Prognosis, counseling, and indications for termination of pregnancy.

As the coincidence of pregnancy and cancer rise, clinicians must be prepared to counsel their patients on the complex relationship between maternal and fetal health. In most types of cancer, maternal prognosis mirrors that of non-pregnant women. However, challenges associated with the timing of diagnosis and treatment can present additional risks. Consequently, pregnant cancer patients must be counseled early and effectively with regard to how their pregnancy status affects treatment options and the range of expected outcomes for both mother and fetus. Some patients choose to terminate pregnancy after such counseling, though the specific course of action depends on the cancer in question, the stage at diagnosis, and the personal priorities and values of the patient.

A comprehensive analysis of authorship trends in Skeletal Radiology since inception from 1976 to 2020.

OBJECTIVE: The purpose of this study is to explore authorship trends within the musculoskeletal radiology subspecialty-focused journal, Skeletal Radiology, from inception to 2020. MATERIALS AND METHODS: Skeletal Radiology articles published in 1976, 1986, 1996, 2006, 2016, and 2020 were reviewed. For each article, the number of authors, the number of distinct institutions, the names of first and last authors, the country of the first author, the article length, and the number of article references were recorded. RESULTS: A total of 885 articles passed the exclusion criteria to be included in the study. Since inception, there has been a significant increase in the number of SR articles published (P = 0.02), the mean number of authors per article (P < 0.01), the mean number of references per article (P < 0.01), the mean number of distinct institutions per article (P = 0.02), and the mean number of pages per article (P < 0.01). The proportion of female first and last authors significantly increased (P = 0.02, P = 0.02). There was a significant increase in the proportion of articles published from Asia (P = 0.04). However, no significant changes in the proportion of articles published from other regions were observed. CONCLUSION: Similar to authorship trends in other medical journals, Skeletal Radiology demonstrated upward trends in authorship count, distinct institutional count, and article length. A rise in first and last female authorship was observed. Finally, an increase in the proportion of authors from Asia was observed while no significant changes in the proportion of authors from other regions were demonstrated.

MRI Volume Changes of Axillary Lymph Nodes as Predictor of Pathologic Complete Responses to Neoadjuvant Chemotherapy in Breast Cancer.

INTRODUCTION: Longitudinal monitoring of breast tumor volume over the course of chemotherapy is informative of pathologic response. This study aims to determine whether axillary lymph node (aLN) volume by magnetic resonance imaging (MRI) could augment the prediction accuracy of treatment response to neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: Level-2a curated data from the I-SPY-1 TRIAL (2002-2006) were used. Patients had stage 2 or 3 breast cancer. MRI was acquired pre-, during, and post-NAC. A subset with visible aLNs on MRI was identified (N = 132). Prediction of pathologic complete response (PCR) was made using breast tumor volume changes, nodal volume changes, and combined breast tumor and nodal volume changes with sub-stratification with and without large lymph nodes (3 mL or ∼1.79 cm diameter cutoff). Receiver operating characteristic curve analysis was used to quantify prediction performance. RESULTS: The rate of change of aLN and breast tumor volume were informative of pathologic response, with prediction being most informative early in treatment (area under the curve (AUC), 0.57-0.87) compared with later in treatment (AUC, 0.50-0.75). Larger aLN volume was associated with hormone receptor negativity, with the largest nodal volume for triple negative subtypes. Sub-stratification by node size improved predictive performance, with the best predictive model for large nodes having AUC of 0.87. CONCLUSION: aLN MRI offers clinically relevant information and has the potential to predict treatment response to NAC in patients with breast cancer.