Ling-Yan Kong1, Wei Zhang1, Yue Zhou2, Hai Xu1, Hai-Bin Shi1, Qing Feng3, Xiao-Quan Xu1, Tong-Fu Yu1. 1. 1 Department of Radiology, The First Affiliated Hospital of Nanjing Medical University , The First Affiliated Hospital of Nanjing Medical University , Nanjing , China. 2. 2 Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University , The First Affiliated Hospital of Nanjing Medical University , Nanjing , China. 3. 3 Department of Nutrition and Food Hygiene,School of Public Health, Nanjing Medical University , School of Public Health, Nanjing Medical University , Nanjing , China.
Abstract
OBJECTIVE: To investigate the value of apparent diffusion coefficients (ADCs) histogram analysis for assessing World Health Organization (WHO) pathological classification and Masaoka clinical stages of thymic epithelial tumours. METHODS: 37 patients with histologically confirmed thymic epithelial tumours were enrolled. ADC measurements were performed using hot-spot ROI (ADCHS-ROI) and histogram-based approach. ADC histogram parameters included mean ADC (ADCmean), median ADC (ADCmedian), 10 and 90 percentile of ADC (ADC10 and ADC90), kurtosis and skewness. One-way ANOVA, independent-sample t-test, and receiver operating characteristic were used for statistical analyses. RESULTS: There were significant differences in ADCmean, ADCmedian, ADC10, ADC90 and ADCHS-ROI among low-risk thymoma (type A, AB, B1; n = 14), high-risk thymoma (type B2, B3; n = 9) and thymic carcinoma (type C, n = 14) groups (all p-values <0.05), while no significant difference in skewness (p = 0.181) and kurtosis (p = 0.088). ADC10 showed best differentiating ability (cut-off value, ≤0.689 × 10-3 mm2 s-1; AUC, 0.957; sensitivity, 95.65%; specificity, 92.86%) for discriminating low-risk thymoma from high-risk thymoma and thymic carcinoma. Advanced Masaoka stages (Stage III and IV; n = 24) tumours showed significant lower ADC parameters and higher kurtosis than early Masaoka stage (Stage I and II; n = 13) tumours (all p-values <0.05), while no significant difference on skewness (p = 0.063). ADC10 showed best differentiating ability (cut-off value, ≤0.689 × 10-3 mm2 s-1; AUC, 0.913; sensitivity, 91.30%; specificity, 85.71%) for discriminating advanced and early Masaoka stage epithelial tumours. CONCLUSION: ADC histogram analysis may assist in assessing the WHO pathological classification and Masaoka clinical stages of thymic epithelial tumours. Advances in knowledge: 1. ADC histogram analysis could help to assess WHO pathological classification of thymic epithelial tumours. 2. ADC histogram analysis could help to evaluate Masaoka clinical stages of thymic epithelial tumours. 3. ADC10 might be a promising imaging biomarker for assessing and characterizing thymic epithelial tumours.
OBJECTIVE: To investigate the value of apparent diffusion coefficients (ADCs) histogram analysis for assessing World Health Organization (WHO) pathological classification and Masaoka clinical stages of thymic epithelial tumours. METHODS: 37 patients with histologically confirmed thymic epithelial tumours were enrolled. ADC measurements were performed using hot-spot ROI (ADCHS-ROI) and histogram-based approach. ADC histogram parameters included mean ADC (ADCmean), median ADC (ADCmedian), 10 and 90 percentile of ADC (ADC10 and ADC90), kurtosis and skewness. One-way ANOVA, independent-sample t-test, and receiver operating characteristic were used for statistical analyses. RESULTS: There were significant differences in ADCmean, ADCmedian, ADC10, ADC90 and ADCHS-ROI among low-risk thymoma (type A, AB, B1; n = 14), high-risk thymoma (type B2, B3; n = 9) and thymic carcinoma (type C, n = 14) groups (all p-values <0.05), while no significant difference in skewness (p = 0.181) and kurtosis (p = 0.088). ADC10 showed best differentiating ability (cut-off value, ≤0.689 × 10-3 mm2 s-1; AUC, 0.957; sensitivity, 95.65%; specificity, 92.86%) for discriminating low-risk thymoma from high-risk thymoma and thymic carcinoma. Advanced Masaoka stages (Stage III and IV; n = 24) tumours showed significant lower ADC parameters and higher kurtosis than early Masaoka stage (Stage I and II; n = 13) tumours (all p-values <0.05), while no significant difference on skewness (p = 0.063). ADC10 showed best differentiating ability (cut-off value, ≤0.689 × 10-3 mm2 s-1; AUC, 0.913; sensitivity, 91.30%; specificity, 85.71%) for discriminating advanced and early Masaoka stage epithelial tumours. CONCLUSION: ADC histogram analysis may assist in assessing the WHO pathological classification and Masaoka clinical stages of thymic epithelial tumours. Advances in knowledge: 1. ADC histogram analysis could help to assess WHO pathological classification of thymic epithelial tumours. 2. ADC histogram analysis could help to evaluate Masaoka clinical stages of thymic epithelial tumours. 3. ADC10 might be a promising imaging biomarker for assessing and characterizing thymic epithelial tumours.
Authors: H Yabuuchi; Y Matsuo; K Abe; S Baba; S Sunami; T Kamitani; M Yonezawa; Y Yamasaki; S Kawanami; M Nagao; T Okamoto; K Nakamura; H Yamamoto; M Sasaki; H Honda Journal: Clin Radiol Date: 2015-08-10 Impact factor: 2.350
Authors: Marcelo F Benveniste; Sonia L Betancourt Cuellar; Brett W Carter; Girish S Shroff; Carol Wu; Edith M Marom Journal: Mediastinum Date: 2019-07-19