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Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs)
Nuclear medicine has acquired a crucial role in the management of patients with neuroendocrine neoplasms (NENs) by improving the accuracy of diagnosis and staging as well as their risk stratification and personalized therapies, including radioligand therapies (RLT). Artificial intelligence (AI) and...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10455722/ https://www.ncbi.nlm.nih.gov/pubmed/37629503 http://dx.doi.org/10.3390/life13081647 |
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author | Balma, Michele Laudicella, Riccardo Gallio, Elena Gusella, Sara Lorenzon, Leda Peano, Simona Costa, Renato P. Rampado, Osvaldo Farsad, Mohsen Evangelista, Laura Deandreis, Desiree Papaleo, Alberto Liberini, Virginia |
author_facet | Balma, Michele Laudicella, Riccardo Gallio, Elena Gusella, Sara Lorenzon, Leda Peano, Simona Costa, Renato P. Rampado, Osvaldo Farsad, Mohsen Evangelista, Laura Deandreis, Desiree Papaleo, Alberto Liberini, Virginia |
author_sort | Balma, Michele |
collection | PubMed |
description | Nuclear medicine has acquired a crucial role in the management of patients with neuroendocrine neoplasms (NENs) by improving the accuracy of diagnosis and staging as well as their risk stratification and personalized therapies, including radioligand therapies (RLT). Artificial intelligence (AI) and radiomics can enable physicians to further improve the overall efficiency and accuracy of the use of these tools in both diagnostic and therapeutic settings by improving the prediction of the tumor grade, differential diagnosis from other malignancies, assessment of tumor behavior and aggressiveness, and prediction of treatment response. This systematic review aims to describe the state-of-the-art AI and radiomics applications in the molecular imaging of NENs. |
format | Online Article Text |
id | pubmed-10455722 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-104557222023-08-26 Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs) Balma, Michele Laudicella, Riccardo Gallio, Elena Gusella, Sara Lorenzon, Leda Peano, Simona Costa, Renato P. Rampado, Osvaldo Farsad, Mohsen Evangelista, Laura Deandreis, Desiree Papaleo, Alberto Liberini, Virginia Life (Basel) Review Nuclear medicine has acquired a crucial role in the management of patients with neuroendocrine neoplasms (NENs) by improving the accuracy of diagnosis and staging as well as their risk stratification and personalized therapies, including radioligand therapies (RLT). Artificial intelligence (AI) and radiomics can enable physicians to further improve the overall efficiency and accuracy of the use of these tools in both diagnostic and therapeutic settings by improving the prediction of the tumor grade, differential diagnosis from other malignancies, assessment of tumor behavior and aggressiveness, and prediction of treatment response. This systematic review aims to describe the state-of-the-art AI and radiomics applications in the molecular imaging of NENs. MDPI 2023-07-28 /pmc/articles/PMC10455722/ /pubmed/37629503 http://dx.doi.org/10.3390/life13081647 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 Balma, Michele Laudicella, Riccardo Gallio, Elena Gusella, Sara Lorenzon, Leda Peano, Simona Costa, Renato P. Rampado, Osvaldo Farsad, Mohsen Evangelista, Laura Deandreis, Desiree Papaleo, Alberto Liberini, Virginia Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs) |
title | Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs) |
title_full | Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs) |
title_fullStr | Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs) |
title_full_unstemmed | Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs) |
title_short | Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs) |
title_sort | applications of artificial intelligence and radiomics in molecular hybrid imaging and theragnostics for neuro-endocrine neoplasms (nens) |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10455722/ https://www.ncbi.nlm.nih.gov/pubmed/37629503 http://dx.doi.org/10.3390/life13081647 |
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