Selective Inversion Recovery Quantitative Magnetization Transfer Brain MRI at 7T: Clinical and Postmortem Validation in Multiple Sclerosis

Bagnato, Francesca; Hametner, Simon; Franco, Giulia; Pawate, Siddharama; Subramaniam, Sriram; Lassmann, Hans; Gore, John C.; Smith, Seth E.; Dortch, Richard D.

doi:10.1111/jon.12511

Cited by 21 publications

(24 citation statements)

References 33 publications

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“…Recent developments in quantitative MT (qMT) methods attempt to reduce these confounding influences by providing more tissue-specific indices. 52 Another promising technique is inhomogeneous magnetization transfer (ihMT) 53 which appears to be specific to CNS lipids, which enrich myelin. Myelin water imaging (MWI) is another MRI technique designed to detect myelin alterations.…”

Section: Advances In Understanding Disease Mechanismsmentioning

confidence: 99%

Advances in brain imaging in multiple sclerosis

Cortese

Collorone

Ciccarelli

et al. 2019

Ther Adv Neurol Disord

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Brain imaging is increasingly used to support clinicians in diagnosing multiple sclerosis (MS) and monitoring its progression. However, the role of magnetic resonance imaging (MRI) in MS goes far beyond its clinical application. Indeed, advanced imaging techniques have helped to detect different components of MS pathogenesis in vivo, which is now considered a heterogeneous process characterized by widespread damage of the central nervous system, rather than multifocal demyelination of white matter. Recently, MRI biomarkers more sensitive to disease activity than clinical disability outcome measures, have been used to monitor response to anti-inflammatory agents in patients with relapsing–remitting MS. Similarly, MRI markers of neurodegeneration exhibit the potential as primary and secondary outcomes in clinical trials for progressive phenotypes. This review will summarize recent advances in brain neuroimaging in MS from the research setting to clinical applications.

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Section: Advances In Understanding Disease Mechanismsmentioning

confidence: 99%

Advances in brain imaging in multiple sclerosis

Cortese

Collorone

Ciccarelli

et al. 2019

Ther Adv Neurol Disord

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“…We propose the first in vivo clinical translation of our optimized and histologically validated 20 SIR-qMT protocol and demonstrate (1) the clinical feasibility of SIR-qMT at 3 T and (2) the ability of SIR-qMT-derived metrics to predict radiological and clinical disease severity. We recognize that additional gains in scan efficiency may be required prior to widespread clinical adoption of the SIR-qMT technique described here.…”

Section: Discussionmentioning

confidence: 99%

“…maps of the main magnetic field, the transmit radio frequency field, and the spin-lattice relaxation time), resulting in a complicated data analysis pipeline. To alleviate these issues, the selective inversion recovery (SIR) qMT 13,18–21 technique was developed. SIR-qMT is based on a simple two-pool model of inversion recovery data that does not require additional measurements.…”

Section: Introductionmentioning

confidence: 99%

Selective inversion recovery quantitative magnetization transfer imaging: Toward a 3 T clinical application in multiple sclerosis

Bagnato

Franco

et al. 2019

Mult Scler

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Background: Assessing the degree of myelin injury in patients with multiple sclerosis (MS) is challenging due to the lack of magnetic resonance imaging (MRI) methods specific to myelin quantity. By measuring distinct tissue parameters from a two-pool model of the magnetization transfer (MT) effect, quantitative magnetization transfer (qMT) may yield these indices. However, due to long scan times, qMT has not been translated clinically. Objectives: We aim to assess the clinical feasibility of a recently optimized selective inversion recovery (SIR) qMT and to test the hypothesis that SIR-qMT-derived metrics are informative of radiological and clinical disease-related changes in MS. Methods: A total of 18 MS patients and 9 age- and sex-matched healthy controls (HCs) underwent a 3.0 Tesla (3 T) brain MRI, including clinical scans and an optimized SIR-qMT protocol. Four subjects were re-scanned at a 2-week interval to determine inter-scan variability. Results: SIR-qMT measures differed between lesional and non-lesional tissue ( p < 0.0001) and between normal-appearing white matter (NAWM) of patients with more advanced disability and normal white matter (WM) of HCs ( p < 0.05). SIR-qMT measures were associated with lesion volumes, disease duration, and disability scores ( p ⩽ 0.002). Conclusion: SIR-qMT at 3 T is clinically feasible and predicts both radiological and clinical disease severity in MS.

