Expectation maximisation pseudo labels.

In this paper, we study pseudo-labelling. Pseudo-labelling employs raw inferences on unlabelled data as pseudo-labels for self-training. We elucidate the empirical successes of pseudo-labelling by establishing a link between this technique and the Expectation Maximisation algorithm. Through this, we realise that the original pseudo-labelling serves as an empirical estimation of its more comprehensive underlying formulation. Following this insight, we present a full generalisation of pseudo-labels under Bayes' theorem, termed Bayesian Pseudo Labels. Subsequently, we introduce a variational approach to generate these Bayesian Pseudo Labels, involving the learning of a threshold to automatically select high-quality pseudo labels. In the remainder of the paper, we showcase the applications of pseudo-labelling and its generalised form, Bayesian Pseudo-Labelling, in the semi-supervised segmentation of medical images. Specifically, we focus on: (1) 3D binary segmentation of lung vessels from CT volumes; (2) 2D multi-class segmentation of brain tumours from MRI volumes; (3) 3D binary segmentation of whole brain tumours from MRI volumes; and (4) 3D binary segmentation of prostate from MRI volumes. We further demonstrate that pseudo-labels can enhance the robustness of the learned representations. The code is released in the following GitHub repository: https://github.com/moucheng2017/EMSSL.

Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021.

Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and interrater variability. Automated rating may benefit biomedical research, as well as clinical assessment, but diagnostic reliability of existing algorithms is unknown. Here, we present the results of the VAscular Lesions DetectiOn and Segmentation (Where is VALDO?) challenge that was run as a satellite event at the international conference on Medical Image Computing and Computer Aided Intervention (MICCAI) 2021. This challenge aimed to promote the development of methods for automated detection and segmentation of small and sparse imaging markers of cerebral small vessel disease, namely enlarged perivascular spaces (EPVS) (Task 1), cerebral microbleeds (Task 2) and lacunes of presumed vascular origin (Task 3) while leveraging weak and noisy labels. Overall, 12 teams participated in the challenge proposing solutions for one or more tasks (4 for Task 1-EPVS, 9 for Task 2-Microbleeds and 6 for Task 3-Lacunes). Multi-cohort data was used in both training and evaluation. Results showed a large variability in performance both across teams and across tasks, with promising results notably for Task 1-EPVS and Task 2-Microbleeds and not practically useful results yet for Task 3-Lacunes. It also highlighted the performance inconsistency across cases that may deter use at an individual level, while still proving useful at a population level.

MisMatch: Calibrated Segmentation via Consistency on Differential Morphological Feature Perturbations With Limited Labels.

Semi-supervised learning (SSL) is a promising machine learning paradigm to address the ubiquitous issue of label scarcity in medical imaging. The state-of-the-art SSL methods in image classification utilise consistency regularisation to learn unlabelled predictions which are invariant to input level perturbations. However, image level perturbations violate the cluster assumption in the setting of segmentation. Moreover, existing image level perturbations are hand-crafted which could be sub-optimal. In this paper, we propose MisMatch, a semi-supervised segmentation framework based on the consistency between paired predictions which are derived from two differently learnt morphological feature perturbations. MisMatch consists of an encoder and two decoders. One decoder learns positive attention for foreground on unlabelled data thereby generating dilated features of foreground. The other decoder learns negative attention for foreground on the same unlabelled data thereby generating eroded features of foreground. We normalise the paired predictions of the decoders, along the batch dimension. A consistency regularisation is then applied between the normalised paired predictions of the decoders. We evaluate MisMatch on four different tasks. Firstly, we develop a 2D U-net based MisMatch framework and perform extensive cross-validation on a CT-based pulmonary vessel segmentation task and show that MisMatch statistically outperforms state-of-the-art semi-supervised methods. Secondly, we show that 2D MisMatch outperforms state-of-the-art methods on an MRI-based brain tumour segmentation task. We then further confirm that 3D V-net based MisMatch outperforms its 3D counterpart based on consistency regularisation with input level perturbations, on two different tasks including, left atrium segmentation from 3D CT images and whole brain tumour segmentation from 3D MRI images. Lastly, we find that the performance improvement of MisMatch over the baseline might originate from its better calibration. This also implies that our proposed AI system makes safer decisions than the previous methods.

