Diagnostic Ability and Correlation of Digital C-Methionine PET/CT in Primary Hyperparathyroidism with Inconclusive Standard Imaging.

Purpose: C-Methionine PET/CT is a promising method for detecting parathyroid lesions in patients with primary hyperparathyroidism (PHPT). We aimed to determine the diagnostic ability and correlation of digital C-Methionine PET/CT for parathyroid lesions in patients with PHPT, particularly in cases where standard imaging methods yielded inconclusive results.

Methods: This retrospective analysis was conducted on patients diagnosed with PHPT who underwent digital C-Methionine PET/CT imaging because of ambiguous results on standard imaging work-up (Tc-MIBI parathyroid scan and/or neck ultrasonography).

Fully automated segmentation and classification of renal tumors on CT scans via machine learning.

Background: To develop and test the performance of a fully automated system for classifying renal tumor subtypes via deep machine learning for automated segmentation and classification.

Materials And Methods: The model was developed using computed tomography (CT) images of pathologically proven renal tumors collected from a prospective cohort at a medical center between March 2016 and December 2020. A total of 561 renal tumors were included: 233 clear cell renal cell carcinomas (RCCs), 82 papillary RCCs, 74 chromophobe RCCs, and 172 angiomyolipomas.

Time-resolved Brownian tomography of single nanocrystals in liquid during oxidative etching.

Colloidal nanocrystals inherently undergo structural changes during chemical reactions. The robust structure-property relationships, originating from their nanoscale dimensions, underscore the significance of comprehending the dynamic structural behavior of nanocrystals in reactive chemical media. Moreover, the complexity and heterogeneity inherent in their atomic structures require tracking of structural transitions in individual nanocrystals at three-dimensional (3D) atomic resolution.