Radiomics in Diagnosis, Grading, and Treatment Response Assessment of Soft Tissue Sarcomas: A Systematic Review and Meta-analysis.

To evaluate radiomics in soft tissue sarcomas (STSs) for diagnostic accuracy, grading, and treatment response assessment, with a focus on clinical relevance. In this diagnostic accuracy study, radiomics was applied using multiple MRI sequences and AI classifiers, with histopathological diagnosis as the reference standard. Statistical analysis involved meta-analysis, random-effects model, and Deeks' funnel plot asymmetry test. Among 579 unique titles and abstracts, 24 articles were included in the systematic review, with 21 used for meta-analysis. Radiomics demonstrated a pooled sensitivity of 84% (95% CI: 80–87) and specificity of 63% (95% CI: 56–70), AUC of 0.93 for diagnosis, sensitivity of 84% (95% CI: 82–87) and specificity of 73% (95% CI: 68–77), AUC of 0.91 for grading, and sensitivity of 83% (95% CI: 67–94) and specificity of 67% (95% CI: 59–74), AUC of 0.87 for treatment response assessment. Radiomics exhibits potential for accurate diagnosis, grading, and treatment response assessment in STSs, emphasizing the need for standardization and prospective trials. Radiomics offers precise tools for STS diagnosis, grading, and treatment response assessment, with implications for optimizing patient care and treatment strategies in this complex malignancy. ● Radiomic studies of soft tissue sarcomas are limited, often due to unvalidated results and a retrospective study design. ● Meta-analyses of studies predicting radiomic models for soft tissue sarcomas have shown success in differentiating benign and malignant tumors, but methodological quality is a major concern. ● The collection and integration of multimodal data and the standardization of research processes can facilitate the development and validation of radiomic models. [ABSTRACT FROM AUTHOR]