PURPOSE: The aim of the present study is to identify predictive imaging findings and construct a diagnostic model for differentiating renal cell carcinoma (RCC) with and without sarcomatoid dedifferentiation (sRCC and non-sRCC). METHODS: This study is a single-center retrospective study. All patients had magnetic resonance imaging (MRI) with gradient-echo T1-weighted images, single-shot T2-weighted images (T2WI), and enhanced nephrographic phase images. Forty pathologically confirmed sRCCs and 80 non-sRCCs were included in this study. Control cases were selected by matching the tumor diameter and the year of MRI. Two radiologists independently evaluated the following findings: growth pattern, presence of low-intensity area on T2WI in the tumor (T2LIA), presence of non-enhancing area, local tumor stage, and presence of regional lymphadenopathy. Two radiologists measured the diameter of the tumor, T2LIA, and the non-enhancing area. Multivariable logistic regression analysis was used to identify independent predictive factors for differentiating sRCC from non-sRCC. Selected variables were entered in the logistic regression model, and the area under the curve (AUC) was calculated for each reader with 95% confidence intervals (CIs). RESULTS: Larger T2LIA-to-tumor diameter ratio, regional lymphadenopathy, and local tumor stage 4 were associated with sRCC, and selected for the subsequent construction of a logistic regression model. With this model, the AUCs were 0.76 (95% CI, 0.66-0.85) and 0.70 (95% CI, 0.59-0.81) for prediction of sRCC. CONCLUSION: In conclusion, larger T2LIA-to-tumor diameter ratio, regional lymphadenopathy, and local tumor stage 4 are predictive findings of sRCC. As a result, the model constructed using these findings demonstrated a moderate degree of diagnostic accuracy.
PURPOSE: The aim of the present study is to identify predictive imaging findings and construct a diagnostic model for differentiating renal cell carcinoma (RCC) with and without sarcomatoid dedifferentiation (sRCC and non-sRCC). METHODS: This study is a single-center retrospective study. All patients had magnetic resonance imaging (MRI) with gradient-echo T1-weighted images, single-shot T2-weighted images (T2WI), and enhanced nephrographic phase images. Forty pathologically confirmed sRCCs and 80 non-sRCCs were included in this study. Control cases were selected by matching the tumor diameter and the year of MRI. Two radiologists independently evaluated the following findings: growth pattern, presence of low-intensity area on T2WI in the tumor (T2LIA), presence of non-enhancing area, local tumor stage, and presence of regional lymphadenopathy. Two radiologists measured the diameter of the tumor, T2LIA, and the non-enhancing area. Multivariable logistic regression analysis was used to identify independent predictive factors for differentiating sRCC from non-sRCC. Selected variables were entered in the logistic regression model, and the area under the curve (AUC) was calculated for each reader with 95% confidence intervals (CIs). RESULTS: Larger T2LIA-to-tumor diameter ratio, regional lymphadenopathy, and local tumor stage 4 were associated with sRCC, and selected for the subsequent construction of a logistic regression model. With this model, the AUCs were 0.76 (95% CI, 0.66-0.85) and 0.70 (95% CI, 0.59-0.81) for prediction of sRCC. CONCLUSION: In conclusion, larger T2LIA-to-tumor diameter ratio, regional lymphadenopathy, and local tumor stage 4 are predictive findings of sRCC. As a result, the model constructed using these findings demonstrated a moderate degree of diagnostic accuracy.
Authors: Cedric Lebacle; Aydin Pooli; Thomas Bessede; Jacques Irani; Allan J Pantuck; Alexandra Drakaki Journal: World J Urol Date: 2018-06-01 Impact factor: 4.226
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Authors: Jonathan R Young; Jocelyn A Young; Daniel J A Margolis; Steven Sauk; James Sayre; Allan J Pantuck; Steven S Raman Journal: Acad Radiol Date: 2017-05-18 Impact factor: 3.173
Authors: Brian I Rini; Thomas Powles; Michael B Atkins; Bernard Escudier; David F McDermott; Cristina Suarez; Sergio Bracarda; Walter M Stadler; Frede Donskov; Jae Lyun Lee; Robert Hawkins; Alain Ravaud; Boris Alekseev; Michael Staehler; Motohide Uemura; Ugo De Giorgi; Begoña Mellado; Camillo Porta; Bohuslav Melichar; Howard Gurney; Jens Bedke; Toni K Choueiri; Francis Parnis; Tarik Khaznadar; Alpa Thobhani; Shi Li; Elisabeth Piault-Louis; Gretchen Frantz; Mahrukh Huseni; Christina Schiff; Marjorie C Green; Robert J Motzer Journal: Lancet Date: 2019-05-09 Impact factor: 79.321
Authors: Paul L Crispen; Rodney H Breau; Cristine Allmer; Christine M Lohse; John C Cheville; Bradley C Leibovich; Michael L Blute Journal: Eur Urol Date: 2010-09-15 Impact factor: 20.096