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Introduction: As hearing loss has been identified as an important risk factor for dementia, we aimed to assess the association between hearing loss and microstructural integrity of the brain., Methods: A total of 1086 dementia-free participants (mean age = 75.2 [standard deviation: 4.9], 61.4% female) of the population-based Atherosclerosis Risk in Communities (ARIC) study underwent hearing assessment (2016-2017) and magnetic resonance imaging of the brain (2011-2013). Microstructural integrity was determined with diffusion tensor imaging. Multivariable linear regression was used to investigate associations between hearing loss and microstructural integrity of different brain regions and white matter (WM) tracts., Results: Hearing loss was associated with lower WM microstructural integrity in the temporal lobe, lower gray matter integrity of the hippocampus, and with lower WM microstructural integrity of the limbic tracts and the uncinate fasciculus., Conclusion: Our results demonstrate that hearing loss is indepedently associated with lower microstructural integrity in brain regions that are important for different cognitive processes., (© 2020 the Alzheimer's Association.)

Objective: The disconnectivity hypothesis postulates that partial loss of connecting white matter fibers between brain regions contributes to the development of dementia. Using diffusion MRI to quantify global and tract-specific white matter microstructural integrity, we tested this hypothesis in a longitudinal population-based study., Methods: Global and tract-specific fractional anisotropy (FA) and mean diffusivity (MD) were obtained in 4,415 people without dementia (mean age 63.9 years, 55.0% women) from the prospective population-based Rotterdam Study with brain MRI between 2005 and 2011. We modeled the association of these diffusion measures with risk of dementia (follow-up until 2016) and with changes on repeated cognitive assessment after on average 5.4 years, adjusting for age, sex, education, macrostructural MRI markers, depressive symptoms, cardiovascular risk factors, and APOE genotype., Results: During a median follow-up of 6.8 years, 101 participants had incident dementia, of whom 83 had clinical Alzheimer disease (AD). Lower global values of FA and higher values of MD were associated with an increased risk of dementia (adjusted hazard ratio [95% confidence interval (CI)] per SD increase for MD 1.79 [1.44-2.23] and FA 0.65 [0.52-0.80]). Similarly, lower global values of FA and higher values of MD related to more cognitive decline in people without dementia (difference in global cognition per SD increase in MD [95% CI] was -0.04 [-0.07 to -0.01]). Associations were most profound in the projection, association, and limbic system tracts., Conclusions: Structural disconnectivity is associated with an increased risk of dementia and more pronounced cognitive decline in the general population., (© 2020 American Academy of Neurology.)

