Objective: To find early predictors of histologic response in soft tissue sarcoma through volume transfer constant (Ktrans) analysis based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).
Materials and methods: 11 Patients with soft tissue sarcoma of the lower extremity that underwent preoperative chemoradiotherapy followed by limb salvage surgery were included in this retrospective study. For each patient, DCE-MRI data sets were collected before and two weeks after therapy initiation, and histologic tumor cell necrosis rate (TCNR) was reported at surgery. The DCE-MRI volumes were aligned by registration. Then, the aligned volumes were used to obtain the Ktrans variation map. Accordingly, three sub-volumes (with increased, decreased or unchanged Ktrans) were defined and identified, and fractions of the sub-volumes, denoted as F+, F- and F0, respectively, were calculated. The predictive ability of volume fractions was determined by using area under a receiver operating characteristic curve (AUC). Linear regression analysis was performed to investigate the relationship between TCNR and volume fractions. In addition, the Ktrans values of the sub-volumes were compared.
Results: The AUC for F- (0.896) and F0 (0.833) were larger than that for change of tumor longest diameter ΔD (0.625) and the change of mean KtransΔKtrans¯ (0.792). Moreover, the regression results indicated that TCNR was directly proportional to F0 (R2=0.75, P=0.0003), while it was inversely proportional to F- (R2=0.77, P=0.0002). However, TCNR had relatively weak linear relationship with ΔKtrans¯ (R2=0.64, P=0.0018). Additionally, TCNR did not have linear relationship with DD (R2=0.16, P=0.1246).
Conclusion: The volume fraction F- and F0 have potential as early predictors of soft tissue sarcoma histologic response.
Keywords: Dynamic contrast-enhanced magnetic resonance imaging; Histologic response prediction; Soft tissue sarcoma; Volume transfer constant; Voxel-wise analysis.
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