An Ly Church

Purpose: The aim of this study was to utilize an intersectional framework to examine academic faculty's lived experiences during COVID-19. Specifically, we set out to: (1) describe the multiple intersectional identities (e.g., gender, race/ethnicity, rank, caregiver status, disability status) represented by the faculty, (2) examine potential disparities in well-being, workload, and productivity linked to these intersectional factors, and (3) identify qualitative themes endorsed by faculty as they relate to lived experiences during COVID-19. Methods: This was a cross-sectional mixed-methods research study. The Center for Women in Medicine and Science (CWIMS) at the University of Minnesota developed and implemented a survey between February–June of 2021 in response to national reports of disparities in the impacts of COVID-19 on faculty with lived experiences from multiple intersections. Results: There were 291 full-time faculty who participated in the study. Quantitative findings indicated that faculty with multiple intersectional identities (e.g., woman+assistant professor+caregiver+underrepresented in medicine) reported greater depression symptoms, work/family conflict, and stress in contrast to faculty with fewer intersectional identities. Furthermore, faculty with more intersectional identities reported higher clinical workloads and service responsibilities and lower productivity with regard to research article submissions, publications, and grant submissions in contrast to faculty with fewer intersectional identities. Qualitative findings supported quantitative findings and broadened understanding of potential underlying reasons. Conclusions: Findings confirm anecdotal evidence that faculty with lived experiences from multiple intersections may be disproportionately experiencing negative outcomes from the pandemic. These findings can inform decisions about how to address these disparities moving into the next several years with regard to promotion and tenure, burnout and well-being, and faculty retention in academic medical settings. Given these findings, it is also important to intentionally plan responses for future public health crises to prevent continued disparities for faculty with multiple intersectional identities.

Lack of background parenchymal enhancement suppression at breast MRI during neoadjuvant chemotherapy may indicate inferior treatment response in hormone receptor–positive breast cancer. Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed ...

We present five cases of axillary lymphadenopathy which occurred after COVID-19 vaccination and that mimicked metastasis in oncologic patients. Initial radiologic diagnosis raised concerns...

Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype.

Axially reformatted simultaneous multislice imaging produced diffusion-weighted images and apparent diffusion coefficient maps with improved image quality, resolution, and coverage compared with a ... Background Diffusion-weighted imaging (DWI) shows promise in detecting and monitoring breast cancer, but standard spin-echo (SE) echo-planar DWI methods often have poor image quality and low spatia...