Subtle changes in white matter (WM) microstructure have been associated with normal aging and neurodegeneration. To study these associations in more detail, it is highly important that the WM tracts can be accurately and reproducibly characterized from brain diffusion MRI. In addition, to enable analysis of WM tracts in large datasets and in clinical practice it is essential to have methodology that is fast and easy to apply. This work therefore presents a new approach for WM tract segmentation: Neuro4Neuro, that is capable of direct extraction of WM tracts from diffusion tensor images using convolutional neural network (CNN). This 3D end-to-end method is trained to segment 25 WM tracts in aging individuals from a large population-based study (N ​= ​9752, 1.5T MRI). The proposed method showed good segmentation performance and high reproducibility, i.e., a high spatial agreement (Cohen's kappa, κ=0.72-0.83) and a low scan-rescan error in tract-specific diffusion measures (e.g., fractional anisotropy: ε=1%-5%). The reproducibility of the proposed method was higher than that of a tractography-based segmentation algorithm, while being orders of magnitude faster (0.5s to segment one tract). In addition, we showed that the method successfully generalizes to diffusion scans from an external dementia dataset (N ​= ​58, 3T MRI). In two proof-of-principle experiments, we associated WM microstructure obtained using the proposed method with age in a normal elderly population, and with disease subtypes in a dementia cohort. In concordance with the literature, results showed a widespread reduction of microstructural organization with aging and substantial group-wise microstructure differences between dementia subtypes. In conclusion, we presented a highly reproducible and fast method for WM tract segmentation that has the potential of being used in large-scale studies and clinical practice., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Study Objectives: Poor sleep may destabilize axonal integrity and deteriorate cerebral white matter. In middle-aged and older adults sleep problems increase alongside structural brain changes, but the temporal relation between these processes is poorly understood. We studied longitudinal associations between sleep and cerebral white matter microstructure., Methods: One thousand one persons (59.3 ± 7.9 years, 55% women) were followed across 5.8 years (3.9-10.8). Total sleep time (TST, hours), sleep efficiency (SE, percentage), sleep onset latency (SOL, minutes), and wake after sleep onset (WASO, minutes) were measured at baseline using a wrist-worn actigraph. White matter microstructure (global and tract-specific fractional anisotropy [FA] and mean diffusivity [MD]) was measured twice with diffusion tensor imaging (DTI)., Results: Poor sleep was associated with worse white matter microstructure up to 7 years later but did not predict trajectories of DTI over time. Longer TST was associated with higher global FA (β = 0.06, 95% CI: 0.01 to 0.12), but not with MD. Persons with higher SE had higher global FA (β = 0.01, 95% CI: 0.002 to 0.01) and lower MD (β = -0.01, 95% CI: -0.01 to -0.0004). Consistently, those with more WASO had lower global FA (β = -0.003, 95% CI: -0.005 to -0.001) and higher MD (β = 0.002, 95% CI: 0.0004 to 0.004). Global findings seemed to be driven by microstructural alterations in the cingulum, anterior forceps of corpus callosum, projection and association tracts., Conclusions: Middle-aged and older persons with more WASO, lower SE and shorter TST have worse microstructure of cerebral white matter. Microstructural alterations are most pronounced projection and association tracts, in the cingulum, and in the anterior forceps of corpus callosum., (© Sleep Research Society 2019. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.)

Previous studies have linked global burden of age-related white matter hyperintensities (WMHs) to cognitive impairment. We aimed to determine how WMHs in individual white matter connections relate to measures of cognitive function relative to measures of connectivity which do not take WMHs into account. Brain connectivity and WMH-related disconnectivity were derived from 3714 participants of the population-based Rotterdam Study. Connectivity was represented by the structural connectome, which was defined using diffusion tensor data, whereas the disconnectome represented disconnectivity due to WMH. The relationship between (dis)connectivity and cognitive measures was estimated using linear regression. We found that lower disconnectivity and higher connectivity corresponded to better cognitive function. There were many more significant associations with cognitive function in the disconnectome than in the connectome. Most connectome associations attenuated when disconnection was included in the model. WMH-related disconnectivity was especially related to worse executive functioning. Better cognitive speed corresponded to higher connectivity in specific connections independent of WMH presence. We conclude that WMH-related disconnectivity explains more variation in cognitive function than does connectivity. Efficient wiring in specific connections is important to information processing speed independent of WMH presence., (Copyright © 2018. Published by Elsevier Inc.)

With aging, the brain undergoes several structural changes. These changes reflect the normal aging process and are therefore not necessarily pathologic. In fact, better understanding of these normal changes is an important cornerstone to also disentangle pathologic changes. Several studies have investigated normal brain aging, both cross-sectional and longitudinal, and focused on a broad range of magnetic resonance imaging (MRI) markers. This study aims to comprise the different aspects in brain aging, by performing a comprehensive longitudinal assessment of brain aging, providing trajectories of volumetric (global and lobar; subcortical and cortical), microstructural, and focal (presence of microbleeds, lacunar or cortical infarcts) brain imaging markers in aging and the sequence in which these markers change in aging. Trajectories were calculated on 10,755 MRI scans that were acquired between 2005 and 2016 among 5286 persons aged 45 years and older from the population-based Rotterdam Study. The average number of MRI scans per participant was 2 scans (ranging from 1 to 4 scans), with a mean interval between MRI scans of 3.3 years (ranging from 0.2 to 9.5 years) and an average follow-up time of 5.2 years (ranging from 0.3 to 9.8 years). We found that trajectories of the different volumetric, microstructural, and focal markers show nonlinear curves, with accelerating change with advancing age. We found earlier acceleration of change in global and lobar volumetric and microstructural markers in men compared with women. For subcortical and cortical volumes, results show a mix of more linear and nonlinear trajectories, either increasing, decreasing, or stable over age for the subcortical and cortical volume and thickness. Differences between men and women are visible in several parcellations; however, the direction of these differences is mixed. The presence of focal markers show a nonlinear increase with age, with men having a higher probability for cortical or lacunar infarcts. The data presented in this study provide insight into the normal aging process in the brain, and its variability., (Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.)

