Histogram Analysis Of Apparent Diffusion Coefficient Maps For Differentiating Anterior Mediastinal Solid Tumors

Part I Histogram analysis of apparent diffusion coefficient maps for assessing thymic epithelial tumors:correlation with world health organization classification and clinical stagingObjective:To investigate the value of apparent diffusion coefficients（ADC）histogram analysis for assessing World Health Organization（WHO）pathological classification and Masaoka clinical stages of thymic epithelial tumors.Materials and Methods:Thirty-seven patients with histologically confirmed thymic epithelial tumors were enrolled.ADC measurements were performed using hot-spot ROI(ADC_HS-ROI)and histogram-based approach.ADC histogram parameters included mean ADC(ADC_mean),median ADC(ADC_median),10 and 90 percentile of ADC(ADC₁₀ and ADC₉₀),kurtosis and skewness.One-way ANOVA,independent-sample t test,and receiver operating characteristic（ROC）were used for statistical analyses.Results:There were significant differences in ADC_mean,ADC_median,ADC₁₀,ADC₉₀and ADC_HS-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 Ps<0.05）,while no significant difference in skewness（p=0.181）and kurtosis（p=0.088）.ADC10 showed best differentiating ability（cut-off value,≦0.689×10-3mm2/s;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）tumors showed significant lower ADC parameters and higher kurtosis than early Masaoka stage（stage I and II;n=13）tumors（All p<0.05）,while no significant difference on skewness（p=0.063）.ADC₁₀showed best differentiating ability（cut-off value,≦0.689×10-3 mm2/s;AUC,0.913;sensitivity,91.30%;specificity,85.71%）for discriminating advanced and early Masaoka stage epithelial tumors.Conclusions:ADC histogram analysis may assist in assessing the WHO pathological classification and Masaoka clinical stages of thymic epithelial tumors.Part Ⅱ Whole-tumor histogram analysis of apparent diffusion coefficient maps for differentiating thymic carcinoma from lymphomaObjective: To assess the performance of whole-tumor histogram analysis of apparent diffusion coefficient（ADC）maps in differentiating thymic carcinoma from lymphoma,and compare with that of commonly used hot-spot region of interest（ROI）based ADC measurement.Materials and Methods: Diffusion weighed imaging（DWI）data of 15 patients with thymic carcinoma and 13 patients with lymphoma were retrospectively collected and processed with mono-exponential model.ADC measurements were performed by using histogram-based and hot-spot ROI based approach.In histogram-based approach,following parameters were generated,including mean ADC（ADCmean）,median ADC（ADCmedian）,10 and 90 percentile of ADC（ADC10 and ADC90）,kurtosis and skewness.The difference of ADCs between thymic carcinoma and lymphoma was compared using t test.Receiver operating characteristic analyses were conducted to determine and compare the differentiating performance of ADCs.Results: Lymphoma demonstrated significantly lower ADCmean,ADCmedian,ADC10,ADC90 and hot-spot ROI based mean ADC than thymic carcinoma（all p values < 0.001）,while no differences were found on kurtosis（p=0.412）and skewness（p=0.273）.ADC10 demonstrated optimal differentiating performance [cut-off value,0.403×10-3 mm2/s;area under curve（AUC）,0.977;sensitivity,92.31%;specificity,93.33%],followed by ADCmean,ADCmedian,ADC90 and hot-spot ROI based mean ADC.The AUC of the ROC curve of ADC10 was significantly higher than that of hot-spot ROI based ADC（0.977 vs 0.797,P=0.036）.Conclusion: Compared with commonly used hot-spot ROI based ADC measurement,histogram analysis of ADC maps holds the promise in improving the differentiating performance between thymic carcinoma and lymphoma.