Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements - 29/10/24
Doi : 10.1016/S1470-2045(24)00316-4
Javier E Villanueva-Meyer, MD a, b, ⁎ 
, Spyridon Bakas, PhD c, d, e, f, g, h, Pallavi Tiwari, PhD i, Janine M Lupo, ProfPhD a, Evan Calabrese, MD PhD j, Christos Davatzikos, ProfPhD k, l, Wenya Linda Bi, MD PhD m, Marwa Ismail, PhD i, Hamed Akbari, MD PhD ad, Philipp Lohmann, PhD p, q, Thomas C Booth, MD r, s, t, Benedikt Wiestler, MD u, Hugo J W L Aerts, ProfPhD o, ae, Ghulam Rasool, PhD ab, Joerg C Tonn, ProfMD v, Martha Nowosielski, ProfPhD w, Rajan Jain, ProfMD x, Rivka R Colen, ProfMD ae, Sarthak Pati, MS c, Ujjwal Baid, PhD c, Philipp Vollmuth, MD y, David Macdonald, ProfMD z, Michael A Vogelbaum, ProfMD PhD aa, ab, Susan M Chang, ProfMD b, Raymond Y Huang, MD PhD n, Norbert Galldiks, ProfMD p, ac
for the
, Spyridon Bakas, PhD c, d, e, f, g, h, Pallavi Tiwari, PhD i, Janine M Lupo, ProfPhD a, Evan Calabrese, MD PhD j, Christos Davatzikos, ProfPhD k, l, Wenya Linda Bi, MD PhD m, Marwa Ismail, PhD i, Hamed Akbari, MD PhD ad, Philipp Lohmann, PhD p, q, Thomas C Booth, MD r, s, t, Benedikt Wiestler, MD u, Hugo J W L Aerts, ProfPhD o, ae, Ghulam Rasool, PhD ab, Joerg C Tonn, ProfMD v, Martha Nowosielski, ProfPhD w, Rajan Jain, ProfMD x, Rivka R Colen, ProfMD ae, Sarthak Pati, MS c, Ujjwal Baid, PhD c, Philipp Vollmuth, MD y, David Macdonald, ProfMD z, Michael A Vogelbaum, ProfMD PhD aa, ab, Susan M Chang, ProfMD b, Raymond Y Huang, MD PhD n, Norbert Galldiks, ProfMD p, acfor the
Response Assessment in Neuro Oncology (RANO) group
a Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
b Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
c Division of Computational Pathology, Department of Pathology & Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
d Department of Radiology & Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
e Department of Biostatistics & Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
f Department of Neurological Surgery, Indiana University School of Medicine, Indianapolis, IN, USA
g Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, USA
h Department of Computer Science, Luddy School of Informatics, Computing, and Engineering, Indiana University, Indianapolis, IN, USA
i Department of Radiology and Biomedical Engineering, University of Wisconsin, Madison, WI, USA
j Duke University Center for Artificial Intelligence in Radiology, Department of Radiology, Duke University, Durham, NC, USA
k Center for Artificial Intelligence and Data Science for Integrated Diagnostics (AI2D) and Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
l Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
m Department of Neurosurgery, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
n Department of Radiology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
o Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA
p Institute of Neuroscience and Medicine (INM-4), Research Center Juelich (FZJ), Juelich, Germany
q Department of Nuclear Medicine, University Hospital RWTH Aachen, Aachen, Germany
r Department of Neuroradiology, Ruskin Wing, King’s College Hospital NHS Foundation Trust, London, UK
s School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
t London Regional Cancer Program, London, UK
u Department of Neuroradiology, University Hospital, Technical University of Munich, Munich, Germany
v Department of Neurosurgery, Ludwig Maximilians University, Munich, Germany and German Cancer Consortium (DKTK), Partner Site Munich, Germany
w Department of Neurology, Medical University Innsbruck, Innsbruck, Austria
x Department of Radiology and Department of Neurosurgery, New York University Langone Health, New York, NY, USA
y Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
z Department of Neuro-Oncology, H Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA
aa Department of Neurosurgery, H Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA
ab Department of Machine Learning, H Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA
ac Department of Neurology, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
ad Department of Bioengineering, Santa Clara University, Santa Clara, CA, USA
ae Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, Netherlands
* Correspondence to: Javier E Villanueva-Meyer, Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA Department of Radiology and Biomedical Imaging University of California San Francisco San Francisco CA 94143 USA
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.
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© 2024
Elsevier Ltd. Tous droits réservés.
Vol 25 - N° 11
P. e581-e588 - novembre 2024 Retour au numéro
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- Spyridon Bakas, Philipp Vollmuth, Norbert Galldiks, Thomas C Booth, Hugo J W L Aerts, Wenya Linda Bi, Benedikt Wiestler, Pallavi Tiwari, Sarthak Pati, Ujjwal Baid, Evan Calabrese, Philipp Lohmann, Martha Nowosielski, Rajan Jain, Rivka Colen, Marwa Ismail, Ghulam Rasool, Janine M Lupo, Hamed Akbari, Joerg C Tonn, David Macdonald, Michael Vogelbaum, Susan M Chang, Christos Davatzikos, Javier E Villanueva-Meyer, Raymond Y Huang, Response Assessment in Neuro Oncology (RANO) group
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