Lingual artery thrombosis as a presentation of infective endocarditis in a pregnant patient: a case report.

Background: Infective endocarditis during pregnancy is a rare condition that compromises the health of both the mother and the foetus, presenting high rates of morbidity and mortality. The clinical manifestations of this disease are varied, with embolic phenomena being a frequent presentation.

Case Summary: We report the case of a Hispanic 37-year-old patient, at 29 weeks of pregnancy, with no known cardiovascular history, who presented with 48 h of sudden mandibular and lingual pain.

Current Concepts in Molecular Breast Imaging.

Molecular breast imaging (MBI) is a functional imaging modality that utilizes technetium 99m sestamibi radiotracer uptake to evaluate the biology of breast tumors. Molecular breast imaging can be a useful tool for supplemental screening of women with dense breasts, for breast cancer diagnosis and staging, and for evaluation of treatment response in patients with breast cancer undergoing neoadjuvant systemic therapy. In addition, MBI is useful in problem-solving when mammography and US imaging are insufficient to arrive at a definite diagnosis and for patients who cannot undergo breast MRI.

An annotated biobank of triple negative breast cancer patient-derived xenografts featuring treatment-naïve and longitudinal samples throughout neoadjuvant chemotherapy.

Triple negative breast cancer (TNBC) that fails to respond to neoadjuvant chemotherapy (NACT) can be lethal. Developing effective strategies to eradicate chemoresistant disease requires experimental models that recapitulate the heterogeneity characteristic of TNBC. To that end, we established a biobank of 92 orthotopic patient-derived xenograft (PDX) models of TNBC from the tumors of 75 patients enrolled in the ARTEMIS clinical trial ( NCT02276443 ) at MD Anderson Cancer Center, including 12 longitudinal sets generated from serial patient biopsies collected throughout NACT and from metastatic disease.

Combining Biology-based and MRI Data-driven Modeling to Predict Response to Neoadjuvant Chemotherapy in Patients with Triple-Negative Breast Cancer.

Purpose To combine deep learning and biology-based modeling to predict the response of locally advanced, triple-negative breast cancer before initiating neoadjuvant chemotherapy (NAC). Materials and Methods In this retrospective study, a biology-based mathematical model of tumor response to NAC was constructed and calibrated on a patient-specific basis using imaging data from patients enrolled in the MD Anderson A Robust TNBC Evaluation FraMework to Improve Survival trial (ARTEMIS; ClinicalTrials.gov registration no.