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Updated: Jun 4, 2025

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
ORACLE: An analytical approach for T1, T2, proton density, and off-resonance mapping with phase-cycled balanced
Nils M J Plähn1,2,3, Yasaman Safarkhanlo2,3,4, Berk C Açikgöz1,2,3
1Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Purpose:
To develop and validate a novel analytical approach simplifying , , proton density (PD), and off-resonance quantifications from phase-cycled balanced steady-state free precession (bSSFP) data. Additionally, to introduce a method to correct aliasing effects in undersampled bSSFP profiles.
Theory And Methods:
Off-resonant-encoded analytical parameter quantification using complex linearized equations (ORACLE) provides analytical solutions for bSSFP profiles. which instantaneously quantify , , proton density (PD), and . An aliasing correction formalism was derived to allow undersampling of bSSFP profiles. ORACLE was used to quantify , , PD, / , and based on fully sampled ( ) bSSFP profiles from numerical simulations and 3T MRI experiments in phantom and 10 healthy subjects' brains. Obtained values were compared with reference scans in the same scan session. Aliasing correction was validated in subsampled ( ) bSSFP profiles in numerical simulations and human brains.
Results:
ORACLE quantifications agreed well with input values from simulations and phantom reference values (R2 = 0.99). In human brains, and quantifications when compared with reference methods showed coefficients of variation below 2.9% and 3.9%, biases of 182 and 16.6 ms, and mean white-matter values of 642 and 51 ms using ORACLE. The quantification differed less than 3 Hz between both methods. PD and maps had comparable histograms. The maps effectively identified cerebrospinal fluid. Aliasing correction removed aliasing-related quantification errors in undersampled bSSFP profiles, significantly reducing scan time.
Conclusion:
ORACLE enables simplified and rapid quantification of , , PD, and from phase-cycled bSSFP profiles, reducing acquisition time and eliminating biomarker maps' coregistration issues.
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