Background Radiomics and radiogenomics are two words that recur often in language of radiologists, nuclear doctors and medical physicists especially in oncology field. Radiomics is the technique of medical images analysis to extract quantitative data that are not detected by human eye. Methods This article is a narrative review on Radiomics in Medical Imaging. In particular, the review exposes the process, the limitations related to radiomics, and future prospects are discussed. Results Several studies showed that radiomics is very promising. However, there were some critical issues: poor standardization and generalization of radiomics results, data-quality control, repeatability, reproducibility, database balancing and issues related to model overfitting. Conclusions Radiomics procedure should made considered all pitfalls and challenges to obtain robust and reproducible results that could be generalized in other patients cohort.
Radiomics in medical imaging: pitfalls and challenges in clinical management / Fusco, Roberta; Granata, Vincenza; Grazzini, Giulia; Pradella, Silvia; Borgheresi, Alessandra; Bruno, Alessandra; Palumbo, Pierpaolo; Bruno, Federico; Grassi, Roberta; Giovagnoni, Andrea; Grassi, Roberto; Miele, Vittorio; Barile, Antonio. - In: JAPANESE JOURNAL OF RADIOLOGY. - ISSN 1867-1071. - 40:9(2022), pp. 919-929. [10.1007/s11604-022-01271-4]
Radiomics in medical imaging: pitfalls and challenges in clinical management
Borgheresi, Alessandra;Bruno, Alessandra;Giovagnoni, Andrea;Grassi, Roberto;
2022-01-01
Abstract
Background Radiomics and radiogenomics are two words that recur often in language of radiologists, nuclear doctors and medical physicists especially in oncology field. Radiomics is the technique of medical images analysis to extract quantitative data that are not detected by human eye. Methods This article is a narrative review on Radiomics in Medical Imaging. In particular, the review exposes the process, the limitations related to radiomics, and future prospects are discussed. Results Several studies showed that radiomics is very promising. However, there were some critical issues: poor standardization and generalization of radiomics results, data-quality control, repeatability, reproducibility, database balancing and issues related to model overfitting. Conclusions Radiomics procedure should made considered all pitfalls and challenges to obtain robust and reproducible results that could be generalized in other patients cohort.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.