Flexible proton density (PD) mapping using multi-contrast variable flip angle (VFA) data

Primary Multiparametric Quantitative Brain MRI: State-of-the-Art Relaxometric and Proton Density Mapping Techniques

This review on brain multiparametric quantitative MRI (MP-qMRI) focuses on the primary subset of quantitative MRI (qMRI) parameters that represent the mobile ("free") and bound ("motion-restricted") proton pools. Such primary parameters are the proton densities, relaxation times, and magnetization transfer parameters. Diffusion qMRI is also included because of its wide implementation in complete clinical MP-qMRI application. MP-qMRI advances were reviewed over the past 2 decades, with substantial progress observed toward accelerating image acquisition and increasing mapping accuracy. Areas that need further investigation and refinement are identified as follows: (a) the biologic underpinnings of qMRI parameter values and their changes with age and/or disease and (b) the theoretical limitations implicitly built into most qMRI mapping algorithms that do not distinguish between the different spatial scales of voxels versus spin packets, the central physical object of the Bloch theory. With rapidly improving image processing techniques and continuous advances in computer hardware, MP-qMRI has the potential for implementation in a wide range of clinical applications. Currently, three emerging MP-qMRI applications are synthetic MRI, macrostructural qMRI, and microstructural tissue modeling.

Quantitative MRI Characterization of the Extremely Preterm Brain at Adolescence: Atypical versus Neurotypical Developmental Pathways

Background Extremely preterm (EP) birth is associated with higher risks of perinatal white matter (WM) injury, potentially causing abnormal neurologic and neurocognitive outcomes. MRI biomarkers distinguishing individuals with and without neurologic disorder guide research on EP birth antecedents, clinical correlates, and prognoses. Purpose To compare multiparametric quantitative MRI (qMRI) parameters of EP-born adolescents with autism spectrum disorder, cerebral palsy, epilepsy, or cognitive impairment (ie, atypically developing) with those without (ie, neurotypically developing), characterizing sex-stratified brain development. Materials and Methods This prospective multicenter study included individuals aged 14-16 years born EP (Extremely Low Gestational Age Newborns-Environmental Influences on Child Health Outcomes Study, or ELGAN-ECHO). Participants underwent 3.0-T MRI evaluation from 2017 to 2019. qMRI outcomes were compared for atypically versus neurotypically developing adolescents and for girls versus boys. Sex-stratified multiple regression models were used to examine associations between spatial entropy density (SEd) and T1, T2, and cerebrospinal fluid (CSF)-normalized proton density (nPD), and between CSF volume and T2. Interaction terms modeled differences in slopes between atypically versus neurotypically developing adolescents. Results A total of 368 adolescents were classified as 116 atypically (66 boys) and 252 neurotypically developing (125 boys) participants. Atypically versus neurotypically developing girls had lower nPD (mean, 557 10 × percent unit [pu] ± 46 [SD] vs 573 10 × pu ± 43; P = .04), while atypically versus neurotypically developing boys had longer T1 (814 msec ± 57 vs 789 msec ± 82; P = .01). Atypically developing girls versus boys had lower nPD and shorter T2 (eg, in WM, 557 10 × pu ± 46 vs 580 10 × pu ± 39 for nPD [P = .006] and 86 msec ± 3 vs 88 msec ± 4 for T2 [P = .003]). Atypically versus neurotypically developing boys had a more moderate negative association between T1 and SEd (slope, -32.0 msec per kB/cm3 [95% CI: -49.8, -14.2] vs -62.3 msec per kB/cm3 [95% CI: -79.7, -45.0]; P = .03). Conclusion Atypically developing participants showed sexual dimorphisms in the cerebrospinal fluid-normalized proton density (nPD) and T2 of both white matter (WM) and gray matter. Atypically versus neurotypically developing girls had lower WM nPD, while atypically versus neurotypically developing boys had longer WM T1 and more moderate T1 associations with microstructural organization in WM. © RSNA, 2022 Online supplemental material is available for this article.