A meta-analysis of structural MRI studies of the brain in systemic lupus erythematosus (SLE).

A comprehensive search of published literature in brain volumetry was conducted in three autoimmune diseases - systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and ulcerative colitis (UC) - with the intention of performing a meta-analysis of published data. Due to the lack of data in RA and UC, the reported meta-analysis was limited to SLE. The MEDLINE database was searched for studies from 1988 to March 2022. A total of 175 papers met the initial inclusion criteria, and 16 were included in a random-effects meta-analysis. The reduction in the number of papers included in the final analysis is primarily due to the lack of overlap in measured and reported brain regions. A significantly lower volume was seen in patients with SLE in the hippocampus, corpus callosum, and total gray matter volume measurements as compared to age- and sex-matched controls. There were not enough studies to perform a meta-analysis for RA and UC; instead, we include a summary of published volumetric studies. The meta-analyses revealed structural brain abnormalities in patients with SLE, suggesting that lower global brain volumes are associated with disease status. This volumetric difference was seen in both the hippocampus and corpus callosum and total gray matter volume measurements. These results indicate both gray and white matter involvements in SLE and suggest there may be both localized and global reductions in brain volume.

Longitudinal diffusion MRI analysis using Segis-Net: A single-step deep-learning framework for simultaneous segmentation and registration.

This work presents a single-step deep-learning framework for longitudinal image analysis, coined Segis-Net. To optimally exploit information available in longitudinal data, this method concurrently learns a multi-class segmentation and nonlinear registration. Segmentation and registration are modeled using a convolutional neural network and optimized simultaneously for their mutual benefit. An objective function that optimizes spatial correspondence for the segmented structures across time-points is proposed. We applied Segis-Net to the analysis of white matter tracts from N=8045 longitudinal brain MRI datasets of 3249 elderly individuals. Segis-Net approach showed a significant increase in registration accuracy, spatio-temporal segmentation consistency, and reproducibility compared with two multistage pipelines. This also led to a significant reduction in the sample-size that would be required to achieve the same statistical power in analyzing tract-specific measures. Thus, we expect that Segis-Net can serve as a new reliable tool to support longitudinal imaging studies to investigate macro- and microstructural brain changes over time.

Advanced imaging for quantification of abnormalities in the salivary glands of patients with primary Sjögren's syndrome.

OBJECTIVES: To assess non-invasive imaging for detection and quantification of gland structure, inflammation and function in patients with primary Sjogren's syndrome (pSS) using PET-CT with 11C-Methionine (11C-MET; radiolabelled amino acid), and 18F-fluorodeoxyglucose (18F-FDG; glucose uptake marker), to assess protein synthesis and inflammation, respectively; multiparametric MRI evaluated salivary gland structural and physiological changes. METHODS: In this imaging/clinical/histology comparative study (GSK study 203818; NCT02899377) patients with pSS and age- and sex-matched healthy volunteers underwent MRI of the salivary glands and 11C-MET PET-CT. Patients also underwent 18F-FDG PET-CT and labial salivary gland biopsies. Clinical and biomarker assessments were performed. Primary endpoints were semi-quantitative parameters of 11C-MET and 18F-FDG uptake in submandibular and parotid salivary glands and quantitative MRI measures of structure and inflammation. Clinical and minor salivary gland histological parameter correlations were explored. RESULTS: Twelve patients with pSS and 13 healthy volunteers were included. Lower 11C-MET uptake in parotid, submandibular and lacrimal glands, lower submandibular gland volume, higher MRI fat fraction, and lower pure diffusion in parotid and submandibular glands were observed in patients vs healthy volunteer, consistent with reduced synthetic function. Disease duration correlated positively with fat fraction and negatively with 11C-MET and 18F-FDG uptake, consistent with impaired function, inflammation and fatty replacement over time. Lacrimal gland 11C-MET uptake positively correlated with tear flow in patients, and parotid gland 18F-FDG uptake positively correlated with salivary gland CD20+ B-cell infiltration. CONCLUSION: Molecular imaging and MRI may be useful tools to non-invasively assess loss of glandular function, increased glandular inflammation and fat accumulation in pSS.

