Multiparametric MR Images for Detection of Aggressive Prostate Cancer in the Peripheral Zone: A Multiple Imager Study

被引:59
作者
Au Hoang Dinh [1 ]
Melodelima, Christelle [2 ,3 ]
Souchon, Remi [1 ]
Lehaire, Jerome [1 ]
Bratan, Flavie [1 ,4 ,7 ]
Mege-Lechevallier, Florence [5 ]
Ruffion, Alain [8 ]
Crouzet, Sebastien [1 ,6 ,7 ]
Colombel, Marc [6 ,7 ]
Rouviere, Olivier [1 ,4 ,7 ]
机构
[1] INSERM, U1032, LabTau, F-69008 Lyon, France
[2] CNRS, UMR 5553, BP 53, Grenoble, France
[3] Univ Grenoble 1, Lab Ecol Alpine, Grenoble, France
[4] Hop Edouard Herriot, Hosp Civils Lyon, Dept Urinary & Vasc Imaging, Pavillon P Radio,5 Pl Arsonval, F-69003 Lyon, France
[5] Hop Edouard Herriot, Hosp Civils Lyon, Dept Pathol, Pavillon P Radio,5 Pl Arsonval, F-69003 Lyon, France
[6] Hop Edouard Herriot, Hosp Civils Lyon, Dept Urol, Pavillon P Radio,5 Pl Arsonval, F-69003 Lyon, France
[7] Univ Lyon 1, Fac Med Lyon Est, F-69365 Lyon, France
[8] Ctr Hosp Lyon Sud, Hosp Civils Lyon, Dept Urol, Pierre Benite, France
关键词
APPARENT DIFFUSION-COEFFICIENT; CONTRAST-ENHANCED MRI; WASH-IN RATE; GLEASON SCORE; ACTIVE SURVEILLANCE; HISTOGRAM ANALYSIS; T; GRADE; TISSUE; BENIGN;
D O I
10.1148/radiol.2016151406
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
Purpose: To assess the intermanufacturer variability of quantitative models in discriminating cancers with a Gleason score of at least 7 among peripheral zone (PZ) lesions seen at 3-T multiparametric magnetic resonance (MR) imaging. Materials and Methods: An institutional review board-approved prospective database of 257 patients who gave written consent and underwent T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced imaging before prostatectomy was retrospectively reviewed. It contained outlined lesions found to be suspicious for malignancy by two independent radiologists and classified as malignant or benign after correlation with prostatectomy whole-mount specimens. One hundred six patients who underwent imaging with 3-T MR systems from two manufacturers were selected (data set A, n = 72; data set B, n = 34). Eleven parameters were calculated in PZ lesions: normalized T2-weighted signal intensity, skewness and kurtosis of T2-weighted signal intensity, T2 value, wash-in rate, washout rate, time to peak (TTP), mean apparent diffusion coefficient (ADC), 10th percentile of the ADC, and skewness and kurtosis of the histogram of the ADC values. Parameters were selected on the basis of their specificity for a sensitivity of 0.95 in diagnosing cancers with a Gleason score of at least 7, and the area under the receiver operating characteristic curve (AUC) for the models was calculated. Results: The model of the 10th percentile of the ADC with TTP yielded the highest AUC in both data sets. In data set A, the AUC was 0.90 (95% confidence interval [CI]: 0.85, 0.95) or 0.89 (95% CI: 0.82, 0.94) when it was trained in data set A or B, respectively. In data set B, the AUC was 0.84 (95% CI: 0.74, 0.94) or 0.86 (95% CI: 0.76, 0.95) when it was trained in data set A or B, respectively. No third variable added significantly independent information in any data set. Conclusion: The model of the 10th percentile of the ADC with TTP yielded accurate results in discriminating cancers with a Gleason score of at least 7 among PZ lesions at 3 T in data from two manufacturers. (C) RSNA, 2016
引用
收藏
页码:117 / 127
页数:11
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