Analysis of the Retinal and Choroidal Vasculature Using Ultrawidefield Fundus Imaging in Mild Cognitive Impairment and Normal Cognition.

Purpose: To utilize ultrawidefield (UWF) imaging to evaluate retinal and choroidal vasculature and structure in individuals with mild cognitive impairment (MCI) compared with that of controls with normal cognition. Design: Prospective cross sectional study. Participants: One hundred thirty-one eyes of 82 MCI patients and 230 eyes of 133 cognitively normal participants from the Eye Multimodal Imaging in Neurodegenerative Disease Study. Methods: A scanning laser ophthalmoscope (California, Optos Inc) was used to obtain UWF fundus color images. Images were analyzed with the Vasculature Assessment Platform for Images of the Retina UWF (VAMPIRE-UWF 2.0, Universities of Edinburgh and Dundee) software. Main outcome measures: Imaging parameters included vessel width gradient, vessel width intercept, large vessel choroidal vascular density, vessel tortuosity, and vessel fractal dimension. Results: Both retinal artery and vein width gradients were less negative in MCI patients compared with controls, demonstrating decreased rates of vessel thinning at the periphery (P < 0.001; P = 0.027). Retinal artery and vein width intercepts, a metric that extrapolates the width of the vessel at the center of the optic disc, were smaller in MCI patients compared with that of controls (P < 0.001; P = 0.017). The large vessel choroidal vascular density, which quantifies the vascular area versus the total choroidal area, was greater in MCI patients compared with controls (P = 0.025). Conclusions: When compared with controls with normal cognition, MCI patients had thinner retinal vasculature manifested in both the retinal arteries and the veins. In MCI, these thinner arteries and veins attenuated at a lower rate when traveling toward the periphery. MCI patients also had increased choroidal vascular density. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Ultra-Widefield Imaging of the Retinal Macrovasculature in Parkinson Disease Versus Controls With Normal Cognition Using Alpha-Shapes Analysis.

Purpose: To investigate retinal vascular characteristics using ultra-widefield (UWF) scanning laser ophthalmoscopy in Parkinson disease (PD). Methods: Individuals with an expert-confirmed clinical diagnosis of PD and controls with normal cognition without PD underwent Optos California UWF imaging. Patients with diabetes, uncontrolled hypertension, glaucoma, dementia, other movement disorders, or known retinal or optic nerve pathology were excluded. Images were analyzed using Vasculature Assessment and Measurement Platform for Images of the Retina (VAMPIRE-UWF) software, which describes retinal vessel width gradient and tortuosity, provides vascular network fractal dimensions, and conducts alpha-shape analysis to further characterize vascular morphology (complexity, Opαmin; spread, OpA). Results: In the PD cohort, 53 eyes of 38 subjects were assessed; in the control cohort, 51 eyes of 33 subjects were assessed. Eyes with PD had more tortuous retinal arteries in the superotemporal quadrant (P = 0.043). In eyes with PD, alpha-shape analysis revealed decreased OpA, indicating less retinal vasculature spread compared to controls (P = 0.032). Opαmin was decreased in PD (P = 0.044), suggesting increased vascular network complexity. No differences were observed in fractal dimension in any region of interest. Conclusions: This pilot study suggests that retinal vasculature assessment on UWF images using alpha-shape analysis reveals differences in retinal vascular network spread and complexity in PD and may be a more sensitive metric compared to fractal dimension. Translational Relevance: Retinal vasculature assessment using these novel methods may be useful in understanding ocular manifestations of PD and the development of retinal biomarkers.

An Open-Source Deep Learning Algorithm for Efficient and Fully Automatic Analysis of the Choroid in Optical Coherence Tomography.

Purpose: To develop an open-source, fully automatic deep learning algorithm, DeepGPET, for choroid region segmentation in optical coherence tomography (OCT) data. Methods: We used a dataset of 715 OCT B-scans (82 subjects, 115 eyes) from three clinical studies related to systemic disease. Ground-truth segmentations were generated using a clinically validated, semiautomatic choroid segmentation method, Gaussian Process Edge Tracing (GPET). We finetuned a U-Net with the MobileNetV3 backbone pretrained on ImageNet. Standard segmentation agreement metrics, as well as derived measures of choroidal thickness and area, were used to evaluate DeepGPET, alongside qualitative evaluation from a clinical ophthalmologist. Results: DeepGPET achieved excellent agreement with GPET on data from three clinical studies (AUC = 0.9994, Dice = 0.9664; Pearson correlation = 0.8908 for choroidal thickness and 0.9082 for choroidal area), while reducing the mean processing time per image on a standard laptop CPU from 34.49 ± 15.09 seconds using GPET to 1.25 ± 0.10 seconds using DeepGPET. Both methods performed similarly according to a clinical ophthalmologist who qualitatively judged a subset of segmentations by GPET and DeepGPET, based on smoothness and accuracy of segmentations. Conclusions: DeepGPET, a fully automatic, open-source algorithm for choroidal segmentation, will enable researchers to efficiently extract choroidal measurements, even for large datasets. As no manual interventions are required, DeepGPET is less subjective than semiautomatic methods and could be deployed in clinical practice without requiring a trained operator. Translational Relevance: DeepGPET addresses the lack of open-source, fully automatic, and clinically relevant choroid segmentation algorithms, and its subsequent public release will facilitate future choroidal research in both ophthalmology and wider systemic health.

3D ultrasound reconstruction of sonographic callus : a novel imaging modality for early evaluation of fracture healing.

