CT-response patterns and the role of CT-textural features in inoperable abdominal/retroperitoneal soft tissue sarcomas treated with trabectedin.

Purpose: To evaluate CT patterns and textural features of soft tissue sarcomas following trabectedin therapy as well as their suitability for predicting therapeutic response.

Material And Methods: A total of 31 patients (18 female, 13 male; mean age, 58.0years; range, 38-79years) with sarcoma under trabectedin as a third-line therapy between October 2008 and July 2017 underwent baseline and follow-up contrast-enhanced CT. Response evaluation was based on modifiedCHOI-criteria and RECIST1.1, classified as partial response(PR), stable disease(SD), progressive disease(PD). For CT-texture analysis (CTTA), mean, entropy and uniformity of intensity/skewness/entropy of co-occurrence matrix (COM) and contrast of neighboring-grey-level-dependence-matrix (NGLDM) were calculated.

Results: Following CHOI-criteria, 9 patients achieved PR, 10 SD and 12 PD. RECIST1.1. classified patients into 5 PR, 15 SD and 11 PD. A frequent (n = 6/31; 19.3%) pattern of response was tumor liquefaction. In responders differences in entropy of entropy-NGLDM(p = 0.028) and uniformity-NGLDM(p = 0.021), in non-responders entropy of average(p = 0.039), deviation(p = 0.04) and uniformity of deviation(p = 0.013) occured between baseline and follow-up. Mean intensity and average were higher when liquefication occured(p = 0.03; p = 0.02), whereas mean deviation was lower(p = 0.02) at baseline compared to other response patterns. Differences in mean(p = 0.023), entropy(p = 0.049) and uniformity(p = 0.023) of entropy-NGLDM were found between responders and non-responders at follow-up. For the mean of heterogeneity a cut-off value was calculated for prediction of response in baseline CTTA (0.12; sensitivity 89%; specificity 77%).

Conclusion: A frequent pattern of response to trabectedin was tumor liquefication being responsible for pseudoprogression, therefore modifiedCHOI should be preferred. Single CT-textural features can be used complementarily for prediction and monitoring response to trabectedin.