Accurate preoperative staging of gastric cancer and the assessment of tumor response to neoadjuvant treatment is of importance for treatment and prognosis. Current imaging techniques, mainly endoscopic ultrasonography (EUS), computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET), have their limitations. Historically, the role of magnetic resonance imaging (MRI) in gastric cancer has been limited, but with the continuous technical improvements, MRI has become a more potent imaging technique for gastrointestinal malignancies. The accuracy of MRI for T- and N-staging of gastric cancer is similar to EUS and CT, making MRI a suitable alternative to other imaging strategies. There is limited evidence on the performance of MRI for M-staging of gastric cancer specifically, but MRI is widely used for diagnosing liver metastases and shows potential for diagnosing peritoneal seeding. Recent pilot studies showed that treatment response assessment as well as detection of lymph node metastases and systemic disease might benefit from functional MRI (e.g. diffusion weighted imaging and dynamic contrast enhancement). Regarding treatment guidance, additional value of MRI might be expected from its role in better defining clinical target volumes and setup verification with MR-guided radiation treatment.

Nearly one third of patients undergoing neoadjuvant chemoradiotherapy (nCRT) for locally advanced esophageal cancer have a pathologic complete response (pCR) of the primary tumor upon histopathological evaluation of the resection specimen. The primary aim of this study is to develop a model that predicts the probability of pCR to nCRT in esophageal cancer, based on diffusion-weighted magnetic resonance imaging (DW-MRI), dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and 18F-fluorodeoxyglucose positron emission tomography with computed tomography (18F-FDG PET-CT). Accurate response prediction could lead to a patient-tailored approach with omission of surgery in the future in case of predicted pCR or additional neoadjuvant treatment in case of non-pCR. The PRIDE study is a prospective, single arm, observational multicenter study designed to develop a multimodal prediction model for histopathological response to nCRT for esophageal cancer. A total of 200 patients with locally advanced esophageal cancer - of which at least 130 patients with adenocarcinoma and at least 61 patients with squamous cell carcinoma - scheduled to receive nCRT followed by esophagectomy will be included. The primary modalities to be incorporated in the prediction model are quantitative parameters derived from MRI and 18F-FDG PET-CT scans, which will be acquired at fixed intervals before, during and after nCRT. Secondary modalities include blood samples for analysis of the presence of circulating tumor DNA (ctDNA) at 3 time-points (before, during and after nCRT), and an endoscopy with (random) bite-on-bite biopsies of the primary tumor site and other suspected lesions in the esophagus as well as an endoscopic ultrasonography (EUS) with fine needle aspiration of suspected lymph nodes after finishing nCRT. The main study endpoint is the performance of the model for pCR prediction. Secondary endpoints include progression-free and overall survival. If the multimodal PRIDE concept provides high predictive performance for pCR, the results of this study will play an important role in accurate identification of esophageal cancer patients with a pCR to nCRT. These patients might benefit from a patient-tailored approach with omission of surgery in the future. Vice versa, patients with non-pCR might benefit from additional neoadjuvant treatment, or ineffective therapy could be stopped. The article reports on a health care intervention on human participants and was prospectively registered on March 22, 2018 under ClinicalTrials.gov Identifier: NCT03474341 .

Risk assessment is relevant to predict outcomes in patients with gastric cancer. This systematic review aimed to investigate the predictive value of low muscle mass for postoperative complications in gastric cancer patients. A systematic literature search was performed to identify all articles reporting on muscle mass as measured on computed tomography (CT) scans in patients with gastric cancer. After full text screening, 15 articles reporting on 4887 patients were included. Meta-analysis demonstrated that patients with low muscle mass had significantly higher odds of postoperative complications (odds ratio (OR): 2.09, 95% confidence interval (CI): 1.55–2.83) and severe postoperative complications (Clavien–Dindo grade ≥III, OR: 1.73, 95% CI: 1.14–2.63). Moreover, patients with low muscle mass had a significantly higher overall mortality (hazard ratio (HR): 1.81, 95% CI: 1.52–2.14) and disease-specific mortality (HR: 1.58, 95% CI: 1.36–1.84). In conclusion, assessment of muscle mass on CT scans is a potential relevant clinical tool for risk prediction in gastric cancer patients. Considering the heterogeneity in definitions applied for low muscle mass on CT scans in the included studies, a universal cutoff value of CT-based low muscle mass is required for more reliable conclusions.

Background: Medical students often do not feel prepared to manage emergency situations after graduation. They experience a lack of practical skills and show significant deficits in cognitive performance to assess and stabilize trauma patients. Most reports in the literature about simulation-based education pertain to postgraduate training. Simulation-based trauma education (SBTE) in undergraduate medical education could improve confidence and performance of recently graduated doctors in trauma resuscitation. We reviewed the literature in search of SBTE effectiveness for medical students. Methods: A PubMed, Embase and CINAHL literature search was performed to identify all studies that reported on the effectiveness of SBTE for medical students, on student perception on SBTE or on the effectiveness of different simulation modalities. Results: Eight studies were included. Three out of four studies reporting on the effectiveness of SBTE demonstrated an increase in performance of students after SBTE. SBTE is generally highly appreciated by medical students. Only one study directly compared two modalities of SBTE and reported favorable results for the mechanical model rather than the standardized live patient model. Conclusion: SBTE appears to be an effective method to prepare medical students for trauma resuscitation. Furthermore, students enjoy SBTE and they perceive SBTE as a very useful learning method.

Objective: This study was conducted in order to determine the optimal timing of diffusion-weighted magnetic resonance imaging (DW-MRI) for prediction of pathologic complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) for esophageal cancer. Methods: Patients with esophageal adenocarcinoma or squamous cell carcinoma who planned to undergo nCRT followed by surgery were enrolled in this prospective study. Patients underwent six DW-MRI scans: one baseline scan before the start of nCRT and weekly scans during 5 weeks of nCRT. Relative changes in mean apparent diffusion coefficient (ADC) values between the baseline scans and the scans during nCRT (ΔADC(%)) were compared between pathologic complete responders (pCR) and non-pCR (tumor regression grades 2–5). The discriminative ability of ΔADC(%) was determined based on the c-statistic. Results: A total of 24 patients with 142 DW-MRI scans were included. pCR was observed in seven patients (29%). ΔADC(%) from baseline to week 2 was significantly higher in patients with pCR versus non-pCR (median [IQR], 36% [30%, 41%] for pCR versus 16% [14%, 29%] for non-pCR, p = 0.004). The ΔADC(%) of the second week in combination with histology resulted in the highest c-statistic for the prediction of pCR versus non-pCR (0.87). The c-statistic of this model increased to 0.97 after additional exclusion of patients with a small tumor volume (< 7 mL, n = 3) and tumor histology of the resection specimen other than adenocarcinoma or squamous cell carcinoma (n = 1). Conclusion: The relative change in tumor ADC (ΔADC(%)) during the first 2 weeks of nCRT is the most predictive for pathologic complete response to nCRT in esophageal cancer patients. Key Points: • DW-MRI during the second week of neoadjuvant chemoradiotherapy is most predictive for pathologic complete response in esophageal cancer. • A model including ΔADC_{week 2}was able to discriminate between pathologic complete responders and non-pathologic complete responders in 87%. • Improvements in future MRI studies for esophageal cancer may be obtained by incorporating motion management techniques.