Siliconomas are rarely found in internal mammary lymph nodes in the context of ruptured, ipsilateral, silicone breast implants. However, they can sometimes cause a diagnostic dilemma, as in the presented case. We discuss the diagnostic pitfalls that can arise from misinterpreting a siliconoma for a metastatic lymph node, review the literature, and suggest appropriate diagnostic approaches.
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http://dx.doi.org/10.2484/rcr.v6i4.601 | DOI Listing |
Breast Cancer Res Treat
January 2025
Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT, USA.
Purpose: Interstitial lung disease (ILD) is a well described and potentially fatal complication of trastuzumab-deruxtecan (T-DXd). It is currently unknown if specific monitoring is beneficial in the early detection of ILD in these patients. We describe the efficacy and feasibility of a novel ILD monitoring protocol in breast cancer patients treated with T-DXd at our institution.
View Article and Find Full Text PDFExpert Opin Pharmacother
January 2025
Department of Neurology, Graduate School of Medicine, Chiba University, Chuo-ku, Chiba, Japan.
Background: Chemotherapy-induced peripheral neuropathy (CIPN) and its associated pain negatively affect patient outcomes and quality of life (QoL). The two-part MiroCIP study included interventional and prospective observational studies. Here, we report the latter, describing CIPN incidence, risk factors, and outcomes.
View Article and Find Full Text PDFAngiology
January 2025
Department of Internal Medicine, Texas Tech University Health Science Center, El Paso, TX, USA.
Breast cancer is the most common malignancy among women. While advances in detection and treatment have improved survival, breast cancer survivors face an increased risk of cardiovascular disease. However, limited data exist on cardiac outcomes after ST-elevation myocardial infarction (STEMI) in this population.
View Article and Find Full Text PDFFront Oncol
January 2025
Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Background: Breast cancer (BC), as a leading cause of cancer mortality in women, demands robust prediction models for early diagnosis and personalized treatment. Artificial Intelligence (AI) and Machine Learning (ML) algorithms offer promising solutions for automated survival prediction, driving this study's systematic review and meta-analysis.
Methods: Three online databases (Web of Science, PubMed, and Scopus) were comprehensively searched (January 2016-August 2023) using key terms ("Breast Cancer", "Survival Prediction", and "Machine Learning") and their synonyms.
J Clin Nurs
January 2025
McGrath Foundation, North Sydney, New South Wales, Australia.
Aim: To develop and psychometrically test two newly developed Cancer Nurse Self-Assessment Tools for early and metastatic breast cancer (CaN-SAT-eBC and CAN-SAT-mBC).
Design: Instrument development and psychometric testing of content validity, reliability and construct validity.
Methods: A three-phase procedure was conducted.
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