Optimization and Validation of the DESIGNER dMRI preprocessing pipeline in white matter aging

Various diffusion MRI (dMRI) preprocessing pipelines are currently available to yield more accurate diffusion parameters. Here, we evaluated accuracy and robustness of the optimized Diffusion parameter EStImation with Gibbs and NoisE Removal (DESIGNER) pipeline in a large clinical dMRI dataset and using ground truth phantoms. DESIGNER has been modified to improve denoising and target Gibbs ringing for partial Fourier acquisitions. We compared the revisited DESIGNER (Dv2) (including denoising, Gibbs removal, correction for motion, EPI distortion, and eddy currents) against the original DESIGNER (Dv1) pipeline, minimal preprocessing (including correction for motion, EPI distortion, and eddy currents only), and no preprocessing on a large clinical dMRI dataset of 524 control subjects with ages between 25 and 75 years old. We evaluated the effect of specific processing steps on age correlations in white matter with DTI and DKI metrics. We also evaluated the added effect of minimal Gaussian smoothing to deal with noise and to reduce outliers in parameter maps compared to DESIGNER (Dv2)'s noise removal method. Moreover, DESIGNER (Dv2)'s updated noise and Gibbs removal methods were assessed using ground truth dMRI phantom to evaluate accuracy. Results show age correlation in white matter with DTI and DKI metrics were affected by the preprocessing pipeline, causing systematic differences in absolute parameter values and loss or gain of statistical significance. Both in clinical dMRI and ground truth phantoms, DESIGNER (Dv2) pipeline resulted in the smallest number of outlier voxels and improved accuracy in DTI and DKI metrics as noise was reduced and Gibbs removal was improved. Thus, DESIGNER (Dv2) provides more accurate and robust DTI and DKI parameter maps as compared to no preprocessing or minimal preprocessing

Mapping tissue microstructure of brain white matter in vivo in health and disease using diffusion MRI

Diffusion magnetic resonance imaging offers unique in vivo sensitivity to tissue microstructure in brain white matter, which undergoes significant changes during development and is compromised in virtually every neurological disorder. Yet, the challenge is to develop biomarkers that are specific to micrometer-scale cellular features in a human MRI scan of a few minutes. Here we quantify the sensitivity and specificity of a multicompartment diffusion modeling framework to the density, orientation and integrity of axons. We demonstrate that using a machine learning based estimator, our biophysical model captures the morphological changes of axons in early development, acute ischemia and multiple sclerosis (total N=821). The methodology of microstructure mapping is widely applicable in clinical settings and in large imaging consortium data to study development, aging and pathology.Comment: 4 figures, 5 supplementary figures, 1 supplementary tabl

Nanostructure-specific X-ray tomography reveals myelin levels, integrity and axon orientations in mouse and human nervous tissue

Myelin insulates neuronal axons and enables fast signal transmission, constituting a key component of brain development, aging and disease. Yet, myelin-specific imaging of macroscopic samples remains a challenge. Here, we exploit myelin’s nanostructural periodicity, and use small-angle X-ray scattering tensor tomography (SAXS-TT) to simultaneously quantify myelin levels, nanostructural integrity and axon orientations in nervous tissue. Proof-of-principle is demonstrated in whole mouse brain, mouse spinal cord and human white and gray matter samples. Outcomes are validated by 2D/3D histology and compared to MRI measurements sensitive to myelin and axon orientations. Specificity to nanostructure is exemplified by concomitantly imaging different myelin types with distinct periodicities. Finally, we illustrate the method’s sensitivity towards myelin-related diseases by quantifying myelin alterations in dysmyelinated mouse brain. This non-destructive, stain-free molecular imaging approach enables quantitative studies of myelination within and across samples during development, aging, disease and treatment, and is applicable to other ordered biomolecules or nanostructures

Denoising of diffusion MRI using random matrix theory

We introduce and evaluate a post-processing technique for fast denoising of diffusion-weighted MR images. By exploiting the intrinsic redundancy in diffusion MRI using universal properties of the eigenspectrum of random covariance matrices, we remove noise-only principal components, thereby enabling signal-to-noise ratio enhancements. This yields parameter maps of improved quality for visual, quantitative, and statistical interpretation. By studying statistics of residuals, we demonstrate that the technique suppresses local signal fluctuations that solely originate from thermal noise rather than from other sources such as anatomical detail. Furthermore, we achieve improved precision in the estimation of diffusion parameters and fiber orientations in the human brain without compromising the accuracy and spatial resolution.Veraart J., Novikov D.S., Christiaens D., Ades-aron B., Sijbers J., Fieremans E., ''Denoising of diffusion MRI using random matrix theory'', NeuroImage, vol. 142, pp. 394-406, 2016.status: publishe

Impact of MR‐guided PET reconstruction on tau detection and quantification with [18F]‐MK‐6240