Thyroid hormone (TH) is crucial during neurodevelopment, but high levels of TH have been linked to neurodegenerative disorders. No data on the association of thyroid function with brain imaging in the general population are available. We therefore investigated the association of thyroid-stimulating hormone and free thyroxine (FT4) with magnetic resonance imaging (MRI)-derived total intracranial volume, brain tissue volumes, and diffusion tensor imaging measures of white matter microstructure in 4683 dementia- and stroke-free participants (mean age 60.2, range 45.6-89.9 years). Higher FT4 levels were associated with larger total intracranial volumes (β = 6.73 mL, 95% confidence interval = 2.94-9.80). Higher FT4 levels were also associated with larger total brain and white matter volumes in younger individuals, but with smaller total brain and white matter volume in older individuals (p-interaction 0.02). There was a similar interaction by age for the association of FT4 with mean diffusivity on diffusion tensor imaging (p-interaction 0.026). These results are in line with differential effects of TH during neurodevelopmental and neurodegenerative processes and can improve the understanding of the role of thyroid function in neurodegenerative disorders., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objective: To investigate the association of kidney function with white matter microstructural integrity., Methods: We included 2,726 participants with a mean age of 56.6 years (45% men) from the population-based Rotterdam Study. Albumin-to-creatinine ratio, and estimated glomerular filtration rate (eGFR), using serum cystatin C (eGFRcys) and creatinine (eGFRcr), were measured to evaluate kidney function. Diffusion-MRI was used to assess microstructural integrity of the normal-appearing white matter. Multiple linear regression models, adjusted for macrostructural MRI markers and cardiovascular risk factors, were used to model the association of kidney function with white matter microstructure., Results: Participants had average eGFRcr of 86.1 mL/min/1.73 m(2), average eGFRcys of 86.2 mL/min/1.73 m(2), and median albumin-to-creatinine ratio of 3.4 mg/g. Lower eGFRcys was associated with worse global white matter microstructural integrity, reflected as lower fractional anisotropy (standardized difference per SD: -0.053, 95% confidence interval [CI]: -0.092, -0.014) and higher mean diffusivity (0.036, 95% CI: 0.001, 0.070). Similarly, higher albumin-to-creatinine ratio was associated with lower fractional anisotropy (-0.044, 95% CI: -0.078, -0.011). There was no linear association between eGFRcr and white matter integrity. Subgroup analyses showed attenuation of the associations after excluding subjects with hypertension. The associations with global diffusion tensor imaging measures did not seem to be driven by particular tracts, but rather spread across multiple tracts in various brain regions., Conclusions: Reduced kidney function is associated with worse white matter microstructural integrity. Our findings highlight the importance for clinicians to consider concomitant macro- and microstructural changes of the brain in patients with impaired kidney function., (© 2015 American Academy of Neurology.)

