MP78-12 UTILITY OF CAD DERIVED PEAK ENHANCEMENT IN DISCRIMINATING CLEAR CELL RENAL CELL CARCINOMA FUHRMAN GRADES I-IV AT FOUR-PHASE MDCT

Abstract

Listen

Translate article

You have accessJournal of UrologyKidney Cancer: Epidemiology & Evaluation/Staging II1 Apr 2016MP78-12 UTILITY OF CAD DERIVED PEAK ENHANCEMENT IN DISCRIMINATING CLEAR CELL RENAL CELL CARCINOMA FUHRMAN GRADES I-IV AT FOUR-PHASE MDCT Heidi Coy, Jonathan Young, Michael Douek, Pechin Lo, Matthew Brown, James Sayre, and Steven Raman Heidi CoyHeidi Coy More articles by this author , Jonathan YoungJonathan Young More articles by this author , Michael DouekMichael Douek More articles by this author , Pechin LoPechin Lo More articles by this author , Matthew BrownMatthew Brown More articles by this author , James SayreJames Sayre More articles by this author , and Steven RamanSteven Raman More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2016.02.1968AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Up to 70% of renal masses are found incidentally at imaging. Lesion characterization is typically assessed on biopsy and nephrectomy. A non-invasive method to assess tumor histology and grade at CT would be of great clinical value, especially in characterization of clear cell renal cell carcinoma (ccRCC) as this is the most common subtype and has the highest metastatic potential. In addition, patients with different Fuhrman tumor grades have a different prognosis and therapeutic pathway. The purpose of our study was to assess if peak enhancement derived from a CAD algorithm discriminates among Fuhrman Grades I-IV in ccRCC on four-phase CT. METHODS With IRB approval for this HIPAA-compliant retrospective study, our pathology and imaging databases were queried to obtain a cohort of ccRCC with preoperative multiphasic multidetector CT imaged with a four-phase renal mass protocol (unenhanced, corticomedullary (C), nephrographic (N), and excretory (E)). A whole lesion 3D contour was obtained in all phases with proprietary software. The CAD algorithm determined a 0.5cm diameter region of peak enhancement ≤300HU within the 3D lesion contour. All contours were confirmed by a radiologist. T-tests were used to compare peak multiphasic enhancement among Fuhrman grades I-IV. P values less than 0.05 were considered to be significant. ROC curves and AUCs were used to evaluate the utility of CAD derived peak HU. RESULTS 107 patients with 111 unique ccRCC lesions (16(14%) Fuhrman grade I, 64(58%) Fuhrman grade II, 23(21%) Fuhrman Grade III, 8(7%) Fuhrman grade IV) were analyzed. In the C phase we discriminated grade I from II (151 HU vs. 180 HU, p=0.0273), grade I from grade IV (151 HU vs. 201 HU, p=0.0038, AUC=0.852), and grade III from grade IV (172 HU vs. 201 HU, p=0.0371). In the N phase, we discriminated grade 1 from grade IV (135 HU vs 157 HU, p=0.0411. AUC=0.742) grade II from grade III (151 HU vs. 129 HU, p=0.0068), and grade III from grade IV (129 HU vs. 157 HU, p=0.0101). CONCLUSIONS CAD derived peak lesion attenuation has highest diagnostic performance in discriminating low grade from high grade ccRCC lesions in the corticomedullary phase. Discrimination of Fuhrman grades at imaging with an objective and reproducible measure of peak lesion attenuation from a CAD algorithm can aid the clinician in stratifying patients to the appropriate therapeutic pathway, and assist in determining which patients can undergo watchful waiting or which may be candidates for novel therapies and clinical trials. © 2016FiguresReferencesRelatedDetails Volume 195Issue 4SApril 2016Page: e1030-e1031 Advertisement Copyright & Permissions© 2016MetricsAuthor Information Heidi Coy More articles by this author Jonathan Young More articles by this author Michael Douek More articles by this author Pechin Lo More articles by this author Matthew Brown More articles by this author James Sayre More articles by this author Steven Raman More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...