Background Tau PET offers the potential of in vivo imaging neurofibrillary tangles (NFT) in the brain to assess Alzheimer’s disease (AD) progression and help guide the development of disease‐modifying treatments. In this study, we evaluate visualization and quantification of NFT using simultaneous acquisition of MRI and PET using [18F]‐MK‐6240 [1]. To overcome limitations in PET spatial resolution resulting in partial volume effects (PVE), MRI‐guided PET reconstruction using an asymmetrical Bowsher prior [2,3] was tested. Method Cognitively normal volunteers from the NYU Center Sleep and Brain Health Center (n=18, 15 female, age=65.4±5.6) underwent examination on a 3‐T integrated PET‐MRI system (Biograph mMR (Siemens Healthcare, Erlangen, Germany). MRI and PET were performed simultaneously; MRI contrasts included MPRAGE (1‐mm isotropic) for anatomy and ultrashort echo‐time (UTE) (1.6‐mm isotropic) for attenuation correction. [18F]‐MK‐6240 was injected intravenously and PET data was reconstructed 70‐90 min post‐injection. Standard iterative reconstruction (OSEM) (2‐mm isotropic) was compared to asymmetrical Bowsher [2,3] reconstruction with MPRAGE prior regularization weight β=30 (1x1x2mm3). PET standard uptake value (SUV) maps were co‐registered to respective MPRAGE, and (cerebellum or pons normalized) SUVR values were extracted from FreeSurfer‐derived regions of interest (ROIs). Results Example SUVR maps of standard PET and MR‐guided PET (Fig.1) reveal the Bowsher reconstruction to have more localized and increased focal uptake in the amygdala and cortical regions including the entorhinal, posterior cingulate and precuneus, with regional SUVR‐increases of 39%, 53%, 32%, and 16% respectively. Over all subjects (Fig.2), Bowsher reconstruction results in 30% or 48% higher SUVR, and an 64% or 84%‐increase of dynamic SUVR‐range (Fig.3) when normalized versus cerebellum or pons, respectively. These trends are emphasized for entorhinal cortex (Fig.4). Conclusions These initial results demonstrate that MR‐guided PET reconstruction of tau data may improve NFT localization and quantification. Study limitations include small number of high uptake tau‐cases and lack of standard such as histology for comparison. Future work will compare against CSF tau‐markers, cognition and comparison to other PVE correction methods. References: [1] Betthauser et al, JNM 2018;60(1):93–99; [2] Bowsher et al, Proc. IEEE Nucl. Sci. Symp., 2004(4):2488–2492; [3] Vunckx & Nuyts, Proc. IEEE Nucl. Sci. Symp., 2010:3262–3266

Diffusion MRI biomarkers of white matter microstructure vary nonmonotonically with increasing cerebral amyloid deposition

Beta amyloid (A beta) accumulation is the earliest pathological marker of Alzheimer's disease (AD), but early AD pathology also affects white matter (WM) integrity. We performed a cross-sectional study including 44 subjects (23 healthy controls and 21 mild cognitive impairment or early AD patients) who underwent simultaneous PET-MR using 18F-Florbetapir, and were categorized into 3 groups based on Ab burden: A beta- [mean mSUVr = 1.17]. Intergroup comparisons of diffusion MRI metrics revealed significant differences across multiple WM tracts. A beta i group displayed more restricted diffusion (higher fractional anisotropy, radial kurtosis, axonal water fraction, and lower radial diffusivity) than both A beta- and A beta+ groups. This nonmonotonic trend was confirmed by significant continuous correlations between mSUVr and diffusion metrics going in opposite direction for 2 cohorts: pooled A beta-/A beta i and pooled A beta i/A beta+. The transient period of increased diffusion restriction may be due to inflammation that accompanies rising A beta burden. In the later stages of A beta accumulation, neurodegeneration is the predominant factor affecting diffusion. (C) 2020 Elsevier Inc. All rights reserved

mTOR Inhibition with Sirolimus in Multiple System Atrophy: A Randomized, Double‐Blind, Placebo‐Controlled Futility Trial and 1‐Year Biomarker Longitudinal Analysis

BackgroundMultiple system atrophy (MSA) is a fatal neurodegenerative disease characterized by the aggregation of α-synuclein in glia and neurons. Sirolimus (rapamycin) is an mTOR inhibitor that promotes α-synuclein autophagy and reduces its associated neurotoxicity in preclinical models.ObjectiveTo investigate the efficacy and safety of sirolimus in patients with MSA using a futility design. We also analyzed 1-year biomarker trajectories in the trial participants.MethodsRandomized, double-blind, parallel group, placebo-controlled clinical trial at the New York University of patients with probable MSA randomly assigned (3:1) to sirolimus (2-6 mg daily) for 48 weeks or placebo. Primary endpoint was change in the Unified MSA Rating Scale (UMSARS) total score from baseline to 48 weeks. (ClinicalTrials.gov NCT03589976).ResultsThe trial was stopped after a pre-planned interim analysis met futility criteria. Between August 15, 2018 and November 15, 2020, 54 participants were screened, and 47 enrolled and randomly assigned (35 sirolimus, 12 placebo). Of those randomized, 34 were included in the intention-to-treat analysis. There was no difference in change from baseline to week 48 between the sirolimus and placebo in UMSARS total score (mean difference, 2.66; 95% CI, -7.35-6.91; P = 0.648). There was no difference in UMSARS-1 and UMSARS-2 scores either. UMSARS scores changes were similar to those reported in natural history studies. Neuroimaging and blood biomarker results were similar in the sirolimus and placebo groups. Adverse events were more frequent with sirolimus. Analysis of 1-year biomarker trajectories in all participants showed that increases in blood neurofilament light chain (NfL) and reductions in whole brain volume correlated best with UMSARS progression.ConclusionsSirolimus for 48 weeks was futile to slow the progression of MSA and had no effect on biomarkers compared to placebo. One-year change in blood NfL and whole brain atrophy are promising biomarkers of disease progression for future clinical trials. © 2022 International Parkinson and Movement Disorder Society