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“…The MT effect is a major confound in all CEST imaging studies if not properly modeled; however, it is also a well‐understood biophysical process. The literature quantifying the MT effect is vast, with many qMT studies in healthy and pathological tissues in the human body; thus, it has a well‐defined parameter range. However, most previous studies of in vivo CEST effects have either ignored the MT effect (eg, using the MTR asym ), or utilized an alternative fitting model, such as AREX, to simultaneously estimate MT and CEST effects.…”

Section: Discussionmentioning

confidence: 99%

“…However, the influence of the MT effect on these analyses has not been systematically explored. While several studies have investigated the MT effect in CEST imaging, most often the MT effect is removed as a confound, despite it having radiological significance in its own right . Therefore, eliminating this contrast mechanism in favour of CEST may also eliminate valuable information about the tissue under investigation.…”

Section: Introductionmentioning

confidence: 99%

Does the magnetization transfer effect bias chemical exchange saturation transfer effects? Quantifying chemical exchange saturation transfer in the presence of magnetization transfer

Smith

Ray

Larkin

et al. 2020

Magnetic Resonance in Med

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Purpose: Chemical exchange saturation transfer (CEST) is an MRI technique sensitive to the presence of low-concentration solute protons exchanging with water. However, magnetization transfer (MT) effects also arise when large semisolid molecules interact with water, which biases CEST parameter estimates if quantitative models do not account for macromolecular effects. This study establishes under what conditions this bias is significant and demonstrates how using an appropriate model provides more accurate quantitative CEST measurements. Methods: CEST and MT data were acquired in phantoms containing bovine serum albumin and agarose. Several quantitative CEST and MT models were used with the phantom data to demonstrate how underfitting can influence estimates of the CEST effect. CEST and MT data were acquired in healthy volunteers, and a twopool model was fit in vivo and in vitro, whereas removing increasing amounts of CEST data to show biases in the CEST analysis also corrupts MT parameter estimates. Results: When all significant CEST/MT effects were included, the derived parameter estimates for each CEST/MT pool significantly correlated (P < .05) with bovine serum albumin/agarose concentration; minimal or negative correlations were found with underfitted data. Additionally, a bootstrap analysis demonstrated that significant biases occur in MT parameter estimates (P < .001) when unmodeled CEST data are included in the analysis. Conclusions: These results indicate that current practices of simultaneously fitting both CEST and MT effects in model-based analyses can lead to significant bias in all 1360 | SMITH eT al. | THEORYSimilar to the analytical solution for a two-pool model described in the various papers by Yarnykh et al 36,37 and Zhou et al,4,38 we parameter estimates unless a sufficiently detailed model is utilized. Therefore, care must be taken when quantifying CEST and MT effects in vivo by properly modeling data to minimize these biases. K E Y W O R D S amide, CEST, MT, NOE, qMT, quantitative 1366 | SMITH eT al. F I G U R E 3 Semisolid (PSR), and amide and NOE (MTR*) maps for the variable agarose phantom experiment. The top row illustrates the full, four-pool model estimation, the middle displays the fixed-qMT estimation, and the bottom row shows the same fit assuming the NOE and MT pools are a single pool, similar to Tee et al 34 F I G U R E 4 Semisolid (PSR), and amide and NOE (MTR*) maps for the variable BSA phantom experiment. The top row illustrates the full, four-pool model estimation, the middle displays the fixed-qMT estimation, and the bottom row shows the same fit assuming the NOE and MT pools are a single pool, similar to similar to Tee et al 34

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Selective Inversion Recovery Quantitative Magnetization Transfer Brain MRI at 7T: Clinical and Postmortem Validation in Multiple Sclerosis

Abstract: SIR-qMT at 7T provides sensitive, quantitative measures of myelin integrity for clinical and research applications.

Cited by 21 publications

References 33 publications

Advances in brain imaging in multiple sclerosis

Advances in brain imaging in multiple sclerosis

Selective inversion recovery quantitative magnetization transfer imaging: Toward a 3 T clinical application in multiple sclerosis

Does the magnetization transfer effect bias chemical exchange saturation transfer effects? Quantifying chemical exchange saturation transfer in the presence of magnetization transfer

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