An automated pipeline for quantitative T2* fetal body MRI and segmentation at low field.
Fetal MRI
Low field
T2*
Journal
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Titre abrégé: Med Image Comput Comput Assist Interv
Pays: Germany
ID NLM: 101249582
Informations de publication
Date de publication:
2023
2023
Historique:
medline:
1
1
2023
pubmed:
1
1
2023
entrez:
15
10
2024
Statut:
ppublish
Résumé
Fetal Magnetic Resonance Imaging at low field strengths is emerging as an exciting direction in perinatal health. Clinical low field (0.55T) scanners are beneficial for fetal imaging due to their reduced susceptibility-induced artefacts, increased T2* values, and wider bore (widening access for the increasingly obese pregnant population). However, the lack of standard automated image processing tools such as segmentation and reconstruction hampers wider clinical use. In this study, we introduce a semi-automatic pipeline using quantitative MRI for the fetal body at low field strength resulting in fast and detailed quantitative T2* relaxometry analysis of all major fetal body organs. Multi-echo dynamic sequences of the fetal body were acquired and reconstructed into a single high-resolution volume using deformable slice-to-volume reconstruction, generating both structural and quantitative T2* 3D volumes. A neural network trained using a semi-supervised approach was created to automatically segment these fetal body 3D volumes into ten different organs (resulting in dice values > 0.74 for 8 out of 10 organs). The T2* values revealed a strong relationship with GA in the lungs, liver, and kidney parenchyma (R
Identifiants
pubmed: 39404664
doi: 10.1007/978-3-031-43990-2_34
pmc: PMC7616578
doi:
Types de publication
Journal Article
Langues
eng