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Artificial Intelligence in Brain Tumor Imaging: A Step toward Personalized Medicine

The application of artificial intelligence (AI) is accelerating the paradigm shift towards patient-tailored brain tumor management, achieving optimal onco-functional balance for each individual. AI-based models can positively impact different stages of the diagnostic and therapeutic process. Althoug...

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Autores principales: Cè, Maurizio, Irmici, Giovanni, Foschini, Chiara, Danesini, Giulia Maria, Falsitta, Lydia Viviana, Serio, Maria Lina, Fontana, Andrea, Martinenghi, Carlo, Oliva, Giancarlo, Cellina, Michaela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047107/
https://www.ncbi.nlm.nih.gov/pubmed/36975416
http://dx.doi.org/10.3390/curroncol30030203
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author Cè, Maurizio
Irmici, Giovanni
Foschini, Chiara
Danesini, Giulia Maria
Falsitta, Lydia Viviana
Serio, Maria Lina
Fontana, Andrea
Martinenghi, Carlo
Oliva, Giancarlo
Cellina, Michaela
author_facet Cè, Maurizio
Irmici, Giovanni
Foschini, Chiara
Danesini, Giulia Maria
Falsitta, Lydia Viviana
Serio, Maria Lina
Fontana, Andrea
Martinenghi, Carlo
Oliva, Giancarlo
Cellina, Michaela
author_sort Cè, Maurizio
collection PubMed
description The application of artificial intelligence (AI) is accelerating the paradigm shift towards patient-tailored brain tumor management, achieving optimal onco-functional balance for each individual. AI-based models can positively impact different stages of the diagnostic and therapeutic process. Although the histological investigation will remain difficult to replace, in the near future the radiomic approach will allow a complementary, repeatable and non-invasive characterization of the lesion, assisting oncologists and neurosurgeons in selecting the best therapeutic option and the correct molecular target in chemotherapy. AI-driven tools are already playing an important role in surgical planning, delimiting the extent of the lesion (segmentation) and its relationships with the brain structures, thus allowing precision brain surgery as radical as reasonably acceptable to preserve the quality of life. Finally, AI-assisted models allow the prediction of complications, recurrences and therapeutic response, suggesting the most appropriate follow-up. Looking to the future, AI-powered models promise to integrate biochemical and clinical data to stratify risk and direct patients to personalized screening protocols.
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spelling pubmed-100471072023-03-29 Artificial Intelligence in Brain Tumor Imaging: A Step toward Personalized Medicine Cè, Maurizio Irmici, Giovanni Foschini, Chiara Danesini, Giulia Maria Falsitta, Lydia Viviana Serio, Maria Lina Fontana, Andrea Martinenghi, Carlo Oliva, Giancarlo Cellina, Michaela Curr Oncol Review The application of artificial intelligence (AI) is accelerating the paradigm shift towards patient-tailored brain tumor management, achieving optimal onco-functional balance for each individual. AI-based models can positively impact different stages of the diagnostic and therapeutic process. Although the histological investigation will remain difficult to replace, in the near future the radiomic approach will allow a complementary, repeatable and non-invasive characterization of the lesion, assisting oncologists and neurosurgeons in selecting the best therapeutic option and the correct molecular target in chemotherapy. AI-driven tools are already playing an important role in surgical planning, delimiting the extent of the lesion (segmentation) and its relationships with the brain structures, thus allowing precision brain surgery as radical as reasonably acceptable to preserve the quality of life. Finally, AI-assisted models allow the prediction of complications, recurrences and therapeutic response, suggesting the most appropriate follow-up. Looking to the future, AI-powered models promise to integrate biochemical and clinical data to stratify risk and direct patients to personalized screening protocols. MDPI 2023-02-22 /pmc/articles/PMC10047107/ /pubmed/36975416 http://dx.doi.org/10.3390/curroncol30030203 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Cè, Maurizio
Irmici, Giovanni
Foschini, Chiara
Danesini, Giulia Maria
Falsitta, Lydia Viviana
Serio, Maria Lina
Fontana, Andrea
Martinenghi, Carlo
Oliva, Giancarlo
Cellina, Michaela
Artificial Intelligence in Brain Tumor Imaging: A Step toward Personalized Medicine
title Artificial Intelligence in Brain Tumor Imaging: A Step toward Personalized Medicine
title_full Artificial Intelligence in Brain Tumor Imaging: A Step toward Personalized Medicine
title_fullStr Artificial Intelligence in Brain Tumor Imaging: A Step toward Personalized Medicine
title_full_unstemmed Artificial Intelligence in Brain Tumor Imaging: A Step toward Personalized Medicine
title_short Artificial Intelligence in Brain Tumor Imaging: A Step toward Personalized Medicine
title_sort artificial intelligence in brain tumor imaging: a step toward personalized medicine
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047107/
https://www.ncbi.nlm.nih.gov/pubmed/36975416
http://dx.doi.org/10.3390/curroncol30030203
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