Pediatric Head CT: Automated Quantitative Analysis with Quantile Regression.

Autor: Cauley KA; From the Departments of Radiology (K.A.C.) keithcauley@hotmail.com., Hu Y; Biomedical and Translational Informatics (Y.H.), Geisinger Medical Center, Danville, Pennsylvania., Fielden SW; Geisinger Autism and Developmental Medicine Institute (S.W.F.), Lewisburg, Pennsylvania.
Jazyk: angličtina
Zdroj: AJNR. American journal of neuroradiology [AJNR Am J Neuroradiol] 2021 Jan; Vol. 42 (2), pp. 382-388. Date of Electronic Publication: 2020 Dec 10.
DOI: 10.3174/ajnr.A6885
Abstrakt: Background and Purpose: Together with quantile regression methods, such a model would have the potential for clinical utility through automated quantitative comparison of individual cases relative to their age and gender-matched peer group. Our aim was to demonstrate the automated processing of digital clinical head CT data in the development of a clinically useful model of age-related changes of the brain in the first 2 decades of life.
Materials and Methods: A total of 415 (209 female) consecutive, clinical head CTs with radiographically normal findings from patients from birth through 20 years of age were retrospectively selected and subjected to automated segmentation. Brain volume, brain parenchymal fraction, brain radiodensity, and brain radiomass were assessed as a function of patient age. Statistical modeling and quantile regression were performed.
Results: Brain volume increased from 400 cm 3 at birth to 1350 cm 3 at 20 years of age (>3-fold). Males had a slightly steeper growth trajectory than females, with approximately 8% difference in volume between the sexes established in the first few years of life. Brain parenchymal fraction was variable at younger than 2 years of age, stabilizing between 0.85 and 0.92 at 2-3 years of age. Brain mean radiodensity was lower at birth (24 HU) and increased through 3 years of age, after which it stabilized near 30 HU, an approximately 25% increase. The product of brain volume and mean brain radiodensity (radiomass), increased from 700 HU × mL at birth to 3900 HU × mL, a 5.6-fold increase, with approximately 5% difference between males and females at 20 years. Quantile regression enables a given metric to be interpreted relative to an age- and sex-matched peer group.
Conclusions: Automated segmentation of clinical head CT images permitted the generation of a reference database for quantitative analysis of pediatric and adolescent brains. Quantile regression facilitates clinical application.
(© 2021 by American Journal of Neuroradiology.)
Databáze: MEDLINE