Differentiating papillary type I RCC from clear cell RCC and oncocytoma: application of whole-lesion volumetric ADC measurement.
Abdom Radiol (NY). 2018 Sep;43(9):2424-2430. doi: 10.1007/s00261-017-1453-4.
Paschall AK1, Mirmomen SM1, Symons R1, Pourmorteza A1, Gautam R1, Sahai A1, Dwyer AJ1, Merino MJ1, Metwalli AR1, Linehan WM1, Malayeri AA2.
PURPOSE: To determine whether objective volumetric whole-lesion apparent diffusion coefficient (ADC) distribution analysis improves upon the capabilities of conventional subjective small region-of-interest (ROI) ADC measurements for prediction of renal cell carcinoma (RCC) subtype.
METHODS: This IRB-approved study retrospectively enrolled 55 patients (152 tumors). Diffusion-weighted imaging DWI was acquired at b values of 0, 250, and 800 s/mm2 on a 1.5T system (Aera, Siemens Healthcare). Whole-lesion measurements were performed by a research fellow and reviewed by a fellowship-trained radiologist. Mean, median, skewness, kurtosis, and every 5th percentile ADCs were determined from the whole-lesion histogram. Linear mixed models that accounted for within-subject correlation of lesions were used to compare ADCs among RCC subtypes. Receiver-operating characteristic (ROC) curve analysis with optimal cutoff points from the Youden index was used to test the ability of ADCs to differentiate clear cell RCC (ccRCC), papillary RCC (pRCC), and oncocytoma subtypes.
RESULTS: Whole-lesion ADC values were significantly different between pRCC and ccRCC, and between pRCC and oncocytoma, demonstrating strong ability to differentiate subtypes across the quantiles (both P < 0.001). Best percentile ROC analysis demonstrated AUC values of 95.2 for ccRCC vs. pRCC; 67.6 for oncocytoma vs. ccRCC; and 95.8 for oncocytoma vs. pRCC. Best percentile ROC analysis further indicated model sensitivities/specificities of 84.5%/93.1% for ccRCC vs. pRCC; 100.0%/10.3% for oncocytoma vs. ccRCC; and 88.5%/93.1% for oncocytoma vs. pRCC.
CONCLUSION: The objective methodology of whole-lesion volumetric ADC measurements maintains the sensitivity/specificity of conventional expert-based ROI analysis, provides information on lesion heterogeneity, and reduces observer bias.