Zhonghua yi xue za zhi
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Zhonghua yi xue za zhi · Mar 2019
[Discussion of correlation between histogram analysis of quantitative diffusion weighted imaging and Gleason score of prostate cancer].
Objective: To discuss the correlation between histogram analysis of quantitative mono-exponential, bi-exponential and diffusion kurtosis models in diffusion weighted imaging and the Gleason score of prostate cancer, and evaluate the application value and diagnostic efficiency in identifying low and high grade prostate cancer. Methods: A total of 50 patients with histologically confirmed as prostate cancer were examined from May 2015 to May 2016 in the Second Affiliated Hospital of Soochow University using DWI performed at 3.0 T with an extended b-value range from 0 to 2 000 s/mm(2). Data were post-processed by whole tumor histogram analysis,the ROI was manually drown in DWI (b=1 000 s/mm(2)) step by step along the outline of cancer, and quantitative analysis were performed respectively by mono-exponential, bi-exponential and diffusion kurtosis models for quantification of apparent diffusion coefficients (ADCs), diffusivity D, pseudo-diffusivity D(*), perfusion fraction f, diffusion coefficients by non-Gaussian distribution (D(k)) and kurtosis coefficient (K). ⋯ The diagnostic efficiency of histogram analysis results of these quantitative parameter values in identifying low and high grade prostate cancer showed that the ADC (median), D (25th), D(k) (mean) and K (25th) had a larger area under the curve, and were 0.844, 0.873, 0.815, and 0.919 respectively, the differences of area under the curve between any two of these parameters above were not statistically significant (all P>0.05). Conclusions: The quantitative parameters of three diffusion models (ADC, D, D(k), K) in DWI are all related to the Gleason score of prostate cancer, but in the differential diagnosis of low and high grade prostate cancer, the diagnostic efficacy of mono-exponential model is sufficient. The more complex model such as bi-exponential and diffusion kurtosis may complement it in other ways.