Abstract

Abstract

Cortical injury on the surface of the brain in children with hypoxic ischemic injury (HII) can be difficult to demonstrate to non-radiologists and lay people using brain images alone. Three-dimensional (3D) printing is helpful to communicate the volume loss and pathology due to HII in children’s brains. 3D printed models represent the brain to scale and can be held up against models of normal brains for appreciation of volume loss. If 3D printed brains are to be used for formal communication, e.g., with medical colleagues or in court, they should have high fidelity of reproduction of the actual size of patients’ brains. Here, we evaluate the size fidelity of 3D printed models from MRI scans of the brain, in children with prior HII. Twelve 3D prints of the brain were created from MRI scans of children with HII and selected to represent a variety of cortical pathologies. Specific predetermined measures of the 3D prints were made and compared to measures in matched planes on MRI. Fronto-occipital length (FOL) and bi-temporal/bi-parietal diameters (BTD/BPD) demonstrated high interclass correlations (ICC). Correlations were moderate to weak for hemispheric height, temporal height, and pons-cerebellar thickness. The average standard error of measurement (SEM) was 0.48 cm. Our results demonstrate high correlations in overall measurements of each 3D printed model derived from brain MRI scans versus the original MRI, evidenced by high ICC values for FOL and BTD/BPD. Measures with low correlation values can be explained by variability in matching the plane of measurement to the MRI slice orientation.

Details

Title
Fidelity of 3D Printed Brains from MRI Scan in Children with Pathology (Prior Hypoxic Ischemic Injury)
Author
Chacko, Anith 1   VIAFID ORCID Logo  ; Rungsiprakarn, Phassawan 2 ; Erlic, Ivan 3 ; Thai, Ngoc Jade 1 ; Andronikou, Savvas 4 

 University of Bristol, School of Clinical Sciences, Faculty of Medicine, Bristol, UK (GRID:grid.5337.2) (ISNI:0000 0004 1936 7603) 
 Children’s Hospital of Philadelphia, Department of Radiology, Philadelphia, USA (GRID:grid.239552.a) (ISNI:0000 0001 0680 8770) 
 University College London, Undergraduate in the Department of Mathematics, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201) 
 Children’s Hospital of Philadelphia, Department of Radiology, Philadelphia, USA (GRID:grid.239552.a) (ISNI:0000 0001 0680 8770); University of Pennsylvania, Department of Radiology, Perelman School of Medicine, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972) 
Pages
17-28
Publication year
2023
Publication date
Feb 2023
Publisher
Springer Nature B.V.
ISSN
08971889
e-ISSN
1618727X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2781922465
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.