峰度
有效扩散系数
前列腺癌
磁共振弥散成像
核医学
磁共振成像
医学
相关系数
核磁共振
皮尔逊积矩相关系数
相关性
癌症
放射科
内科学
数学
物理
统计
几何学
作者
Shiteng Suo,Xiaoxi Chen,Lian‐Ming Wu,Xiaofei Zhang,Qiuying Yao,Yu Fan,He Wang,Jianrong Xu
标识
DOI:10.1016/j.mri.2014.01.015
摘要
To evaluate the non-Gaussian water diffusion properties of prostate cancer (PCa) and determine the diagnostic performance of diffusion kurtosis (DK) imaging for distinguishing PCa from benign tissues within the peripheral zone (PZ), and assessing tumor lesions with different Gleason scores. Nineteen patients who underwent diffusion weighted (DW) magnetic resonance imaging using multiple b-values and were pathologically confirmed with PCa were enrolled in this study. Apparent diffusion coefficient (ADC) was derived using a monoexponential model, while diffusion coefficient (D) and kurtosis (K) were determined using a DK model. Differences between the ADC, D and K values of benign PZ and PCa, as well as those of tumor lesions with Gleason scores of 6, 7 and ≥ 8 were assessed. Correlations between parameters D and K in PCa were analyzed using Pearson's correlation coefficient. ADC, D and K values were correlated with Gleason scores of 6, 7 and ≥ 8, respectively. ADC and D values were significantly (p < 0.001) lower in PCa (0.79 ± 0.14 μm2/ms and 1.56 ± 0.23 μm2/ms, respectively) compared to benign PZ (1.23 ± 0.19 μm2/ms and 2.54 ± 0.24 μm2/ms, respectively). K values were significantly (p < 0.001) greater in PCa (0.96 ± 0.20) compared to benign PZ (0.59 ± 0.08). D and K showed fewer overlapping values between benign PZ and PCa compared to ADC. There was a strong negative correlation between D and K values in PCa (Pearson correlation coefficient r = − 0.729; p < 0.001). ADC and K values differed significantly in tumor lesions with Gleason scores of 6, 7 and ≥ 8 (p < 0.001 and p = 0.001, respectively), although no significant difference was detected for D values (p = 0.325). Significant correlations were found between the ADC value and Gleason score (r = − 0.828; p < 0.001), as well as the K value and Gleason score (r = 0.729; p < 0.001). DK model may add value in PCa detection and diagnosis. K potentially offers a new metric for assessment of PCa.
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