Viscoelastic properties of the brain reflect tissue architecture at multiple length scales. However, little is known about the relation between vital tissue functions, such as perfusion, and the macroscopic mechanical properties of cerebral tissue. In this study, arterial spin labelling is paired with magnetic resonance elastography to investigate the relationship between tissue stiffness and cerebral blood flow (CBF) in the in vivo human brain. The viscoelastic modulus, | G*|, and CBF were studied in deep gray matter (DGM) of 14 healthy male volunteers in the following sub-regions: putamen, nucleus accumbens, hippocampus, thalamus, globus pallidus, and amygdala. CBF was further normalized by vessel area data to obtain the flux rate q which is proportional to the perfusion pressure gradient. The striatum (represented by putamen and nucleus accumbens) was distinct from the other DGM regions by displaying markedly higher stiffness and perfusion values. q was a predictive marker for DGM stiffness as analyzed by linear regression | G*| = q·(4.2 ± 0.6)kPa·s + (0.80 ± 0.06)kPa ( R 2 = 0.92, P = 0.006). These results suggest a high sensitivity of MRE in DGM to perfusion pressure. The distinct mechano-vascular properties of striatum tissue, as compared to the rest of DGM, may reflect elevated perfusion pressure, which could explain the well-known susceptibility of the putamen to hemorrhages.
Dementia due to Alzheimer's Disease (AD) is a neurodegenerative disease for which treatment strategies at an early stage are of great clinical importance. So far, there is still a lack of non-invasive diagnostic tools to sensitively detect AD in early stages and to predict individual disease progression. Magnetic resonance elastography (MRE) of the brain may be a promising novel tool. In this proof-of-concept study, we investigated whether multifrequency-MRE (MMRE) can detect differences in hippocampal stiffness between patients with clinical diagnosis of dementia due to AD and healthy controls (HC). Further, we analyzed if the combination of three MRI-derived parameters, i.e., hippocampal stiffness, hippocampal volume and mean diffusivity (MD), improves diagnostic accuracy. Diagnostic criteria for probable dementia due to AD were in line with the NINCDS-ADRDA criteria and were verified through history-taking (patient and informant), neuropsychological testing, routine blood results and routine MRI to exclude other medical causes of a cognitive decline. 21 AD patients and 21 HC (median age 75 years) underwent MMRE and structural MRI, from which hippocampal volume and MD were calculated. From the MMRE-images maps of the magnitude |G*| and phase angle φ of the complex shear modulus were reconstructed using multifrequency inversion. Median values of |G*| and φ were extracted within three regions of interest (hippocampus, thalamus and whole brain white matter). To test the predictive value of the main outcome parameters, we performed receiver operating characteristic (ROC) curve analyses. Hippocampal stiffness (|G*|) and viscosity (φ) were significantly lower in the patient group (both p < 0.001). ROC curve analyses showed an area under the curve (AUC) for | G*| of 0.81 [95%CI 0.68-0.94]; with sensitivity 86%, specificity 67% for cutoff at |G*| = 980 Pa) and for φ an AUC of 0.79 [95%CI 0.66-0.93]. In comparison, the AUC of MD and hippocampal volume were 0.83 [95%CI 0.71-0.95] and 0.86 [95%CI 0.74-0.97], respectively. A combined ROC curve of |G*|, MD and hippocampal volume yielded a significantly improved AUC of 0.90 [95%CI 0.81-0.99]. In conclusion, we demonstrated reduced hippocampal stiffness and reduced hippocampal viscosity, as determined by MMRE, in patients with clinical diagnosis of dementia of the AD type. Diagnostic sensitivity was further improved by the combination with two other MRI-based hippocampal parameters. These findings motivate further investigation whether MMRE can detect decreased brain stiffness already in pre-dementia stages, and whether these changes predict cognitive decline.
