Impact of Renal Cell Carcinoma Histological Variants on Recurrence After Partial Nephrectomy: A Multi-Institutional, Prospective Study (UROCCR Study 82)

Tabourin, Thomas; Pinar, Ugo; Parra, J.; Vaessen, Christophe; Bensalah, Charles-Karim; Audenet, François; Bigot, Pierre; Champy, C.; Olivier, Jonathan; Bruyère, F.; Doumerc, N.; Paparel, P.; Parier, Bastien; Nouhaud, François-Xavier; Durand, Xavier; Lang, Hervé; Branger, Nicolas; Long, Jean-Alexandre; Durand, Matthieu; Waeckel, Thibaut; Charles, T.; Cussenot, Olivier; Xylinas, Évanguelos; Boissier, Romain; Tambwe, R.; Patard, Jean‐Jacques; Bernhard, Jean‐Christophe; Rouprêt, Morgan

doi:10.1245/s10434-022-12052-8

Cited by 2 publications

(2 citation statements)

References 32 publications

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“…Fuhrman grade is an important pathological risk factor impacting on patients’ oncological outcomes, especially the risk of recurrence. 80 Indeed, despite this information might be achieved through renal mass biopsy, this procedure is invasive and not devoid of complications and suffers from several limitations. 17 , 81 Therefore, being able to preoperatively predict a renal mass nuclear grade differentiation, directly by imaging, could be of outmost importance to address the patient to the best treatment.…”

Section: Resultsmentioning

confidence: 99%

Artificial intelligence and radiomics in evaluation of kidney lesions: a comprehensive literature review

Russo

Crocetto

Barone

et al. 2023

Therapeutic Advances in Urology

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Radiomics and artificial intelligence (AI) may increase the differentiation of benign from malignant kidney lesions, differentiation of angiomyolipoma (AML) from renal cell carcinoma (RCC), differentiation of oncocytoma from RCC, differentiation of different subtypes of RCC, to predict Fuhrman grade, to predict gene mutation through molecular biomarkers and to predict treatment response in metastatic RCC undergoing immunotherapy. Neural networks analyze imaging data. Statistical, geometrical, textural features derived are giving quantitative data of contour, internal heterogeneity and gray zone features of lesions. A comprehensive literature review was performed, until July 2022. Studies investigating the diagnostic value of radiomics in differentiation of renal lesions, grade prediction, gene alterations, molecular biomarkers and ongoing clinical trials have been analyzed. The application of AI and radiomics could lead to improved sensitivity, specificity, accuracy in detecting and differentiating between renal lesions. Standardization of scanner protocols will improve preoperative differentiation between benign, low-risk cancers and clinically significant renal cancers and holds the premises to enhance the diagnostic ability of imaging tools to characterize renal lesions.

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Section: Resultsmentioning

confidence: 99%

Artificial intelligence and radiomics in evaluation of kidney lesions: a comprehensive literature review

Russo

Crocetto

Barone

et al. 2023

Therapeutic Advances in Urology

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“…Yu et al [ 8 ] found that the prognosis of patients with low-grade RCC is relatively better than that of high-grade patients, the safety of partial nephrectomy is higher, and the incidence of postoperative complications is lower. Tabourin et al [ 9 ] reported that Fuhrman grade > 2 is one of the important risk factors for postoperative recurrence of RCC. However, Fuhrman grade can only be determined by postoperative pathology examination, and it is still challenging to obtain them timely and effectively before surgical treatment of RCC.…”

Section: Introductionmentioning

confidence: 99%

Characterization of renal artery variation in patients with clear cell renal cell carcinoma and the predictive value of accessory renal artery in pathological grading of renal cell carcinoma: a retrospective and observational study

Zhou

Cui

et al. 2023

BMC Cancer

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Objective To explore the characteristics of renal artery variation in patients with renal cell carcinoma and to evaluate the predicting value of accessory renal artery in the pathological grading of renal cell carcinoma. Methods The clinicopathological data of patients with clear cell renal cell carcinoma diagnosed in the Department of Urology of the First Hospital of Shanxi Medical University from September 2019 to March 2023 were retrospectively analyzed. All patients underwent visual three-dimensional model reconstruction from computed tomography images. All kidneys were divided into two groups: the affected kidney and the healthy kidney, and the incidence of renal artery variation in the two groups was analyzed. Then, according to the existence of accessory renal artery in the affected kidney, the patients were divided into two groups, and the relationship between accessory renal artery and clinicopathological features of patients with clear cell renal cell carcinoma was analyzed. Finally, univariate and multivariate logistic regression analyses were performed to determine the predictors of Fuhrman grading of clear cell renal cell carcinoma, and the predictive ability of the model was evaluated by the receiver operating characteristic curve. Results The incidence of renal artery variation and accessory renal artery in the affected kidney was significantly higher than them in the healthy kidney. The patients with accessory renal artery in the affected kidney had larger tumor maximum diameter, higher Fuhrman grade and more exophytic growth. The presence of accessory renal artery on the affected kidney and the maximum diameter of tumor are independent predictors of high-grade renal cell carcinoma. The receiver operating characteristic curve suggests that the model has a good predictive ability. Conclusion The existence of accessory renal artery on the affected kidney may be related to the occurrence and development of clear cell renal cell carcinoma, and can better predict Fuhrman grade of clear cell renal cell carcinoma. The finding provides a reference for the future diagnostic evaluation of RCC, and provides a new direction for the study of the pathogenesis of RCC.

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Impact of Renal Cell Carcinoma Histological Variants on Recurrence After Partial Nephrectomy: A Multi-Institutional, Prospective Study (UROCCR Study 82)

Cited by 2 publications

References 32 publications

Artificial intelligence and radiomics in evaluation of kidney lesions: a comprehensive literature review

Artificial intelligence and radiomics in evaluation of kidney lesions: a comprehensive literature review

Characterization of renal artery variation in patients with clear cell renal cell carcinoma and the predictive value of accessory renal artery in pathological grading of renal cell carcinoma: a retrospective and observational study

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