Publications

In this paper, we present a deep learning method, DDMReg, for accurate registration between diffusion MRI (dMRI) datasets. In dMRI registration, the goal is to spatially align brain anatomical structures while ensuring that local fiber orientations remain consistent with the underlying white matter fiber tract anatomy. DDMReg is a novel method that uses joint whole-brain and tract-specific information for dMRI registration. Based on the successful VoxelMorph framework for image registration, we propose a novel registration architecture that leverages not only whole brain information but also tract-specific fiber orientation information. DDMReg is an unsupervised method for deformable registration between pairs of dMRI datasets: it does not require nonlinearly pre-registered training data or the corresponding deformation fields as ground truth. We perform comparisons with four state-of-the-art registration methods on multiple independently acquired datasets from different populations (including teenagers, young and elderly adults) and different imaging protocols and scanners. We evaluate the registration performance by assessing the ability to align anatomically corresponding brain structures and ensure fiber spatial agreement between different subjects after registration. Experimental results show that DDMReg obtains significantly improved registration performance compared to the state-of-the-art methods. Importantly, we demonstrate successful generalization of DDMReg to dMRI data from different populations with varying ages and acquired using different acquisition protocols and different scanners.

Transmembrane water exchange is a potential biomarker in the diagnosis and understanding of cancers, brain disorders, and other diseases. Filter-exchange imaging (FEXI), a special case of diffusion exchange spectroscopy adapted for clinical applications, has the potential to reveal different physiological water exchange processes. However, it is still controversial whether modulating the diffusion encoding gradient direction can affect the apparent exchange rate (AXR) measurements of FEXI in white matter (WM) where water diffusion shows strong anisotropy. In this study, we explored the diffusion-encoding direction dependence of FEXI in human brain white matter by performing FEXI with 20 diffusion-encoding directions on a clinical 3T scanner in-vivo. The results show that the AXR values measured when the gradients are perpendicular to the fiber orientation (0.77 ± 0.13 s - 1, mean ± standard deviation of all the subjects) are significantly larger than the AXR estimates when the gradients are parallel to the fiber orientation (0.33 ± 0.14 s - 1, p < 0.001) in WM voxels with coherently-orientated fibers. In addition, no significant correlation is found between AXRs measured along these two directions, indicating that they are measuring different water exchange processes. What’s more, only the perpendicular AXR rather than the parallel AXR shows dependence on axonal diameter, indicating that the perpendicular AXR might reflect transmembrane water exchange between intra-axonal and extra-cellular spaces. Further finite difference (FD) simulations having three water compartments (intra-axonal, intra-glial, and extra-cellular spaces) to mimic WM micro-environments also suggest that the perpendicular AXR is more sensitive to the axonal water transmembrane exchange than parallel AXR. Taken together, our results show that AXR measured along different directions could be utilized to probe different water exchange processes in WM.

White-matter abnormalities, including increases in extracellular free-water, are implicated in the pathophysiology of schizophrenia. Recent advances in diffusion magnetic resonance imaging (MRI) enable free-water levels to be indexed. However, the brain levels in patients with schizophrenia have not yet been systematically investigated. We aimed to meta-analyse white-matter free-water levels in patients with schizophrenia compared to healthy volunteers. We performed a literature search in EMBASE, MEDLINE, and PsycINFO databases. Diffusion MRI studies reporting free-water in patients with schizophrenia compared to healthy controls were included. We investigated the effect of demographic variables, illness duration, chlorpromazine equivalents of antipsychotic medication, type of scanner, and clinical symptoms severity on free-water measures. Ten studies, including five of first episode of psychosis have investigated free-water levels in schizophrenia, with significantly higher levels reported in whole-brain and specific brain regions (including corona radiata, internal capsule, superior and inferior longitudinal fasciculus, cingulum bundle, and corpus callosum). Six studies, including a total of 614 participants met the inclusion criteria for quantitative analysis. Whole-brain free-water levels were significantly higher in patients relative to healthy volunteers (Hedge’s g = 0.38, 95% confidence interval (CI) 0.07-0.69, p = 0.02). Sex moderated this effect, such that smaller effects were seen in samples with more females (z = -2.54, p < 0.05), but antipsychotic dose, illness duration and symptom severity did not. Patients with schizophrenia have increased free-water compared to healthy volunteers. Future studies are necessary to determine the pathological sources of increased free-water, and its relationship with illness duration and severity.