Hearing loss and microstructural integrity of the brain in a dementia-free older population.

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.

Structural disconnectivity and the risk of dementia in the general population.

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.

Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging.

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 â€‹= â€‹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 â€‹= â€‹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.

Quantifying disease activity in rheumatoid arthritis with the TSPO PET ligand 18F-GE-180 and comparison with 18F-FDG and DCE-MRI.

PURPOSE: While the aetiology of rheumatoid arthritis (RA) remains unclear, many of the inflammatory components are well characterised. For diagnosis and therapy evaluation, in vivo insight into these processes would be valuable. Various imaging probes have shown value including dynamic contrast-enhanced (DCE) MRI and PET/CT using 18F-fluorodeoxyglucose (18F-FDG) or tracers targeting the translocator protein (TSPO). To evaluate 18F-GE-180, a novel TSPO PET tracer, for detecting and quantifying disease activity in RA, we compared 18F-GE-180 uptake with that of 18F-FDG and DCE-MRI measures of inflammation. METHODS: Eight RA patients with moderate-to-high, stable disease activity and active disease in at least one wrist were included in this study (NCT02350426). Participants underwent PET/CT examinations with 18F-GE-180 and 18F-FDG on separate visits, covering the shoulders and from the pelvis to the feet, including hands and wrists. DCE-MRI was performed on one affected hand. Uptake was compared visually between tracers as judged by an experienced radiologist and quantitatively using the maximum standardised uptake value (SUVmax). Uptake for both tracers was correlated with DCE-MRI parameters of inflammation, including the volume transfer coefficient Ktrans using Pearson correlation (r). RESULTS: PET/CT imaging with 18F-GE-180 in RA patients showed marked extra-synovial uptake around the affected joints. Overall sensitivity for detecting clinically affected joints was low (14%). 18F-GE-180 uptake did not or only weakly correlate with DCE-MRI parameters in the wrist (r = 0.09-0.31). 18F-FDG showed higher sensitivity for detecting symptomatic joints (34%), as well as strong positive correlation with DCE-MRI parameters (SUVmax vs. Ktrans: r = 0.92 for wrist; r = 0.68 for metacarpophalangeal joints). CONCLUSIONS: The correlations between DCE-MRI parameters and 18F-FDG uptake support use of this PET tracer for quantification of inflammatory burden in RA. The TSPO tracer 18F-GE-180, however, has shown limited use for the investigation of RA due to its poor sensitivity and ability to quantify disease activity in RA.

Prevalence and clinical relevance of diffusion-weighted imaging lesions: The Rotterdam study.

OBJECTIVE: To examine the association of diffusion-weighted image (DWI) lesions with markers of cerebrovascular disease, neurodegeneration, and cognitive functioning and to further explore the evolution of these DWI lesions and their link to risk of dementia, stroke, or TIA in the Rotterdam Study. METHODS: Two thousand one hundred seventy-six participants with baseline MRI scans (assessed between January 2009 and December 2013) and data on incident clinical outcomes (until January 2016) were included. DWIs were inspected for presence of acute or subacute lesions. Markers of cerebrovascular disease, brain tissue segmentation, and microstructural integrity were collected. Cognition was assessed with a detailed neuropsychological test. Evolution of DWI lesions was evaluated on follow-up scans. RESULTS: Thirty-three individuals (1.5%) had ≥1 DWI lesions. Persons with lacunes, white matter hyperintensities (WMHs), and reduced white matter microstructural integrity were more likely to have DWI lesions. Persons with DWI lesions performed worse on Stroop test 1. For 17 of 33 persons, follow-up scans were available to determine lesion evolution. During a mean follow-up of 4.7 years, 58.8% of DWI lesions appeared as WMHs, 17.6% developed cavitation, 5.9% changed into cortical cerebral microinfarcts, and 17.6% disappeared. People with DWI lesions at baseline were at increased risk of strokes (hazard ratio 3.72, 95% confidence interval 1.35-10.27). CONCLUSION: Asymptomatic DWI lesions in community-dwelling persons are associated with markers of cerebral small vessel disease, reduced microstructural integrity, and worse cognition. Presence of DWI lesions increases the risk of further strokes. Future investigations will have to show whether screening and treating persons with DWI lesions can effectively reduce the burden of stroke.

