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Perfusion fraction of diffusion‐weighted MRI for predicting the presence of blood supply in ovarian masses
Author(s) -
Morita Satoru,
Kojima Shinya,
Hirata Masami,
Suzuki Kazufumi,
Ueno Eiko
Publication year - 2011
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.22695
Subject(s) - medicine , nuclear medicine , receiver operating characteristic , magnetic resonance imaging , perfusion , gadolinium , effective diffusion coefficient , diffusion mri , area under the curve , contrast (vision) , radiology , chemistry , physics , organic chemistry , optics
Purpose: To evaluate whether perfusion fraction (PF) calculated with diffusion‐weighted magnetic resonance imaging (MRI) predicts the presence of blood supply in ovarian masses. Materials and Methods: PFs of 92 ovarian lesions in 53 patients administered gadolinium were retrospectively calculated with diffusion‐weighted images at b‐values of 0, 500, and 1000 sec/mm 2 . PFs were compared between ovarian lesions, except for fat, with ( n = 21) or without contrast enhancement ( n = 57), using Student's t ‐test and receiver operating characteristics (ROC) curve analysis. Lesion enhancement rates of contrast‐enhanced images at 30 and 180 seconds after gadolinium injection (ER 30sec and ER 180sec ) and PFs were compared using Pearson's correlation coefficient. Results: PFs of the lesions with contrast enhancement were significantly higher than those without contrast enhancement (0.22 ± 0.09 and 0.02 ± 0.08, respectively, P < 0.0001). The ROC curve identified the best cutoff point for PF at 0.135 (95.2% sensitivity and 94.7% specificity) as a predictor of the contrast enhancement effect. The area under the ROC curve was 0.984. PF correlated moderately with ER 30sec (0.62, y = 0.13x + 0.04, P < 0.0001) and ER 180sec (0.74, y = 0.13x + 0.03, P < 0.0001). Conclusion: PF calculated with diffusion‐weighted images can potentially predict blood supply in ovarian masses. J. Magn. Reson. Imaging 2011. © 2011 Wiley Periodicals, Inc.