Differentiating Transition Zone Cancers From Benign Prostatic Hyperplasia by Histogram Analysis of Apparent Diffusion Coefficient Maps With Standard and Ultrahigh b-value Diffusion-weighted MR Imaging

2019 ◽  
Vol 43 (2) ◽  
pp. 235-241 ◽  
Author(s):  
Zhi-hua Lu ◽  
Li-biao Ji ◽  
Wen-lu Zhao ◽  
Yong-sheng Zhang ◽  
Jiang-fen Wu ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Benign Prostatic Hyperplasia ◽  
Mr Imaging ◽  
Apparent Diffusion Coefficient ◽  
Transition Zone ◽  
B Value ◽  
Prostatic Hyperplasia ◽  
Histogram Analysis ◽  
Apparent Diffusion ◽  
Apparent Diffusion Coefficient Maps

Differentiation of prostate cancer and stromal hyperplasia in the transition zone with histogram analysis of the apparent diffusion coefficient

2017 ◽  
Vol 58 (12) ◽  
pp. 1528-1534 ◽  
Author(s):  
Liu Xiaohang ◽  
Zhou Bingni ◽  
Zhou Liangping ◽  
Peng Weijun ◽  
Yang Xiaoqun ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Transition Zone ◽  
B Value ◽  
Histogram Analysis ◽  
Apparent Diffusion ◽  
Adc Values ◽  
The Mean ◽  
Magnetic Resonance Imaging Mri

Background Prostate cancer and stromal hyperplasia (SH) in the transition zone (TZ) are difficult to discriminate by conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI). Purpose To investigate the apparent diffusion coefficient (ADC) of prostate cancer and SH in the TZ with histogram analysis and the ability of ADC metrics to differentiate between these two tissues. Material and Methods Thirty-three cancer and 29 SH lesions in the TZ of 54 patients undergoing preoperative DWI (b-value 0, 1000 s/mm2) were analyzed. All the lesions on the MR images were localized based on histopathologic correlations. The 10th, 25th, and 50th percentiles, and the mean ADC values were calculated for the two tissues and compared. The efficiencies of the 10th, 25th, and 50th ADC percentiles in differentiating the two tissues were compared with that of the mean ADC with receiver operating characteristic (ROC) analysis. Results The 10th, 25th, and 50th percentiles and mean ADC values (×10−3 mm2/s) were 0.86 ± 0.15, 0.89 ± 0.16, 0.94 ± 0.16, and 1.03 ± 0.17 in SH and 0.64 ± 0.12, 0.69 ± 0.12, 0.72 ± 0.16, and 0.83 ± 0.15 in TZ cancer, respectively. The parameters were all significantly lower in cancer than SH. The 10th ADC percentile yielded an area under the ROC curve (AUC) of 0.87 for the differentiation of carcinomas from SH, which was higher than the mean ADC (0.80) ( P < 0.05), and the AUCs of the 25th (0.82) and 50th (0.83) percentiles exhibited no differences from those of the mean ADC ( P > 0.05). Conclusion Histogram analysis of ADC values may potentially improve the differentiation of prostate cancer from SH in the TZ.

scholarly journals Whole-tumor histogram analysis of apparent diffusion coefficient maps in grading diagnosis of ependymoma

2020 ◽  
Vol 2 (3-4) ◽  
pp. 41-46
Author(s):  
Huiyu Huang ◽  
Yong Zhang ◽  
Jingliang Cheng ◽  
Mengmeng Wen
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Sensitivity And Specificity ◽  
Histogram Analysis ◽  
Diagnostic Efficiency ◽  
Diagnostic Efficacy ◽  
Who Grade ◽  
Significant Difference ◽  
Apparent Diffusion ◽  
Apparent Diffusion Coefficient Maps

Abstract Objective To study the value of whole-tumor histogram analysis which is based on apparent diffusion coefficient maps in grading diagnosis of ependymoma. Methods 71 patients with ependymal tumors were retrospectively analyzed, including 13 cases of WHO grade I, 28 cases of WHO grade II, and 30 cases of WHO grade III. Mazda software was used to draw the region of interest (ROI) in the apparent diffusion coefficient maps of three groups on every layer of tumor level. The whole-tumor gray histogram analysis was carried to obtained nine characteristic parameters, including mean, variance, kurtosis, skewness, Perc.01%, Perc.10%, Perc.50%, Perc.90%, and Perc.99%. When the parameters satisfy the test of normal distribution and homogeneity of variance, single factor analysis of variance (ANOVA) was carried to compare the three groups and LSD t test was performed to compare the two groups. Besides, the ROC curve was used to analyze the diagnostic efficacy of the parameters. Results Variance, Perc.01%, and Perc.10% had significant differences among the three groups (all P < 0.05). The remaining six parameters had no significant difference among the three groups (all P > 0.05). And, between WHO I and WHO II, the sensitivity and specificity of the Perc.10% were 85.7% and 100.0%, the AUC was 0.872, and the cut-off was 126.5. Between WHO I and WHO III, the sensitivity and specificity of the Perc.10% were 85.7% and 87.7%, the AUC was 0.835, and the optimum critical value was 131.33. Besides, the sensitivity, specificity, and AUC of variance between WHO II and WHO III are 68.4%, 76.9%, 0.794, and 2645.7, respectively. They had higher identification efficiency. Conclusion Whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps could provide ancillary diagnostic value in grading diagnosis of ependymoma. Perc.10% had a high diagnostic efficiency.

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