Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements

The development, application, and benchmarking of artificial intelligence (AI) tools to improve diagnosis, prognostication, and therapy in neuro-oncology are increasing at a rapid pace. This Policy Review provides an overview and critical assessment of the work to date in this field, focusing on dia...

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Bibliographic Details
Published in:The lancet oncology 2024-11, Vol.25 (11), p.e581-e588
Main Authors: Villanueva-Meyer, Javier E, Bakas, Spyridon, Tiwari, Pallavi, Lupo, Janine M, Calabrese, Evan, Davatzikos, Christos, Bi, Wenya Linda, Ismail, Marwa, Akbari, Hamed, Lohmann, Philipp, Booth, Thomas C, Wiestler, Benedikt, Aerts, Hugo J W L, Rasool, Ghulam, Tonn, Joerg C, Nowosielski, Martha, Jain, Rajan, Colen, Rivka R, Pati, Sarthak, Baid, Ujjwal, Vollmuth, Philipp, Macdonald, David, Vogelbaum, Michael A, Chang, Susan M, Huang, Raymond Y, Galldiks, Norbert
Format: Article
Language:English
Subjects:
Artificial Intelligence
Biomarkers
Brain cancer
Brain Neoplasms - genetics
Brain Neoplasms - pathology
Brain Neoplasms - therapy
Datasets
Humans
Medical Oncology - methods
Neural networks
Oncology
Prognosis
Treatment Outcome
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Summary:The development, application, and benchmarking of artificial intelligence (AI) tools to improve diagnosis, prognostication, and therapy in neuro-oncology are increasing at a rapid pace. This Policy Review provides an overview and critical assessment of the work to date in this field, focusing on diagnostic AI models of key genomic markers, predictive AI models of response before and after therapy, and differentiation of true disease progression from treatment-related changes, which is a considerable challenge based on current clinical care in neuro-oncology. Furthermore, promising future directions, including the use of AI for automated response assessment in neuro-oncology, are discussed.
ISSN:1470-2045
1474-5488
1474-5488
DOI:10.1016/S1470-2045(24)00316-4