Improved image quality and reduced acquisition time in brain MRI using deep learning-based reconstruction: A quantitative and subjective assessment compared to standard MPRAGE in 0.55 T MRI

To assess the impact of deep learning (DL)–based image reconstruction on quantitative and subjective image quality in brain MRI at 0.55 T by comparing DL-reconstructed MPRAGE with standard MPRAGE using comparable acquisition geometry and timing parameters. In this prospective study, 30 patients underwent two consecutive 3D T1-weighted MPRAGE acquisitions on a 0.55 T MRI system (MAGNETOM Free.Max, Siemens Healthineers): a standard reconstruction and a DL-based reconstruction generated from undersampled k-space data using a variational-network architecture. Identical circular regions of interest (ROIs) were placed in gray matter (caudate nucleus), white matter (centrum semiovale), cerebrospinal fluid (lateral ventricle), and air for noise estimation. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were computed. Three blinded radiologists independently evaluated image quality using a 5-point Likert scale based on anatomical detail, gray–white matter differentiation, vascular visibility, artifact burden, and overall diagnostic quality. DL-based reconstruction significantly improved objective image quality across all metrics. SNR increased from 40.83 ± 10.11 to 106.30 ± 51.38 in gray matter ( p < 0.0001), from 48.95 ± 12.52 to 125.30 ± 58.01 in white matter ( p < 0.0001), and from 5.77 ± 1.10 to 7.75 ± 4.76 in CSF ( p = 0.021). CNR between gray and white matter increased from 8.12 ± 4.24 to 18.99 ± 11.21 (p < 0.0001). Subjective ratings favored DL reconstruction for anatomical detail (4.05 ± 0.62 vs. 3.68 ± 0.64), vascular visibility (4.37 ± 0.56 vs. 3.63 ± 0.72), and overall image quality (4.07 ± 0.72 vs. 3.57 ± 0.73). Standard reconstruction showed slightly better artifact suppression (3.80 ± 0.61 vs. 3.27 ± 0.78) and gray–white matter contrast (4.00 ± 0.64 vs. 3.87 ± 0.71). Acquisition time was reduced from 6:44 min (standard MPRAGE) to 3:06 min with DL reconstruction, corresponding to a substantial scan time reduction. DL-based reconstruction markedly enhances quantitative and subjective image quality in low-field brain MRI and enables a markedly shorter acquisition time compared to the standard protocol. This study adds clinical evidence that DL reconstruction can substantially improve 0.55 T MPRAGE imaging, supporting its integration into routine neuroimaging workflows to improve efficiency, patient comfort, and diagnostic confidence. • Question: Low-field brain MRI provides limited image quality and long acquisition times; improved reconstruction techniques are required to enhance diagnostic confidence and clinical workflow efficiency. • Findings: DL-based reconstruction significantly increased SNR and CNR, improved radiologist-rated image quality, and reduced MPRAGE scan time substantially at 0.55 T. • Clinical Relevance Statement: By improving image quality and markedly reducing acquisition time, DL-based reconstruction enhances patient comfort, reduces motion artifacts, and enables efficient, high-quality low-field neuroimaging in routine clinical practice.

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Journal
Magnetic Resonance Imaging
Published
2026-03-05
DOI
https://doi.org/10.1016/j.mri.2026.110656
Primary Topic
Advanced MRI Techniques and Applications
Type
article
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article

Improved image quality and reduced acquisition time in brain MRI using deep learning-based reconstruction: A quantitative and subjective assessment compared to standard MPRAGE in 0.55 T MRI

Lynn Johann Frohwein, Saher Saeed, Jan Borggrefe, Jan Boriesosdick et al.
Magnetic Resonance Imaging
Advanced MRI Techniques and Applications
article

Improved image quality and reduced acquisition time in brain MRI using deep learning-based reconstruction: A quantitative and subjective assessment compared to standard MPRAGE in 0.55 T MRI

Lynn Johann Frohwein, Saher Saeed, Jan Borggrefe, Jan Boriesosdick, Julian Schreck, D Schönbeck, M M Wöltjen, Julius Henning Niehoff, Christoph Mönninghoff, Jan Robert Kroeger, Dominik Nickel, Maria Katz, Elisabeth Weiland, Iram Shahzadi, Nina Haag, Georg Reiman
article en

Abstract

To assess the impact of deep learning (DL)–based image reconstruction on quantitative and subjective image quality in brain MRI at 0.55 T by comparing DL-reconstructed MPRAGE with standard MPRAGE using comparable acquisition geometry and timing parameters. In this prospective study, 30 patients underwent two consecutive 3D T1-weighted MPRAGE acquisitions on a 0.55 T MRI system (MAGNETOM Free.Max, Siemens Healthineers): a standard reconstruction and a DL-based reconstruction generated from undersampled k-space data using a variational-network architecture. Identical circular regions of interest (ROIs) were placed in gray matter (caudate nucleus), white matter (centrum semiovale), cerebrospinal fluid (lateral ventricle), and air for noise estimation. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were computed. Three blinded radiologists independently evaluated image quality using a 5-point Likert scale based on anatomical detail, gray–white matter differentiation, vascular visibility, artifact burden, and overall diagnostic quality. DL-based reconstruction significantly improved objective image quality across all metrics. SNR increased from 40.83 ± 10.11 to 106.30 ± 51.38 in gray matter ( p < 0.0001), from 48.95 ± 12.52 to 125.30 ± 58.01 in white matter ( p < 0.0001), and from 5.77 ± 1.10 to 7.75 ± 4.76 in CSF ( p = 0.021). CNR between gray and white matter increased from 8.12 ± 4.24 to 18.99 ± 11.21 (p < 0.0001). Subjective ratings favored DL reconstruction for anatomical detail (4.05 ± 0.62 vs. 3.68 ± 0.64), vascular visibility (4.37 ± 0.56 vs. 3.63 ± 0.72), and overall image quality (4.07 ± 0.72 vs. 3.57 ± 0.73). Standard reconstruction showed slightly better artifact suppression (3.80 ± 0.61 vs. 3.27 ± 0.78) and gray–white matter contrast (4.00 ± 0.64 vs. 3.87 ± 0.71). Acquisition time was reduced from 6:44 min (standard MPRAGE) to 3:06 min with DL reconstruction, corresponding to a substantial scan time reduction. DL-based reconstruction markedly enhances quantitative and subjective image quality in low-field brain MRI and enables a markedly shorter acquisition time compared to the standard protocol. This study adds clinical evidence that DL reconstruction can substantially improve 0.55 T MPRAGE imaging, supporting its integration into routine neuroimaging workflows to improve efficiency, patient comfort, and diagnostic confidence. • Question: Low-field brain MRI provides limited image quality and long acquisition times; improved reconstruction techniques are required to enhance diagnostic confidence and clinical workflow efficiency. • Findings: DL-based reconstruction significantly increased SNR and CNR, improved radiologist-rated image quality, and reduced MPRAGE scan time substantially at 0.55 T. • Clinical Relevance Statement: By improving image quality and markedly reducing acquisition time, DL-based reconstruction enhances patient comfort, reduces motion artifacts, and enables efficient, high-quality low-field neuroimaging in routine clinical practice.

Magnetic Resonance ImagingVol. 129
Siemens (Germany) (DE), Siemens Healthineers (Germany) (DE), Johannes Wesling Klinikum Minden (DE)
Openalex Percentile: Top 35%
Advanced MRI Techniques and Applications
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