Abstract
OBJECTIVE: In this study, the utility of histogram parameters derived from diffusion-weighted imaging for differentiate renal cell carcinoma (RCC) from oncocytoma was investigated. METHODS: This research tracked 126 individuals who were diagnosed with RCC and oncocytoma through histopathological analysis, using magnetic resonance imaging (MRI) assessments from 2015 to 2023. We observed various attributes of these patients, including demographic details, surgical records, pre-surgery MRI results, MRI apparent diffusion coefficient (ADC) histogram analysis, and post-surgery histopathological outcomes. Calculations of ADC measurements such as mean, minimum, and maximum in conjunction with the 5(th), 10(th), 25(th), 50(th), 75(th), 90(th), and 95(th) quantile points were made. In addition, we also noted the skewness, kurtosis, and variance of these data points. RESULTS: The focus group for this investigation consisted of 75 male and 51 female patients. Out of these, 82 were diagnosed with RCC and 44 with oncocytoma. All ADC parameters including ADCmin, ADCmedian, ADCmean, and ADCmax, including the 5(th), 10(th), 25(th), 50(th), 75(th), 90(th), and 95(th) quantile divisions among the oncocytoma cohort were observed to be higher than the corresponding ones in the RCC group. A statistically meaningful difference was discovered between the minimum ADC value along with the 5(th) ranking of ADC measurements (p<0.001), in addition to mean of ADC (p=0.050), and the 10(th) (p=0.002) and 25(th) (p=0.015) quantiles of ADC data. When considering the region below the curve (AUC) in ROC analysis, the value of ADCmin was recorded as 0.739, with a sensitivity of 75.0%, and specificity of 68.2%. CONCLUSION: To distinguish oncocytoma from RCC, it may be useful to conduct a whole-tumor histogram and textural analysis of ADC values.