Radiomics of Musculoskeletal Sarcomas: A Narrative Review
Bone and soft-tissue primary malignant tumors or sarcomas are a large, diverse group of mesenchymal-derived malignancies. They represent a model for intra- and intertumoral heterogeneities, making them particularly suitable for radiomics analyses. Radiomic features offer information on cancer phenot...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Journal of Imaging |
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| Online Access: | https://www.mdpi.com/2313-433X/8/2/45 |
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| author | Cristiana Fanciullo Salvatore Gitto Eleonora Carlicchi Domenico Albano Carmelo Messina Luca Maria Sconfienza |
| author_facet | Cristiana Fanciullo Salvatore Gitto Eleonora Carlicchi Domenico Albano Carmelo Messina Luca Maria Sconfienza |
| author_sort | Cristiana Fanciullo |
| collection | DOAJ |
| description | Bone and soft-tissue primary malignant tumors or sarcomas are a large, diverse group of mesenchymal-derived malignancies. They represent a model for intra- and intertumoral heterogeneities, making them particularly suitable for radiomics analyses. Radiomic features offer information on cancer phenotype as well as the tumor microenvironment which, combined with other pertinent data such as genomics and proteomics and correlated with outcomes data, can produce accurate, robust, evidence-based, clinical-decision support systems. Our purpose in this narrative review is to offer an overview of radiomics studies dealing with Magnetic Resonance Imaging (MRI)-based radiomics models of bone and soft-tissue sarcomas that could help distinguish different histotypes, low-grade from high-grade sarcomas, predict response to multimodality therapy, and thus better tailor patients’ treatments and finally improve their survivals. Although showing promising results, interobserver segmentation variability, feature reproducibility, and model validation are three main challenges of radiomics that need to be addressed in order to translate radiomics studies to clinical applications. These efforts, together with a better knowledge and application of the “Radiomics Quality Score” and Image Biomarker Standardization Initiative reporting guidelines, could improve the quality of sarcoma radiomics studies and facilitate radiomics towards clinical translation. |
| first_indexed | 2024-03-09T21:40:13Z |
| format | Article |
| id | doaj.art-78a5494d4f5545fdb7c7697c3f8cbd0d |
| institution | Directory Open Access Journal |
| issn | 2313-433X |
| language | English |
| last_indexed | 2024-03-09T21:40:13Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Imaging |
| spelling | doaj.art-78a5494d4f5545fdb7c7697c3f8cbd0d2023-11-23T20:33:27ZengMDPI AGJournal of Imaging2313-433X2022-02-01824510.3390/jimaging8020045Radiomics of Musculoskeletal Sarcomas: A Narrative ReviewCristiana Fanciullo0Salvatore Gitto1Eleonora Carlicchi2Domenico Albano3Carmelo Messina4Luca Maria Sconfienza5Scuola di Specializzazione in Radiodiagnostica, Università degli Studi di Milano, 20122 Milan, ItalyDipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, via Riccardo Galeazzi 4, 20161 Milan, ItalyScuola di Specializzazione in Radiodiagnostica, Università degli Studi di Milano, 20122 Milan, ItalyIRCCS Istituto Ortopedico Galeazzi, 20161 Milan, ItalyIRCCS Istituto Ortopedico Galeazzi, 20161 Milan, ItalyDipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, via Riccardo Galeazzi 4, 20161 Milan, ItalyBone and soft-tissue primary malignant tumors or sarcomas are a large, diverse group of mesenchymal-derived malignancies. They represent a model for intra- and intertumoral heterogeneities, making them particularly suitable for radiomics analyses. Radiomic features offer information on cancer phenotype as well as the tumor microenvironment which, combined with other pertinent data such as genomics and proteomics and correlated with outcomes data, can produce accurate, robust, evidence-based, clinical-decision support systems. Our purpose in this narrative review is to offer an overview of radiomics studies dealing with Magnetic Resonance Imaging (MRI)-based radiomics models of bone and soft-tissue sarcomas that could help distinguish different histotypes, low-grade from high-grade sarcomas, predict response to multimodality therapy, and thus better tailor patients’ treatments and finally improve their survivals. Although showing promising results, interobserver segmentation variability, feature reproducibility, and model validation are three main challenges of radiomics that need to be addressed in order to translate radiomics studies to clinical applications. These efforts, together with a better knowledge and application of the “Radiomics Quality Score” and Image Biomarker Standardization Initiative reporting guidelines, could improve the quality of sarcoma radiomics studies and facilitate radiomics towards clinical translation.https://www.mdpi.com/2313-433X/8/2/45artificial intelligencemusculoskeletalradiomicssarcoma |
| spellingShingle | Cristiana Fanciullo Salvatore Gitto Eleonora Carlicchi Domenico Albano Carmelo Messina Luca Maria Sconfienza Radiomics of Musculoskeletal Sarcomas: A Narrative Review Journal of Imaging artificial intelligence musculoskeletal radiomics sarcoma |
| title | Radiomics of Musculoskeletal Sarcomas: A Narrative Review |
| title_full | Radiomics of Musculoskeletal Sarcomas: A Narrative Review |
| title_fullStr | Radiomics of Musculoskeletal Sarcomas: A Narrative Review |
| title_full_unstemmed | Radiomics of Musculoskeletal Sarcomas: A Narrative Review |
| title_short | Radiomics of Musculoskeletal Sarcomas: A Narrative Review |
| title_sort | radiomics of musculoskeletal sarcomas a narrative review |
| topic | artificial intelligence musculoskeletal radiomics sarcoma |
| url | https://www.mdpi.com/2313-433X/8/2/45 |
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