The COVID-19 pandemic is a significant worldwide health crisis. Breast cancer patients with COVID-19 are fragile and require particular clinical care. This study aimed to identify the clinical characteristics of breast cancer patients with COVID-19 and the risks associated with anti-cancer treatment. The medical records of breast cancer patients with laboratory-confirmed COVID-19 were collected among 9559 COVID-19 patients from seven designated hospitals from 13th January to 18th March 2020 in Hubei, China. Univariate and multivariate analyses were performed to assess risk factors for COVID-19 severity. Of the 45 breast cancer patients with COVID-19, 33 (73.3%) developed non-severe COVID-19, while 12 (26.7%) developed severe COVID-19, of which 3 (6.7%) patients died. The median age was 62 years, and 3 (6.7%) patients had stage IV breast cancer. Univariate analysis showed that age over 75 and the Eastern Cooperative Oncology Group (ECOG) score were associated with COVID-19 disease severity (P < 0.05). Multivariate analysis showed that patients who received chemotherapy within 7 days had a significantly higher risk for severe COVID-19 (logistic regression model: RR = 13.886, 95% CI 1.014–190.243, P = 0.049; Cox proportional hazards model: HR = 13.909, 95% CI 1.086–178.150, P = 0.043), with more pronounced neutropenia and higher LDH, CRP and procalcitonin levels than other patients (P < 0.05). In our breast cancer cohort, the severity of COVID-19 could be associated with baseline factors such as age over 75 and ECOG scores. Chemotherapy within 7 days before symptom onset could be a risk factor for severe COVID-19, reflected by neutropenia and elevated LDH, CRP and procalcitonin levels.

Background and purpose: Precise manual annotation of the left ventricular myocardial (LVM) wall is essential for cardiac substructure research, wall-specific radiation dosimetry, and segmentation model development. However, existing radiotherapy-oriented atlases and conventional CT viewing planes lack an explicit framework for reproducible, wall-level LVM delineation. To address this gap, we developed an anatomy-guided manual segmentation protocol for delineating the five LVM walls on non-contrast-enhanced CT (NECT) or contrast-enhanced CT (CECT) scans. Materials and methods: This protocol was developed using 60 chest CT scans from two prospective cohorts at Heidelberg University Hospital, including 50 CECTs from IMRT-MC2 cohort and 10 NECTs from MAGELLAN cohort. Manual contouring was performed in 3D Slicer. Segmentation rules were established through review by a radiation oncologist and a cardiology expert, based on the American Heart Association 17-segment model, and were tested on additional CT scans before final protocol definition. Results: The protocol centers on three geometric steps: (1) defining the LV long axis using the endocardial apex and the center of the mitral annulus; (2) constructing an apical delimitation plane based on LV geometry; and (3) partitioning wall regions via intersections of the right ventricular and LV cavity centers in the short-axis view. This workflow enables structured segmentation of the anterior, septal, lateral, inferior, and apical LVM walls, supporting anatomically coherent 3D reconstruction. Conclusion: This study provides contouring steps and a representative atlas as a methodological basis for standardized annotation, with potential applications in dose-mapping cardiotoxicity analysis and deep-learning modeling for radiotherapy.