Towards in vivo g-ratio mapping using MRI: Unifying myelin and diffusion imaging

BACKGROUND

The g-ratio, quantifying the comparative thickness of the myelin sheath encasing an axon, is a geometrical invariant that has high functional relevance because of its importance in determining neuronal conduction velocity. Advances in MRI data acquisition and signal modelling have put in vivo mapping of the g-ratio, across the entire white matter, within our reach. This capacity would greatly increase our knowledge of the nervous system: how it functions, and how it is impacted by disease.

NEW METHOD

This is the second review on the topic of g-ratio mapping using MRI.

RESULTS

This review summarizes the most recent developments in the field, while also providing methodological background pertinent to aggregate g-ratio weighted mapping, and discussing pitfalls associated with these approaches.

COMPARISON WITH EXISTING METHODS

Using simulations based on recently published data, this review reveals caveats to the state-of-the-art calibration methods that have been used for in vivo g-ratio mapping. It highlights the need to estimate both the slope and offset of the relationship between these MRI-based markers and the true myelin volume fraction if we are really to achieve the goal of precise, high sensitivity g-ratio mapping in vivo. Other challenges discussed in this review further evidence the need for gold standard measurements of human brain tissue from ex vivo histology.

CONCLUSIONS

We conclude that the quest to find the most appropriate MRI biomarkers to enable in vivo g-ratio mapping is ongoing, with the full potential of many novel techniques yet to be investigated.

Sensitive detection of extremely small iron oxide nanoparticles in living mice using MP2RAGE with advanced image co-registration

Magnetic resonance imaging (MRI) is a widely used non-invasive methodology for both preclinical and clinical studies. However, MRI lacks molecular specificity. Molecular contrast agents for MRI would be highly beneficial for detecting specific pathological lesions and quantitatively evaluating therapeutic efficacy in vivo. In this study, an optimized Magnetization Prepared—RApid Gradient Echo (MP-RAGE) with 2 inversion times called MP2RAGE combined with advanced image co-registration is presented as an effective non-invasive methodology to quantitatively detect T1 MR contrast agents. The optimized MP2RAGE produced high quality in vivo mouse brain T1 (or R1 = 1/T1) map with high spatial resolution, 160 × 160 × 160 µm³ voxel at 9.4 T. Test–retest signal to noise was > 20 for most voxels. Extremely small iron oxide nanoparticles (ESIONPs) having 3 nm core size and 11 nm hydrodynamic radius after polyethylene glycol (PEG) coating were intracranially injected into mouse brain and detected as a proof-of-concept. Two independent MP2RAGE MR scans were performed pre- and post-injection of ESIONPs followed by advanced image co-registration. The comparison of two T1 (or R1) maps after image co-registration provided precise and quantitative assessment of the effects of the injected ESIONPs at each voxel. The proposed MR protocol has potential for future use in the detection of T1 molecular contrast agents.

Multiparametric mapping in post-mortem perinatal MRI: a feasibility study

OBJECTIVES

To demonstrate feasibility of a 3 T multiparametric mapping (MPM) quantitative pipeline for perinatal post-mortem MR (PMMR) imaging.

METHODS

Whole body quantitative PMMR imaging was acquired in four cases, mean gestational age 34 weeks, range (29-38 weeks) on a 3 T Siemens Prisma scanner. A multicontrast protocol yielded proton density, T₁ and magnetic transfer (MT) weighted multi-echo images obtained from variable flip angle (FA) 3D fast low angle single-shot (FLASH) acquisitions, radiofrequency transmit field map and one B₀ field map alongside four MT weighted acquisitions with saturation pulses of 180, 220, 260 and 300 degrees were acquired, all at 1 mm isotropic resolution.

RESULTS

Whole body MPM was achievable in all four foetuses, with R₁, R₂*, PD and MT maps reconstructed from a single protocol. Multiparametric maps were of high quality and show good tissue contrast, especially the MT maps.

