue motion and for the blood pressures. Then, we demonstrate that we can also adequately represent the behavior of the acutely infarcted heart by changing only the parameters directly related to the pathology, and to the physiological state of the subject during the exams

: Myocardial Perfusion

International audienceThe analysis of myocardial perfusion is a key step in the cardiac MRI examination. In routine work, this exploration carried out at rest is based on the qualitative first pass study of gadolinium with an ECG-triggered saturation recovery bFFE sequence. In view of recent knowledge, the analysis of the myocardial perfusion under vasodilator stress may be carried out by scintigraphy or MRI, the latter benefiting from the absence of exposure to ionizing rays and a lower cost. Besides coronary disease, the perfusion sequence provides a rich semiology to compare with the clinics and the data from other sequences. Arterial Spin Labeling (ASL) is an alternative technique used in the animal to quantify myocardial perfusion