Use of MRI in Differentiation of Papillary Renal Cell Carcinoma Subtypes: Qualitative and Quantitative Analysis

被引:37
作者
Doshi, Ankur M. [1 ]
Ream, Justin M. [1 ]
Kierans, Andrea S. [2 ]
Bilbily, Matthew [1 ]
Rusinek, Henry [1 ]
Huang, William C. [3 ]
Chandarana, Hersh [1 ]
机构
[1] NYU, Sch Med, Langone Med Ctr, Dept Radiol,Ctr Biomed Imaging, 660 First Ave,3rd Fl, New York, NY 10016 USA
[2] New York Presbyterian Hosp, Dept Radiol, Weill Cornell Med Ctr, New York, NY USA
[3] NYU, Div Urol Oncol, Langone Med Ctr, Dept Urol, New York, NY USA
关键词
papillary renal cell carcinoma; texture; CT TEXTURE ANALYSIS; TUMOR HETEROGENEITY; POTENTIAL MARKER; SURVIVAL; CLASSIFICATION; PATHOLOGY; TYPE-1; MASSES; STAGE;
D O I
10.2214/AJR.15.15004
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
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.
引用
收藏
页码:566 / 572
页数:7
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