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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.