Purpose To assess if higher‐resolution magnetic resonance elastography (MRE) is a technique that can measure the in vivo mechanical properties of brain tissue and is sensitive to early signatures of brain tissue degradation in patients with clinically isolated syndrome (CIS). Materials and Methods Seventeen patients with CIS and 33 controls were investigated by MRE with a 3T MRI scanner. Full‐wave field data were acquired at seven drive frequencies from 30 to 60 Hz. The spatially resolved higher‐resolution maps of magnitude |G*| and phase angle φ of the complex‐valued shear modulus were obtained in addition to springpot model parameters. These parameters were spatially averaged in white matter (WM) and whole‐brain regions and correlated with clinical and radiological parameters. Results Spatially resolved MRE revealed that CIS reduced WM viscoelasticity, independent of imaging markers of multiple sclerosis and clinical scores. |G*| was reduced by 14% in CIS (1.4 ± 0.2 kPa vs. 1.7 ± 0.2 kPa, P < 0.001, 95% confidence interval [CI] [–0.4, –0.1] kPa), while φ (0.66 ± 0.04 vs. 0.67 ± 0.04, P = 0.65, 95% CI [–0.04, 0.02]) remained unaltered. Springpot‐based shear elasticity showed only a trend of CIS‐related reduction (3.4 ± 0.5 kPa vs. 3.7 ± 0.5 kPa, P = 0.06, 95% CI [–0.6, 0.02] kPa) in the whole brain. Conclusion We demonstrate that CIS leads to significantly reduced elasticity of brain parenchyma, raising the prospect of using MRE as an imaging marker for subtle and diffuse tissue damage in neuroinflammatory diseases. J. Magn. Reson. Imaging 2016;44:51–58.
Detection and discrimination of neurodegenerative Parkinson syndromes are challenging clinical tasks and the use of standard T1- and T2-weighted cerebral magnetic resonance (MR) imaging is limited to exclude symptomatic Parkinsonism. We used a quantitative structural MR-based technique, MR-elastography (MRE), to assess viscoelastic properties of the brain, providing insights into altered tissue architecture in neurodegenerative diseases on a macroscopic level. We measured single-slice multifrequency MRE (MMRE) and three-dimensional MRE (3DMRE) in two neurodegenerative disorders with overlapping clinical presentation but different neuropathology - progressive supranuclear palsy (PSP: N = 16) and idiopathic Parkinson's disease (PD: N = 18) as well as in controls (N = 18). In PSP, both MMRE (Δμ = - 28.8%, Δα = - 4.9%) and 3DMRE (Δ|G*|: - 10.6%, Δφ: - 34.6%) were significantly reduced compared to controls, with a pronounced reduction within the lentiform nucleus (Δμ = - 34.6%, Δα = - 8.1%; Δ|G*|: - 7.8%, Δφ: - 44.8%). MRE in PD showed a comparable pattern, but overall reduction in brain elasticity was less severe reaching significance only in the lentiform nucleus (Δμ n.s., Δα = - 7.4%; Δ|G*|: - 6.9%, Δφ: n.s.). Beyond that, patients showed a close negative correlation between MRE constants and clinical severity. Our data indicate that brain viscoelasticity in PSP and PD is differently affected by the underlying neurodegeneration; whereas in PSP all MRE constants are reduced and changes in brain softness (reduced μ and |G*|) predominate those of viscosity (α and φ) in PD.
Cerebral viscoelastic constants can be measured in a noninvasive, image-based way by magnetic resonance elastography (MRE) for the detection of neurological disorders. However, MRE brain maps of viscoelastic constants are still limited by low spatial resolution. Here we introduce three-dimensional multifrequency MRE of the brain combined with a novel reconstruction algorithm based on a model-free multifrequency inversion for calculating spatially resolved viscoelastic parameter maps of the human brain corresponding to the dynamic range of shear oscillations between 30 and 60 Hz. Maps of two viscoelastic parameters, the magnitude and the phase angle of the complex shear modulus, |G*| and φ, were obtained and normalized to group templates of 23 healthy volunteers in the age range of 22 to 72 years. This atlas of the anatomy of brain mechanics reveals a significant contrast in the stiffness parameter |G*| between different anatomical regions such as white matter (WM; 1.252±0.260 kPa), the corpus callosum genu (CCG; 1.104±0.280 kPa), the thalamus (TH; 1.058±0.208 kPa) and the head of the caudate nucleus (HCN; 0.649±0.101 kPa). φ, which is sensitive to the lossy behavior of the tissue, was in the order of CCG (1.011±0.172), TH (1.037±0.173), CN (0.906±0.257) and WM (0.854±0.169). The proposed method provides the first normalized maps of brain viscoelasticity with anatomical details in subcortical regions and provides useful background data for clinical applications of cerebral MRE.
