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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Biomimetic phantom with anatomical accuracy for evaluating brain volumetric measurements with magnetic resonance imaging

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Author(s):
Azimbagirad, Mehran [1, 2] ; Grillo, Felipe Wilker [2] ; Hadadian, Yaser [2] ; Oliveira Carneiro, Antonio Adilton [2] ; Murta Jr, Luiz Otavio
Total Authors: 5
Affiliation:
[1] Univ Western Brittany, Fac Med & Hlth Sci, Brest - France
[2] Univ Sao Paulo, Fac Philosophy Sci & Languages, Dept Phys, Ribeirao Preto, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: JOURNAL OF MEDICAL IMAGING; v. 8, n. 1 JAN 2021.
Web of Science Citations: 0
Abstract

Purpose: Brain image volumetric measurements (BVM) methods have been used to quantify brain tissue volumes using magnetic resonance imaging (MRI) when investigating abnormalities. Although BVM methods are widely used, they need to be evaluated to quantify their reliability. Currently, the gold-standard reference to evaluate a BVM is usually manual labeling measurement. Manual volume labeling is a time-consuming and expensive task, but the confidence level ascribed to this method is not absolute. We describe and evaluate a biomimetic brain phantom as an alternative for the manual validation of BVM. Methods: We printed a three-dimensional (3D) brain mold using an MRI of a three-year-old boy diagnosed with Sturge-Weber syndrome. Then we prepared three different mixtures of styreneethylene/butylene-styrene gel and paraffin to mimic white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). The mold was filled by these three mixtures with known volumes. We scanned the brain phantom using two MRI scanners, 1.5 and 3.0 Tesla. Our suggestion is a new challenging model to evaluate the BVM which includes the measured volumes of the phantom compartments and its MRI. We investigated the performance of an automatic BVM, i.e., the expectation-maximization (EM) method, to estimate its accuracy in BVM. Results: The automatic BVM results using the EM method showed a relative error (regarding the phantom volume) of 0.08, 0.03, and 0.13 (+/- 0.03 uncertainty) percentages of the GM, CSF, and WM volume, respectively, which was in good agreement with the results reported using manual segmentation. Conclusions: The phantom can be a potential quantifier for a wide range of segmentation methods. (C) 2021 Society of Photo-Optical Instrumentation Engineers (SPIE) (AU)