Radiomics of Musculoskeletal Sarcomas: A Narrative Review.
Cristiana FanciulloSalvatore GittoEleonora CarlicchiDomenico AlbanoCarmelo MessinaLuca Maria SconfienzaPublished in: Journal of imaging (2022)
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.
Keyphrases
- high grade
- contrast enhanced
- lymph node metastasis
- low grade
- magnetic resonance imaging
- soft tissue
- papillary thyroid
- electronic health record
- clinical decision support
- computed tomography
- deep learning
- squamous cell carcinoma
- magnetic resonance
- healthcare
- end stage renal disease
- emergency department
- ejection fraction
- newly diagnosed
- machine learning
- bone marrow
- bone mineral density
- young adults
- diffusion weighted imaging
- insulin resistance
- high resolution
- big data
- artificial intelligence
- childhood cancer