The prospective association of objectively measured sleep and cerebral white matter microstructure in middle-aged and older persons.

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 (ß = 0.06, 95% CI: 0.01 to 0.12), but not with MD. Persons with higher SE had higher global FA (ß = 0.01, 95% CI: 0.002 to 0.01) and lower MD (ß = -0.01, 95% CI: -0.01 to -0.0004). Consistently, those with more WASO had lower global FA (ß = -0.003, 95% CI: -0.005 to -0.001) and higher MD (ß = 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.

Use of autologous 99mTechnetium-labelled neutrophils to quantify lung neutrophil clearance in COPD.

RATIONALE: There is a need to develop imaging protocols which assess neutrophilic inflammation in the lung. AIM: To quantify whole lung neutrophil accumulation in (1) healthy volunteers (HV) following inhaled lipopolysaccharide (LPS) or saline and (2) patients with COPD using radiolabelled autologous neutrophils and single-photon emission computed tomography/CT (SPECT/CT). METHODS: 20 patients with COPD (Global initiative for chronic obstructive lung disease (GOLD) stages 2-3) and 18 HVs were studied. HVs received inhaled saline (n=6) or LPS (50 µg, n=12) prior to the injection of radiolabelled cells. Neutrophils were isolated using dextran sedimentation and Percoll plasma gradients and labelled with 99mTechnetium (Tc)-hexamethylpropyleneamine oxime. SPECT was performed over the thorax/upper abdomen at 45 min, 2 hours, 4 hours and 6 hours. Circulating biomarkers were measured prechallenge and post challenge. Blood neutrophil clearance in the lung was determined using Patlak-Rutland graphical analysis. RESULTS: There was increased accumulation of 99mTc-neutrophils in the lungs of patients with COPD and LPS-challenged subjects compared with saline-challenged subjects (saline: 0.0006±0.0003 mL/min/mL lung blood distribution volume [mean ±1 SD]; COPD: 0.0022±0.0010 mL/min/mL [p<0.001]; LPS: 0.0025±0.0008 mL/min/mL [p<0.001]). The accumulation of labelled neutrophils in 10 patients with COPD who underwent repeat radiolabelling/imaging 7-10 days later was highly reproducible (0.0022±0.0010 mL/min/mL vs 0.0023±0.0009 mL/min/mL). Baseline interleukin (IL)-6 levels in patients with COPD were elevated compared with HVs (1.5±1.06 pg/mL [mean ±1 SD] vs 0.4±0.24 pg/mL). LPS challenge increased the circulating IL-6 levels (7.5±2.72 pg/mL) 9 hours post challenge. CONCLUSIONS: This study shows the ability to quantify 'whole lung' neutrophil accumulation in HVs following LPS inhalation and in subjects with COPD using autologous radiolabelled neutrophils and SPECT/CT imaging. Moreover, the reproducibility observed supports the feasibility of using this approach to determine the efficacy of therapeutic agents aimed at altering neutrophil migration to the lungs.

Differences in spatial distribution between WHO 2016 low-grade glioma molecular subgroups.

