Recent evidence shows that neuroinflammation plays a role in many neurological diseases including mild cognitive impairment (MCI) and Alzheimer's disease (AD), and that free water (FW) modeling from clinically acquired diffusion MRI (DTI-like acquisitions) can be sensitive to this phenomenon. This FW index measures the fraction of the diffusion signal explained by isotropically unconstrained water, as estimated from a bi-tensor model. In this study, we developed a simple but powerful whole-brain FW measure designed for easy translation to clinical settings and potential use as a priori outcome measure in clinical trials. These simple FW measures use a “safe” white matter (WM) mask without gray matter (GM)/CSF partial volume contamination (WMsafe) near ventricles and sulci. We investigated if FW inside the WMsafe mask, including and excluding areas of white matter damage such as white matter hyperintensities (WMHs) as shown on T2 FLAIR, computed across the whole white matter could be indicative of diagnostic grouping along the AD continuum. After careful quality control, 81 cognitively normal controls (NC), 103 subjects with MCI and 42 with AD were selected from the ADNIGO and ADNI2 databases. We show that MCI and AD have significantly higher FW measures even after removing all partial volume contamination. We also show, for the first time, that when WMHs are removed from the masks, the significant results are maintained, which demonstrates that the FW measures are not just a byproduct of WMHs. Our new and simple FW measures can be used to increase our understanding of the role of inflammation-associated edema in AD and may aid in the differentiation of healthy subjects from MCI and AD patients.

Alzheimer’s disease neurodegeneration is thought to spread across anatomically and functionally connected brain regions. However, the precise sequence of spread remains ambiguous. The prevailing model used to guide in vivo human neuroimaging and non-human animal research assumes that Alzheimer’s degeneration starts in the entorhinal cortices, before spreading to the temporoparietal cortex. Challenging this model, we previously provided evidence that in vivo markers of neurodegeneration within the nucleus basalis of Meynert (NbM), a subregion of the basal forebrain heavily populated by cortically projecting cholinergic neurons, precedes and predicts entorhinal degeneration. There have been few systematic attempts at directly comparing staging models using in vivo longitudinal biomarker data, and none to our knowledge testing if comparative evidence generalizes across independent samples. Here we addressed the sequence of pathological staging in Alzheimer’s disease using two independent samples of the Alzheimer’s Disease Neuroimaging Initiative (n1 = 284; n2 = 553) with harmonized CSF assays of amyloid-β and hyperphosphorylated tau (pTau), and longitudinal structural MRI data over 2 years. We derived measures of grey matter degeneration in a priori NbM and the entorhinal cortical regions of interest. To examine the spreading of degeneration, we used a predictive modelling strategy that tests whether baseline grey matter volume in a seed region accounts for longitudinal change in a target region. We demonstrated that predictive spread favoured the NbM→entorhinal over the entorhinal→NbM model. This evidence generalized across the independent samples. We also showed that CSF concentrations of pTau/amyloid-β moderated the observed predictive relationship, consistent with evidence in rodent models of an underlying trans-synaptic mechanism of pathophysiological spread. The moderating effect of CSF was robust to additional factors, including clinical diagnosis. We then applied our predictive modelling strategy to an exploratory whole-brain voxel-wise analysis to examine the spatial specificity of the NbM→entorhinal model. We found that smaller baseline NbM volumes predicted greater degeneration in localized regions of the entorhinal and perirhinal cortices. By contrast, smaller baseline entorhinal volumes predicted degeneration in the medial temporal cortex, recapitulating a prior influential staging model. Our findings suggest that degeneration of the basal forebrain cholinergic projection system is a robust and reliable upstream event of entorhinal and neocortical degeneration, calling into question a prevailing view of Alzheimer’s disease pathogenesis.

The vascular effects of antiangiogenic treatment may pose problems for evaluating brain tumor response based on contrast-enhanced magnetic resonance imaging (MRI). We used serial dynamic contrast-enhanced MRI at 12 T to assess vascular responses to antiangiogenic versus steroid therapy. Athymic rats with intracerebral U87MG human glioma (n = 17) underwent susceptibility-weighted perfusion MRI with ferumoxytol, a solely intravascular ultrasmall superparamagnetic iron oxide (USPIO) nanoparticle, followed by T1-weighted dynamic gadodiamide-enhanced MRI to measure vascular permeability. Rats were imaged before and after 24, 48, and 72 h of treatment with the antiangiogenic agent bevacizumab or the corticosteroid dexamethasone. Contrast agent extravasation was seen rapidly after gadodiamide, but not with ferumoxytol administration. Bevacizumab significantly decreased the blood volume and decreased permeability in tumors as determined by increased time-to-peak enhancement. A single dose of 45 mg/kg bevacizumab resulted in changes analogous to dexamethasone given in an extremely high dose (12 mg/kg per day), and was significantly more effective than dexamethasone at 2 mg/kg per day. We conclude that dynamic perfusion MRI measurements with ferumoxytol USPIO to assess cerebral blood volume, along with dynamic gadodiamide-enhanced MR to assess vascular permeability, hold promise in more accurately detecting therapeutic responses to antiangiogenic therapy.

The accurate mapping of the tumor blood volume (TBV) fraction (v b ) is a highly desired imaging biometric goal. It is commonly thought that achieving this is difficult, if not impossible, when small molecule contrast reagents (CRs) are used for the T 1 -weighted (Dynamic-Contrast-Enhanced) DCE-MRI technique. This is because angiogenic malignant tumor vessels allow facile CR extravasation. Here, a three-site equilibrium water exchange model is applied to DCE-MRI data from the cerebrallyimplanted rat brain U87 glioma, a tumor exhibiting rapid CR extravasation. Analyses of segments of the (and the entire) DCE data time course with this "shutter-speed" pharmacokinetic model, which admits finite water exchange kinetics, allow TBV estimation from the first-pass segment. Pairwise parameter determinances were tested with grid searches of 2D parametric error surfaces. Tumor blood volume (v b ), as well as v e [the extracellular, extravascular space volume fraction], and K trans [a CR extravasation rate measure] parametric maps are presented. The role of the Patlak Plot in DCE-MRI is also considered.