Deep learning-based image reconstruction improves radiologic evaluation of pituitary axis and cavernous sinus invasion in pituitary adenoma.

Purpose: To compare performance of 1-mm deep learning reconstruction (DLR) with 3-mm routine MRI imaging for the delineation of pituitary axis and identification of cavernous sinus invasion for pituitary macroadenoma.

Method: This retrospective study included 104 patients (59.4 ± 13.

Diffuse glioma, not otherwise specified: imaging-based risk stratification achieves histomolecular-level prognostication.

Objectives: To determine whether imaging-based risk stratification enables prognostication in diffuse glioma, NOS (not otherwise specified).

Methods: Data from 220 patients classified as diffuse glioma, NOS, between January 2011 and December 2020 were retrospectively included. Two neuroradiologists analyzed pre-surgical CT and MRI to assign gliomas to the three imaging-based risk types considering well-known imaging phenotypes (e.

Intraoperative Graft Isometry in Anatomic Single-Bundle Anterior Cruciate Ligament Reconstruction.

Purpose: Little is known about the isometry of anatomic single-bundle anterior cruciate ligament (ACL) tunnel positions although it is closely related to graft tension throughout the range of motion. The purpose of this study was to evaluate intraoperative graft isometry in anatomic single-bundle ACL reconstruction .

Materials And Methods: Graft length changes were assessed before bio-screw fixation in the tibial tunnel by pulling the graft with tensions of 20 lbs and 30 lbs in full extension at flexion angles of 30°, 60°, 90°, and 120°.