Epidemiology of Mycobacterium abscessus.

Background: Nontuberculous mycobacteria (NTM) are highly abundant in soil, dust, and water sources, making human-pathogen contact frequent and recurrent. NTM represents over 200 species/subspecies; some are considered strict or opportunistic pathogens. Mycobacterium abscessus, often regarded as one of the most antibiotic-resistant mycobacteria, is the second most frequent NTM pulmonary disease pathogen.

Prognostic utility of the chest computed tomography severity score for the requirement of mechanical ventilation and mortality in hospitalized patients with COVID-19.

Purpose: To correlate the chest computed tomography severity score (CT-SS) with the need for mechanical ventilation and mortality in hospitalized patients with COVID-19.

Materials And Methods: The chest CT images of 224 inpatients with COVID-19, confirmed by reverse transcriptase-polymerase chain reaction (RT-PCR), were retrospectively reviewed from April 1 to 25, 2020, in a tertiary health care center. We calculated the CT-SS (dividing each lung into 20 segments and assigning scores of 0, 1, and 2 due to opacification involving 0%, <50%, and ≥50% of each region for a global range of 0-40 points, including both lungs), and collected clinical data.

Semiautomatic assessment of whole-body tumor burden with 18F-PSMA-1007 in biochemical recurrent prostate cancer.

Objective: The aim of the study was to evaluate the 18F-PSMA-1007 PET/computed tomography (CT) semiautomatic volumetric parameters to assess the whole-body tumor burden and its correlation with prostate-specific antigen (PSA) and Gleason score in patients with biochemically recurrent prostate cancer (PCa).

Materials And Methods: A total of 110 patients referred for 18F-PSMA-1007 PET/CT due to biochemical recurrence were retrospectively analyzed. Whole-body total lesion prostate-specific membrane antigen (wbTl-PSMA) and whole-body PSMA-derived tumor volume (wbPSMA-TV) metrics on 18F-PSMA-1007 were obtained semiautomatically in dedicated software.

Validation of Chest Computed Tomography Artificial Intelligence to Determine the Requirement for Mechanical Ventilation and Risk of Mortality in Hospitalized Coronavirus Disease-19 Patients in a Tertiary Care Center In Mexico City.

Background: Artificial intelligence (AI) in radiology has improved diagnostic performance and shortened reading times of coronavirus disease 2019 (COVID-19) patients' studies.

Objectives: The objectives pf the study were to analyze the performance of a chest computed tomography (CT) AI quantitative algorithm for determining the risk of mortality/mechanical ventilation (MV) in hospitalized COVID-19 patients and explore a prognostic multivariate model in a tertiary-care center in Mexico City.

Methods: Chest CT images of 166 COVID-19 patients hospitalized from April 1 to 20, 2020, were retrospectively analyzed using AI algorithm software.

[Evaluation of the characteristics of aortic dissection by computed angio-tomography in the Mexican population].

Objective: To review aortic dissection (AD) in the Mexican population.

Method: A retrospective study was conducted using 434 medical records of patients with aortic angio-tomography between November 2014 and October 2015. A sample was obtained of 32 patients with a first time diagnosis of AD.