CONCLUSION

MPM is a feasible technique in a perinatal post-mortem setting, which may allow quantification of post-mortem change, prior to being evaluated in a clinical setting.

ADVANCES IN KNOWLEDGE

We have shown that the MPM sequence is feasible in PMMR imaging and shown the potential of MT imaging in this setting.

Three-dimensional motion-corrected T1 relaxometry with MPnRAGE

PURPOSE

To test the performance of the MPnRAGE motion-correction algorithm on quantitative relaxometry estimates.

METHODS

Twelve children (9.4 ± 2.6 years, min = 6.5 years, max = 13.8 years) were imaged 3 times in a session without sedation. Stabilization padding was not used for the second and third scans. Quantitative T₁ values were estimated in each voxel on images reconstructed with and without motion correction. Mean T₁ values were assessed in various regions determined from automated segmentation algorithms. Statistical tests were performed on mean values and the coefficient of variation across the measurements. Accuracy of T₁ estimates were determined by scanning the High Precision Devices (Boulder, CO) MRI system phantom with the same protocol.

RESULTS

The T₁ values obtained with MPnRAGE agreed within 4% of the reference values of the High Precision Devices phantom. The best fit line was T₁ (MPnRAGE) = 1.02 T₁ (reference)-0.9 ms, R²  = 0.9999. For in vivo studies, motion correction reduced the coefficients of variation of mean T₁ values in whole-brain tissue regions determined by FSL FAST by 74% ± 7%, and subcortical regions determined by FIRST and FreeSurfer by 32% ± 21% and 33% ± 26%, respectively. Across all participants, the mean coefficients of variation ranged from 0.8% to 2.0% for subcortical regions and 0.6% ± 0.5% for cortical regions when motion correction was applied.

CONCLUSION

The MPnRAGE technique demonstrated highly accurate values in phantom measurements. When combined with retrospective motion correction, MPnRAGE demonstrated highly reproducible T₁ values, even in participants who moved during the acquisition.

A Single-Scan, Rapid Whole-Brain Protocol for Quantitative Water Content Mapping With Neurobiological Implications

Water concentration is tightly regulated in the healthy human brain and changes only slightly with age and gender in healthy subjects. Consequently, changes in water content are important for the characterization of disease. MRI can be used to measure changes in brain water content, but as these changes are usually in the low percentage range, highly accurate and precise methods are required for detection. The method proposed here is based on a long-TR (10 s) multiple-echo gradient-echo measurement with an acquisition time of 7:21 min. Using such a long TR ensures that there is no T₁ weighting, meaning that the image intensity at zero echo time is only proportional to the water content, the transmit field, and to the receive field. The receive and transmit corrections, which are increasingly large at higher field strengths and for highly segmented coil arrays, are multiplicative and can be approached heuristically using a bias field correction. The method was tested on 21 healthy volunteers at 3T field strength. Calibration using cerebral-spinal fluid values (~100% water content) resulted in mean values and standard deviations of the water content distribution in white matter and gray matter of 69.1% (1.7%) and 83.7% (1.2%), respectively. Measured distributions were coil-independent, as seen by using either a 12-channel receiver coil or a 32-channel receiver coil. In a test-retest investigation using 12 scans on one volunteer, the variation in the mean value of water content for different tissue types was ~0.3% and the mean voxel variability was ~1%. Robustness against reduced SNR was assessed by comparing results for 5 additional volunteers at 1.5T and 3T. Furthermore, water content distribution in gray matter is investigated and regional contrast reported for the first time. Clinical applicability is illustrated with data from one stroke patient and one brain tumor patient. It is anticipated that this fast, stable, easy-to-use, high-quality mapping method will facilitate routine quantitative MR imaging of water content.

hMRI - A toolbox for quantitative MRI in neuroscience and clinical research

Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2⋆, proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.