Background and Objectives The glymphatic system is a whole-brain perivascular network, which promotes CSF/interstitial fluid exchange. Alterations to this system may play a pivotal role in amyloid β (Aβ) accumulation. However, its involvement in Alzheimer disease (AD) pathogenesis is not fully understood. Here, we investigated the changes in noninvasive MRI measurements related to the perivascular network in patients with mild cognitive impairment (MCI) and AD. Additionally, we explored the associations of MRI measures with neuropsychological score, PET standardized uptake value ratio (SUVR), and Aβ deposition. Methods MRI measures, including perivascular space (PVS) volume fraction (PVSVF), fractional volume of free water in white matter (FW-WM), and index of diffusivity along the perivascular space (ALPS index) of patients with MCI, those with AD, and healthy controls from the Alzheimer9s Disease Neuroimaging Initiative database were compared. MRI measures were also correlated with the levels of CSF biomarkers, PET SUVR, and cognitive score in the combined subcohort of patients with MCI and AD. Statistical analyses were performed with age, sex, years of education, and APOE status as confounding factors. Results In total, 36 patients with AD, 44 patients with MCI, and 31 healthy controls were analyzed. Patients with AD had significantly higher total, WM, and basal ganglia PVSVF (Cohen d = 1.15–1.48; p < 0.001) and FW-WM (Cohen d = 0.73; p < 0.05) and a lower ALPS index (Cohen d = 0.63; p < 0.05) than healthy controls. Meanwhile, the MCI group only showed significantly higher total (Cohen d = 0.99; p < 0.05) and WM (Cohen d = 0.91; p < 0.05) PVSVF. Low ALPS index was associated with lower CSF Aβ42 (r_s = 0.41, p_fdr = 0.026), FDG-PET uptake (r_s = 0.54, p_fdr < 0.001), and worse multiple cognitive domain deficits. High FW-WM was also associated with lower CSF Aβ42 (r_s = −0.47, p_fdr = 0.021) and worse cognitive performances. Discussion Our study indicates that changes in PVS-related MRI parameters occur in MCI and AD, possibly due to impairment of the glymphatic system. We also report the associations between MRI parameters and Aβ deposition, neuronal change, and cognitive impairment in AD.

Magnetization transfer (MT) imaging has been widely used for estimating myelin content in the brain. Recently, two other approaches, namely simultaneous tissue relaxometry of R₁ and R₂ relaxation rates and proton density (SyMRI) and the ratio of T₁-weighted to T₂-weighted images (T₁w/T₂w ratio), were also proposed as methods for measuring myelin. SyMRI and MT imaging have been reported to correlate well with actual myelin by histology. However, for T₁w/T₂w ratio, such evidence is limited. In 20 healthy adults, we examined the correlation between these three methods, using MT saturation index (MT_sat) for MT imaging. After calibration, white matter (WM) to gray matter (GM) contrast was the highest for SyMRI among these three metrics. Even though SyMRI and MT_sat showed strong correlation in the WM (r = 0.72), only weak correlation was found between T₁w/T₂w and SyMRI (r = 0.45) or MT_sat (r = 0.38) (correlation coefficients significantly different from each other, with p values < 0.001). In subcortical and cortical GM, these measurements showed moderate to strong correlations to each other (r = 0.54 to 0.78). In conclusion, the high correlation between SyMRI and MT_sat indicates that both methods are similarly suited to measure myelin in the WM, whereas T₁w/T₂w ratio may be less optimal.

