An update on radiomics techniques in primary liver cancers
Abstract Background Radiomics is a progressing field of research that deals with the extraction of quantitative metrics from medical images. Radiomic features detention indirectly tissue features such as heterogeneity and shape and can, alone or in combination with demographic, histological, genomic...
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| Format: | Article |
| Language: | English |
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BMC
2022-03-01
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| Series: | Infectious Agents and Cancer |
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| Online Access: | https://doi.org/10.1186/s13027-022-00422-6 |
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| author | Vincenza Granata Roberta Fusco Sergio Venazio Setola Igino Simonetti Diletta Cozzi Giulia Grazzini Francesca Grassi Andrea Belli Vittorio Miele Francesco Izzo Antonella Petrillo |
| author_facet | Vincenza Granata Roberta Fusco Sergio Venazio Setola Igino Simonetti Diletta Cozzi Giulia Grazzini Francesca Grassi Andrea Belli Vittorio Miele Francesco Izzo Antonella Petrillo |
| author_sort | Vincenza Granata |
| collection | DOAJ |
| description | Abstract Background Radiomics is a progressing field of research that deals with the extraction of quantitative metrics from medical images. Radiomic features detention indirectly tissue features such as heterogeneity and shape and can, alone or in combination with demographic, histological, genomic, or proteomic data, be used for decision support system in clinical setting. Methods This article is a narrative review on Radiomics in Primary Liver Cancers. Particularly, limitations and future perspectives are discussed. Results In oncology, assessment of tissue heterogeneity is of particular interest: genomic analysis have demonstrated that the degree of tumour heterogeneity is a prognostic determinant of survival and an obstacle to cancer control. Therefore, that Radiomics could support cancer detection, diagnosis, evaluation of prognosis and response to treatment, so as could supervise disease status in hepatocellular carcinoma (HCC) and Intrahepatic Cholangiocarcinoma (ICC) patients. Radiomic analysis is a convenient radiological image analysis technique used to support clinical decisions as it is able to provide prognostic and / or predictive biomarkers that allow a fast, objective and repeatable tool for disease monitoring. Conclusions Although several studies have shown that this analysis is very promising, there is little standardization and generalization of the results, which limits the translation of this method into the clinical context. The limitations are mainly related to the evaluation of data quality, repeatability, reproducibility, overfitting of the model. Trial registration: Not applicable. |
| first_indexed | 2024-12-20T00:05:55Z |
| format | Article |
| id | doaj.art-b4d65f83b77b4d80ba8469b0e09c0f24 |
| institution | Directory Open Access Journal |
| issn | 1750-9378 |
| language | English |
| last_indexed | 2024-12-20T00:05:55Z |
| publishDate | 2022-03-01 |
| publisher | BMC |
| record_format | Article |
| series | Infectious Agents and Cancer |
| spelling | doaj.art-b4d65f83b77b4d80ba8469b0e09c0f242022-12-21T20:00:40ZengBMCInfectious Agents and Cancer1750-93782022-03-0117111110.1186/s13027-022-00422-6An update on radiomics techniques in primary liver cancersVincenza Granata0Roberta Fusco1Sergio Venazio Setola2Igino Simonetti3Diletta Cozzi4Giulia Grazzini5Francesca Grassi6Andrea Belli7Vittorio Miele8Francesco Izzo9Antonella Petrillo10Division of Radiology, “Istituto Nazionale Tumori IRCCS Fondazione Pascale – IRCCS di Napoli”Medical Oncology Division, Igea SpADivision of Radiology, “Istituto Nazionale Tumori IRCCS Fondazione Pascale – IRCCS di Napoli”Division of Radiology, “Istituto Nazionale Tumori IRCCS Fondazione Pascale – IRCCS di Napoli”Department of Radiology, Azienda Ospedaliero-Universitaria CareggiDepartment of Radiology, Azienda Ospedaliero-Universitaria CareggiDivision of Radiology, “Università Degli Studi Della Campania Luigi Vanvitelli”Division of Hepatobiliary Surgical Oncology, “Istituto Nazionale Tumori IRCCS Fondazione Pascale – IRCCS di Napoli”Department of Radiology, Azienda Ospedaliero-Universitaria CareggiDivision of Hepatobiliary Surgical Oncology, “Istituto Nazionale Tumori IRCCS Fondazione Pascale – IRCCS di Napoli”Division of Radiology, “Istituto Nazionale Tumori IRCCS Fondazione Pascale – IRCCS di Napoli”Abstract Background Radiomics is a progressing field of research that deals with the extraction of quantitative metrics from medical images. Radiomic features detention indirectly tissue features such as heterogeneity and shape and can, alone or in combination with demographic, histological, genomic, or proteomic data, be used for decision support system in clinical setting. Methods This article is a narrative review on Radiomics in Primary Liver Cancers. Particularly, limitations and future perspectives are discussed. Results In oncology, assessment of tissue heterogeneity is of particular interest: genomic analysis have demonstrated that the degree of tumour heterogeneity is a prognostic determinant of survival and an obstacle to cancer control. Therefore, that Radiomics could support cancer detection, diagnosis, evaluation of prognosis and response to treatment, so as could supervise disease status in hepatocellular carcinoma (HCC) and Intrahepatic Cholangiocarcinoma (ICC) patients. Radiomic analysis is a convenient radiological image analysis technique used to support clinical decisions as it is able to provide prognostic and / or predictive biomarkers that allow a fast, objective and repeatable tool for disease monitoring. Conclusions Although several studies have shown that this analysis is very promising, there is little standardization and generalization of the results, which limits the translation of this method into the clinical context. The limitations are mainly related to the evaluation of data quality, repeatability, reproducibility, overfitting of the model. Trial registration: Not applicable.https://doi.org/10.1186/s13027-022-00422-6RadiomicsTexture analysisMachine learningsHepatocellular carcinomaCholangiocarcinoma |
| spellingShingle | Vincenza Granata Roberta Fusco Sergio Venazio Setola Igino Simonetti Diletta Cozzi Giulia Grazzini Francesca Grassi Andrea Belli Vittorio Miele Francesco Izzo Antonella Petrillo An update on radiomics techniques in primary liver cancers Infectious Agents and Cancer Radiomics Texture analysis Machine learnings Hepatocellular carcinoma Cholangiocarcinoma |
| title | An update on radiomics techniques in primary liver cancers |
| title_full | An update on radiomics techniques in primary liver cancers |
| title_fullStr | An update on radiomics techniques in primary liver cancers |
| title_full_unstemmed | An update on radiomics techniques in primary liver cancers |
| title_short | An update on radiomics techniques in primary liver cancers |
| title_sort | update on radiomics techniques in primary liver cancers |
| topic | Radiomics Texture analysis Machine learnings Hepatocellular carcinoma Cholangiocarcinoma |
| url | https://doi.org/10.1186/s13027-022-00422-6 |
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