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Published on: January 22, 2013
Use of MRI in Differentiation of Papillary Renal Cell Carcinoma Subtypes: Qualitative and Quantitative Analysis
Ankur M Doshi1, Justin M Ream1, Andrea S Kierans2
11 Department of Radiology, Center for Biomedical Imaging, NYU School of Medicine, NYU Langone Medical Center, 660 First Ave, 3rd Fl, New York, NY 10016.
Objective:
The purpose of this study was to determine whether qualitative and quantitative MRI feature analysis is useful for differentiating type 1 from type 2 papillary renal cell carcinoma (PRCC).
Materials And Methods:
This retrospective study included 21 type 1 and 17 type 2 PRCCs evaluated with preoperative MRI. Two radiologists independently evaluated various qualitative features, including signal intensity, heterogeneity, and margin. For the quantitative analysis, a radiology fellow and a medical student independently drew 3D volumes of interest over the entire tumor on T2-weighted HASTE images, apparent diffusion coefficient parametric maps, and nephrographic phase contrast-enhanced MR images to derive first-order texture metrics. Qualitative and quantitative features were compared between the groups.
Results:
For both readers, qualitative features with greater frequency in type 2 PRCC included heterogeneous enhancement, indistinct margin, and T2 heterogeneity (all, p < 0.035). Indistinct margins and heterogeneous enhancement were independent predictors (AUC, 0.822). Quantitative analysis revealed that apparent diffusion coefficient, HASTE, and contrast-enhanced entropy were greater in type 2 PRCC (p < 0.05; AUC, 0.682-0.716). A combined quantitative and qualitative model had an AUC of 0.859. Qualitative features within the model had interreader concordance of 84-95%, and the quantitative data had intraclass coefficients of 0.873-0.961.
Conclusion:
Qualitative and quantitative features can help discriminate between type 1 and type 2 PRCC. Quantitative analysis may capture useful information that complements the qualitative appearance while benefiting from high interobserver agreement.
