Publications by authors named "L Tanenbaum"
Article Synopsis
- * The paper aims to help radiologists by discussing MRI protocols, workflows, and reporting practices for monitoring amyloid-related imaging abnormalities (ARIA).
- * Key topics include FDA guidelines for ARIA evaluation, standard MRI sequences, patient imaging scenarios, the radiologist's role in treatment, and results from a 2023 survey on dementia imaging practices.
Article Synopsis
- * Research is focused on creating next-generation GBCAs, such as Gadopiclenol, which offers high relaxivity and stability, allowing for lower doses without sacrificing imaging quality.
- * Future approaches may combine these advanced GBCAs with new imaging technologies and AI to improve diagnostic accuracy while reducing gadolinium exposure for patients.
Background And Purpose: Deep learning image reconstruction allows faster MR imaging acquisitions while matching or exceeding the standard of care and can create synthetic images from existing data sets. This multicenter, multireader spine study evaluated the performance of synthetically created STIR compared with acquired STIR.
Materials And Methods: From a multicenter, multiscanner data base of 328 clinical cases, a nonreader neuroradiologist randomly selected 110 spine MR imaging studies in 93 patients (sagittal T1, T2, and STIR) and classified them into 5 categories of disease and healthy.
Objective: This prospective multicenter multireader study evaluated the performance of 40% scan-time reduced spinal magnetic resonance imaging (MRI) reconstructed with deep learning (DL).
Methods: A total of 61 patients underwent standard of care (SOC) and accelerated (FAST) spine MRI. DL was used to enhance the accelerated set (FAST-DL).