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Quantitative multiparametric MRI of ovarian cancer
Author(s) -
Carter Jori S.,
Koopmeiners Joseph S.,
KuehnHajder Jessica E.,
Metzger Gregory J.,
Lakkadi Navneeth,
Downs Levi S.,
Bolan Patrick J.
Publication year - 2013
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.24119
Subject(s) - kurtosis , magnetic resonance imaging , medicine , effective diffusion coefficient , nuclear medicine , standard deviation , malignancy , skewness , logistic regression , radiology , mathematics , pathology , statistics
Purpose To identify parameters associated with ovarian malignancy using multiparametric quantitative magnetic resonance imaging (MRI). Materials and Methods After Institutional Review Board (IRB) approval, women with ovarian masses underwent preoperative imaging with 3 T MRI. Dynamic contrast‐enhanced (DCE)‐MRI with pharmacokinetic modeling, quantitative T 2 mapping, and diffusion‐weighted imaging with quantitative mapping of the water diffusion parameters were performed. Ovarian masses had one or more discreet regions of interest, categorized as cystic or solid, and histologically diagnosed as benign or malignant. Mean region of interest (ROI) values were compared between benign and malignant masses using generalized estimating equations. In addition, we compared classification accuracy for the mean ROI value to a combination of histogram characteristics (standard deviation, skewness, and kurtosis) from T 2 map ROIs using logistic regression and ROC curve. The significance level was P = 0.05. Results Several DCE‐MRI parameters differentiated solid benign from malignant masses. Toft's rate constant (k ep ) was significantly higher in malignant masses ( P < 0.001), as well as quantitative T 2 values ( P = 0.003), and signal intensity on T 2 weighted imaging ( P = 0.008). A linear combination of the mean, standard deviation, skewness, and kurtosis of T 2 within solid regions (area under the curve [AUC] 0.90) provided better classification accuracy than the mean of T 2 alone (AUC 0.81). Conclusion Quantitative parameters from DCE‐MRI and T 2 mapping can differentiate benign from malignant ovarian masses. J. Magn. Reson. Imaging 2013;38:1501–1509. © 2013 Wiley Periodicals, Inc.