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  • Title: [Stretched-exponential and mono-exponential diffusion-weighted imaging for assessing the aggressiveness of prostate cancer: A histogram analysis].
    Author: Yu YN, Zhang SJ.
    Journal: Zhonghua Nan Ke Xue; 2019 Dec; 25(12):1106-1112. PubMed ID: 32251563.
    Abstract:
    OBJECTIVE: To assess the value of stretched-exponential and mono-exponential diffusion-weighted imaging (DWI) in predicting the aggressiveness of PCa. METHODS: This retrospective study included 36 cases of PCa with 48 lesions in the peripheral zone diagnosed by DWI with b-values of 0, 500, 1000, and 2000 s/mm2. We reconstructed the apparent diffusion coefficient (ADC), distributed diffusion coefficient (DDC) and α maps on the post-processing workstation, performed a histogram analysis on the largest slice of PCa on T2WI and Spearman's rank-order analysis on the correlation of the histogram variables with Gleason grade grouping (GG). Then, we assessed the values of the histogram variables in differentiating low-grade from high-grade PCa using the receiver operating characteristic (ROC) curve. RESULTS: The percentile and mean ADCs and DDCs were correlated with GG (ρ: 0.392－0.641) but not the α value, skewnesses and kurtosises (ρ: 0.055－0.266). High-grade PCa exhibited significantly lower 10th-, 25th-, 50th- and 75th-percentile and mean ADCs (490 ± 141, 591 ± 137, 695 ± 137, 781 ± 139 and 888 ± 135 mm2/s) and DDCs (420 ± 146, 534 ± 167, 666 ± 182, 787 ± 190 and 912 ± 175 mm2/s) than low-grade PCa (ADCs: 636 ± 74, 727 ± 86, 825 ± 85, 907 ± 85 and 975 ± 117 mm2/s; DDCs: 542 ± 80, 666 ± 93, 806 ± 108, 910 ± 110 and 1023 ± 105 mm2/s), but there were no statistically significant differences between low- and high-grade PCa in the α value (0.67 ± 0.042 vs 0.64 ± 0.036), kurtosises (ADC 0.105 vs 0.078; DDC －0.027 vs －0.401) or skewnesses (ADC －0.042 vs 0.067; DDC －0.058 vs 0.162). Both 10th-percentile ADCs and DDCs showed a higher efficiency than the mean ones in differentiating high- from low-grade PCa, though with no statistically significant difference (P > 0.05). CONCLUSIONS: Histogram variables DDCs and ADCs, rather than the α value, can be used to predict the aggressiveness of PCa, even more efficiently at the 10th percentile than on the mean.
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