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.

Conventional magnetic resonance images are usually evaluated using the image signal contrast between tissues and not based on their absolute signal intensities. Quantification of tissue parameters, such as relaxation rates and proton density, would provide an absolute scale; however, these methods have mainly been performed in a research setting. The development of rapid quantification, with scan times in the order of 6 minutes for full head coverage, has provided the prerequisites for clinical use. The aim of this review article was to introduce a specific quantification method and synthesis of contrast-weighted images based on the acquired absolute values, and to present automatic segmentation of brain tissues and measurement of myelin based on the quantitative values, along with application of these techniques to various brain diseases. The entire technique is referred to as “SyMRI” in this review. SyMRI has shown promising results in previous studies when used for multiple sclerosis, brain metastases, Sturge-Weber syndrome, idiopathic normal pressure hydrocephalus, meningitis, and postmortem imaging.

Radiological images have been assessed qualitatively in most clinical settings by the expert eyes of radiologists and other clinicians. On the other hand, quantification of radiological images has the potential to detect early disease that may be difficult to detect with human eyes, complement or replace biopsy, and provide clear differentiation of disease stage. Further, objective assessment by quantification is a prerequisite of personalized/precision medicine. This review article aims to summarize and discuss how the variability of quantitative values derived from radiological images are induced by a number of factors and how these variabilities are mitigated and standardization of the quantitative values are achieved. We discuss the variabilities of specific biomarkers derived from magnetic resonance imaging and computed tomography, and focus on diffusion-weighted imaging, relaxometry, lung density evaluation, and computer-aided computed tomography volumetry. We also review the sources of variability and current efforts of standardization of the rapidly evolving techniques, which include radiomics and artificial intelligence.

Low-field magnetic resonance imaging (MRI) systems have seen a renaissance recently due to improvements in technology (both hardware and software). Originally, the performance of low-field MRI systems was rated lower than their actual clinical usefulness, and they were viewed as low-cost but poorly performing systems. However, various applications similar to high-field MRI systems (1.5 T and 3 T) have gradually become possible, culminating with high-performance low-field MRI systems and their adaptations now being proposed that have unique advantages over high-field MRI systems in various aspects. This review article describes the physical characteristics of low-field MRI systems and presents both their advantages and disadvantages for clinical use (past to present), along with their cutting-edge clinical applications.

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.