Automating quantitative measures of an established conventional MRI scoring system for preterm-born infants scanned between 29 to 47 weeks' postmenstrual age.

van Eijk, Liza, Seidel, M., Pannek, K., George, J.M., Fiori, S., Guzzetta, A., Coulthard, A., Bursle, J., Ware, R.S., Bradford, D., Rose, S., Colditz, P.B., Boyd, R.N., and Fripp, J. (2021) Automating quantitative measures of an established conventional MRI scoring system for preterm-born infants scanned between 29 to 47 weeks' postmenstrual age. American Journal of Neuroradiology. (In Press)

Full text not available from this repository


Abstract

Background and Purpose: Conventional MRI scoring is a valuable tool for risk stratification and prognostication of outcomes, but manual scoring is time-consuming, operator-dependent, and requires high-level expertise. This study aims to automate the regional measurements of an established brain MRI scoring system for preterm neonates scanned between 29-47 weeks post-menstrual age (PMA). Materials and Methods: This study used T2WI from the longitudinal Prediction of PREterm Motor Outcomes cohort study (PPREMO) and developing Human Connectome Project. Measures of biparietal width, interhemispheric distance, callosal thickness, transcerebellar diameter, lateral ventricular diameter, and deep grey matter area were extracted manually (PPREMO only) and automatically. Scans with poor quality, failure of automated analysis, or severe pathology were excluded. Agreement, reliability, and associations between manual and automated measures were assessed, and compared against statistics for manual measures. Associations between measures with PMA, gestational age at birth (GA), and birth weight were examined (Pearson’s correlation) in both cohorts. Results: 652 MRIs (86%) were suitable for analysis. Automated measures showed good to excellent agreement and good reliability with manual measures, except for interhemispheric distance at early MRI (scanned between 29-35 weeks PMA; in line with poor manual reliability) and callosal thickness measures. All measures were positively associated with PMA (r=0.11-0.94; R2=0.01-0.89). Negative and positive associations were found with GA (r=-0.26-0.71; R2=0.05-0.52), and birth weight (r=-0.25-0.75; R2=0.06-0.56). Automated measures were successfully extracted for 80-99% of suitable scans. Conclusion: Measures of brain injury and impaired brain growth can be automatically extracted from neonatal MRI, which could assist with clinical reporting.

Item ID: 68921
Item Type: Article (Research - C1)
Keywords: Brain, MR, Pediatrics, neonatal imaging
Date Deposited: 11 Aug 2021 01:41
FoR Codes: 32 BIOMEDICAL AND CLINICAL SCIENCES > 3209 Neurosciences > 320999 Neurosciences not elsewhere classified @ 80%
32 BIOMEDICAL AND CLINICAL SCIENCES > 3213 Paediatrics > 321303 Neonatology @ 20%
SEO Codes: 20 HEALTH > 2099 Other health > 209999 Other health not elsewhere classified @ 100%
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page