BACKGROUND: Several studies reported a correlation between anatomic location and genetic background of low-grade gliomas (LGGs). As such, tumor location may contribute to presurgical clinical decision-making. Our purpose was to visualize and compare the spatial distribution of different WHO 2016 gliomas, frequently aberrated single genes and DNA copy number alterations within subgroups, and groups of postoperative tumor volume. METHODS: Adult grade II glioma patients (WHO 2016 classified) diagnosed between 2003 and 2016 were included. Tumor volume and location were assessed with semi-automatic software. All volumes of interest were mapped to a standard reference brain. Location heatmaps were created for each WHO 2016 glioma subgroup, frequently aberrated single genes and copy numbers (CNVs), as well as heatmaps according to groups of postoperative tumor volume. Differences between subgroups were determined using voxelwise permutation testing. RESULTS: A total of 110 IDH mutated astrocytoma patients, 92 IDH mutated and 1p19q co-deleted oligodendroglioma patients, and 22 IDH wild-type astrocytoma patients were included. We identified small regions in which specific molecular subtypes occurred more frequently. IDH-mutated LGGs were more frequently located in the frontal lobes and IDH wild-type tumors more frequently in the basal ganglia of the right hemisphere. We found no localizations of significant difference for single genes/CNVs in subgroups, except for loss of 9p in oligodendrogliomas with a predilection for the left parietal lobes. More extensive resections in LGG were associated with frontal locations. CONCLUSIONS: WHO low-grade glioma subgroups show differences in spatial distribution. Our data may contribute to presurgical clinical decision-making in LGG patients.

Trajectories of imaging markers in brain aging: the Rotterdam Study.

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.

Disconnection due to white matter hyperintensities is associated with lower cognitive scores.

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.

White-matter microstructure and hearing acuity in older adults: a population-based cross-sectional DTI study.

To study the relation between the microstructure of white matter in the brain and hearing function in older adults we carried out a population-based, cross-sectional study. In 2562 participants of the Rotterdam Study, we conducted diffusion tensor imaging to determine the microstructure of the white-matter tracts. We performed pure-tone audiogram and digit-in-noise tests to quantify hearing acuity. Poorer white-matter microstructure, especially in the association tracts, was related to poorer hearing acuity. After differentiating the separate white-matter tracts in the left and right hemisphere, poorer white-matter microstructure in the right superior longitudinal fasciculus and the right uncinate fasciculus remained significantly associated with worse hearing. These associations did not significantly differ between middle-aged (51-69 years old) and older (70-100 years old) participants. Progressing age was thus not found to be an effect modifier. In a voxel-based analysis no voxels in the white matter were significantly associated with hearing impairment.

Age-dependent association of thyroid function with brain morphology and microstructural organization: evidence from brain imaging.

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 (ß = 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.

The effect of hippocampal function, volume and connectivity on posterior cingulate cortex functioning during episodic memory fMRI in mild cognitive impairment.

OBJECTIVES: Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer's disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI). METHOD: MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus. RESULTS: We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors. CONCLUSIONS: Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI. KEY POINTS: • PCC functioning during episodic memory relates to hippocampal functioning in MCI. • PCC functioning during episodic memory does not relate to hippocampal structure in MCI. • Functional network changes are an important predictor of PCC functioning in MCI.

White matter lesions relate to tract-specific reductions in functional connectivity.

White matter lesions play a role in cognitive decline and dementia. One presumed pathway is through disconnection of functional networks. Little is known about location-specific effects of lesions on functional connectivity. This study examined location-specific effects within anatomically-defined white matter tracts in 1584 participants of the Rotterdam Study, aged 50-95. Tracts were delineated from diffusion magnetic resonance images using probabilistic tractography. Lesions were segmented on fluid-attenuated inversion recovery images. Functional connectivity was defined across each tract on resting-state functional magnetic resonance images by using gray matter parcellations corresponding to the tract ends and calculating the correlation of the mean functional activity between the gray matter regions. A significant relationship between both local and brain-wide lesion load and tract-specific functional connectivity was found in several tracts using linear regressions, also after Bonferroni correction. Indirect connectivity analyses revealed that tract-specific functional connectivity is affected by lesions in several tracts simultaneously. These results suggest that local white matter lesions can decrease tract-specific functional connectivity, both in direct and indirect connections.