Repeat it without me: Crowdsourcing the T1 mapping common ground via the ISMRM reproducibility challenge.

PURPOSE: T1 mapping is a widely used quantitative MRI technique, but its tissue-specific values remain inconsistent across protocols, sites, and vendors. The ISMRM Reproducible Research and Quantitative MR study groups jointly launched a challenge to assess the reproducibility of a well-established inversion-recovery T1 mapping technique, using acquisition details from a seminal T1 mapping paper on a standardized phantom and in human brains. METHODS: The challenge used the acquisition protocol from Barral et al. (2010). Researchers collected T1 mapping data on the ISMRM/NIST phantom and/or in human brains. Data submission, pipeline development, and analysis were conducted using open-source platforms. Intersubmission and intrasubmission comparisons were performed. RESULTS: Eighteen submissions (39 phantom and 56 human datasets) on scanners by three MRI vendors were collected at 3 T (except one, at 0.35 T). The mean coefficient of variation was 6.1% for intersubmission phantom measurements, and 2.9% for intrasubmission measurements. For humans, the intersubmission/intrasubmission coefficient of variation was 5.9/3.2% in the genu and 16/6.9% in the cortex. An interactive dashboard for data visualization was also developed: https://rrsg2020.dashboards.neurolibre.org. CONCLUSION: The T1 intersubmission variability was twice as high as the intrasubmission variability in both phantoms and human brains, indicating that the acquisition details in the original paper were insufficient to reproduce a quantitative MRI protocol. This study reports the inherent uncertainty in T1 measures across independent research groups, bringing us one step closer to a practical clinical baseline of T1 variations in vivo.

MR-oximetry with fat DESPOT.

PURPOSE: The R1 relaxation rate of fat is a promising marker of tissue oxygenation. Existing techniques to map fat R1 in MR-oximetry offer limited spatial coverage, require long scan times, or pulse sequences that are not readily available on clinical scanners. This work addresses these limitations with a 3D voxel-wise fat R1 mapping technique for MR-oximetry based on a variable flip angle (VFA) approach at 3 T. METHODS: Varying levels of dissolved oxygen (O2) were generated in a phantom consisting of vials of safflower oil emulsion, used to approximate human fat. Joint voxel-wise mapping of fat and water R1 was performed with a two-compartment VFA model fitted to multi-echo gradient-echo magnitude data acquired at four flip angles, referred to as Fat DESPOT. Global R1 was also calculated. Variations of fat, water, and global R1 were investigated as a function of the partial pressure of O2 (pO2). Inversion-prepared stimulated echo magnetic resonance spectroscopy was used as the reference technique for R1 measurements. RESULTS: Fat R1 from Fat DESPOT was more sensitive than water R1 and global R1 to variations in pO2, consistent with previous studies performed with different R1 mapping techniques. Fat R1 sensitivity to pO2 variations with Fat DESPOT (median O2 relaxivity r1, O2 = 1.57× 10-3 s-1 mmHg-1) was comparable to spectroscopy-based measurements for methylene, the main fat resonance (median r1, O2= 1.80 × 10-3 s-1 mmHg-1). CONCLUSION: Fat and water R1 can be measured on a voxel-wise basis using a two-component fit to multi-echo 3D VFA magnitude data in a clinically acceptable scan time. Fat and water R1 measured with Fat DESPOT were sensitive to variations in pO2. These observations suggest an approach to 3D in vivo MR oximetry.

Longitudinal relaxation in fat-water mixtures and its dependence on fat content at 3 T.

