Nicolas Boulant
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Articles (11)
Year:
2025
Year:
2025
Year:
2025
Year:
2025
Year:
2025
Year:
2024
Year:
2024
Year:
2024
Year:
2024
Purpose MP2RAGE parameter optimization is redefined to allow more time‐efficient MR acquisitions, whereas the T 1 ‐based synthetic imaging framework is used to obtain on‐demand T 1 ‐weighted contrasts. Our aim was to validate this concept on healthy volunteers and patients with multiple sclerosis, using plug‐and‐play parallel‐transmission brain imaging at 7 T. Methods A “time‐efficient” MP2RAGE sequence was designed with optimized parameters including TI and TR set as small as possible. Extended phase graph formalism was used to set flip‐angle values to maximize the gray–to–white‐matter contrast‐to‐noise ratio (CNR). Several synthetic contrasts (UNI, EDGE, FGATIR, FLAWS MIN , FLAWS HCO ) were generated online based on the acquired T 1 maps. Experimental validation was performed on 4 healthy volunteers at various spatial resolutions. Clinical applicability was evaluated on 6 patients with multiple sclerosis, scanned with both time‐efficient and conventional MP2RAGE parameterizations. Results The proposed time‐efficient MP2RAGE protocols reduced acquisition time by 40%, 30%, and 19% for brain imaging at (1 mm) 3 , (0.80 mm) 3 and (0.65 mm) 3 , respectively, when compared with conventional parameterizations. They also provided all synthetic contrasts and comparable contrast‐to‐noise ratio on UNI images. The flexibility in parameter selection allowed us to obtain a whole‐brain (0.45 mm) 3 acquisition in 19 min 56 s. On patients with multiple sclerosis, a (0.67 mm) 3 time‐efficient acquisition enhanced cortical lesion visualization compared with a conventional (0.80 mm) 3 protocol, while decreasing the scan time by 15%. Conclusion The proposed optimization, associated with T 1 ‐based synthetic contrasts, enabled substantial decrease of the acquisition time or higher spatial resolution scans for a given time budget, while generating all typical brain contrasts derived from MP2RAGE.
Year:
2023
Year:
2023
Collaborators (3)
Jeroen Siero
Associate Professor
University Medical Center Groningen
Alexandre Vignaud
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Edwin Versteeg
Asssistant Professor
University Medical Center Utrecht, Utrecht University
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