Breast reconstruction following mastectomy or sectorectomy significantly impacts the quality of life and psychological well-being of breast cancer patients. Since its inception in the 1950s, artificial intelligence (AI) has gradually entered the medical field, promising to transform surgical planning, intraoperative guidance, postoperative care, and medical research. This article examines AI applications in breast reconstruction, supported by recent studies. AI shows promise in enhancing imaging for tumor detection and surgical planning, improving microsurgical precision, predicting complications such as flap failure, and optimizing postoperative monitoring. However, challenges remain, including data quality, safety, algorithm transparency, and clinical integration. Despite these shortcomings, AI has the potential to revolutionize breast reconstruction by improving preoperative planning, surgical precision, operative efficiency, and patient outcomes. This review provides a foundation for further research as AI continues to evolve and clinical trials expand its applications, offering greater benefits to patients and healthcare providers.

Background and Objectives: Breast Implant-Associated Anaplastic Large Cell Lymphoma (BIA-ALCL) is a T-cell lymphoma that has shown an interest in the medical community in recent years. Given its emerging clinical relevance, accurate imaging plays a crucial role in diagnosis, staging, and follow-up. This systematic review aims to evaluate the role of Fluorine-18 Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in the staging and follow-up of patients with BIA-ALCL, focusing on its diagnostic accuracy and clinical impact. Materials and Methods: A systematic search of PubMed and National Center for Biotechnology Information (NCBI) was conducted to identify studies assessing the use of 18F-FDG PET/CT in BIA-ALCL up to and including 15 April 2024, using the following keywords “breast implant-associated anaplastic large cell lymphoma” AND “PET/CT” AND “BIA-ALCL”. Data regarding the role of PET/CT in disease detection, staging, therapeutic guidance, and post-treatment surveillance was analyzed and synthesized in a tabulated format for comparative analysis. Given study heterogeneity, findings were synthesized narratively and diagnostic performance metrics were summarized descriptively, and no formal risk-of-bias assessment was performed due to the descriptive, case-based nature of evidence. Results: A total of 28 studies met the inclusion criteria, comprising 27 individual case reports and one case series that included seven patients. Across these studies, 18F-FDG PET/CT demonstrated diagnostic utility in the evaluation of BIA-ALCL, serving primarily for initial disease staging in 27 cases and for monitoring treatment response in 16 cases. Discussion: The review’s limitations include potential search bias due to variable radiotracer terminology and the restriction to English-language studies, which may limit literature retrieval and generalizability. Conclusions: Thus, 18F-FDG PET/CT demonstrated significant value in early lesion detection, accurate staging, assisting in monitoring treatment response and detecting recurrence.