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Characterization of Multi-Scale Perfusion in Patients with Relapsing-Remitting Multiple Sclerosis (RR-MS)

Ashley Nespodzany¹, Charrid Simpson², Aimee Borazanci², and Ashley M Stokes¹

¹Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States, ²Neurology, Barrow Neurological Institute, Phoenix, AZ, United States

Synopsis

The purpose of this study is to characterize multi-scale cerebral perfusion in patients with multiple sclerosis (MS) using an advanced spin- and gradient-echo (SAGE) dynamic susceptibility contrast (DSC) MRI method. SAGE DSC-MRI provides macro- and micro-vascular perfusion, permeability, and other vascular parameters. We have acquired SAGE DSC-MRI data in 24 patients, along with a quality of life metric. Preliminary analysis of the first five patients demonstrated reduced perfusion in patients with lower quality of life scores than patients with higher quality of life scores. Work is ongoing to characterize the full set of SAGE-based hemodynamic metrics in these patients.

Introduction

Multiple sclerosis (MS) is the most common debilitating neurological disorder and affects 2.5 million people worldwide [1]. Although the precise mechanism of MS is unknown, vascular inflammation is known to play a critical role in the early pathogenesis [2,3]. Numerous studies have shown both increased and decreased locoregional perfusion across the brain, reflecting the complex spatiotemporal dynamics of MS disease progression. Moreover, unlike conventional MRI, perfusion changes have been found to correlate with clinical disability [2] and neuropsychological dysfunction (GM) [4]. This study aims to establish macro- and microvascular perfusion metrics in patients with RR-MS using a combined spin- and gradient-echo (SAGE) DSC-MRI method. The acquisition of both spin-echo and gradient-echo dynamic data provides complementary sensitivities to both microvasculature and total vasculature, respectively [5,6]. Macrovascular perfusion has been characterized in patients with MS using standard DSC-MRI methods, but to our knowledge, no study has undertaken a comprehensive characterization of multi-scale hemodynamics in MS. Microvascular sensitivity is particularly important given the known microvascular changes that occur in MS. SAGE DSC-MRI can provide a multitude of parameters related to cerebral hemodynamics - including macro- and microvascular cerebral blood volume (CBV) and flow (CBF). More advanced parameters such as mean vessel diameter and capillary transit time heterogeneity can also be derived [7,8]. SAGE-based DSC-MRI also permits quantification of T1 changes with contrast agent passage, which allows simultaneous dynamic contrast-enhanced (DCE) MRI analysis within a DSC protocol [9], enabling the quantification of vascular permeability [10]. Such measures could enable the detection of the earliest signs of MS-induced hemodynamic abnormalities.

Methods

Patients with RR-MS (n = 24, 5 male, mean age 35 years, range 19-46) were recruited to this study. All subjects were scheduled for a standard brain MRI with and without contrast at 3T (Philips). Prior to MRI, subjects completed the Functional Assessment of Multiple Sclerosis (v4, FAMS) to assess quality of life (QoL), where higher FAMS scores indicate higher QoL (range 0 to 176). Standard imaging included T2-weighted FLAIR and T1-w pre- and post-contrast images. SAGE-based DSC-MRI was acquired during bolus injection of a single-dose of contrast agent (0.1 mmol/kg, Gadavist). SAGE parameters were as follows: 5 echoes (2 gradient echo, 2 asymmetric spin echoes, 1 spin echo), TR = 1.8s, flip = 90, TEs = 8.8/26/55/72/88ms, SENSE = 2, voxel size = 2.5 x 2.5 x 5.0mm3, 15 slices, 150 dynamics acquired over 4.5 min). The ∆R2* and ∆R2 were obtained analytically from the GE and SE signals using the simplified SAGE equations [11,12]. The AIF was selected using an automated algorithm [13]. CBV and CBF were calculated using standard DSC-MRI post-processing. The signal at TE = 0 was also extrapolated from the first two (gradient) echoes. White and grey matter (WM and GM) were segmented using FAST (FSL).

Results/Discussion

Figure 1 shows the DR2* and DR2 curves in WM and GM during bolus passage across the first five MS patients. The FAMS scores in these five patients ranged from 46 (associated with low QoL, blue lines) to 167 (high QoL, green lines). As expected, GM DR2* and DR2 were higher than WM, and the patients with the highest FAMS scores (purple and green) had higher peak DR2* and DR2. The dynamic T1-weighted signal was also quantified as a percent of baseline, as shown in Figure 2, across the same five patients. Small but consistent contrast agent extravasation was observed in both WM and GM, consistent with literature results [14]. Interestingly, higher T1-weighted signals were observed in patients with higher QoL metrics. Figure 3 shows the T2-weighted FLAIR and macro- and microvascular CBV in two representative patients with high and low FAMS scores. The patient with a low FAMS score (right) demonstrated marked decreases in both CBV metrics relative to the high FAMS patient (left). This trend is also seen in the macro- and microvascular CBF, shown in Figure 4.

