Fibromuscular Dysplasia Implicated in Spontaneous Coronary Artery Dissection (SCAD): A Case Report of Chest Pain in Young Women.

Spontaneous coronary artery dissection (SCAD) is a well-recognized cause of acute coronary syndrome (ACS) which can lead to myocardial infarction and sudden death. Unlike typical atherosclerosis, SCAD operates through distinct pathophysiology, affecting both individuals with and without conventional cardiovascular risk factors. We present a case of a young female presented with retrosternal chest pain radiating to the left arm, mimicking ACS symptoms with mildly elevated troponin levels, and slightly reduced left ventricular ejection fraction (45%). Subsequent evaluation using coronary angiography unveiled a Type 2A SCAD. A comprehensive computed tomography angiography (CTA) of her entire body revealed findings suggestive of fibromuscular dysplasia (FMD) affecting multiple arteries in different sites. Our case entailed the successful management of a young female patient with SCAD stemming from FMD.

Bioinspired Lubricity from Surface Gel Layers.

Surface gel layers on commercially available contact lenses have been shown to reduce frictional shear stresses and mitigate damage during sliding contact with fragile epithelial cell layers in vitro. Spencer and co-workers recently demonstrated that surface gel layers could arise from oxygen-inhibited free-radical polymerization. In this study, polyacrylamide hydrogel shell probes (7.5 wt % acrylamide, 0.3 wt % N,N'-methylenebisacrylamide) were polymerized in three hemispherical molds listed in order of decreasing surface energy and increasing oxygen permeability: borosilicate glass, polyether ether ketone (PEEK), and polytetrafluoroethylene (PTFE). Hydrogel probes polymerized in PEEK and PTFE molds exhibited 100× lower elastic moduli at the surface (EPEEK* = 80 ± 31 and EPTFE* = 106 ± 26 Pa, respectively) than those polymerized in glass molds (Eglass* = 31,560 ± 1,570 Pa), in agreement with previous investigations by Spencer and co-workers. Biotribological experiments revealed that hydrogel probes with surface gel layers reduced frictional shear stresses against cells (τPEEK = 35 ± 15 and τPTFE = 22 ± 16 Pa) more than those without (τglass = 68 ± 15 Pa) and offered greater protection against cell damage when sliding against human telomerase-immortalized corneal epithelial (hTCEpi) cell monolayers. Our work demonstrates that the "mold effect" resulting in oxygen-inhibition polymerization creates hydrogels with surface gel layers that reduce shear stresses in sliding contact with cell monolayers, similar to the protection offered by gradient mucin gel networks across epithelial cell layers.

Utility of machine learning of apparent diffusion coefficient (ADC) and T2-weighted (T2W) radiomic features in PI-RADS version 2.1 category 3 lesions to predict prostate cancer diagnosis.

PURPOSE: To evaluate if machine learning (ML) of radiomic features extracted from apparent diffusion coefficient (ADC) and T2-weighted (T2W) MRI can predict prostate cancer (PCa) diagnosis in Prostate Imaging-Reporting and Data System (PI-RADS) version 2.1 category 3 lesions. METHODS: This multi-institutional review board-approved retrospective case-control study evaluated 158 men with 160 PI-RADS category 3 lesions (79 peripheral zone, 81 transition zone) diagnosed at 3-Tesla MRI with histopathology diagnosis by MRI-TRUS-guided targeted biopsy. A blinded radiologist confirmed PI-RADS v2.1 score and segmented lesions on axial T2W and ADC images using 3D Slicer, extracting radiomic features with an open-source software (Pyradiomics). Diagnostic accuracy for (1) any PCa and (2) clinically significant (CS; International Society of Urogenital Pathology Grade Group ≥ 2) PCa was assessed using XGBoost with tenfold cross -validation. RESULTS: From 160 PI-RADS 3 lesions, there were 50.0% (80/160) PCa, including 36.3% (29/80) CS-PCa (63.8% [51/80] ISUP 1, 23.8% [19/80] ISUP 2, 8.8% [7/80] ISUP 3, 3.8% [3/80] ISUP 4). The remaining 50.0% (80/160) lesions were benign. ML of all radiomic features from T2W and ADC achieved area under receiver operating characteristic curve (AUC) for diagnosis of (1) CS-PCa 0.547 (95% Confidence Intervals 0.510-0.584) for T2W and 0.684 (CI 0.652-0.715) for ADC and (2) any PCa 0.608 (CI 0.579-0.636) for T2W and 0.642 (CI 0.614-0.0.670) for ADC. CONCLUSION: Our results indicate ML of radiomic features extracted from T2W and ADC achieved at best moderate accuracy for determining which PI-RADS category 3 lesions represent PCa.