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Radiomics, a Promising New Discipline: Example of Hepatocellular Carcinoma

Radiomics is a discipline that involves studying medical images through their digital data. Using “artificial intelligence” algorithms, radiomics utilizes quantitative and high-throughput analysis of an image’s textural richness to obtain relevant information for clinicians, from diagnosis assistanc...

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Autores principales: Lévi-Strauss, Thomas, Tortorici, Bettina, Lopez, Olivier, Viau, Philippe, Ouizeman, Dann J., Schall, Baptiste, Adhoute, Xavier, Humbert, Olivier, Chevallier, Patrick, Gual, Philippe, Fillatre, Lionel, Anty, Rodolphe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10093101/
https://www.ncbi.nlm.nih.gov/pubmed/37046521
http://dx.doi.org/10.3390/diagnostics13071303
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author Lévi-Strauss, Thomas
Tortorici, Bettina
Lopez, Olivier
Viau, Philippe
Ouizeman, Dann J.
Schall, Baptiste
Adhoute, Xavier
Humbert, Olivier
Chevallier, Patrick
Gual, Philippe
Fillatre, Lionel
Anty, Rodolphe
author_facet Lévi-Strauss, Thomas
Tortorici, Bettina
Lopez, Olivier
Viau, Philippe
Ouizeman, Dann J.
Schall, Baptiste
Adhoute, Xavier
Humbert, Olivier
Chevallier, Patrick
Gual, Philippe
Fillatre, Lionel
Anty, Rodolphe
author_sort Lévi-Strauss, Thomas
collection PubMed
description Radiomics is a discipline that involves studying medical images through their digital data. Using “artificial intelligence” algorithms, radiomics utilizes quantitative and high-throughput analysis of an image’s textural richness to obtain relevant information for clinicians, from diagnosis assistance to therapeutic guidance. Exploitation of these data could allow for a more detailed characterization of each phenotype, for each patient, making radiomics a new biomarker of interest, highly promising in the era of precision medicine. Moreover, radiomics is non-invasive, cost-effective, and easily reproducible in time. In the field of oncology, it performs an analysis of the entire tumor, which is impossible with a single biopsy but is essential for understanding the tumor’s heterogeneity and is known to be closely related to prognosis. However, current results are sometimes less accurate than expected and often require the addition of non-radiomics data to create a performing model. To highlight the strengths and weaknesses of this new technology, we take the example of hepatocellular carcinoma and show how radiomics could facilitate its diagnosis in difficult cases, predict certain histological features, and estimate treatment response, whether medical or surgical.
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spelling pubmed-100931012023-04-13 Radiomics, a Promising New Discipline: Example of Hepatocellular Carcinoma Lévi-Strauss, Thomas Tortorici, Bettina Lopez, Olivier Viau, Philippe Ouizeman, Dann J. Schall, Baptiste Adhoute, Xavier Humbert, Olivier Chevallier, Patrick Gual, Philippe Fillatre, Lionel Anty, Rodolphe Diagnostics (Basel) Review Radiomics is a discipline that involves studying medical images through their digital data. Using “artificial intelligence” algorithms, radiomics utilizes quantitative and high-throughput analysis of an image’s textural richness to obtain relevant information for clinicians, from diagnosis assistance to therapeutic guidance. Exploitation of these data could allow for a more detailed characterization of each phenotype, for each patient, making radiomics a new biomarker of interest, highly promising in the era of precision medicine. Moreover, radiomics is non-invasive, cost-effective, and easily reproducible in time. In the field of oncology, it performs an analysis of the entire tumor, which is impossible with a single biopsy but is essential for understanding the tumor’s heterogeneity and is known to be closely related to prognosis. However, current results are sometimes less accurate than expected and often require the addition of non-radiomics data to create a performing model. To highlight the strengths and weaknesses of this new technology, we take the example of hepatocellular carcinoma and show how radiomics could facilitate its diagnosis in difficult cases, predict certain histological features, and estimate treatment response, whether medical or surgical. MDPI 2023-03-30 /pmc/articles/PMC10093101/ /pubmed/37046521 http://dx.doi.org/10.3390/diagnostics13071303 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
Lévi-Strauss, Thomas
Tortorici, Bettina
Lopez, Olivier
Viau, Philippe
Ouizeman, Dann J.
Schall, Baptiste
Adhoute, Xavier
Humbert, Olivier
Chevallier, Patrick
Gual, Philippe
Fillatre, Lionel
Anty, Rodolphe
Radiomics, a Promising New Discipline: Example of Hepatocellular Carcinoma
title Radiomics, a Promising New Discipline: Example of Hepatocellular Carcinoma
title_full Radiomics, a Promising New Discipline: Example of Hepatocellular Carcinoma
title_fullStr Radiomics, a Promising New Discipline: Example of Hepatocellular Carcinoma
title_full_unstemmed Radiomics, a Promising New Discipline: Example of Hepatocellular Carcinoma
title_short Radiomics, a Promising New Discipline: Example of Hepatocellular Carcinoma
title_sort radiomics, a promising new discipline: example of hepatocellular carcinoma
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10093101/
https://www.ncbi.nlm.nih.gov/pubmed/37046521
http://dx.doi.org/10.3390/diagnostics13071303
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