{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T01:36:38Z","timestamp":1792805798063,"version":"4.5.0"},"reference-count":168,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T00:00:00Z","timestamp":1751932800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Brain Sciences"],"abstract":"<jats:p>Brain metastases (BMs) are the most common intracranial tumors in adults. Their heterogeneity, potential multifocality, and complex biomolecular behavior pose significant diagnostic and therapeutic challenges. Artificial intelligence (AI) has the potential to revolutionize BM diagnosis by facilitating early lesion detection, precise imaging segmentation, and non-invasive molecular characterization. Machine learning (ML) and deep learning (DL) models have shown promising results in differentiating BMs from other intracranial tumors with similar imaging characteristics\u2014such as gliomas and primary central nervous system lymphomas (PCNSLs)\u2014and predicting tumor features (e.g., genetic mutations) that can guide individualized and targeted therapies. Intraoperatively, AI-driven systems can enable optimal tumor resection by integrating functional brain maps into preoperative imaging, thus facilitating the identification and safeguarding of eloquent brain regions through augmented reality (AR)-assisted neuronavigation. Even postoperatively, AI can be instrumental for radiotherapy planning personalization through the optimization of dose distribution, maximizing disease control while minimizing adjacent healthy tissue damage. Applications in systemic chemo- and immunotherapy include predictive insights into treatment responses; AI can analyze genomic and radiomic features to facilitate the selection of the most suitable, patient-specific treatment regimen, especially for those whose disease demonstrates specific genetic profiles such as epidermal growth factor receptor mutations (e.g., EGFR, HER2). Moreover, AI-based prognostic models can significantly ameliorate survival and recurrence risk prediction, further contributing to follow-up strategy personalization. Despite these advancements and the promising landscape, multiple challenges\u2014including data availability and variability, decision-making interpretability, and ethical, legal, and regulatory concerns\u2014limit the broader implementation of AI into the everyday clinical management of BMs. Future endeavors should thus prioritize the development of generalized AI models, the combination of large and diverse datasets, and the integration of clinical and molecular data into imaging, in an effort to maximally enhance the clinical application of AI in BM care and optimize patient outcomes.<\/jats:p>","DOI":"10.3390\/brainsci15070730","type":"journal-article","created":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T07:31:57Z","timestamp":1751959917000},"page":"730","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Diagnostic, Therapeutic, and Prognostic Applications of Artificial Intelligence (AI) in the Clinical Management of Brain Metastases (BMs)"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3240-5366","authenticated-orcid":false,"given":"Kyriacos","family":"Evangelou","sequence":"first","affiliation":[{"name":"Department of Neurosurgery, Attikon University General Hospital, National and Kapodistrian University of Athens, 10679 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Panagiotis","family":"Zemperligkos","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Attikon University General Hospital, National and Kapodistrian University of Athens, 10679 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6899-1937","authenticated-orcid":false,"given":"Anastasios","family":"Politis","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Attikon University General Hospital, National and Kapodistrian University of Athens, 10679 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6168-4230","authenticated-orcid":false,"given":"Evgenia","family":"Lani","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Attikon University General Hospital, National and Kapodistrian University of Athens, 10679 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enrique","family":"Gutierrez-Valencia","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, University of Toronto, Toronto, ON M5S 1A1, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ioannis","family":"Kotsantis","sequence":"additional","affiliation":[{"name":"Section of Medical Oncology, Second Department of Internal Medicine, Faculty of Medicine, National and Kapodistrian University of Athens, Attikon University Hospital, 10679 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0050-284X","authenticated-orcid":false,"given":"Georgios","family":"Velonakis","sequence":"additional","affiliation":[{"name":"Second Department of Radiology, Faculty of Medicine, National and Kapodistrian University of Athens, Attikon University Hospital, 10679 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8000-9739","authenticated-orcid":false,"given":"Efstathios","family":"Boviatsis","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Attikon University General Hospital, National and Kapodistrian University of Athens, 10679 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lampis C.","family":"Stavrinou","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Attikon University General Hospital, National and Kapodistrian University of Athens, 10679 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0222-488X","authenticated-orcid":false,"given":"Aristotelis","family":"Kalyvas","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Attikon University General Hospital, National and Kapodistrian University of Athens, 10679 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1038\/s41572-018-0055-y","article-title":"Brain metastases","volume":"5","author":"Achrol","year":"2019","journal-title":"Nat. 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