AI-based Evaluation of cardiac real-time MRI with congenital heart disease

Cardiac MRI scans are an important tool used by cardiologists. It can be utilized for diagnoses and assessment of vital parameters like the stroke volume or blood flow. The significant reduction in acquisition time that is achievable nowadays allows the recording of realtime 3D videos of the human heart. Such high frame rates yield very large amounts of data. To evaluate this data highly efficiently and with as little manual intervention as possible, it must be processed and interpreted automatically. We introduce the key challenges in such automated evaluations of realtime cardiac MRI. As patients are able breath freely during the examination, the effect of respiration on parameters such as blood flow and stroke volume can be investigated. However, this leads to the challenge of respiratory synchronization. Also, as the 3D representation of the heart is acquired slice by slice, the cardiac cycles in those slices must be synchronized. Another challenge is the physiological segmentation of the images. Especially for pathological hearts (e.g. univentricular hearts) this is a great challenge as high accuracy and automation are demanded. Furthermore, we present our workflow to tackle those challenges and show and discuss first results. One result is a breath- and cardiac cycle synchronized segmented univentricular heart in 4D (3D+time)

Glucose-sensitive hypothalamic nuclei traced through functional magnetic resonance imaging

IntroductionHypothalamic glucose-sensitive neural circuits, which regulate energy metabolism and can contribute to diseases such as obesity and type 2 diabetes, have been difficult to study in humans. We developed an approach to assess hypothalamic functional connectivity changes during glucose loading using functional magnetic resonance imaging (fMRI).MethodsTo do so, we conducted oral glucose tolerance tests while acquiring functional images before, and 10 and 45 min after glucose ingestion in a healthy male and cross-sectionally in 20 healthy participants on two different diets.ResultsAt group level, 39 fMRI sessions were not sufficient to detect glucose-mediated connectivity changes. However, 10 repeated sessions in a single subject revealed significant intrinsic functional connectivity increases 45 min after glucose intake in the arcuate, paraventricular, and dorsomedial nuclei, as well as in the posterior hypothalamic area, median eminence, and mammillary bodies.DiscussionOur methodology allowed to outline glucose-sensitive hypothalamic pathways in a single human being and holds promise in delineating individual pathophysiology mechanisms in patients with dysglycemia