Bluetooth Noise-Canceling Headphones Improve the Quality of Ophthalmic Exams in Patients With Hearing Loss: A Randomized Controlled Trial.

Introduction: This study tests the utilization of Bluetooth noise-canceling headphones in improving the quality of eye exams in patients with hearing loss. This prospective study was approved on ethical standards by the University of Texas Medical Branch (UTMB) Institutional Review Board (Approval No. 22-0079) and registered with the National Institutes of Health (NCT05420038).

Incidence of Ophthalmological Complications in NF-1 Patients Treated with MEK Inhibitors.

MEK inhibitors (MEKi) represent innovative and promising treatments for managing manifestations of neurofibromatosis type 1 (NF1). To mitigate potential ophthalmic side effects, such as MEKi-associated retinopathy (MEKAR), patients undergoing MEKi therapy routinely receive ophthalmology evaluations. Our study aims to assess the necessity of this regular screening within a predominantly pediatric NF1 population by examining the occurrence of ocular adverse events (OAE).

Comprehensive Analysis of the Spatial Distribution of Gadolinium, Iron, Manganese, and Phosphorus in the Brain of Healthy Rats After High-Dose Administrations of Gadodiamide and Gadobutrol.

Objectives: After the administration of gadolinium-based contrast agents (GBCAs), residual gadolinium (Gd) has been detected in a few distinct morphological structures of the central nervous system (CNS). However, a systematic, comprehensive, and quantitative analysis of the spatial Gd distribution in the entire brain is not yet available. The first aim of this study is to provide this analysis in healthy rats after administration of high GBCA doses.

Dynamic parametric MRI and deep learning: Unveiling renal pathophysiology through accurate kidney size quantification.

Renal pathologies often manifest as alterations in kidney size, providing a valuable avenue for employing dynamic parametric MRI as a means to derive kidney size measurements for the diagnosis, treatment, and monitoring of renal disease. Furthermore, this approach holds significant potential in supporting MRI data-driven preclinical investigations into the intricate mechanisms underlying renal pathophysiology. The integration of deep learning algorithms is crucial in achieving rapid and precise segmentation of the kidney from temporally resolved parametric MRI, facilitating the use of kidney size as a meaningful (pre)clinical biomarker for renal disease.