Comparison of Axillary Lymph Nodes on Breast MRI Before and After COVID-19 Booster Vaccination.

RATIONALE AND OBJECTIVES: Vaccine-related lymphadenopathy is a frequent finding following initial coronavirus disease 2019 (COVID-19) vaccination, but the frequency after COVID-19 booster vaccination is still unknown. In this study we compare axillary lymph node morphology on breast MRI before and after COVID-19 booster vaccination. MATERIALS AND METHODS: This retrospective, single-center, IRB-approved study included patients who underwent breast MRI between October 2021 and December 2021 after the COVID-19 booster vaccination. The axillary lymph node with the greatest cortical thickness ipsilateral to the side of vaccination was measured on MRI after booster vaccination and before initial COVID-19 vaccination. Comparisons were made between patients with and without increase in cortical thickness of ≥ 0.2 cm. Continuous covariates were compared using Wilcoxon rank-sum test and categorical covariates were compared using Fisher's exact test. Multiple comparison adjustment was made using the Benjamini-Hochberg procedure. RESULTS: All 128 patients were included. Twenty-four of 128 (19%) displayed an increase in lymph node cortical thickness of ≥ 0.2 cm. Patients who received the booster more recently were more likely to present cortical thickening, with a median of 9 days (IQR 5, 20) vs. 36 days (IQR 18, 59) (p < 0.001). Age (p = 0.5) and type of vaccine (p = 0.7) were not associated with thickening. No ipsilateral breast cancer or malignant lymphadenopathy were diagnosed on follow-up. CONCLUSION: Axillary lymphadenopathy on breast MRI following COVID-19 booster vaccination is a frequent finding, especially in the first 3 weeks after vaccination. Additional evaluation or follow-up may be omitted in patients with low concern for malignancy.

Artificial Intelligence-Enhanced Breast MRI: Applications in Breast Cancer Primary Treatment Response Assessment and Prediction.

ABSTRACT: Primary systemic therapy (PST) is the treatment of choice in patients with locally advanced breast cancer and is nowadays also often used in patients with early-stage breast cancer. Although imaging remains pivotal to assess response to PST accurately, the use of imaging to predict response to PST has the potential to not only better prognostication but also allow the de-escalation or omission of potentially toxic treatment with undesirable adverse effects, the accelerated implementation of new targeted therapies, and the mitigation of surgical delays in selected patients. In response to the limited ability of radiologists to predict response to PST via qualitative, subjective assessments of tumors on magnetic resonance imaging (MRI), artificial intelligence-enhanced MRI with classical machine learning, and in more recent times, deep learning, have been used with promising results to predict response, both before the start of PST and in the early stages of treatment. This review provides an overview of the current applications of artificial intelligence to MRI in assessing and predicting response to PST, and discusses the challenges and limitations of their clinical implementation.

A phased approach to implementing the Breast Imaging Reporting and Data System (BI-RADS) in low-income and middle-income countries.

BACKGROUND: Successful breast cancer detection programs rely on standardized reporting and interpreting systems, such as the Breast Imaging Reporting and Data System (BI-RADS), to improve system performance. In low-income and middle-income countries, evolving diagnostic programs have insufficient resources to either fully implement BI-RADS or to periodically evaluate the program's performance, which is a necessary component of BI-RADS. This leads to inconsistent breast ultrasound interpretation and a failure to improve performance. METHODS: The authors applied the Breast Health Global Initiative's phased implementation strategy to implement diagnostic ultrasound and BI-RADS within the context of a limited-resource setting. RESULTS: The authors recommended starting with triage ultrasound to distinguish suspicious masses from normal breast tissue and benign masses such as cysts because the majority of health workers performing ultrasounds at this level have minimal breast imaging experience. Transitioning to full diagnostic ultrasound with condensed or full BI-RADS should occur after performance and quality metrics have been met. CONCLUSIONS: Transitioning through these phases across facilities likely will occur at different times, particularly in rural versus urban settings.

Estudio epidemiológico de leishmaniasis tegumentaria americana en Maypuco, Peru / Epidemiologic study of American cutaneous leishmaniasis in Maypuco, Peru

Se estudió la prevalencia de leishmaniasis tegumentaria americana en una localidad de selva baja en Loreto, Perú. En 67 sujetos (17,6% del total de la población) se determinó la hipersensibilidad cutánea (intradermorreacción de Montenegro) y el nivel de anticuerpos en el suero por el método de inmunofluorescencia indirecta. Ninguno de los reactores presentaba leishmaniasis activa en el momento de la prueba, aunque se observaron lesiones con cicatrices clinicamente compatibles con leishmaniasis tegumentaria americana en 4 de los 18 reactores (22,0%), lo que sugiere la importancia de la infección subclinica en la población estudiada. La intradermorreacción de Montenegro fue positiva en 26,8% de los sujetos estudiados y en 68,0% de los agricultores. Estos resultados sugieren que la infección no se adquiere en áreas pobladas y mas bien esta relacionada con ocupaciones desarrolladas en áreas alejadas, donde se encuentran el vector y los reservorios naturales