Background/Objectives: Autologous fat grafting (AFT) has become a widely used technique in breast reconstruction, offering natural aesthetics, tissue integration, and patient satisfaction. However, its clinical outcomes require comparison with implant-based reconstruction (IBR), the most common method in clinical practice. While AFT provides a more natural appearance and avoids foreign body-related complications, issues such as fat resorption, procedural variability, and oncological concerns necessitate further investigation. Additionally, artificial intelligence (AI) has been increasingly integrated into breast imaging and reconstructive planning, improving diagnostic accuracy, procedural optimization, and complication prevention. This study aims to compare AFT and IBR while exploring AI’s role in enhancing breast reconstruction outcomes. Methods: A comprehensive review of clinical studies was conducted to evaluate the advantages, limitations, and oncological implications of AFT versus IBR. AI-driven applications in breast imaging and reconstructive planning were examined for their potential in predicting fat graft retention and optimizing implant selection. Data from systematic reviews and meta-analyses were incorporated to refine reconstruction strategies. Results: AFT offers superior aesthetic outcomes with better tissue integration but presents variability in fat resorption. IBR remains the preferred approach due to its predictability but carries risks of implant-related complications. AI technologies contribute to improved reconstruction planning, enhancing surgical precision and long-term patient outcomes. Conclusions: Optimized patient selection and long-term follow-up are essential for improving breast reconstruction techniques. AI-driven approaches provide valuable tools for enhancing procedural predictability and personalized treatment strategies. Future research should focus on refining AI algorithms and establishing standardized protocols for reconstructive decision-making.

Background: Preoperative breast MRI is widely used in surgical planning because of its high sensitivity. However, discrepancies with histopathology remain common and can affect tumor size assessment and treatment decisions. In addition, recent comparative studies have highlighted the growing role of contrast-enhanced mammography (CEM) and multiparametric MRI (mpMRI), both of which may improve specificity and accessibility compared to conventional MRI. Methods: A structured literature review was conducted in PubMed (2000–2025) according to PRISMA guidelines. Studies included if they evaluated preoperative breast MRI with histopathological correlation and reported sensitivity, specificity, or concordance outcomes. Data extraction focused on study design, patient and tumor characteristics, imaging methods, and clinical impact. Results: MRI demonstrates high sensitivity, particularly in detecting IDC and ILC. However, overestimation of tumor size remains a concern, particularly in ILC and high-grade DCIS, while underestimation is frequently observed after neoadjuvant therapy, especially in Luminal A tumors. Tumor size and stage significantly affect concordance, with advanced-stage tumors (T2–T3) showing better MRI-histopathology concordance than early-stage lesions (T0–T1). Specificity remains limited, particularly in DCIS and multifocal disease. Emerging evidence suggests that contrast-enhanced mammography (CEM) achieves comparable sensitivity with higher specificity, while multiparametric MRI (mpMRI) incorporating diffusion-weighted imaging (DWI) improves lesion characterization and prediction of treatment response. Conclusions: While MRI remains a valuable diagnostic tool for breast cancer, histopathological validation is essential to guide treatment decisions. Future research should focus on AI-enhanced imaging techniques, CEM and multiparametric MRI to improve concordance rates, reduce overdiagnosis and translate imaging advances into meaningful clinical outcomes.

Background/objectives: Metaplastic breast carcinoma (MpBC) is a rare, poorly differentiated breast cancer defined by the presence of ductal carcinoma along with areas of matrix-producing, spindle-cell, sarcomatous, or squamous differentiation. It does not express hormone receptors and has a poor overall prognosis. The Hippo molecular pathway was recently related to cancer progression and adjuvant therapy resistance. The objective of this study was to evaluate the expression of Hippo pathway transducers, YAP/TAZ, CCND1, and CTGF, in MpBC and their relation to the clinicopathological characteristics of the disease. Methods: Specimens from patients with MpBC treated at our department from 2003 to 2021 were analyzed utilizing immunohistochemistry and real-time PCR. Results: Forty-four female patients (62.6 ± 14.7 years old) met inclusion criteria and were included in this study. Strong nuclear YAP/TAZ expression was found in 61.4% of patients, while the expressions of CCND1 and CTGF were 3.9% and 12.5%, respectively. Patients presenting at an advanced stage had a statistically worse prognosis compared to the ones diagnosed with stage IA disease. Adjuvant chemotherapy was associated with better overall survival, while disease recurrence was significantly associated with a worse prognosis. Conclusions: Advanced stage at diagnosis and disease recurrence were significantly associated with worse prognosis in MpBC. However, adjuvant chemotherapy significantly led to better overall survival. The Hippo pathway is frequently deregulated (nuclear YAP/TAZ in 61.4% of patients), suggesting it is a compelling novel therapeutic target for this aggressive disease.