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...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-02-01
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| Series: | Current Oncology |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1718-7729/30/3/203 |
| _version_ | 1797612495458795520 |
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| author | Maurizio Cè Giovanni Irmici Chiara Foschini Giulia Maria Danesini Lydia Viviana Falsitta Maria Lina Serio Andrea Fontana Carlo Martinenghi Giancarlo Oliva Michaela Cellina |
| author_facet | Maurizio Cè Giovanni Irmici Chiara Foschini Giulia Maria Danesini Lydia Viviana Falsitta Maria Lina Serio Andrea Fontana Carlo Martinenghi Giancarlo Oliva Michaela Cellina |
| author_sort | Maurizio Cè |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-11T06:42:04Z |
| format | Article |
| id | doaj.art-a07bf98c55d6459d96a9b5bbf3d37a47 |
| institution | Directory Open Access Journal |
| issn | 1198-0052 1718-7729 |
| language | English |
| last_indexed | 2024-03-11T06:42:04Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Current Oncology |
| spelling | doaj.art-a07bf98c55d6459d96a9b5bbf3d37a472023-11-17T10:30:39ZengMDPI AGCurrent Oncology1198-00521718-77292023-02-013032673270110.3390/curroncol30030203Artificial Intelligence in Brain Tumor Imaging: A Step toward Personalized MedicineMaurizio Cè0Giovanni Irmici1Chiara Foschini2Giulia Maria Danesini3Lydia Viviana Falsitta4Maria Lina Serio5Andrea Fontana6Carlo Martinenghi7Giancarlo Oliva8Michaela Cellina9Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, ItalyPostgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, ItalyPostgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, ItalyPostgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, ItalyPostgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, ItalyPostgraduation School in Radiodiagnostics, University of Rome Tor Vergata, Viale Oxford 81, 00133 Rome, ItalyPostgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, ItalyRadiology Department, San Raffaele Hospital, Via Olgettina 60, 20132 Milan, ItalyRadiology Department, Fatebenefratelli Hospital, ASST Fatebenefratelli Sacco, Piazza Principessa Clotilde 3, 20121 Milan, ItalyRadiology Department, Fatebenefratelli Hospital, ASST Fatebenefratelli Sacco, Piazza Principessa Clotilde 3, 20121 Milan, ItalyThe 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.https://www.mdpi.com/1718-7729/30/3/203artificial intelligencebrain tumorsglioblastomadeep learningprognosis prediction |
| spellingShingle | Maurizio Cè Giovanni Irmici Chiara Foschini Giulia Maria Danesini Lydia Viviana Falsitta Maria Lina Serio Andrea Fontana Carlo Martinenghi Giancarlo Oliva Michaela Cellina Artificial Intelligence in Brain Tumor Imaging: A Step toward Personalized Medicine Current Oncology artificial intelligence brain tumors glioblastoma deep learning prognosis prediction |
| 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 | artificial intelligence brain tumors glioblastoma deep learning prognosis prediction |
| url | https://www.mdpi.com/1718-7729/30/3/203 |
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