TY - JOUR
T1 - Arterial spin-labeling magnetic resonance imaging of brain maturation in early childhood
T2 - Mathematical model fitting to assess age-dependent change of cerebral blood flow
AU - Wong, Alex Mun Ching
AU - Liu, Ho Ling
AU - Tsai, Ming Lun
AU - Schwartz, Erin Simon
AU - Yeh, Chih Hua
AU - Wang, Huei Shyong
AU - Wu, Tai Wei
AU - Lin, Chien Yuan
N1 - Publisher Copyright:
© 2019 Elsevier Inc.
PY - 2019/6
Y1 - 2019/6
N2 - Purpose: To determine the trajectory of age-dependent cerebral blood flow (CBF) change in infants and young children by fitting mathematical models to the imaging data. Methods: In this retrospective study, we reviewed the arterial spin-labeling imaging studies of 49 typically developing infants and young children at postmenstrual age (PMA) ranging from 38 to 194 weeks. All patients had normal structural MR imaging. Coregistration and gray matter segmentation were performed to extract whole-brain CBF values. Regional CBF values were obtained using manual region-of-interest placement. Curve estimation regression procedures with the corrected Akaike information criterion (AICc) were performed to determine the mathematical model best fitting the relationship between the CBF (whole-brain and regional measurements) and PMA of the patients. Results: Whole-brain CBF trajectory was best fitted by a cubic model (AICc = 215.95; R 2 = 0.566; P <.001). Whole-brain CBF at 1, 6, 12, and 24 months was estimated to be 36, 52, 58, and 55 mL/100 g/min, respectively. Regional CBF trajectory was also best fitted by a cubic model in the frontal (AICc = 233.63; R 2 = 0.442; P <.001), parietal (AICc = 229.18; R 2 = 0.614; P <.001), basal ganglion (AICc = 239.39; R 2 = 0.178; P =.043), temporal (AICc = 236.01; R 2 = 0.441; P <.001), and occipital (AICc = 236.46; R 2 = 0.475; P <.001) regions. Conclusions: In early childhood, the trajectory of CBF change was nonlinear and best fitted by the cubic model for the whole brain and all brain regions.
AB - Purpose: To determine the trajectory of age-dependent cerebral blood flow (CBF) change in infants and young children by fitting mathematical models to the imaging data. Methods: In this retrospective study, we reviewed the arterial spin-labeling imaging studies of 49 typically developing infants and young children at postmenstrual age (PMA) ranging from 38 to 194 weeks. All patients had normal structural MR imaging. Coregistration and gray matter segmentation were performed to extract whole-brain CBF values. Regional CBF values were obtained using manual region-of-interest placement. Curve estimation regression procedures with the corrected Akaike information criterion (AICc) were performed to determine the mathematical model best fitting the relationship between the CBF (whole-brain and regional measurements) and PMA of the patients. Results: Whole-brain CBF trajectory was best fitted by a cubic model (AICc = 215.95; R 2 = 0.566; P <.001). Whole-brain CBF at 1, 6, 12, and 24 months was estimated to be 36, 52, 58, and 55 mL/100 g/min, respectively. Regional CBF trajectory was also best fitted by a cubic model in the frontal (AICc = 233.63; R 2 = 0.442; P <.001), parietal (AICc = 229.18; R 2 = 0.614; P <.001), basal ganglion (AICc = 239.39; R 2 = 0.178; P =.043), temporal (AICc = 236.01; R 2 = 0.441; P <.001), and occipital (AICc = 236.46; R 2 = 0.475; P <.001) regions. Conclusions: In early childhood, the trajectory of CBF change was nonlinear and best fitted by the cubic model for the whole brain and all brain regions.
KW - Akaike information criterion
KW - Arterial spin-labeling imaging
KW - Cerebral blood flow
KW - Mathematical model fitting
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U2 - 10.1016/j.mri.2019.03.016
DO - 10.1016/j.mri.2019.03.016
M3 - Article
C2 - 30905764
AN - SCOPUS:85063401905
SN - 0730-725X
VL - 59
SP - 114
EP - 120
JO - Magnetic Resonance Imaging
JF - Magnetic Resonance Imaging
ER -