Longitudinal (T1 ) relaxation of triglyceride molecules and water is of interest for fat-water separation and fat quantification. A better understanding of T1 relaxation could benefit modeling for applications in fat quantification and relaxation mapping. This work investigated T1 relaxation of spectral resonances of triglyceride molecules and water in liquid fat-water mixtures and its dependence on the fat fraction. Dairy cream and a safflower oil emulsion were used. These were diluted with distilled water to produce a variety of fat mass fractions (4.4% to 35% in dairy cream and 6.3% to 52.3% in safflower oil emulsion). T1 was measured at room temperature at 3 T using an inversion recovery STimulated Echo Acquisition Mode (STEAM) MR spectroscopy method with a series of inversion times. T1 variations as a function of fat fraction were investigated for various resonances. A two-component model was developed to describe the relaxation in a fat-water mixture as a function of the fat fraction. The T1 of water and of all fat resonances studied in this work decreased as the fat fraction increased. The relative variation in T1 was different for each fat resonance. The T1 of the methylene resonance showed the least variation as a function of the fat fraction. The proposed two-component model closely fits the observed T1 variations. In conclusion, this work clarifies how the T1 of major and minor fat resonances and of the water resonance varies as a function of the fat fraction in fat-water mixtures. Knowledge of these variations could serve modeling, analysis of MRI measurements in fat-water mixtures, and phantom preparation.

A role for magnetic susceptibility in synthetic computed tomography.

PURPOSE: Radiotherapy treatment planning based on magnetic resonance imaging (MRI) benefits from increased soft-tissue contrast and functional imaging. MRI-only planning is attractive but limited by the lack of electron density information required for dose calculation, and the difficulty to differentiate air and bone. MRI can map magnetic susceptibility to separate bone from air. A method is introduced to produce synthetic CT (sCT) through automatic voxel-wise assignment of CT numbers from an MRI dataset processed that includes magnetic susceptibility mapping. METHODS: Volumetric multi-echo gradient echo datasets were acquired in the heads of five healthy volunteers and fourteen patients with cancer using a 3 T MRI system. An algorithm for CT synthesis was designed using the volunteer data, based on fuzzy c-means clustering and adaptive thresholding of the MR data (magnitude, fat, water, and magnetic susceptibility). Susceptibility mapping was performed using a modified version of the iterative phase replacement algorithm. On patient data, the algorithm was assessed by direct comparison to X-ray computed tomography (CT) scans. RESULTS: The skull, spine, teeth, and major sinuses were clearly distinguished in all sCT, from healthy volunteers and patients. The mean absolute CT number error between X-ray CT and sCT in patients ranged from 78 and 134 HU. CONCLUSION: Susceptibility mapping using MRI can differentiate air and bone for CT synthesis. The proposed method is automated, fast, and based on a commercially available MRI pulse sequence. The method avoids registration errors and does not rely on a priori information, making it suitable for nonstandard anatomy.

Phase processing for quantitative susceptibility mapping of regions with large susceptibility and lack of signal.

PURPOSE: Phase processing impacts the accuracy of quantitative susceptibility mapping (QSM). Techniques for phase unwrapping and background removal have been proposed and demonstrated mostly in brain. In this work, phase processing was evaluated in the context of large susceptibility variations (Δχ) and negligible signal, in particular for susceptibility estimation using the iterative phase replacement (IPR) algorithm. METHODS: Continuous Laplacian, region-growing, and quality-guided unwrapping were evaluated. For background removal, Laplacian boundary value (LBV), projection onto dipole fields (PDF), sophisticated harmonic artifact reduction for phase data (SHARP), variable-kernel sophisticated harmonic artifact reduction for phase data (V-SHARP), regularization enabled sophisticated harmonic artifact reduction for phase data (RESHARP), and 3D quadratic polynomial field removal were studied. Each algorithm was quantitatively evaluated in simulation and qualitatively in vivo. Additionally, IPR-QSM maps were produced to evaluate the impact of phase processing on the susceptibility in the context of large Δχ with negligible signal. RESULTS: Quality-guided unwrapping was the most accurate technique, whereas continuous Laplacian performed poorly in this context. All background removal algorithms tested resulted in important phase inaccuracies, suggesting that techniques used for brain do not translate well to situations where large Δχ and no or low signal are expected. LBV produced the smallest errors, followed closely by PDF. CONCLUSION: Results suggest that quality-guided unwrapping should be preferred, with PDF or LBV for background removal, for QSM in regions with large Δχ and negligible signal. This reduces the susceptibility inaccuracy introduced by phase processing. Accurate background removal remains an open question. Magn Reson Med 79:3103-3113, 2017. © 2017 International Society for Magnetic Resonance in Medicine.