Editorial for “Preliminary Assessment of Intravoxel Incoherent Motion Diffusion‐Weighted MRI (IVIM‐DWI) Metrics in Alzheimer's Disease”

Differentiation between Alzheimer’s disease (AD) and mild cognitive impairment (MCI) is important, as the protocol of management and prognosis is different. Routine structural magnetic resonance imaging (MRI) has a limited role in this issue. Several neuroimaging metrics were used to assess brain changes in subjects with AD and MCI, but their results are overlapping. We need to provide imaging biomarkers that can help with the diagnosis of AD and differentiation from MCI. Voxel-based morphometry (VBM)-based methods were used to assess volumetric brain changes in AD and MCI relative to health controls (HCs). VBM shows widespread gray matter changes mainly in the temporal lobe, amygdala, and hippocampus in AD compared to HC due to increased deposition of neurofibrillary tangles in patients with AD. Few studies discus the role of VBM in different regions of the brain parenchyma in patients with AD from differentiation from MCI and HC. One study discusses the role of VBM combined with diffusion-weighted imaging (DWI) in the evaluation of demented patients. VBM is sensitive to subtle changes in the gray matter (GM), and DWI is sensitive to the changes of the white matter (WM). There is a difference in the spatiotemporal distribution at VBM, and DWI measures may be related to their differing underlying sensitivities to the GM and WM. Intravoxel incoherent motion (IVIM) is an advanced module of DWI that has the ability to analyze non-Gaussian diffusion of the tissue using a biexponential fit. This sequence gives an idea about diffusion and perfusion properties of the tissue without the injection of contrast medium. IVIM is sensitive to both molecular diffusions in the tissues and to microcirculation (perfusion) based on the assumption that the flow of blood through capillaries mimics a diffusion process, due to the pseudorandom organization of capillaries in tissue. IVIM can provide quantitative maps of the density of small, functional blood vessels related to flowing blood volume fraction. Separation of perfusion from diffusion at IVIM module requires high signal-to-noise ratios, with advanced postprocessing to overcome some of these technical challenges. In this issue, Bergamino et al describe the role of neuroimaging metrics of IVIM and VBM in the differentiation of AD, MCI, and HC and correlates these metrics with tests for cognition. This study was done on 49 subjects, AD (n = 13), MCI (n = 12), and HC (n = 24). All groups underwent IVIM using seven b-values (25, 50, 75,100, 200, 500, and 1000 s/mm, anatomical T1-weighted imaging (T1WI) using a 3D magnetization-prepared rapid acquisition gradient echo (MP-RAGE) sequence and cognitive tests. VBM of different regions of the brain was calculated and metrics of IVIM-DWI maps (pure diffusion coefficient [D], pseudodiffusion coefficient [D*], and perfusion fraction [f]) were generated and calculated. This study reported clusters of significant groupwise differences of all IVIM and VBM in the temporal lobe, hippocampus, and amygdala (P = 0.05). The VBM showed a significant difference between AD and MCI and between AD and HC and insignificant differences between MCI and HC. The ADC and IVIM-D showed significant differences (P = 0.05) between MCI and HC, mainly in the hippocampus and amygdala. In addition, there were clusters of correlations between neuroimaging metrics (ADC, IVIM-D, IVIM-f, and VBM) for memory (amygdala and hippocampus), visuospatial skill (left caudate), and orientation (amygdala and hippocampus) and a congestive test in cognitively impaired groups (P = 0.05). In conclusion, this study introduces the initial results of IVIM and VBM in the evaluation of the GM and WM of demented patients and the differentiation of AD from MCI. The new matrices of IVIM combined with VBM can help in the diagnosis and differentiation of AD and MCI from HC. Further multicenter studies with a large number of patients will validate this study in the future and can be applied in clinical practice. In addition, longitudinal studies on patients with MCI for prediction of a converter to AD as