Background: Loss of brain white matter microstructure is presumed to be an early sign of neurodegenerative disease. Yet, little is known on microstructural changes of various white matter tracts with normal aging., Methods: In 4532 nondemented elderly persons, we studied age-related changes in tract-specific diffusion characteristics for 25 tracts using probabilistic tractography. We studied how diffusion differs across tracts with aging, whether this depends on macrostructural white matter changes, and whether cardiovascular risk factors affect microstructure., Results: With increasing age, loss of microstructural organization occurred in association, commissural and limbic tracts. White matter lesions and atrophy each partially explained this loss. We observed worse microstructure with severe hypertension, current smoking and diabetes mellitus, independent from age and macrostructural white matter changes., Conclusions: Microstructure of white matter tracts changes with age, and may mark neurodegeneration more sensitively than white matter lesion load and atrophy. Cardiovascular factors relate to loss in microstructural organization., (Copyright © 2015 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Background: Brain changes on magnetic resonance imaging (MRI) reflect accumulating pathology and have clinically disabling consequences, such as dementia. However, little is known on the relation of these MRI markers with daily functioning in nondemented individuals. We investigated whether structural and microstructural brain changes are associated with impairment in activities of daily living in a community-dwelling population., Methods: Between 2005 and 2009, 2025 stroke-free nondemented participants (aged 59.9 years) from the population-based Rotterdam Study underwent brain MRI, yielding global MRI markers, focal MRI markers, and microstructural MRI markers. We used the Stanford Health Assessment Questionnaire to assess basic activities of daily living, and the Instrumental Activities of Daily Living Scale to assess instrumental activities of daily living. Follow-up on activities of daily living was obtained between 2008 and 2013 (mean follow-up 5.7 years). We used linear regression to analyze continuous scores of daily living and logistic regression for incident impairment., Results: Eighty-two participants became impaired in basic and 33 in instrumental activities of daily living. Smaller brain and hippocampal volume and higher diffusivity were associated with larger change in activities of daily living. Smaller brain volume (odds ratio [OR] 4.05 per SD; 95% confidence interval [CI], 1.81-9.02), larger white matter lesion volume (OR 1.33/SD; 95% CI 1.02-1.72) and higher mean (OR 1.55/SD; 95% CI, 1.11-2.15), axial (OR 1.49/SD; 95% CI, 1.08-2.07), and radial diffusivity (OR 1.51/SD; 95% CI, 1.09-2.10) were associated with higher risk of impairment in basic activities of daily living., Conclusions: In community-dwelling individuals, brain changes are associated with deterioration and incident impairment in daily functioning., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Microstructural white matter deterioration is a frequent finding in mild cognitive impairment (MCI), potentially underlying default mode network (DMN) dysfunctioning. Thus far, microstructural damage in MCI has been attributed to Alzheimer's disease pathophysiology. A cerebrovascular role, in particular the role of cerebral small vessel disease (CSVD), received less interest. Here, we used diffusion tensor imaging (DTI) to examine the role of CSVD in microstructural deterioration within the normal appearing white matter (NAWM) in MCI. MCI patients were subdivided into those with (n = 20) and without (n = 31) macrostructural CSVD evidence on MRI. Using TBSS we performed microstructural integrity comparisons within the whole brain NAWM. Secondly, we segmented white matter tracts interconnecting DMN brain regions by means of automated tractography segmentation. We used NAWM DTI measures from these tracts as dependent variables in a stepwise-linear regression analysis, with structural and demographical predictors. Our results indicated microstructural deterioration within the anterior corpus callosum, internal and external capsule and periventricular white matter in MCI patients with CSVD, while in MCI patients without CSVD, deterioration was restricted to the right perforant path, a tract along the hippocampus. Within the full cohort of MCI patients, microstructure within the NAWM of the DMN fiber tracts was affected by the presence of CSVD. Within the cingulum along the hippocampal cortex we found a relationship between microstructural integrity and ipsilateral hippocampal volume and the extent of white matter hyperintensity. In conclusion, we found evidence of CSVD-related microstructural damage in fiber tracts subserving the DMN in MCI., (Copyright © 2013 Wiley Periodicals, Inc.)