Objective: Aging is the highest risk factor for Parkinson disease (PD). Under physiological conditions, spermidine and spermine experimentally enhance longevity via autophagy induction. Accordingly, we evaluated the ability of each polyamine metabolite to act as an age‐related, diagnostic, and severity‐associated PD biomarker.Methods: Comprehensive metabolome analysis of plasma was performed in Cohort A (controls, n = 45; PD, n = 145), followed by analysis of 7 polyamine metabolites in Cohort B (controls, n = 49; PD, n = 186; progressive supranuclear palsy, n = 19; Alzheimer disease, n = 23). Furthermore, 20 patients with PD who were successively examined within Cohort B were studied using diffusion tensor imaging (DTI). Association of each polyamine metabolite with disease severity was assessed according to Hoehn and Yahr stage (H&Y) and Unified Parkinson's Disease Rating Scale motor section (UPDRS‐III). Additionally, the autophagy induction ability of each polyamine metabolite was examined in vitro in various cell lines.Results: In Cohort A, N8‐acetylspermidine and N‐acetylputrescine levels were significantly and mildly elevated in PD, respectively. In Cohort B, spermine levels and spermine/spermidine ratio were significantly reduced in PD, concomitant with hyperacetylation. Furthermore, N1,N8‐diacetylspermidine levels had the highest diagnostic value, and correlated with H&Y, UPDRS‐III, and axonal degeneration quantified by DTI. The spermine/spermidine ratio in controls declined with age, but was consistently suppressed in PD. Among polyamine metabolites, spermine was the strongest autophagy inducer, especially in SH‐SY5Y cells. No significant genetic variations in 5 genes encoding enzymes associated with spermine/spermidine metabolism were detected compared with controls.Interpretation: Spermine synthesis and N1,N8‐diacetylspermidine may respectively be useful diagnostic and severity‐associated biomarkers for PD. ANN NEUROL 2019;86:251–263

Objectives: The aim of this study was to evaluate the linearity, bias, intrascanner repeatability, and interscanner reproducibility of quantitative values derived from a multidynamic multiecho (MDME) sequence for rapid simultaneous relaxometry.Materials and Methods: The NIST/ISMRM (National Institute of Standards and Technology/International Society for Magnetic Resonance in Medicine) phantom, containing spheres with standardized T1 and T2 relaxation times and proton density (PD), and 10 healthy volunteers, were scanned 10 times on different days and 2 times during the same session, using the MDME sequence, on three 3 T scanners from different vendors. For healthy volunteers, brain volumetry and myelin estimation were performed based on the measured T1, T2, and PD. The measured phantom values were compared with reference values; volunteer values were compared with their averages across 3 scanners.Results: The linearity of both phantom and volunteer measurements in T1, T2, and PD values was very strong (R²= 0.973–1.000, 0.979–1.000, and 0.982–0.999, respectively) The highest intrascanner coefficients of variation (CVs) for T1, T2, and PD were 2.07%, 7.60%, and 12.86% for phantom data, and 1.33%, 0.89%, and 0.77% for volunteer data, respectively. The highest interscanner CVs of T1, T2, and PD were 10.86%, 15.27%, and 9.95% for phantom data, and 3.15%, 5.76%, and 3.21% for volunteer data, respectively. Variation of T1 and T2 tended to be larger at higher values outside the range of those typically observed in brain tissue. The highest intrascanner and interscanner CVs for brain tissue volumetry were 2.50% and 5.74%, respectively, for cerebrospinal fluid.Conclusions: Quantitative values derived from the MDME sequence are overall robust for brain relaxometry and volumetry on 3 T scanners from different vendors. Caution is warranted when applying MDME sequence on anatomies with relaxometry values outside the range of those typically observed in brain tissue.

Recently, non-Gaussian diffusion-weighted imaging (DWI) techniques, including q-space imaging (QSI) and diffusional kurtosis imaging (DKI), have emerged as advanced methods to evaluate tissue microstructure in vivo using water diffusion. QSI and DKI have shown promising results in clinical applications, such as in the evaluation of brain tumors (e.g., grading gliomas), degenerative diseases (e.g., specific diagnosis of Parkinson disease), demyelinating diseases (e.g., assessment of normal-appearing tissue of multiple sclerosis), and cerebrovascular diseases (e.g., assessment of the microstructural environment of fresh infarctions). Representative metrics in clinical use are the full width at half maximum, also known as the mean displacement of the probability density function curve, which is derived from QSI, and diffusional kurtosis, which is derived from DKI. These new metrics may provide information on tissue structure in addition to that provided by conventional Gaussian DWI investigations that use the apparent diffusion coefficient and fractional anisotropy, recognized indices for evaluating disease and normal development in the brain and spine. In some clinical situations, sensitivity for detecting pathological conditions is higher using QSI and DKI than conventional DWI and diffusion tensor imaging (DTI) because DWI and DTI calculations are based on the assumption that water molecules follow a Gaussian distribution, whereas hindrance of the distribution of water molecules by complex and restricted structures in actual neural tissues produces distributions that are far from Gaussian. We review the technical aspects and clinical applications of QSI and DKI, focusing on clinical use and in vivo studies and highlighting differences from conventional diffusional metrics.