<p>Added value of histogram analysis of apparent diffusion coefficient maps for differentiating triple-negative breast cancer from other subtypes of breast cancer on standard MRI</p>

Background Breast cancer is a heterogeneous disease. Recent studies showed that apparent diffusion coefficient (ADC) values have various association with tumor aggressiveness and prognosis. Purpose To evaluate the value of histogram analysis of ADC values obtained from the whole tumor volume in invasive ductal cancer (IDC) and ductal carcinoma in situ (DCIS). Material and Methods This retrospective study included 201 patients with confirmed DCIS (n = 37) and IDC (n = 164). The IDC group was divided into two groups based on the presence of a DCIS component: IDC–DCIS (n = 76) and pure IDC (n = 88). All patients underwent preoperative breast magnetic resonance imaging (MRI) with diffusion-weighted images at 3.0 T. Histogram parameters of cumulative ADC values, skewness, and kurtosis were calculated and statistically analyzed. Results The differences between DCIS, IDC–DCIS, and pure IDC were significant in all percentiles of ADC values, in descending order of DCIS, IDC–DCIS, and pure IDC. IDC showed significantly lower ADC values than DCIS, and ADC50 was the best indicator for discriminating IDC from DCIS, with a threshold of 1.185 × 10–3 mm2/s (sensitivity of 82.9%, specificity of 75.7%). However, multivariate analysis of obtained ADC values showed no significant differences between DCIS, IDC–DCIS, and pure IDC ( P > 0.05). Conclusion Volume-based ADC values showed association with heterogeneity of breast cancer. However, there was no additional diagnostic performance in histogram analysis for differentiating between DCIS, IDC–DCIS, and pure IDC.

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Gliomas: Histogram Analysis of Apparent Diffusion Coefficient Maps with Standard- or High-b-Value Diffusion-weighted MR Imaging—Correlation with Tumor Grade

Radiology ◽

10.1148/radiol.11110686 ◽

2011 ◽

Vol 261 (3) ◽

pp. 882-890 ◽

Cited By ~ 202

Author(s):

Yusuhn Kang ◽

Seung Hong Choi ◽

Young-Jae Kim ◽

Kwang Gi Kim ◽

Chul-Ho Sohn ◽

...

Keyword(s):

Diffusion Coefficient ◽

Mr Imaging ◽

Apparent Diffusion Coefficient ◽

Tumor Grade ◽

B Value ◽

Histogram Analysis ◽

High B Value ◽

Diffusion Weighted ◽

Apparent Diffusion ◽

Apparent Diffusion Coefficient Maps

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The Histogram Analysis of Apparent Diffusion Coefficient Maps with Standard- or Ultrahigh-b Value Diffusion-Weighted MR Imaging for Differentiating the Gleason Grade of Prostate Cancer

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2018.2363 ◽

2018 ◽

Vol 8 (3) ◽

pp. 577-582 ◽

Cited By ~ 2

Author(s):

Zhi-Hua Lu ◽

Wen-Lu Zhao ◽

Li-Biao Ji ◽

Ru Wen ◽

Yong-Sheng Zhang ◽

...

Keyword(s):

Prostate Cancer ◽

Diffusion Coefficient ◽

Mr Imaging ◽

Apparent Diffusion Coefficient ◽

B Value ◽

Histogram Analysis ◽

Gleason Grade ◽

Diffusion Weighted ◽

Apparent Diffusion ◽

Apparent Diffusion Coefficient Maps

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

Chinese Journal of Academic Radiology ◽

10.1007/s42058-019-00019-w ◽

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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