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

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.

2020 ◽  
pp. 028418512095195
Author(s):  
Ji Hyun Hong ◽  
Won-Hee Jee ◽  
Sunyoung Whang ◽  
Chan-Kwon Jung ◽  
Yang-Guk Chung ◽  
...  

Background Making the preoperative diagnosis of soft-tissue lymphoma is important because the treatments for lymphoma and sarcoma are different. Purpose To determine the reliability and accuracy of single-slice and whole-tumor apparent diffusion coefficient (ADC) histogram analysis when differentiating soft-tissue lymphoma from undifferentiated sarcoma. Material and Methods Patients with confirmed soft-tissue lymphoma or undifferentiated sarcoma who underwent 3-T magnetic resonance imaging (MRI), including diffusion-weighted imaging, were included. Single-slice and whole-tumor ADC histogram analyses were performed using software. Mean, standard deviation (SD), 5th and 95th percentiles, skewness, and kurtosis were compared between groups, and a receiver operating characteristic curve with area under the curve (AUC) was obtained. Results Thirteen patients with soft-tissue lymphoma and 12 patients with undifferentiated sarcoma were included. ADC histogram analysis of single-slice and whole-tumor, mean, SD, and 5th and 95th percentiles was significantly lower in lymphoma than in undifferentiated sarcoma. Whole-tumor analysis kurtosis was significantly higher in lymphoma than in undifferentiated sarcoma. All AUCs were high in single-slice and whole-tumor analysis: 0.987 vs. 1.000 in mean; 0.821 vs. 0.782 in SD; 0.949 vs. 0.949 in 5th percentile; and 1.000 vs. 1.000 in 95th percentile without significant difference. AUC of kurtosis in whole-tumor ADC histogram analysis was 0.750. Conclusion Single-slice and whole-tumor ADC histogram analysis seems to be reliable and accurate for differentiating soft-tissue lymphoma from undifferentiated sarcoma.


2019 ◽  
Vol 48 (7) ◽  
pp. 20190100 ◽  
Author(s):  
Zanxia Zhang ◽  
Chengru Song ◽  
Yong Zhang ◽  
Baohong Wen ◽  
Jinxia Zhu ◽  
...  

Objectives To explore the utility of whole-lesion apparent diffusion coefficient (ADC) histogram analysis for differentiating parotid gland tumors following readout-segmented diffusion-weighted imaging (RESOLVE). Methods 80 patients (40 with pleomorphic adenomas, 14 with Warthin tumors, and 26 with malignant parotid gland tumors) who underwent routine head-and-neck MRI and RESOLVE examinations, were retrospectively evaluated. RESOLVE data were acquired from a MAGNETOM Skyra 3T MR system. Eleven whole-lesion histogram parameters derived from histogram analysis (ADC_mean, ADC_minimum, ADC_maximum, ADC_1th, ADC_10th, ADC_50th, ADC_90th, ADC_99th, skewness, variance and kurtosis) were calculated for each patient using MaZda. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of the ADC for distinguishing among the three groups. Results In total, nine parameters (ADC_minimum, ADC_maximum, ADC_mean, ADC_10th, ADC_50th, ADC_90th, ADC_99th, variance, skewness) were statistically significant (all p < 0.05) for all three groups, in the comparison of pleomorphic adenomas to Warthin tumors; the ADC_mean, ADC_50th, and skewness revealed high diagnostic efficiency with areas under the receiver operating characteristic curve of 0.976, 0.970, and 0.970, respectively. In the comparison of pleomorphic adenomas to malignant parotid gland tumors, these nine parameters were also found to be statistically different (all p < 0.05); the ADC_mean, ADC_10th and ADC_50th revealed high diagnostic efficiency with area under the curve of 0.851, 0.866, and 0.841, respectively. However, in the comparison of Warthin tumors to malignant parotid gland tumors, only three parameters (ADC_mean, ADC_50th, skewness) were statistically significant (all p < 0.05). Conclusions Whole-lesion ADC histograms are effective in differentiating common parotid gland tumors.


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