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Kidney tumor diffusion-weighted magnetic resonance imaging derived ADC histogram parameters combined with patient characteristics and tumor volume to discriminate oncocytoma from renal cell carcinoma

Authors :
Johan F. Langenhuijsen
Peter F.A. Mulders
Tim J. van Oostenbrugge
Ilse M. Spenkelink
Henry Rusinek
Louisa Bokacheva
Martin J. van Amerongen
Jurgen J. Fütterer
Source :
European Journal of Radiology, 145
Publication Year :
2021

Abstract

PURPOSE To assess the ability to discriminate oncocytoma from RCC based on a model using whole tumor ADC histogram parameters with additional use of tumor volume and patient characteristics. METHOD In this prospective study, 39 patients (mean age 65 years, range 28-79; 9/39 (23%) female) with 39 renal tumors (32/39 (82%) RCC and 7/39 (18%) oncocytoma) underwent multiparametric MRI between November 2014 and June 2018. Two regions of interest (ROIs) were drawn to cover both the entire tumor volume and a part of healthy renal cortex. ROI ADC maps were calculated using a mono-exponential model and ADC histogram distribution parameters were calculated. A logistic regression model was created using ADC histogram parameters, radiographic and patient characteristics that were significantly different between oncocytoma and RCC. A ROC curve of the model was constructed and the AUC, sensitivity and specificity were calculated. Furthermore, differences in intra-patient ADC histogram parameters between renal tumor and healthy cortex were calculated. A separate ROC curve was constructed to differentiate oncocytoma from RCC using statistically significant intra-patient parameter differences. RESULTS ADC standard deviation (p = 0.008), entropy (p = 0.010), tumor volume (p = 0.012), and patient sex (p = 0.018) were significantly different between RCC and oncocytoma. The regression model of these parameters combined had an ROC-AUC of 0.91 with a sensitivity of 86% and specificity of 84%. Intra-patient difference in ADC 25th percentile (p

Details

ISSN :
0720048X
Volume :
145
Database :
OpenAIRE
Journal :
European Journal of Radiology
Accession number :
edsair.doi.dedup.....a278ee3347e222869b64c9ca3cbd88ae