You have accessJournal of UrologyKidney Cancer: Epidemiology & Evaluation/Staging/Surveillance III (MP61)1 Sep 2021MP61-03 A NEW METHOD FOR ASSESSING THE DEGREE OF CELLULAR ANAPLASIA IN KIDNEY CANCER BASED ON MORPHOMETRIC ANALYSIS OF 3D COMPUTER ASSISTED TOMOGRAPHY IMAGES Anastasia Shpikina, Alexandra Proskura, Dmitry Fiev, Evgeniy Sirota, Vasiliy Kozlov, Mikhail Chernenkiy, Kirill Puzakov, Alexander Tarasov, Camilla Azilgareeva, Andrey Vinarov, and Petr Glybochko Anastasia ShpikinaAnastasia Shpikina More articles by this author , Alexandra ProskuraAlexandra Proskura More articles by this author , Dmitry FievDmitry Fiev More articles by this author , Evgeniy SirotaEvgeniy Sirota More articles by this author , Vasiliy KozlovVasiliy Kozlov More articles by this author , Mikhail ChernenkiyMikhail Chernenkiy More articles by this author , Kirill PuzakovKirill Puzakov More articles by this author , Alexander TarasovAlexander Tarasov More articles by this author , Camilla AzilgareevaCamilla Azilgareeva More articles by this author , Andrey VinarovAndrey Vinarov More articles by this author , and Petr GlybochkoPetr Glybochko More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002101.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: We present the results of our retrospective analysis of the association between clinical variables and morphometric characteristics of kidney cancer with the grade of its histological structure differentiation. METHODS: The cellular anaplasia grade (G) of malignant tumors was determined in 231 cases: G1 - 77 cases (33.3%), G2 - 129 cases (55.8%), G3 - 24 cases (10.4%), G4 - in one case (0.4%). The study inclusion criteria were unilateral solid kidney neoplasms, age over 18 years. Exclusion criteria: bilateral and solitary kidney tumors, renal sinus, polyfocal and cystic kidney tumors. All patients underwent 3D modeling of the kidney tumor based on the contrast-enhanced CT of the kidneys. The clinical variables were age, gender, maximum neoplasm size. The morphometric parameters were the side of the tumor, tumor location on the kidney segments and surfaces, the tumor invasion depth, the shape of the renal parenchyma neoplasms. To assess the significance of kidney cancer predictors, we used multivariate and univariate logistic regression analysis. RESULTS: To assess the role of clinical variables and morphometric predictors in the G grade identification, all patients (n=231) were classified into two groups: group 1 (n=77) with G1; group 2 (n=154) with G2-G4. The multivariate analysis revealed a significant association between the G grade of renal tumors and the predominantly intraorgan tumor growth (p = 0.037). A high grade of tumor differentiation (G1) was associated with oval (p = 0.036) and spherical with a conical base (p = 0.018) renal neoplasms. The univariate analysis revealed a significant correlation between G and a spherical with a cone-shaped base kidney tumor only (p = 0.029). No statistically significant predictors were identified in the stepwise algorithm (p> 0.05). CONCLUSIONS: High kidney tumor grade (G3) in the multivariate analysis was associated with the predominantly interorgan tumor growth. While low kidney tumor grade (G1) was associated with oval and spherical with a conical base renal neoplasm and exophytic growth. The univariate analysis revealed correlation of G1 only with a spherical with a conical base renal tumor. The proposed algorithm can serve as an effective non-invasive tool for predicting kidney cancer G, the diagnostic value of which will improve with subsequent data collection and analysis. Source of Funding: None © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e1083-e1084 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Anastasia Shpikina More articles by this author Alexandra Proskura More articles by this author Dmitry Fiev More articles by this author Evgeniy Sirota More articles by this author Vasiliy Kozlov More articles by this author Mikhail Chernenkiy More articles by this author Kirill Puzakov More articles by this author Alexander Tarasov More articles by this author Camilla Azilgareeva More articles by this author Andrey Vinarov More articles by this author Petr Glybochko More articles by this author Expand All Advertisement Loading ...
Read full abstract