Accelerating 3D MTC-BOOST in patients with congenital heart disease using a joint multi-scale variational neural network reconstruction

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dc.contributor.authorFotaki, Anastasia
dc.contributor.authorFuin, Niccolo
dc.contributor.authorNordio, Giovanna
dc.contributor.authorJimeno, Carlos Velasco
dc.contributor.authorQi, Haikun
dc.contributor.authorEmmanuel, Yaso
dc.contributor.authorPushparajah, Kuberan
dc.contributor.authorBotnar, Rene M.
dc.contributor.authorPrieto, Claudia
dc.date.accessioned2025-01-20T21:04:11Z
dc.date.available2025-01-20T21:04:11Z
dc.date.issued2022
dc.description.abstractPurpose: Free-breathing Magnetization Transfer Contrast Bright blOOd phase SensiTive (MTC-BOOST) is a pro-totype balanced-Steady-State Free Precession sequence for 3D whole-heart imaging, that employs the endoge-nous magnetisation transfer contrast mechanism. This achieves reduction of flow and off-resonance artefacts, that often arise with the clinical T2prepared balanced-Steady-State Free Precession sequence, enabling high quality, contrast-agent free imaging of the thoracic cardiovascular anatomy. Fully-sampled MTC-BOOST acquisition requires long scan times (~10-24 min) and therefore acceleration is needed to permit its clinical incorporation. The aim of this study is to enable and clinically validate the 5-fold accelerated MTC-BOOST acquisition with joint Multi-Scale Variational Neural Network (jMS-VNN) reconstruction. Methods: Thirty-six patients underwent free-breathing, 3D whole-heart imaging with the MTC-BOOST sequence, which is combined with variable density spiral-like Cartesian sampling and 2D image navigators for translational motion estimation. This sequence acquires two differently weighted bright-blood volumes in an interleaved fashion, which are then joined in a phase sensitive inversion recovery reconstruction to obtain a complementary fully co-registered black-blood volume. Data from eighteen patients were used for training, whereas data from the remaining eighteen patients were used for testing/evaluation. The proposed deep-learning based approach adopts a supervised multi-scale variational neural network for joint reconstruction of the two differently weighted bright-blood volumes acquired with the 5-fold accelerated MTC-BOOST. The two contrast images are stacked as different channels in the network to exploit the shared information. The proposed approach is compared to the fully-sampled MTC-BOOST and 5-fold undersampled MTC-BOOST acquisition with Compressed Sensing (CS) reconstruction in terms of scan/reconstruction time and bright-blood image quality. Comparison against conventional 2-fold undersampled T2-prepared 3D bright-blood whole-heart clinical sequence (T2prep-3DWH) is also included. Results: Acquisition time was 3.0 & PLUSMN; 1.0 min for the 5-fold accelerated MTC-BOOST versus 9.0 +/- 1.1 min for the fully-sampled MTC-BOOST and 11.1 +/- 2.6 min for the T2prep-3DWH (p < 0.001 and p < 0.001, respectively). Reconstruction time was significantly lower with the jMS-VNN method compared to CS (10 +/- 0.5 min vs 20 +/- 2 s, p < 0.001). Image quality was higher for the proposed 5-fold undersampled jMS-VNN versus conventional CS, comparable or higher to the corresponding T2prep-3DWH dataset and similar to the fully-sampled MTC-BOOST. Conclusion: The proposed 5-fold accelerated jMS-VNN MTC-BOOST framework provides efficient 3D whole-heart bright-blood imaging in fast acquisition and reconstruction time with concomitant reduction of flow and off-resonance artefacts, that are frequently encountered with the clinical sequence. Image quality of the cardiac anatomy and thoracic vasculature is comparable or superior to the clinical scan and 5-fold CS reconstruction in faster reconstruction time, promising potential clinical adoption.
dc.fuente.origenWOS
dc.identifier.doi10.1016/j.mri.2022.06.012
dc.identifier.eissn1873-5894
dc.identifier.issn0730-725X
dc.identifier.urihttps://doi.org/10.1016/j.mri.2022.06.012
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/93219
dc.identifier.wosidWOS:000827273800002
dc.language.isoen
dc.pagina.final132
dc.pagina.inicio120
dc.revistaMagnetic resonance imaging
dc.rightsacceso restringido
dc.subjectCardiac MRI
dc.subjectNeural network
dc.subjectFree-breathing
dc.subject3D whole-heart imaging
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleAccelerating 3D MTC-BOOST in patients with congenital heart disease using a joint multi-scale variational neural network reconstruction
dc.typeartículo
dc.volumen92
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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