MRI Volumetrics and Image Texture Analysis in Assessing Systemic Treatment Response in Extra-Abdominal Desmoid Fibromatosis.

Purpose To determine whether MRI volumetric and image texture analysis correlates with treatment-induced biologic changes in desmoid fibromatosis (DF) earlier than conventional response criteria. Materials and Methods This retrospective study included 27 patients with histologically proven extra-abdominal DF who were managed with active surveillance or systemic therapy (from 2004 to 2016). MRI volumetric and image texture parameters were derived from manual tumor segmentations, and tumor signal intensity was normalized to muscle. Results were compared with objective response rates based on Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1, World Health Organization (WHO) lesion response, volumetrics, and MRI-modified Choi criteria. Correlation coefficients (r) between image texture features and maximum tumor diameters were obtained by using a meta-analysis approach. Results The 27 included patients (mean age, 39 years; 74% women) were followed for an average of 4 years, comprising 207 distinct time-point assessments. The mean baseline tumor maximum diameter was 7.9 cm (range, 3.4-15.2 cm). Partial response (PR) rates as best response were 37%, 44%, 70%, and 81% by RECIST, WHO, volumetrics, and MRI-modified Choi criteria, respectively. Among the 10 tumors showing RECIST PR, a preceding MRI-modified Choi PR was observed in 70% (seven of 10), on average 1.3 years earlier. Multiple image texture parameters showed associations with objective measurements of tumor diameter including mean tumor-to-muscle signal ratio (r = 0.51; P = .004), median tumor-to-muscle signal ratio (r = 0.52; P = .003), energy (r = 0.48; P < .001), run entropy (r = 0.32, P = .04), and gray-level nonuniformity (r = 0.54; P ≤ .001). Conclusion Volumetric signal and image texture assessment allows more comprehensive analysis of DF biologic change and may permit early prediction of DF behavior and therapeutic response. Keywords: MR Imaging, Soft Tissues/Skin, Neoplasms-Primary © RSNA, 2021.