Abstract:Objective: To investigate the value of the related parameters of diffusion kurtosis imaging(DKI) in differential diagnosis between prostate cancer(PCa) and benign prostatic hyperplasia(BPH), and its relationship with pathological grades. Methods: A total of 57 cases of prostate diseases proved by surgery or biopsy, including 25 PCa and 32 BPH, were collected in the retrospective study. All patients underwent routine prostate MRI and DKI scan. Mean kurtosis (MK), mean diffusivity(MD) and fractional anisotropy(FA) values were obtained. The receiver operating characteristic curve(ROC) was used to evaluate the diagnosis efficiency of these parameters on PCa and BPH. The correlation between DKI parameters and the clinical pathological grade of PCa according to the American Joint Committee on Cancer(AJCC, 8th edition) was analyzed. P<0.05 was considered statistically significant. Results: The difference of MK and MD value between BPH and PCa were statistically significant(P=0.000). The ROC curve showed that the MK value has the greatest diagnostic efficacy(AUC=0.99). There were significant differences in MK and FA value among different clinical groups and Gleason scores(P<0.05). There was no significant difference in MD value among different Gleason scores(P>0.05). There was a significant positive correlation between the MK value of the DKI model and the AJCC clinical classification and Gleason score(r values were 0.860 and 0.805, respectively) and FA values were moderately negatively correlated(r values were -0.463 and -0.465, respectively). Conclusion: Quantitative analysis of DKI model is helpful for the differential diagnosis of BPH and PCa. The MK value is highly sensitive and specific in diagnosis, which can help predic tthe clinical pathological grade of PCa.
王 睿1,仲津漫1,汪 洋1,杨如武2,赵明增2,任小军2,任 芳1,范 颖1,任 静1. DKI对前列腺癌的鉴别诊断及临床病理分级的定量预测研究[J]. 中国临床医学影像杂志, 2019, 30(2): 122-125.
WANG Rui1, ZHONG Jin-man1, WANG Yang1, YANG Ru-wu2, ZHAO Ming-zeng2, . Quantitative research of DKI in the differential diagnosis of prostate cancer and #br# its correlation with pathological grades. JOURNAL OF CHINA MEDICAL IMAGING, 2019, 30(2): 122-125.
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