Geometric Reliability of Super-Resolution Reconstructed Images from Clinical Fetal MRI in the Second Trimester
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Published:2023-06-07
Issue:3
Volume:21
Page:549-563
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ISSN:1539-2791
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Container-title:Neuroinformatics
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language:en
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Short-container-title:Neuroinform
Author:
Ciceri Tommaso,Squarcina Letizia,Pigoni Alessandro,Ferro Adele,Montano Florian,Bertoldo Alessandra,Persico Nicola,Boito Simona,Triulzi Fabio Maria,Conte Giorgio,Brambilla Paolo,Peruzzo Denis
Abstract
AbstractFetal Magnetic Resonance Imaging (MRI) is an important noninvasive diagnostic tool to characterize the central nervous system (CNS) development, significantly contributing to pregnancy management. In clinical practice, fetal MRI of the brain includes the acquisition of fast anatomical sequences over different planes on which several biometric measurements are manually extracted. Recently, modern toolkits use the acquired two-dimensional (2D) images to reconstruct a Super-Resolution (SR) isotropic volume of the brain, enabling three-dimensional (3D) analysis of the fetal CNS.We analyzed 17 fetal MR exams performed in the second trimester, including orthogonal T2-weighted (T2w) Turbo Spin Echo (TSE) and balanced Fast Field Echo (b-FFE) sequences. For each subject and type of sequence, three distinct high-resolution volumes were reconstructed via NiftyMIC, MIALSRTK, and SVRTK toolkits. Fifteen biometric measurements were assessed both on the acquired 2D images and SR reconstructed volumes, and compared using Passing-Bablok regression, Bland-Altman plot analysis, and statistical tests.Results indicate that NiftyMIC and MIALSRTK provide reliable SR reconstructed volumes, suitable for biometric assessments. NiftyMIC also improves the operator intraclass correlation coefficient on the quantitative biometric measures with respect to the acquired 2D images. In addition, TSE sequences lead to more robust fetal brain reconstructions against intensity artifacts compared to b-FFE sequences, despite the latter exhibiting more defined anatomical details.Our findings strengthen the adoption of automatic toolkits for fetal brain reconstructions to perform biometry evaluations of fetal brain development over common clinical MR at an early pregnancy stage.
Funder
Università degli Studi di Milano
Publisher
Springer Science and Business Media LLC
Subject
Information Systems,General Neuroscience,Software
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