Objectives: To date, only four small studies have investigated the effects of adjuvant chemotherapy for breast cancer on the microstructure of cerebral white matter with magnetic resonance imaging (MRI). These studies, which were conducted shortly up to 10 years post-treatment, showed that chemotherapy is associated with focal loss of microstructural white matter integrity. We investigated the long-term effect of chemotherapy on white matter microstructural integrity by comparing the brains of chemotherapy-exposed breast cancer survivors to those of a population-based sample of women without a history of cancer., Experimental Design: Diffusion tensor imaging (DTI) MRI (1.5 T) was performed in 187 CMF (cyclophosphamide, methotrexate, and 5-flourouracil) chemotherapy-exposed breast cancer survivors, mean age 64.2 (sd = 6.5) years, who had been diagnosed with cancer on average 21.2 (sd = 4.4) years before, and 374 age-matched cancer-free reference subjects from a population-based cohort study. Outcome measures were whole-brain microstructural integrity as measured by fractional anisotropy and mean/axial/radial diffusivity and focal white matter integrity, which was analyzed with tract-based spatial statistics. All analyses were adjusted for age, cardiovascular risk factors, education, and symptoms of depression., Principal Observations: No significant group differences were observed in white matter integrity. However, within the breast cancer survivors, time since treatment was inversely associated with lower global and focal white matter integrity., Conclusions: This cross-sectional study suggests that among chemotherapy-exposed breast cancer survivors white matter microstructural integrity deteriorates with accumulating time since treatment. This warrants further investigation., (Copyright © 2012 Wiley Periodicals, Inc.)

Objective: To investigate whether the presence of cerebral microbleeds, which present as focal lesions on imaging, is associated with a diffuse loss of white matter microstructural integrity in the brain., Methods: In the prospective, population-based Rotterdam Scan Study, a total of 4,493 participants underwent brain MRI to determine microbleed status. With diffusion tensor imaging, global fractional anisotropy (FA) and mean diffusivity (MD) were measured in normal-appearing white matter. Multiple linear regression models, adjusted for age, sex, cardiovascular risk factors, white matter lesions, and infarcts, were applied to investigate the independent association between microbleeds and organization of brain white matter. Analyses were repeated after stratification by APOE ε4 carriership., Results: Presence of microbleeds was related to a lower mean FA and higher mean MD, in a dose-dependent manner, and was already apparent for a single microbleed (standardized FA: -0.13, 95% confidence interval -0.21 to -0.05; MD: 0.12, 95% confidence interval 0.05 to 0.19). For lobar microbleeds, alterations in diffusion tensor imaging measurements were solely driven by APOE ε4 carriers., Conclusions: Presence of microbleeds relates to poorer microstructural integrity of brain white matter, even after adjusting for cardiovascular risk and other markers of cerebral small-vessel disease. Our data suggest that microbleeds reflect diffuse brain pathology, even when only a single microbleed is present.

Background and Purpose: It is unknown whether white matter lesions (WML) develop abruptly in previously normal brain areas, or whether tissue changes are already present before WML become apparent on MRI. We therefore investigated whether development of WML is preceded by quantifiable changes in normal-appearing white matter (NAWM)., Methods: In 689 participants from the general population (mean age 67 years), we performed 2 MRI scans (including diffusion tensor imaging and Fluid Attenuation Inversion Recovery [FLAIR] sequences) 3.5 years apart using the same 1.5-T scanner. Using automated tissue segmentation, we identified NAWM at baseline. We assessed which NAWM regions converted into WML during follow-up and differentiated new WML into regions of WML growth and de novo WML. Fractional anisotropy, mean diffusivity, and FLAIR intensity of regions converting to WML and regions of persistent NAWM were compared using 3 approaches: a whole-brain analysis, a regionally matched approach, and a voxel-wise approach., Results: All 3 approaches showed that low fractional anisotropy, high mean diffusivity, and relatively high FLAIR intensity at baseline were associated with WML development during follow-up. Compared with persistent NAWM regions, NAWM regions converting to WML had significantly lower fractional anisotropy (0.337 vs 0.387; P<0.001), higher mean diffusivity (0.910 × 10(-3) mm(2)/s vs 0.729 × 10(-3) mm(2)/s; P<0.001), and relatively higher normalized FLAIR intensity (1.233 vs -0.340; P<0.001). This applied to both NAWM developing into growing and de novo WML., Conclusions: White matter changes in NAWM are present and can be quantified on diffusion tensor imaging and FLAIR before WML develop. This suggests that WML develop gradually, and that visually appreciable WML are only the tip of the iceberg of white matter pathology.

