Histogram analysis in prostate cancer: a comparison of diffusion kurtosis imaging model versus monoexponential model.

BACKGROUND

There is still little research about histogram analysis of diffusion kurtosis imaging (DKI) using in prostate cancer at present.

PURPOSE

To verify the utility of histogram analysis of DKI model in detection and assessment of aggressiveness of prostate cancer, compared with monoexponential model (MEM).

MATERIAL AND METHODS

Twenty-three patients were enrolled in this study. For DKI model and MEM, the D, K, and apparent diffusion coefficient (ADC) were obtained by using single-shot echo-planar imaging sequence. The pathologies were confirmed by in-bore magnetic resonance (MR)-guided biopsy. Regions of interest (ROI) were drawn manually in the position where biopsy needle was put. The mean values and histogram parameters in cancer and noncancerous foci were compared using independent-samples T test. Receiver operating characteristic curves were used to investigate the diagnostic efficiency. Spearman's test was used to evaluate the correlation of parameters and Gleason scores.

RESULTS

The mean, 10th, 25th, 50th, 75th, and 90th percentiles of ADC and D were significantly lower in prostate cancer than non-cancerous foci ( < 0.001). The mean, 50th, 75th, and 90th percentiles of K were significantly higher in prostate cancer ( < 0.05). There was no significant difference between the AUCs of two models (0.971 vs. 0.963,  > 0.05). With the increasing Gleason scores, the 10th ADC decreased ( = -0.583,  = 0.018), but the 90th K increased ( = 0.642,  = 0.007).

CONCLUSION

Histogram analysis of DKI model is feasible for diagnosing and grading prostate cancer, but it has no significant advantage over MEM.