Scanner-based real-time 3D brain+body slice-to-volume reconstruction for T2-weighted 0.55T low field fetal MRI

Purpose: Integrating the SVRTK methods within the Gadgetron framework enables automated 3D fetal brain and body reconstruction in the low-field 0.55T MRI scanner within the duration of the scan. Methods: A deep-learning based, integrated, robust, and deployable workflow from several motion-corrupted individual T2-weighted single-shot Turbo Spin Echo stacks to produce super-resolved 3D reconstructed fetal brain and body is enabled by combining automated deformable and rigid Slice-to-Volume (D/SVR) reconstruction adapted for low field MRI with a real-time scanner-based Gadgetron workflow. Qualitative evaluation of the pipeline in terms of image quality and efficiency is performed in 12 prospectively acquired fetal datasets from the 22-40 weeks gestational age range. Results: The reconstructions were available on average 6:42+-3:13 minutes after the acquisition of the final stack and could be assessed and archived on the scanner console during the ongoing fetal MRI scan. The output image data quality was rated as good to acceptable for interpretation. The additional retrospective testing of the pipeline on 83 0.55T datasets demonstrated stable reconstruction quality for low-field MRI. Conclusion: The proposed pipeline allows scanner-based prospective motion correction for low-field fetal MRI. The main novel components of this work are the compilation of automated fetal and body D/SVR methods into one combined pipeline, the first application of 3D reconstruction methods to 0.55T T2-weighted data, and the online integration into the scanner environment. ### Competing Interest Statement Sarah McElroy - Siemens Healthineers ### Funding Statement This work was supported by the Wellcome Trust, Sir Henry Wellcome Fellowship to JH [201374/Z/16/Z], the UKRI FLF to JH [MR/T018119/1], DFG Heisenberg [502024488] the High Tech Agenda Bavaria to JH, the NIHR Advanced Fellowship to LS [NIHR3016640], the MRC grants [MR/W019469/1] and [MR/X010007/1], and the Wellcome/EPSRC Centre [WT203148/Z/16/Z]. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The fetal MRI data used in this study were acquired at St.Thomas' Hospital, London as part of the ethically approved MEERKAT [REC: 21/LO/0742], MiBirth [REC: 23/LO/0685] and NANO [REC: 22/YH/0210] studies. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The code for the proposed Gadgetron-based D/SVR scanner integration for 0.55T fetal MRI is publicly available at gadgetron-svrtk-integration SVRTK GitHub repository.