Search Results (2)

This study was undertaken to compare Fuhrman grading with World Health Organization/International Society of Urological Pathology (WHO/ISUP) grading and stereologically measured nuclear area in patients with Clear Cell Renal Cell Carcinoma (ccRCC) or Papillary Renal Cell Carcinoma (PRCC) and to evaluate the independent predictive value of Fuhrman, WHO/ISUP and stereologically measured nuclear area combined with necrosis in a series of patients with ccRCC in relation to cancer-specific survival. In all, 124 cases of ccRCC and PRCC were included. All slides were blindly scored by two trained pathologists according to the Fuhrman and WHO/ISUP grading systems. Nuclear measurements were performed on digitally scanned slides in Visiopharm^® and correlated to survival. Analysis of ccRCC and PRCC cases showed that application of WHO/ISUP grading resulted in a significant downgrading of cases from G2 to G1, when comparing with Fuhrman grading. Neither of these patients experienced progression. Cancer specific survival estimates in 101 ccRCC patients showed that WHO/ISUP grading was slightly superior in predicting cancer-specific survival. Novel models included WHO/ISUP grading and mean nuclear area (MNA) each of which combined with necrosis. Both demonstrated an increased ability to predict cancer-specific survival. The study demonstrates that WHO/ISUP grading provides superior prognostic information compared to Fuhrman grading and stereologically measured nuclear area. Necrosis in combination with either WHO/ISUP grading or MNA adds additional prognostic information. Full article

Nuclear grade is important for treatment selection and prognosis in patients with clear cell renal cell carcinoma (ccRCC). This study aimed to determine the ability of preoperative four-phase multiphasic multidetector computed tomography (MDCT)-based radiomics features to predict the WHO/ISUP nuclear grade. In all 102 patients with histologically confirmed ccRCC, the training set (n = 62) and validation set (n = 40) were randomly assigned. In both datasets, patients were categorized according to the WHO/ISUP grading system into low-grade ccRCC (grades 1 and 2) and high-grade ccRCC (grades 3 and 4). The feature selection process consisted of three steps, including least absolute shrinkage and selection operator (LASSO) regression analysis, and the radiomics scores were developed using 48 radiomics features (10 in the unenhanced phase, 17 in the corticomedullary (CM) phase, 14 in the nephrographic (NP) phase, and 7 in the excretory phase). The radiomics score (Rad-Score) derived from the CM phase achieved the best predictive ability, with a sensitivity, specificity, and an area under the curve (AUC) of 90.91%, 95.00%, and 0.97 in the training set. In the validation set, the Rad-Score derived from the NP phase achieved the best predictive ability, with a sensitivity, specificity, and an AUC of 72.73%, 85.30%, and 0.84. We constructed a complex model, adding the radiomics score for each of the phases to the clinicoradiological characteristics, and found significantly better performance in the discrimination of the nuclear grades of ccRCCs in all MDCT phases. The highest AUC of 0.99 (95% CI, 0.92–1.00, p < 0.0001) was demonstrated for the CM phase. Our results showed that the MDCT radiomics features may play a role as potential imaging biomarkers to preoperatively predict the WHO/ISUP grade of ccRCCs. Full article