INTRODUCTION: Cardiorespiratory fitness is not limited by pulmonary mechanical reasons in the majority of adults. However, the degree to which lung function contributes to exercise response patterns among ostensibly healthy individuals remains unclear. METHODS: We examined 2314 Framingham Heart Study participants who underwent cardiopulmonary exercise testing (CPET) and pulmonary function testing. We investigated the association of FEV1, FVC, FEV1/FVC and DLCO with the primary outcome of peak VO2, along with other CPET parameters using multivariable linear regression. Finally, we investigated the association of total and peripheral pulmonary blood vessel volume with peak VO2. RESULTS: We found lower FEV1, FVC and DLCO were associated with lower peak VO2. For example, a one-liter lower FEV1 and FVC were associated with 7.1% (95% CI: 5.1%, 9.1%) and 6.0% (95% CI: 4.3%, 7.7%) lower peak VO2, respectively. By contrast, FEV1/FVC ratio was not associated with peak VO2. Lower lung function was associated with lower oxygen uptake efficiency slope oxygen pulse slope, VO2 at AT, VE at AT and breathing reserve. In addition, lower total and peripheral pulmonary blood vessel volume were associated with a lower peak VO2. CONCLUSION: In a large, community-based cohort of adults, we found lower FEV1, FVC and DLCO were associated with lower exercise capacity, as well as oxygen uptake efficiency slope and ventilatory efficiency. In addition, lower total and peripheral pulmonary blood vessel volume were associated with lower peak VO2. These findings underscore the importance of lung function and blood vessel volume as contributors to overall exercise capacity.

ABSTRACT: In the field of neuropsychiatry, neuroinflammation is one of the prevailing hypotheses to explain the pathophysiology of mood and psychotic disorders. Neuroinflammation encompasses an ill-defined set of pathophysiological processes in the central nervous system that cause neuronal or glial atrophy or death and disruptions in neurotransmitter signaling, resulting in cognitive and behavioral changes. Positron emission tomography for the brain-based translocator protein has been shown to be a useful tool to measure glial activation in neuropsychiatric disorders. Recent neuroimaging studies also indicate a potential disruption in the choroid plexus and blood-brain barrier, which modulate the transfer of ions, molecules, toxins, and cells from the periphery into the brain. Simultaneously, peripheral inflammatory markers have consistently been shown to be altered in mood and psychotic disorders. The crosstalk (i.e., the communication between peripheral and central inflammatory pathways) is not well understood in these disorders, however, and neuroimaging studies hold promise to shed light on this complex process. In the current Perspectives article, we discuss the neuroimaging insights into neuroimmune crosstalk offered in selected works. Overall, evidence exists for peripheral immune cell infiltration into the central nervous system in some patients, but the reason for this is unknown. Future neuroimaging studies should aim to extend our knowledge of this system and the role it likely plays in symptom onset and recurrence.

Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain’s white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain’s structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain’s structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain’s white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.

Rationale: Multiple studies have demonstrated an increased risk of chronic obstructive pulmonary disease (COPD) in heterozygous carriers of the AAT (alpha-1 antitrypsin) Z allele. However, it is not known if MZ subjects with COPD are phenotypically different from noncarriers (MM genotype) with COPD. Objectives: To assess if MZ subjects with COPD have different clinical features compared with MM subjects with COPD. Methods: Genotypes of SERPINA1 were ascertained by using whole-genome sequencing data in three independent studies. We compared outcomes between MM subjects with COPD and MZ subjects with COPD in each study and combined the results in a meta-analysis. We performed longitudinal and survival analyses to compare outcomes in MM and MZ subjects with COPD over time. Measurements and Main Results: We included 290 MZ subjects with COPD and 6,184 MM subjects with COPD across the three studies. MZ subjects had a lower FEV1% predicted and greater quantitative emphysema on chest computed tomography scans compared with MM subjects. In a meta-analysis, the FEV1 was 3.9% lower (95% confidence interval [CI], -6.55% to -1.26%) and emphysema (the percentage of lung attenuation areas <-950 HU) was 4.14% greater (95% CI, 1.44% to 6.84%) in MZ subjects. We found one gene, PGF (placental growth factor), to be differentially expressed in lung tissue from one study between MZ subjects and MM subjects. Conclusions: Carriers of the AAT Z allele (those who were MZ heterozygous) with COPD had lower lung function and more emphysema than MM subjects with COPD. Taken with the subtle differences in gene expression between the two groups, our findings suggest that MZ subjects represent an endotype of COPD.

