Prospective evaluation of soft tissue tumors: Correlation of ST-RADS MRI reporting guidelines with histopathological findings
Authors:   Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences, Chennai, India, Kannadasan Karpagam , Evangeline Christina P ,   Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences, Chennai, India, Krishna Karthik ,   Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences, Chennai, India, Muthiah P. ,   Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences, Chennai, India, Natarajan Paarthipan ,   Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences, Chennai, India
Published: December 2024

Introduction. Soft tissue tumors, ranging from benign to highly malignant, pose diagnostic challenges due to their histological diversity. MRI is the preferred imaging modality for these tumors, but variability in interpretation affects consistency. The Soft Tissue Reporting and Data System (ST-RADs), modeled after BI-RADS, offers a standardized approach for classifying soft tissue lesions based on MRI features, potentially improving diagnostic accuracy and reducing unnecessary biopsies. This study aims to validate the clinical utility of ST-RADs by correlating MRI findings with histopathological examination (HPE), providing evidence for its use in routine practice to enhance diagnostic confidence and optimize patient management. Purpose. This study aims to evaluate the efficacy of the Soft Tissue Reporting and Data System (ST-RADS) in diagnosing soft tissue tumors using Magnetic Resonance Imaging (MRI), correlating MRI findings with histopathological examination (HPE) outcomes. Knowledge generated. Diagnostic accuracy was found to be high, with a ROC AUC of 0.959. Epidemiological insights indicate that a significant portion of the affected population is over 40 years old, with a balanced gender distribution. Clinical utility highlights the potential to reduce invasive diagnostic procedures through a reliable, non-invasive, imaging-based classification. Histopathological correlation confirms that MRI findings are consistent with HPE diagnoses, further validating the reliability of ST-RADs. Methods. A prospective observational study was conducted over 18 months at Saveetha Medical College and Hospital, involving 40 patients with suspected soft tissue tumors. MRI scans were performed using a 1.5 Tesla MRI system and classified according to ST-RADS guidelines. Histopathological examination was used as the gold standard for diagnosis. Statistical analysis included frequency percentages and Receiver Operating Characteristic (ROC) curves. Results. The study primarily involved older adults, with 28 participants aged over 40 years (70%), including a significant portion aged 60-70 years (13 participants, 32.5%). The gender distribution was balanced, with 18 males (45%) and 22 females (55%). Diagnoses revealed 17 sarcomas (42.5%), 11 lipomas (27.5%), and 3 ganglion cysts (7.5%). Most lesions were benign, found in 27 cases (67.5%), and the ST-RADS classification demonstrated high diagnostic accuracy (ROC AUC = 0.959, P < 0.0001). The optimal cutoff at ST-RADS 0-3 versus 4-5 provided a sensitivity of 92.31% and specificity of 85.19%, which is crucial for distinguishing benign from malignant tumors. Conclusion. The ST-RADS system provides a structured approach to MRI assessment of soft tissue tumors, facilitating accurate differentiation between benign and malignant lesions. Correlation with histopathological findings supports its clinical utility, potentially reducing the need for invasive procedures and guiding appropriate treatment strategies. Future enhancements and integration with advanced diagnostic tools could further improve diagnostic precision and patient care outcomes.