Association Between Body Composition and Survival in Patients With Gastroesophageal Adenocarcinoma: An Automated Deep Learning Approach.

PURPOSE: Body composition (BC) may play a role in outcome prognostication in patients with gastroesophageal adenocarcinoma (GEAC). Artificial intelligence provides new possibilities to opportunistically quantify BC from computed tomography (CT) scans. We developed a deep learning (DL) model for fully automatic BC quantification on routine staging CTs and determined its prognostic role in a clinical cohort of patients with GEAC. MATERIALS AND METHODS: We developed and tested a DL model to quantify BC measures defined as subcutaneous and visceral adipose tissue (VAT) and skeletal muscle on routine CT and investigated their prognostic value in a cohort of patients with GEAC using baseline, 3-6-month, and 6-12-month postoperative CTs. Primary outcome was all-cause mortality, and secondary outcome was disease-free survival (DFS). Cox regression assessed the association between (1) BC at baseline and mortality and (2) the decrease in BC between baseline and follow-up scans and mortality/DFS. RESULTS: Model performance was high with Dice coefficients ≥0.94 ± 0.06. Among 299 patients with GEAC (age 63.0 ± 10.7 years; 19.4% female), 140 deaths (47%) occurred over a median follow-up of 31.3 months. At baseline, no BC measure was associated with DFS. Only a substantial decrease in VAT >70% after a 6- to 12-month follow-up was associated with mortality (hazard ratio [HR], 1.99 [95% CI, 1.18 to 3.34]; P = .009) and DFS (HR, 1.73 [95% CI, 1.01 to 2.95]; P = .045) independent of age, sex, BMI, Union for International Cancer Control stage, histologic grading, resection status, neoadjuvant therapy, and time between surgery and follow-up CT. CONCLUSION: DL enables opportunistic estimation of BC from routine staging CT to quantify prognostic information. In patients with GEAC, only a substantial decrease of VAT 6-12 months postsurgery was an independent predictor for DFS beyond traditional risk factors, which may help to identify individuals at high risk who go otherwise unnoticed.

Time-resolved magnetic resonance angiography and flow-sensitive 4-dimensional magnetic resonance imaging at 3 Tesla for blood flow and wall shear stress analysis.

OBJECTIVES: In light of the ongoing discussion about flow-mediated arterial remodeling, it was the aim of this report to demonstrate the detailed assessment of 3-dimensional vascular hemodynamics by high-field magnetic resonance imaging in healthy volunteers and to illustrate its potential in comparison with results in a patient with stenosis. MATERIALS AND METHODS: All examinations consisted of flow-sensitive 4-dimensional magnetic resonance imaging at 3 Tesla. Retrospective blood flow visualization and segmental quantification of wall shear stress and oscillatory shear index were performed. The results from 11 healthy individuals were compared with a 13-year-old patient with aortic stenosis who received a combined protocol with time-resolved 3-dimensional magnetic resonance angiography before and 5 and 9 months after intervention. RESULTS: Evaluation of normal blood flow characteristics demonstrated predominantly right-handed helical flow in the ascending aorta. Vortex formation was observed in 1 of 11 volunteers. Consistently high segmental wall shear stress was found along the circumference of the ascending aorta (average wall shear stress = 0.191 +/- 0.06 N/m(2)) and descending aorta (average 0.191 +/- 0.06 N/m(2)). Compared with volunteers, the patient revealed substantial flow changes proximal and distal to the stenosis. Blood flow alterations in the ascending aorta were also observed associated with changes in velocities and wall shear stress that gradually normalized after intervention. CONCLUSION: Flow-sensitive 4-dimensional magnetic resonance imaging at 3 Tesla can provide deeper insights into hemodynamic alterations in the diagnosis and follow-up of aortic pathologies. These findings indicate the potential of the methodology for the evaluation of effects of localized pathologies on the entire vascular system, which will have to be confirmed in future studies.