Factorized sensitivity estimation for artifact suppression in phase‐cycled bSSFP MRI

Bıyık, Erdem; Keskin, Kübra; Dar, Salman Ul Hassan; Koç, Aykut; Çukur, Tolga

doi:10.1002/nbm.4228

Cited by 3 publications

(1 citation statement)

References 45 publications

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“…The high sensitivity of the bSSFP sequence to magnetic field inhomogeneities is probably one reason for the scatter of the measured SIR values, since a standard bSSFP sequence was used. Maybe, results could be enhanced using proposed measures to reduce bSSFP signal reduction caused by susceptibility effects [13,14].…”

Section: Limitationsmentioning

confidence: 99%

Noninvasive liver iron quantification by MRI using refocused gradient-echo (bSSFP): preliminary results

Wunderlich

Cario²,

Goetz³

et al. 2023

Rofo

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Purpose To evaluate the feasibility of using a balanced steady-state free precession sequence (bSSFP) to determine liver iron content (LIC). Method Thirty-five consecutive patients with liver iron overload were examined with bSSFP. Signal intensity ratios of liver parenchyma to paraspinal muscles were retrospectively correlated with LIC values obtained by FerriScan, which was used as the reference method. Combinations of bSSFP protocols were also evaluated. The best combination was utilized to calculate LIC from bSSFP data. The sensitivity and specificity for the therapeutically relevant LIC threshold of 80 µmol/g (4.5 mg/g) were determined. Results LIC values ranged from 24 to 756 µmol/g. The best SIR-to-LIC correlation of a single protocol was obtained with a 3.5-ms repetition time (TR) and 17° excitation flip angle (FA). A combination of protocols with TRs of 3.5, 5, and 6.5 ms, each at 17° FA, yielded a superior correlation. LIC values calculated using this combination resulted in a sensitivity/specificity of 0.91/0.85. Conclusion bSSFP is basically suitable to determine LIC. Its advantages are high SNR efficiency and the ability to acquire the entire liver in a breath hold without acceleration techniques. Key Points: Citation Format

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Section: Limitationsmentioning

confidence: 99%

Noninvasive liver iron quantification by MRI using refocused gradient-echo (bSSFP): preliminary results

Wunderlich

Cario²,

Goetz³

et al. 2023

Rofo

View full text Add to dashboard Cite

show abstract

SIMPLEX: Multiple phase-cycled bSSFP quantitative magnetization transfer imaging with physic-guided simulation learning of neural network

Luu,

Park

2023

NeuroImage

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A dual-stage partially interpretable neural network for joint suppression of bSSFP banding and flow artifacts in non-phase-cycled cine imaging

Chen,

Hua,

Gao

et al. 2023

Journal of Cardiovascular Magnetic Resonance

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Purpose To develop a partially interpretable neural network for joint suppression of banding and flow artifacts in non-phase-cycled bSSFP cine imaging. Methods A dual-stage neural network consisting of a voxel-identification (VI) sub-network and artifact-suppression (AS) sub-network is proposed. The VI sub-network provides identification of artifacts, which guides artifact suppression and improves interpretability. The AS sub-network reduces banding and flow artifacts. Short-axis cine images of 12 frequency offsets from 28 healthy subjects were used to train and test the dual-stage network. An additional 77 patients were retrospectively enrolled to evaluate its clinical generalizability. For healthy subjects, artifact suppression performance was analyzed by comparison with traditional phase cycling. The partial interpretability provided by the VI sub-network was analyzed via correlation analysis. Generalizability was evaluated for cine obtained with different sequence parameters and scanners. For patients, artifact suppression performance and partial interpretability of the network were qualitatively evaluated by 3 clinicians. Cardiac function before and after artifact suppression was assessed via left ventricular ejection fraction (LVEF). Results For the healthy subjects, visual inspection and quantitative analysis found a considerable reduction of banding and flow artifacts by the proposed network. Compared with traditional phase cycling, the proposed network improved flow artifact scores (4.57 ± 0.23 vs 3.40 ± 0.38, P = 0.002) and overall image quality (4.33 ± 0.22 vs 3.60 ± 0.38, P = 0.002). The VI sub-network well identified the location of banding and flow artifacts in the original movie and significantly correlated with the change of signal intensities in these regions. Changes of imaging parameters or the scanner did not cause a significant change of overall image quality relative to the baseline dataset, suggesting a good generalizability. For the patients, qualitative analysis showed a significant improvement of banding artifacts (4.01 ± 0.50 vs 2.77 ± 0.40, P < 0.001), flow artifacts (4.22 ± 0.38 vs 2.97 ± 0.57, P < 0.001), and image quality (3.91 ± 0.45 vs 2.60 ± 0.43, P < 0.001) relative to the original cine. The artifact suppression slightly reduced the LVEF (mean bias = -1.25%, P = 0.01). Conclusions The dual-stage network simultaneously reduces banding and flow artifacts in bSSFP cine imaging with a partial interpretability, sparing the need for sequence modification. The method can be easily deployed in a clinical setting to identify artifacts and improve cine image quality.

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Factorized sensitivity estimation for artifact suppression in phase‐cycled bSSFP MRI

Cited by 3 publications

References 45 publications

Noninvasive liver iron quantification by MRI using refocused gradient-echo (bSSFP): preliminary results

Noninvasive liver iron quantification by MRI using refocused gradient-echo (bSSFP): preliminary results

SIMPLEX: Multiple phase-cycled bSSFP quantitative magnetization transfer imaging with physic-guided simulation learning of neural network

A dual-stage partially interpretable neural network for joint suppression of bSSFP banding and flow artifacts in non-phase-cycled cine imaging

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