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Quantitative analysis of dynamic contrast-enhanced MRI in distinguishing different grades of prostate cancer / 中国医学影像技术
Chinese Journal of Medical Imaging Technology ; (12): 901-905, 2018.
Article in Chinese | WPRIM | ID: wpr-706353
ABSTRACT
Objective To investigate the value of quantitative analysis parameters of dynamic contrast-enhanced MRI (DCE-MRI) in distinguishing low or high grade prostate cancer.Methods Data of DCE-MRI in 26 patients with prostate cancer confirmed by surgical pathology following radical prostatectomy were retrospectively analyzed.These patients were divided into low grade prostate cancer (n=10) group or high grade prostate cancer group (n=16).The parameters,including transport constant (K trans),rat constant (Kep) and extravascular extracellular volume fraction (Vc.) were measured and compared between the two groups.ROC curve was used to determine the efficacy of the parameters in distinguishing low or high grade prostate cancer.The correlation between the parameters and Gleason score were assessed.Results Ktrans,Kep and Ve values in the low grade prostate cancer group was (0.22± 0.07)/min,(1.24 ± 0.57)/min and 0.21±0.08 respectively,and (0.36±0.10)/min,(1.82±0.66)/min,0.21±0.10 respectively in the high grade prostate cancer group.The differences of K trans and Kep were statistically significant between the two groups (both P<0.05),while of Vc.was not statistically significant (P=0.994).The area under ROC curves of K trans and keapvalues for distinguishing low or high grade prostate cancers was 0.872 and 0.737,respectively.No correlation was found between any parameters nor Gleason scores (all P>0.05).Conclusion K trans and Kep,the quantitative analysis parameters of DCE-MRI,contribute to the differential diagnosis of low and high grade prostate cancer.

Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Medical Imaging Technology Year: 2018 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Medical Imaging Technology Year: 2018 Type: Article