Mycobacterial cavity on chest computed tomography: clinical implications and deep learning-based automatic detection with quantification.

Background: This study aimed (I) to investigate the clinical implication of computed tomography (CT) cavity volume in tuberculosis (TB) and non-tuberculous mycobacterial pulmonary disease (NTM-PD), and (II) to develop a three-dimensional (3D) nnU-Net model to automatically detect and quantify cavity volume on CT images.

Methods: We retrospectively included conveniently sampled 206 TB and 186 NTM-PD patients in a tertiary referral hospital, who underwent thin-section chest CT scans from 2012 through 2019. TB was microbiologically confirmed, and NTM-PD was diagnosed by 2007 Infectious Diseases Society of America/American Thoracic Society guideline.

Added value of [F]FDG PET/MRI over MDCT alone in the staging of recurrent gastric cancer.

Objectives: To investigate whether 2-[F]fluoro-2-deoxy-D-glucose ([F]FDG) positron emission tomography/magnetic resonance imaging (PET/MRI) can improve the diagnostic performance of TNM staging and help in making an accurate decision regarding resectability in patients with recurrent gastric cancer compared to multi-detector computed tomography (MDCT).

Methods: Fifty patients with histologically (n = 31) or clinically (n = 19) confirmed recurrent gastric cancer underwent both MDCT and [F]FDG PET/MRI. Two radiologists independently assessed TNM staging using MDCT with and without [F]FDG PET/MRI and scored resectability using a 5-point confidence scale.