Fat fraction mapping using bSSFP Signal Profile Asymmetries for Robust multi-Compartment Quantification (SPARCQ)

Purpose: To develop a novel quantitative method for detection of different tissue compartments based on bSSFP signal profile asymmetries (SPARCQ) and to provide a validation and proof-of-concept for voxel-wise water-fat separation and fat fraction mapping. Methods: The SPARCQ framework uses phase-cycled bSSFP acquisitions to obtain bSSFP signal profiles. For each voxel, the profile is decomposed into a weighted sum of simulated profiles with specific off-resonance and relaxation time ratios. From the obtained set of weights, voxel-wise estimations of the fractions of the different components and their equilibrium magnetization are extracted. For the entire image volume, component-specific quantitative maps as well as banding-artifact-free images are generated. A SPARCQ proof-of-concept was provided for water-fat separation and fat fraction mapping. Noise robustness was assessed using simulations. A dedicated water-fat phantom was used to validate fat fractions estimated with SPARCQ against gold-standard 1H MRS. Quantitative maps were obtained in knees of six healthy volunteers, and SPARCQ repeatability was evaluated in scan rescan experiments. Results: Simulations showed that fat fraction estimations are accurate and robust for signal-to-noise ratios above 20. Phantom experiments showed good agreement between SPARCQ and gold-standard (GS) fat fractions (fF(SPARCQ) = 1.02*fF(GS) + 0.00235). In volunteers, quantitative maps and banding-artifact-free water-fat-separated images obtained with SPARCQ demonstrated the expected contrast between fatty and non-fatty tissues. The coefficient of repeatability of SPARCQ fat fraction was 0.0512. Conclusion: The SPARCQ framework was proposed as a novel quantitative mapping technique for detecting different tissue compartments, and its potential was demonstrated for quantitative water-fat separation.Comment: 20 pages, 7 figures, submitted to Magnetic Resonance in Medicin

SPARCQ: A new approach for fat fraction mapping using asymmetries in the phase-cycle bSSFP signal profile

This repository contains in vitro and in vivo MRI data acquired on a 3T clinical system (MAGNETOM Prismafit, Siemens Healthcare, Erlangen, Germany) using a commercially available 18-channel body coil. All data includes both magnitude and phase information in DICOM format. Data was collected and used in a study untitled "SPARCQ: A new approach for fat fraction mapping using asymmetries in the phase-cycled bSSFP signal profile" by Rossi et. al. (2023). The detailed contents of the repository are listed below: /PHANTOM: 3D acquisitions of a custom fat-water phantom with 6 vials of different peanut oil and water concentrations /PCbSSFP NPC=37 Phase-Cycled bSSFP acquisitions with phase increments [0°:10°:360°] /MEGRE MultiEcho GRE acquisition with 13 monopolar echoes TE1/$\Delta$TE=1.34/1.98 ms /V1 to /V6: 3D knee acquisitions from n=6 healthy volunteers /Scan NPC=37 Phase-Cycled bSSFP acquisitions with phase increments [0°:10°:360°] /Rescan NPC=37 Phase-Cycled bSSFP acquisitions with phase increments [0°:10°:360°] after volunteer repositioning (repeatability experiment) /Dixon In-phase, out-of-phase, fat-only and water-only images reconstructed from a Turbo Spin Echo Dixon sequence /V7 and /V8: 3D knee acquisitions from n=2 healthy volunteers /Scan NPC=37 Phase-Cycled bSSFP acquisitions with phase increments [0°:10°:360°] /MEGRE MultiEcho GRE acquisition with 13 monopolar echoes TE1/$\Delta$TE=1.34/1.98 ms ************************************************************************************************************************************************************************************************************************************************************ Link to publication: https://onlinelibrary.wiley.com/doi/full/10.1002/mrm.29813 ************************************************************************************************************************************************************************************************************************************************************ Data was collected and approved for sharing according to institutional rules (Ethics Commitee, CHUV, Lausanne, Switzerland)