Conclusions

Perfusion changes may be indicative of any number of underlying pathophysiological processes associated with MS, including neuro-inflammation, metabolic or vascular dysfunction, or even primary ischemia. This study aims to characterize both macrovascular and microvascular perfusion changes using SAGE DSC-MRI. We hypothesize that these changes will correlate with QoL metrics and serve as a new biomarker for MS. In this preliminary subset of the five initial patients, we found lower perfusion in patients with lower QoL for both macrovascular and microvascular CBV and CBF. Work is ongoing to analyze the remaining datasets in patients with MS and to fully characterize the wide range of hemodynamic metrics available from SAGE DSC-MRI.

Acknowledgements

This work was supported by the Barrow Neurological Foundation and Philips Healthcare.

References

[1] Lublin FD, Reingold SC, Cohen JA, Cutter GR, Sørensen PS, Thompson AJ, et al. Defining the clinical course of multiple sclerosis: The 2013 revisions. Neurology 2014;83:278–86. doi:10.1212/wnl.0000000000000560.

[2] Bester M, Forkert ND, Stellmann JP, Sturner K, Aly L, Drabik A, et al. Increased perfusion in normal appearing white matter in high inflammatory multiple sclerosis patients. PLoS One 2015;10:e0119356. doi:10.1371/journal.pone.0119356.

[3] Ge Y, Law M, Johnson G, Herbert J, Babb JS, Mannon LJ, et al. Dynamic Susceptibility Contrast Perfusion MR Imaging of Multiple Sclerosis Lesions: Characterizing Hemodynamic Impairment and Inflammatory Activity. Am J Neuroradiol 2005;26:1539–47.

[4] Inglese M, Adhya S, Johnson G, Babb JS, Miles L, Jaggi H, et al. Perfusion magnetic resonance imaging correlates of neuropsychological impairment in multiple sclerosis. J Cereb Blood Flow Metab 2008;28:164–71. doi:10.1038/sj.jcbfm.9600504.

[5] Dennie J, Mandeville J, Boxerman J, Packard S, Rosen B, Weisskoff R. NMR imaging of changes in vascular morphology due to tumor angiogenesis. Magn Reson Med 1998;40:793–9.

[6] Boxerman JL, Hamberg LM, Rosen BR, Weisskoff RM. MR contrast due to intravascular magnetic susceptibility perturbations. Magn Reson Med 1995;34:555–66. doi:10.1002/mrm.1910340412.

[7] Kiselev VG, Strecker R, Ziyeh S, Speck O, Hennig J. Vessel size imaging in humans. Magn Reson Med 2005;53:553–63. doi:Doi 10.1002/Mrm.20383.

[8] Østergaard L, Chesler DA, Weisskoff RM, Sorensen AG, Rosen BR. Modeling Cerebral Blood Flow and Flow Heterogeneity from Magnetic Resonance Residue Data. J Cereb Blood Flow Metab 1999;19:690–9. doi:10.1097/00004647-199906000-00013.

[9] Quarles CC, Gore JC, Xu L, Yankeelov TE. Comparison of dual-echo DSC-MRI- and DCE-MRI-derived contrast agent kinetic parameters. Magn Reson Imaging 2012;30:944–53. doi:10.1016/j.mri.2012.03.008.

[10] Stokes AM, Semmineh N, Quarles CC. Validation of a T1 and T2* leakage correction method based on multiecho dynamic susceptibility contrast MRI using MION as a reference standard. Magn Reson Med 2016;76:613–25. doi:10.1002/mrm.25906.

[11] Stokes AM, Skinner JT, Yankeelov T, Quarles CC. Assessment of a simplified spin and gradient echo (sSAGE) approach for human brain tumor perfusion imaging. Magn Reson Imaging 2016;34:1248–55. doi:http://dx.doi.org/10.1016/j.mri.2016.07.004.

[12] Stokes AM, Quarles CC. A simplified spin and gradient echo approach for brain tumor perfusion imaging. Magn Reson Med 2016;75:356–62. doi:10.1002/mrm.25591.

[13] Newton AT, Pruthi S, Stokes AM, Skinner JT, Quarles CC. Improving Perfusion Measurement in DSC-MRI Through the Use of Multi-echo Information for AIF Determination. AJNR Am J Neuroradiol n.d.;in press.

[14] Cramer SP, Larsson HB. Accurate determination of blood-brain barrier permeability using dynamic contrast-enhanced T1-weighted MRI: a simulation and in vivo study on healthy subjects and multiple sclerosis patients. J Cereb Blood Flow Metab 2014;34:1655–65. doi:10.1038/jcbfm.2014.126.

Figures

ΔR₂^* (top) and ΔR₂ (bottom) curves white matter and grey matter in five patients with MS. Each patient is color-coded by their quality of life metric (FAMS score, range 46 to 167, where higher scores indicate better QoL). Higher peak ΔR₂^* and ΔR₂ were observed for patients with higher FAMS scores.

Normalized T₁-weighted signals (extrapolated to TE = 0) are shown in WM and GM across the first five patients with MS. Higher contrast extravasation is observed in GM and in patients with higher QoL scores. Work is ongoing to quantify permeability in these subjects.

T₂-weighted FLAIR, macrovascular CBV, and microvascular CBV in two patients (high FAMS score on left, low FAMS score on right). Higher CBV is observed in the patient with higher FAMS score, consistent with the ΔR₂^* and ΔR₂ curves.

Macrovascular (top) and microvascular (bottom) CBF in the same two patients. Higher macrovascular and microvascular CBF is observed in the patient with a higher FAMS score.

Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)

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