Navigating the Uncertainty of B3 Breast Lesions: Diagnostic Challenges and Evolving Management Strategies

• DOI: 10.20944/preprints202411.1677.v1
• Publication Date: 2024-11-22T02:21:47Z
• Authors: Sabatino D'Archi; Beatrice Carnassale; Alejandro Martin ...; Cristina Accetta; Paolo Belli; Flavia De Lauretis; Enrico Di Guglielmo; Alba Di Leone; Antonio Franco; Stefano Magno; Francesca Moschella; Maria Natale; Lorenzo Scardina; Marta Silenzi; Riccardo Masetti; Gianluca Francesc...
• Keywords: B3 breast lesions; diagnosis; biopsy methods; genomic analysis in breast tumor diagnosis; Review; breast surgery; AI in breast tumor screening; imaging techniques

B3 breast lesions, classified as lesions of uncertain malignant potential, present a significant di-agnostic and therapeutic challenge due to their heterogeneous nature variable risk pro-gression malignancy. These which include atypical ductal hyperplasia (ADH), papil-lary (PL), flat epithelial atypia (FEA), radial scar (RS), lobular neoplasia (LN), phyl-lodes tumors (PT), occupy "grey zone" between benign pathologies, making management complex often controversial. This article explores the diagnostic difficul-ties associated with focusing on limitations current imaging techniques, in-cluding mammography, ultrasound, magnetic resonance (MRI), well chal-lenges in histopathological interpretation. Core needle biopsy (CNB) vacuum-assisted bi-opsy (VAB) are widely used for diagnosis, but both methods have inherent limitations, includ-ing sampling errors inability determine malignancy some cases definitively. The approach is nuanced, treatment decisions strongly influenced by factors such lesion size, radiological findings, characteristics, patient factors. While can be safely monitored watchful waiting, others may require excision (VAE) or surgical rule out deci-sion-making process further complicated discordance BIRADS score results, presence additional factors, microcalcifications. review provides an in-depth analysis challenges strate-gies emphasizing importance multidisciplinary management. By synthesizing most recent research, aims provide clinicians clearer understanding complexities involved diagnosing treating while highlighting areas future Artificial Intelligence Genomics, improve accuracy outcomes.