Diffusion MRI can be used to study the structural connectivity within the brain. Brain connectivity is often represented by a binary network whose topology can be studied using graph theory. We present a framework for the construction of weighted structural brain networks, containing information about connectivity, which can be effectively analyzed using statistical methods. Network nodes are defined by segmentation of subcortical structures and by cortical parcellation. Connectivity is established using a minimum cost path (mcp) method with an anisotropic local cost function based directly on diffusion weighted images. We refer to this framework as Statistical Analysis of Minimum cost path based Structural Connectivity (SAMSCo) and the weighted structural connectivity networks as mcp-networks. In a proof of principle study we investigated the information contained in mcp-networks by predicting subject age based on the mcp-networks of a group of 974 middle-aged and elderly subjects. Using SAMSCo, age was predicted with an average error of 3.7 years. This was significantly better than predictions based on fractional anisotropy or mean diffusivity averaged over the whole white matter or over the corpus callosum, which showed average prediction errors of at least 4.8 years. Additionally, we classified subjects, based on the mcp-networks, into groups with low and high white matter lesion load, while correcting for age, sex and white matter atrophy. The SAMSCo classification outperformed the classification based on the diffusion measures with a classification accuracy of 76.0% versus 63.2%. We also performed a classification in groups with mild and severe atrophy, correcting for age, sex and white matter lesion load. In this case, mcp-networks and diffusion measures yielded similar classification accuracies of 68.3% and 67.8% respectively. The SAMSCo prediction and classification experiments indicate that the mcp-networks contain information regarding age, white matter lesion load and white matter atrophy, and that in case of age and white matter lesion load the mcp-network based models outperformed the predictions based on diffusion measures., (Copyright © 2010 Elsevier Inc. All rights reserved.)

We present a framework for statistical analysis in large cohorts of structural brain connectivity, derived from diffusion weighted MRI. A brain network is defined between subcortical gray matter structures and a cortical parcellation obtained with FreeSurfer. Connectivity is established through minimum cost paths with an anisotropic local cost function and is quantified per connection. The connectivity network potentially encodes important information about brain structure, and can be analyzed using multivariate regression methods. The proposed framework can be used to study the relation between connectivity and e.g. brain function or neurodegenerative disease. As a proof of principle, we perform principal component regression in order to predict age and gender, based on the connectivity networks of 979 middle-aged and elderly subjects, in a 10-fold cross-validation. The results are compared to predictions based on fractional anisotropy and mean diffusivity averaged over the white matter and over the corpus callosum. Additionally, the predictions are performed based on the best predicting connection in the network. Principal component regression outperformed all other prediction models, demonstrating the age and gender information encoded in the connectivity network.

The importance of macrostructural white matter changes, including white matter lesions and atrophy, in intact brain functioning is increasingly being recognized. Diffusion tensor imaging (DTI) enables measurement of the microstructural integrity of white matter. Loss of white matter integrity in aging has been reported, but whether this is inherent to the aging process itself or results from specific white matter pathology is unknown. In 832 persons aged 60 years and older from the population-based Rotterdam Study, we measured fractional anisotropy (FA) and directional diffusivities in normal-appearing white matter using DTI. All subjects' DTI measures were projected onto a common white matter skeleton to enable robust voxelwise comparison. With increasing age, multiple regions showed significant decreases in FA or increases in axial or radial diffusivity in normal-appearing white matter. However, nearly all of these regional changes were explained by either white matter atrophy or by white matter lesions; each of which related to changes in distinct brain regions. These results indicate that loss of white matter integrity in aging is primarily explained by atrophy and lesion formation and not by the aging process itself. Furthermore, white matter atrophy and white matter lesion formation relate to loss of integrity in distinct brain regions, indicating the two processes are pathophysiologically different.