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Improving Reproducibility of Prenatal Diffusion-Weighted Magnetic Resonance Imaging Biomarker to Detect Hypoxic-Ischemic Brain Injury in Rabbit Fetus

Carolann Walkuski, Justin Jeong-Won Jeong, Wayne State University, 42 W Warren Ave 48202

Cerebral palsy remains the leading motor disability among young children. Hypoxia-ischemia (H-I) in the prenatal period is a cause of cerebral palsy, suggesting an urgent need of non-invasive biomarker for early brain injury in the prenatal period. Our NIH-funded study using diffusion-weighted imaging (DWI) of rabbit dam suggests that average apparent diffusion coefficient (ADC) of 2-D cross-sectional region of interest (ROI) in fetal brain can be an excellent biomarker to predict motor deficits after birth. We have not been satisfied with the subjective evaluation of the mean value of ADC, which varies depending on the location and size of the selected 2-D ROI. This study investigates if the second order statistics: kurtosis and skewness of ADC value obtained from a 3-D ROI covering whole-brain can improve the reproducibility for detection of brain injury in the rabbit fetus affected by uterine ischemia. A rabbit dam (25 days gestation with 8 fetuses) underwent a series of 2 minutes DWI scans for 60 minutes while receiving a 40-minute-uterine H­I insult in the middle of DWI acquisition. Both 2-D contour ROI and 3-D sphere ROI (0.5 mm radius) were manually demarcated by two raters on each ADC map to assess the H-I related fetal brain injury. Finally, intra-class correlation coefficient (ICC) of two raters was evaluated from three measures of ADC time series, 1) Mean of 2-D ROI, 2) Kurtosis of 3-D ROI and 3) skewness of 3-D ROI. We found that both kurtosis and skewness provide better reproducibility than mean (ICC of kurtosis/skewness/mean = 0.92/0.91/0.74), suggesting that the high order statistics provide more consistent detection of the spatially uneven ADC abnormality-evaluation across raters. Further investigation with a large cohort should warrant that the proposed 3-D ROI analysis can accurately predict behavioral outcomes after birth. 




Additional Abstract Information

Presenter: Carolann Walkuski

Institution: Wayne State University

Type: Poster

Subject: Nursing & Public Health

Status: Approved


Time and Location

Session: Poster 9
Date/Time: Wed 12:00pm-1:00pm
Session Number: 6032