Quantitative assessment of bone marrow infiltration and characterization of tumor burden using dual-layer spectral CT in patients with multiple myeloma.

BACKGROUND: The aim of the study was to evaluate whether virtual calcium subtraction (VNCa) image extracted from dual-layer spectral CT could estimate bone marrow (BM) infiltration with MRI as the reference standard and characterize tumor burden in patients with multiple myeloma (MM). PATIENTS AND METHODS: Forty-seven patients with newly diagnosed MM were retrospectively enrolled. They had undergone whole-body low-dose dual-layer spectral CT (DLCT) and whole-body MRI within one week. VNCa images with calcium-suppressed (CaSupp) indices ranging from 25 to 95 at an interval of 10 and apparent diffusion coefficient (ADC) maps were quantitatively analyzed on vertebral bodies L1-L5 at the central slice of images. The optimal combination was selected by correlation analysis between CT numbers and ADC values. Then, it was used to characterize tumor burden by correlation analysis and receiver operating characteristic (ROC) curves analysis, including plasma cell infiltration rate (PCIR), high serum-free light chains (SFLC) ratio and the high-risk cytogenetic (HRC) status. RESULTS: The most significant quantitative correlation between CT numbers of VNCa images and ADC values could be found at CaSupp index 85 for averaged L1-L5 (r = 0.612, p < 0.001). It allowed quantitative evaluation of PCIR (r = 0.835, p < 0.001). It could also anticipate high SFLC ratio and the HRC status with area under the curve (AUC) of 0.876 and 0.760, respectively. CONCLUSIONS: The VNCa measurements of averaged L1-L5 showed the highest correlation with ADC at CaSupp index 85. It could therefore be used as additional imaging biomarker for non-invasive assessment of tumor burden if ADC is not feasible.

Mechanisms underlying the relationship between the intersectionality of multiple social identities with depression among US adults: A population-based study on the mediating roles of lifestyle behaviors.

BACKGROUND: Despite substantial efforts to investigate the inequalities in mental health among people with marginalized identities, most research has concentrated on single social identities rather than complete persons. The current study aimed to explore the mechanisms underlying the relationship between the intersectionality of multiple social identities with depression among US adults. METHODS: Data for this study came from the National Health and Nutrition Examination Survey waves between 2015 and 2018, including a total of 11,268 US adults. A latent class analysis (LCA) was conducted to identify latent subpopulations based on sex, race/ethnicity, immigrant status, disability, household income, employment status, and education level. Interclass differences in lifestyle factors and depression were examined. Multiple mediation analysis was used to examine the mediating roles of lifestyle behaviors. RESULTS: LCA identified four potential subpopulations: "least marginalized", "immigrant minorities", "disabled, less-educated non-workers", and "low-income minorities" groups. There was enormous heterogeneity in mental health among immigrant minority individuals. The "disabled, less-educated non-workers" group had the highest rates of depression; in contrast, the "immigrant minorities" group had the best mental health, even better than that of the "least marginalized" group. Distributions of lifestyle factors followed a similar pattern. In addition, lifestyle behaviors significantly mediated the relationship between intersectional social identities and depression. LIMITATIONS: The cross-sectional design prevented establishment of the causality of relationships. CONCLUSIONS: This study suggests that applying a person-centered approach is important when examining intersectional inequalities in mental health and highlights the effects of structural social hierarchies on individuals' health behaviors and mental health.