Rationale: The ability of peripheral blood biomarkers to assess chronic obstructive pulmonary disease (COPD) risk and progression is unknown. Genetics and gene expression may capture important aspects of COPD-related biology that predict disease activity. Objectives: Develop a transcriptional risk score (TRS) for COPD and assess the contribution of the TRS and a polygenic risk score (PRS) for disease susceptibility and progression. Methods: We randomly split 2,569 COPDGene (Genetic Epidemiology of COPD) participants with whole-blood RNA sequencing into training (n = 1,945) and testing (n = 624) samples and used 468 ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points) COPD cases with microarray data for replication. We developed a TRS using penalized regression (least absolute shrinkage and selection operator) to model FEV1/FVC and studied the predictive value of TRS for COPD (Global Initiative for Chronic Obstructive Lung Disease 2-4), prospective FEV1 change (ml/yr), and additional COPD-related traits. We adjusted for potential confounders, including age and smoking. We evaluated the predictive performance of the TRS in the context of a previously derived PRS and clinical factors. Measurements and Main Results: The TRS included 147 transcripts and was associated with COPD (odds ratio, 3.3; 95% confidence interval [CI], 2.4-4.5; P < 0.001), FEV1 change (β, -17 ml/yr; 95% CI, -28 to -6.6; P = 0.002), and other COPD-related traits. In ECLIPSE cases, we replicated the association with FEV1 change (β, -8.2; 95% CI, -15 to -1; P = 0.025) and the majority of other COPD-related traits. Models including PRS, TRS, and clinical factors were more predictive of COPD (area under the receiver operator characteristic curve, 0.84) and annualized FEV1 change compared with models with one risk score or clinical factors alone. Conclusions: Blood transcriptomics can improve prediction of COPD and lung function decline when added to a PRS and clinical risk factors.

BACKGROUND: Interstitial lung abnormalities (ILA) share many features with idiopathic pulmonary fibrosis; however, it is not known if ILA are associated with decreased mean telomere length (MTL). METHODS: Telomere length was measured with quantitative PCR in the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) and Age Gene/Environment Susceptibility Reykjavik (AGES-Reykjavik) cohorts and Southern blot analysis was used in the Framingham Heart Study (FHS). Logistic and linear regression were used to assess the association between ILA and MTL; Cox proportional hazards models were used to assess the association between MTL and mortality. RESULTS: In all three cohorts, ILA were associated with decreased MTL. In the COPDGene and AGES-Reykjavik cohorts, after adjustment there was greater than twofold increase in the odds of ILA when comparing the shortest quartile of telomere length to the longest quartile (OR 2.2, 95% CI 1.5-3.4, p=0.0001, and OR 2.6, 95% CI 1.4-4.9, p=0.003, respectively). In the FHS, those with ILA had shorter telomeres than those without ILA (-767 bp, 95% CI 76-1584 bp, p=0.03). Although decreased MTL was associated with chronic obstructive pulmonary disease (OR 1.3, 95% CI 1.1-1.6, p=0.01) in COPDGene, the effect estimate was less than that noted with ILA. There was no consistent association between MTL and risk of death when comparing the shortest quartile of telomere length in COPDGene and AGES-Reykjavik (HR 0.82, 95% CI 0.4-1.7, p=0.6, and HR 1.2, 95% CI 0.6-2.2, p=0.5, respectively). CONCLUSION: ILA are associated with decreased MTL.