The comparative study of in transition zone prostate cancer: diagnostic performance of new intravoxel incoherent motion and diffusion kurtosis imaging models / 中华放射学杂志

ABSTRACT

Objective@#To evaluate the diagnostic value of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters in diagnosing prostate cancer(PCa) in transition zone (TZ) and stratifying pathologic Gleason grade of prostate cancer.@*Methods@#A total of 55 patients who were undergoing preoperative muti-parameters MRI of T2WI, DWI, IVIM and DKI model for the exploration of prostate cancer (January 2015 to June 2017) with pathologically confirmed by MRI-transrectal ultrasound (TRUS) targeted fusion biopsy were retrospectively included. Parameters were postprocessed by IVIM models including quantitation of perfusion fraction (f), diffusivity (D) and pseudo-diffusivity (D*) and DKI models including the mean diffusivity (MD), mean kurtosis (MK) and fractional anisotropy (FA) by outlining the 3D VOI. Independent sample t-test was used to compare the differences in lesion parameters between prostate cancer and BPH, low-risk (BPH+Gleason score 6 points) and medium-high-risk lesions (Gleason score ≥7 points). Correlation between ADC values, IVIM and DKI parameters and Gleason scores were assessed with Spearman analysis. Receiver operating characteristic curve analysis was used to evaluate the efficacy of various parameters in the differential diagnosis of prostate cancer and BPH with low-risk or high-risk.@*Results@#27 (36 focus) cases of PCa and 28 (40 focus) cases of benign prostatic hyperplasia (BPH) in PZ were included, meanwhile, the cases of GS ≥7 and and BPH+(GS=6) were 33,43,respectively. There were significant differences in ADC, D, MD, MK, and FA between patients in PCa-BHP group and high-low risk group in TZ (P<0.05), D* and f had no significant differences (P>0.05). ADC and MD showed relatively higher negativity correlations (r were -0.585 and -0.489, P<0.05) with GS of PCa in TZ. ADC exhibited a higher area under the curve (AUC 0.864) compared with D with area under the curve (AUC 0.853), however, the difference is not significant (P>0.05). Of model DKI in diagnose of PCa and BPH, the highest classification accuracy was MD(AUC 0.796). The AUC derived from multiple model parameters in different combination of ADC+D value, ADC+MD value, and ADC+MD+D value were 0.892, 0.884, and 0.897, respectively. ADC and D of IVIM model showed a significance difference between GS ≥7 and BPH+(GS=6) with a higher AUC of 0.826 and 0.743. The AUC was 0.851 of the combination of mean ADC and D, 0.846 of combination of mean ADC and MD, the AUC (0.856) of the combination of ADC, D and MD significant higher than any two combined parameters (P>0.05).@*Conclusions@#IVIM and DKI models may help to discriminate prostate cancer from BPH, and predict mid-higher GS PCa in TZ. But there is no significant advantage compared with ADC values. It is feasible to stratify the pathological grade of prostate cancer in TZ by mean ADC and MD.