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

Javier e Villanueva-Meyer; Spyridon Bakas; Pallavi Tiwari; Janine m Lupo; Evan Calabrese; Christos Davatzikos; Wenya linda Bi; Marwa Ismail; Hamed Akbari; Philipp Lohmann; Thomas c Booth; Benedikt Wiestler; Hugo j w l Aerts; Ghulam Rasool; Joerg c Tonn; Martha Nowosielski; Rajan Jain; Rivka r Colen; Sarthak Pati; Ujjwal Baid; Philipp Vollmuth; David Macdonald; Michael a Vogelbaum; Susan m Chang; Raymond y Huang; Norbert Galldiks

doi:10.1016/S1470-2045(24)00316-4

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

Javier e Villanueva-Meyer, Spyridon Bakas, Pallavi Tiwari, Janine m Lupo, Evan Calabrese, Christos Davatzikos, Wenya linda Bi, Marwa Ismail, Hamed Akbari, Philipp Lohmann, Thomas c Booth, Benedikt Wiestler, Hugo j w l Aerts, Ghulam Rasool, Joerg c Tonn, Martha Nowosielski, Rajan Jain, Rivka r Colen, Sarthak Pati, Ujjwal BaidPhilipp Vollmuth, David Macdonald, Michael a Vogelbaum, Susan m Chang, Raymond y Huang, Norbert Galldiks

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Abstract

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.

Original language	English
Pages (from-to)	e581-e588
Journal	The Lancet Oncology
Volume	25
Issue number	11
Early online date	28 Oct 2024
DOIs	https://doi.org/10.1016/S1470-2045(24)00316-4
Publication status	Published - 1 Nov 2024

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10.1016/S1470-2045(24)00316-4

https://linkinghub.elsevier.com/retrieve/pii/S1470204524003164

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Villanueva-Meyer, J. E., Bakas, S., Tiwari, P., Lupo, J. M., Calabrese, E., Davatzikos, C., Bi, W. L., Ismail, M., Akbari, H., Lohmann, P., Booth, T. C., Wiestler, B., Aerts, H. J. W. L., Rasool, G., Tonn, J. C., Nowosielski, M., Jain, R., Colen, R. R., Pati, S., ... Galldiks, N. (2024). Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements. The Lancet Oncology, 25(11), e581-e588. https://doi.org/10.1016/S1470-2045(24)00316-4

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

abstract = "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.",

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Villanueva-Meyer, JE, Bakas, S, Tiwari, P, Lupo, JM, Calabrese, E, Davatzikos, C, Bi, WL, Ismail, M, Akbari, H, Lohmann, P, Booth, TC, Wiestler, B, Aerts, HJWL, Rasool, G, Tonn, JC, Nowosielski, M, Jain, R, Colen, RR, Pati, S, Baid, U, Vollmuth, P, Macdonald, D, Vogelbaum, MA, Chang, SM, Huang, RY & Galldiks, N 2024, 'Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements', The Lancet Oncology, vol. 25, no. 11, pp. e581-e588. https://doi.org/10.1016/S1470-2045(24)00316-4

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AU - Villanueva-Meyer, Javier e

AU - Bakas, Spyridon

AU - Tiwari, Pallavi

AU - Lupo, Janine m

AU - Calabrese, Evan

AU - Davatzikos, Christos

AU - Bi, Wenya linda

AU - Ismail, Marwa

AU - Akbari, Hamed

AU - Lohmann, Philipp

AU - Booth, Thomas c

AU - Wiestler, Benedikt

AU - Aerts, Hugo j w l

AU - Rasool, Ghulam

AU - Tonn, Joerg c

AU - Nowosielski, Martha

AU - Jain, Rajan

AU - Colen, Rivka r

AU - Pati, Sarthak

AU - Baid, Ujjwal

AU - Vollmuth, Philipp

AU - Macdonald, David

AU - Vogelbaum, Michael a

AU - Chang, Susan m

AU - Huang, Raymond y

AU - Galldiks, Norbert

PY - 2024/11/1

Y1 - 2024/11/1

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AB - 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.

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JO - The Lancet Oncology

JF - The Lancet Oncology

IS - 11

ER -

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

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