Real‐time fetal brain tracking for functional fetal MRI

Author:

Neves Silva Sara12ORCID,Aviles Verdera Jordina12ORCID,Tomi‐Tricot Raphael123,Neji Radhouene23,Uus Alena12,Grigorescu Irina12,Wilkinson Thomas12ORCID,Ozenne Valery4,Lewin Alexander56,Story Lisa17,De Vita Enrico28,Rutherford Mary12,Pushparajah Kuberan2,Hajnal Jo12,Hutter Jana12ORCID

Affiliation:

1. Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences King's College London London UK

2. Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences King's College London London UK

3. MR Research Collaborations Siemens Healthcare Limited Camberley UK

4. CNRS, CRMSB, UMR 5536, IHU Liryc Université de Bordeaux Bordeaux France

5. Institute of Neuroscience and Medicine 11, INM‐11 Forschungszentrum Jülich Jülich Germany

6. RWTH Aachen University Aachen Germany

7. Department of Women & Children's Health King's College London London UK

8. MRI Physics Group Great Ormond Street Hospital London UK

Abstract

AbstractPurposeTo improve motion robustness of functional fetal MRI scans by developing an intrinsic real‐time motion correction method. MRI provides an ideal tool to characterize fetal brain development and growth. It is, however, a relatively slow imaging technique and therefore extremely susceptible to subject motion, particularly in functional MRI experiments acquiring multiple Echo‐Planar‐Imaging‐based repetitions, for example, diffusion MRI or blood‐oxygen‐level‐dependency MRI.MethodsA 3D UNet was trained on 125 fetal datasets to track the fetal brain position in each repetition of the scan in real time. This tracking, inserted into a Gadgetron pipeline on a clinical scanner, allows updating the position of the field of view in a modified echo‐planar imaging sequence. The method was evaluated in real‐time in controlled‐motion phantom experiments and ten fetal MR studies (17 + 4‐34 + 3 gestational weeks) at 3T. The localization network was additionally tested retrospectively on 29 low‐field (0.55T) datasets.ResultsOur method achieved real‐time fetal head tracking and prospective correction of the acquisition geometry. Localization performance achieved Dice scores of 84.4% and 82.3%, respectively for both the unseen 1.5T/3T and 0.55T fetal data, with values higher for cephalic fetuses and increasing with gestational age.ConclusionsOur technique was able to follow the fetal brain even for fetuses under 18 weeks GA in real‐time at 3T and was successfully applied “offline” to new cohorts on 0.55T. Next, it will be deployed to other modalities such as fetal diffusion MRI and to cohorts of pregnant participants diagnosed with pregnancy complications, for example, pre‐eclampsia and congenital heart disease.

Funder

Health Services and Delivery Research Programme

UK Research and Innovation

Wellcome Trust

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging

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