Assessment of renal solid masses with histogram analysis in computerized tomography imaging

The aim of this retrospective study is to investigate the role of computed tomography histogram analysis (CTHA) in the diagnosis and differentiation of renal solid lesions. After the approval of the local ethics committee, 125 lesions were included, who underwent a contrast-enhanced abdominal CT in our hospital between January 2010 and January 2021.The included cases were evaluated on the workstation. In the evaluation of the primary lesion, cystic components, areas of necrosis, calcification and large feding vessels within mass were not included. For histogram analysis, the region of interest was placed on the solid segment with the least amount of fat and cystic component using the manuel drawing tool. The HU value of each pixel within the area of interest was exported to an XML (eXtensible Markum Language) file. In histogram analysis, piksel, mean, standart deviation, minimum, median, maximum, variance, entropy, size %L, size %U, size %M, kurtosis, skewness, uniformity, percent01, percent03, percent05, percent10, percent25, percent75, percent90, percent95, percent 97 and percent99 parameters were examined. Normally distributed data were compared with Student T and ANOVA, and non-normally distributed data were compared with Mann-Whitney U and Kruskal-Wallis tests. The normal distribution suitability of the data was evaluated with the "Kolmogorov-Smirov Test". P value of <0.05 was considered statistically significant. In our study, data were obtained that mean, median, uniformity and skewness values from various parameters obtained by histogram analysis may contribute to this distinction. The mean value of ROC analysis revealed the highest sensitivity and specificity. We found the mean value to be 14.10 ± 50.04 in benign lesions and 68.65 ± 46.65 (p<0.001) in malignant lesions. When the mean value was chosen as the cut-off value of 53,381, the sensitivity was calculated as 78% and the specificity as 79% in the differentiation of benign and malignant lesions. The uniformity, which we used as one of the histogram analysis parameters, indicates the homogeneity in the area we measure with the ROI. In our study, the uniformity value was found to be 0,2071 ± 0,1188 in benign lesions and 0,1184 ± 0,081 in malignant lesions. When the uniformity cut-off value was taken as 0,169, the sensitivity calculated as %71 and the specificity calculated as %69 in the differentiation of benign and malignant lesions. In conclusion, the use of CT histograms in renal mass lesions is promising in lesion characterization and differentiation of tumor types, and studies involving more patient groups are needed for use in large scales and standardization. Keywords: Renal Cell Carcinoma, Angiomyolipoma, Oncocytoma, Computed Tomography Histogram Analysis