Contrast agent-free synthesis and segmentation of ischemic heart disease images using progressive sequential causal GANs.

The elimination of gadolinium contrast agent (CA) injections and manual segmentation are crucial for ischemic heart disease (IHD) diagnosis and treatment. In the clinic, CA-based late gadolinium enhancement (LGE) imaging and manual segmentation remain subject to concerns about potential toxicity, interobserver variability, and ineffectiveness. In this study, progressive sequential causal GANs (PSCGAN) are proposed.

Segmentation and quantification of infarction without contrast agents via spatiotemporal generative adversarial learning.

Accurate and simultaneous segmentation and full quantification (all indices are required in a clinical assessment) of the myocardial infarction (MI) area are crucial for early diagnosis and surgical planning. Current clinical methods remain subject to potential high-risk, nonreproducibility and time-consumption issues. In this study, a deep spatiotemporal adversarial network (DSTGAN) is proposed as a contrast-free, stable and automatic clinical tool to simultaneously segment and quantify MIs directly from the cine MR image.

Characterization of cholesterol homeostasis in telomerase-immortalized Tangier disease fibroblasts reveals marked phenotype variability.

We compared the consequences of an ABCA1 mutation that produced an apparent lack of atherosclerosis (Tangier family 1, N935S) with an ABCA1 mutation with functional ABCA1 knockout that was associated with severe atherosclerosis (Tangier family 2, Leu(548):Leu(575)-End), using primary and telomerase-immortalized fibroblasts. Telomerase-immortalized Tangier fibroblasts of family 1 (TT1) showed 30% residual cholesterol efflux capacity in response to apolipoprotein A-I, whereas telomerase-immortalized Tangier fibroblasts of family 2 (TT2) showed only 20%. However, there were a number of secondary differences that were often stronger and may help to explain the more rapid development of atherosclerosis in family 2.