Prediction of Chemotherapeutic Response in Bladder Cancer Using K-means Clustering of Dynamic Contrast-Enhanced (DCE)-MRI Pharmacokinetic Parameters

PurposeTo apply k-means clustering of two pharmacokinetic parameters derived from 3T dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict the chemotherapeutic response in bladder cancer at the mid-cycle timepoint. Materials and MethodsWith the predetermined number of three clusters, k-means clustering was performed on nondimensionalized Amp and k(ep) estimates of each bladder tumor. Three cluster volume fractions (VFs) were calculated for each tumor at baseline and mid-cycle. The changes of three cluster VFs from baseline to mid-cycle were correlated with the tumor's chemotherapeutic response. Receiver-operating-characteristics curve analysis was used to evaluate the performance of each cluster VF change as a biomarker of chemotherapeutic response in bladder cancer. ResultsThe k-means clustering partitioned each bladder tumor into cluster 1 (low k(ep) and low Amp), cluster 2 (low k(ep) and high Amp), cluster 3 (high k(ep) and low Amp). The changes of all three cluster VFs were found to be associated with bladder tumor response to chemotherapy. The VF change of cluster 2 presented with the highest area-under-the-curve value (0.96) and the highest sensitivity/specificity/accuracy (96%/100%/97%) with a selected cutoff value. ConclusionThe k-means clustering of the two DCE-MRI pharmacokinetic parameters can characterize the complex microcirculatory changes within a bladder tumor to enable early prediction of the tumor's chemotherapeutic response. J. Magn. Reson. Imaging 2015;41:1374-1382. (c) 2014 Wiley Periodicals, Inc.