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Background: Current radiomics for treatment response assessment in gastric cancer (GC) have focused solely on Computed tomography (CT). The importance of multi‐parametric magnetic resonance imaging (mp‐MRI) radiomics in GC is less clear. Purpose: To compare and combine CT and mp‐MRI radiomics for pretreatment identification of pathological response to neoadjuvant chemotherapy in GC. Study Type: Retrospective. Population: Two hundred twenty‐five GC patients were recruited and split into training (157) and validation dataset (68) in the ratio of 7:3 randomly. Field/Sequence: T2‐weighted fast spin echo (fat suppressed T2‐weighted imaging [fs‐T2WI]), diffusion weighted echo planar imaging (DWI), and fast gradient echo (dynamic contrast enhanced [DCE]) sequences at 3.0T. Assessment: Apparent diffusion coefficient (ADC) maps were generated from DWI. CT, fs‐T2WI, ADC, DCE, and mp‐MRI Radiomics score (Radscores) were compared between responders and non‐responders. A multimodal nomogram combining CT and mp‐MRI Radscores was developed. Patients were followed up for 3–65 months (median 19) after surgery, the overall survival (OS) and progression free survival (PFS) were calculated. Statistical Tests: A logistic regression classifier was applied to construct the five models. Each model's performance was evaluated using a receiver operating characteristic curve. The association of the nomogram with OS/PFS was evaluated by Kaplan–Meier survival analysis and C‐index. A P value <0.05 was considered statistically significant. Results: CT Radscore, mp‐MRI Radscore and nomogram were significantly associated with tumor regression grading. The nomogram achieved the highest area under the curves (AUCs) of 0.893 (0.834–0.937) and 0.871 (0.767–0.940) in training and validation datasets, respectively. The C‐index was 0.589 for OS and 0.601 for PFS. The AUCs of the mp‐MRI model were not significantly different to that of the CT model in training (0.831 vs. 0.770, P = 0.267) and validation dataset (0.797 vs. 0.746, P = 0.137). Data Conclusions: mp‐MRI radiomics provides similar results to CT radiomics for early identification of pathologic response to neoadjuvant chemotherapy. The multimodal radiomics nomogram further improved the capability. Evidence Level: 3 Technical Efficacy: 2 [ABSTRACT FROM AUTHOR]

This study examines how community-level cumulative environmental stress affects child and adolescent emotional distress and chronic health conditions both directly and indirectly through stressors at the household, family, and individual levels. Data comes from the Women and their Children’s Health (WaTCH) Study, which sought to understand the health implications of exposure to the 2010 Deepwater Horizon oil spill (DHOS) among a cohort of 596 mothers with children ages 10 to 17 in southeastern Louisiana. Community-level environmental stress was measured using a newly developed geospatial index. Household-level stressors included previous hurricane impacts, impacts of DHOS, degree of financial difficulty, and degree of housing physical decay. Family stressors included maternal depression, self-rated physical health, and degree of parenting stress. Child stress was based on perceived stress; child mental health was based on serious emotional disturbance; and child physical health was based on diagnosis of chronic illness. Structural equation modeling used weighted least squares means and variance and theta parameterization. Results showed a significant negative direct path between community-level cumulative environmental stress and child/adolescent serious emotional disturbance and chronic illness. However, the indirect relationship through household, family, and individual-level stressors was significant and positive for both child/adolescent serious emotional disturbance and chronic illness. These findings point to the centrality of the household and family in determining child and adolescent physical and mental health outcomes in communities exposed to frequent disasters and ongoing environmental stressors. [ABSTRACT FROM AUTHOR]