title: Quantitative cerebral perfusion using dynamic susceptibility contrast MRI: evaluation of reproducibility and age- and gender-dependence with fully automatic image postprocessing algorithm.
abstract: A novel approach for quantifying cerebral blood flow (CBF) is proposed that combines the bookend technique of calculating cerebral perfusion with an automatic postprocessing algorithm. The reproducibility of the quantitative CBF (qCBF) measurement in healthy controls (N = 8) showed a higher intraclass correlation coefficient (ICC) and lower coefficient of variation (COV) when calculated with automatic analysis (ICC/COV = 0.90/0.09) than when compared to conventional manual analysis (ICC/COV = 0.58/0.19). Also, the reproducibility in patients (N = 25) was successfully evaluated with the automatic analysis (ICC/COV = 0.81/0.14). In 175 consecutive clinical scans, we found 3.0% and 7.4% of qCBF decrease per decade in white matter (WM) (21.5 +/- 6.66 ml/100 g-min) and gray matter (GM) (49.6 +/- 16.2 ml/100 g-min), respectively. Cerebral blood volume (CBV) showed a significant 3.7% decrease per decade in GM (3.00 +/- 0.94 ml/100 g) but not in WM (1.69 +/- 0.40 ml/100 g). Mean transit time (MTT) increased by 1.9% and 3.8% per decade in WM (5.04 +/- 0.88 s) and GM (4.14 +/- 0.80 s), respectively. qCBF and MTT values between males (N = 85) and females (N = 90) were significantly different in GM. Women showed 11% higher qCBF as well as a higher decrease in qCBF with increasing age than men in the whole brain (WB). Our results supported the notion that population average empirical quantification of cerebral perfusion is subject to individual variation as well as age- and gender-dependent variability.
authors.affiliation: Department of Biomedical Engineering, Northwestern University, Evanston, Illinois, USA.
authors.forename: Wanyong
authors.initials: W
authors.lastname: Shin
authors.forename: Sandra
authors.initials: S
authors.lastname: Horowitz
authors.forename: Ann
authors.initials: A
authors.lastname: Ragin
authors.forename: Yufen
authors.initials: Y
authors.lastname: Chen
authors.forename: Matthew
authors.initials: M
authors.lastname: Walker
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Carroll
mesh_terms: D000328:Adult; D000367:Age Factors; D000465:Algorithms; D001185:Artificial Intelligence; D001783:Blood Flow Velocity / Q000502:physiology*; D002560:Cerebrovascular Circulation / Q000502:physiology*; D003287:Contrast Media; D005260:Female; D019786:Gadolinium DTPA; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012737:Sex Factors
chemical_list: D003287:Contrast Media; D019786:Gadolinium DTPA