Assessing Treatment Response in Soft Tissue Sarcoma Using Dynamic Contrast-Enhanced MRI: A Systematic Review
- Author:
Peyman MIRGHADERI
1
;
Nasim ESHRAGHI
;
Hyeyun LEE
;
Hyun Su KIM
;
Sara HASELI
;
Arash AZHIDEH
;
Chankue PARK
;
In Sook LEE
;
Peter C. THURLOW
;
Majid CHALIAN
Author Information
- Publication Type:Focus
- From:Korean Journal of Radiology 2026;27(6):555-567
- CountryRepublic of Korea
- Language:English
- Abstract: Conventional size-based criteria have limitations in accurately assessing neoadjuvant therapy (NAT) response in soft tissue sarcomas (STS). This systematic review evaluated the association between dynamic contrast-enhanced MRI (DCE-MRI) parameters and histopathology-based response to NAT in STS and summarized which DCE-MRI parameters show the most consistent associations across diverse clinical contexts. Following Preferred Reporting Items for Systematic Reviews and MetaAnalyses (PRISMA) guidelines, a comprehensive search was conducted to identify studies evaluating treatment response to NAT in STS using DCE-MRI. Thirteen studies comprising 234 patients were included. Quantitative DCE-MRI parameters, particularly Ktrans , showed a strong predictive performance for treatment response and demonstrated high discriminatory ability in several cohorts during both early and late post-treatment phases. Related measures such as ΔKtrans , Kep, and Ve also correlated significantly with histopathologic necrosis. Semi-quantitative markers, including the integrated area under the curve in the first 60 seconds after injection (iAUC60), wash-in rate, and time-to-peak, showed consistent associations with tumor perfusion and hypoxia. Qualitative features, including time–intensity curve patterns, effectively differentiated responders from non-responders, with type II curves most strongly associated with favorable outcomes. In conclusion, DCE-MRI, particularly quantitative pharmacokinetic parameters such as Ktrans , shows promise for assessing treatment response in STS and demonstrates generally concordant associations with histopathology-based response. However, protocol and endpoint heterogeneity and small cohort sizes limit the ability to establish definitive cutoffs and reduce generalizability, highlighting the need for standardized prospective validation.