AIMS: The aim of this study was to establish a reliable method for producing 3D reconstruction of sonographic callus. METHODS: A cohort of ten closed tibial shaft fractures managed with intramedullary nailing underwent ultrasound scanning at two, six, and 12 weeks post-surgery. Ultrasound capture was performed using infrared tracking technology to map each image to a 3D lattice. Using echo intensity, semi-automated mapping was performed to produce an anatomical 3D representation of the fracture site. Two reviewers independently performed 3D reconstructions and kappa coefficient was used to determine agreement. A further validation study was undertaken with ten reviewers to estimate the clinical application of this imaging technique using the intraclass correlation coefficient (ICC). RESULTS: Nine of the ten patients achieved union at six months. At six weeks, seven patients had bridging callus of ≥ one cortex on the 3D reconstruction and when present all achieved union. Compared to six-week radiographs, no bridging callus was present in any patient. Of the three patients lacking sonographic bridging callus, one went onto a nonunion (77.8% sensitive and 100% specific to predict union). At 12 weeks, nine patients had bridging callus at ≥ one cortex on 3D reconstruction (100%-sensitive and 100%-specific to predict union). Presence of sonographic bridging callus on 3D reconstruction demonstrated excellent reviewer agreement on ICC at 0.87 (95% confidence interval 0.74 to 0.96). CONCLUSION: 3D fracture reconstruction can be created using multiple ultrasound images in order to evaluate the presence of bridging callus. This imaging modality has the potential to enhance the usability and accuracy of identification of early fracture healing. Cite this article: Bone Joint Res 2021;10(12):759-766.

DiCyc: GAN-based deformation invariant cross-domain information fusion for medical image synthesis.

Cycle-consistent generative adversarial network (CycleGAN) has been widely used for cross-domain medical image synthesis tasks particularly due to its ability to deal with unpaired data. However, most CycleGAN-based synthesis methods cannot achieve good alignment between the synthesized images and data from the source domain, even with additional image alignment losses. This is because the CycleGAN generator network can encode the relative deformations and noises associated to different domains. This can be detrimental for the downstream applications that rely on the synthesized images, such as generating pseudo-CT for PET-MR attenuation correction. In this paper, we present a deformation invariant cycle-consistency model that can filter out these domain-specific deformation. The deformation is globally parameterized by thin-plate-spline (TPS), and locally learned by modified deformable convolutional layers. Robustness to domain-specific deformations has been evaluated through experiments on multi-sequence brain MR data and multi-modality abdominal CT and MR data. Experiment results demonstrated that our method can achieve better alignment between the source and target data while maintaining superior image quality of signal compared to several state-of-the-art CycleGAN-based methods.

Sonographic bridging callus at six weeks following displaced midshaft clavicle fracture can accurately predict healing.

AIMS: To evaluate if union of clavicle fractures can be predicted at six weeks post-injury by the presence of bridging callus on ultrasound. METHODS: Adult patients managed nonoperatively with a displaced mid-shaft clavicle were recruited prospectively. Ultrasound evaluation of the fracture was undertaken to determine if sonographic bridging callus was present. Clinical risk factors at six weeks were used to stratify patients at high risk of nonunion with a combination of Quick Disabilities of the Arm, Shoulder and Hand questionnaire (QuickDASH) ≥ 40, fracture movement on examination, or absence of callus on radiograph. RESULTS: A total of 112 patients completed follow-up at six months with a nonunion incidence of 16.7% (n = 18/112). Sonographic bridging callus was detected in 62.5% (n = 70/112) of the cohort at six weeks post-injury. If present, union occurred in 98.6% of the fractures (n = 69/70). If absent, nonunion developed in 40.5% of cases (n = 17/42). The sensitivity to predict union with sonographic bridging callus at six weeks was 73.4% and the specificity was 94.4%. Regression analysis found that failure to detect sonographic bridging callus at six weeks was associated with older age, female sex, simple fracture pattern, smoking, and greater fracture displacement (Nagelkerke R2 = 0.48). Of the cohort, 30.4% (n = 34/112) had absent sonographic bridging callus in addition to one or more of the clinical risk factors at six weeks that predispose to nonunion. If one was present the nonunion rate was 35%, 60% with two, and 100% when combined with all three. CONCLUSION: Ultrasound combined with clinical risk factors can accurately predict fracture healing at six weeks following a displaced midshaft clavicle fracture. Cite this article: Bone Joint Res 2021;10(2):113-121.

A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification.

The eye affords a unique opportunity to inspect a rich part of the human microvasculature non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are prime steps for the diagnosis and risk assessment of microvascular and systemic diseases. A high volume of techniques based on deep learning have been published in recent years. In this context, we review 158 papers published between 2012 and 2020, focussing on methods based on machine and deep learning (DL) for automatic vessel segmentation and classification for fundus camera images. We divide the methods into various classes by task (segmentation or artery-vein classification), technique (supervised or unsupervised, deep and non-deep learning, hand-crafted methods) and more specific algorithms (e.g. multiscale, morphology). We discuss advantages and limitations, and include tables summarising results at-a-glance. Finally, we attempt to assess the quantitative merit of DL methods in terms of accuracy improvement compared to other methods. The results allow us to offer our views on the outlook for vessel segmentation and classification for fundus camera images.

Retinal venular tortuosity and fractal dimension predict incident retinopathy in adults with type 2 diabetes: the Edinburgh Type 2 Diabetes Study.

AIMS/HYPOTHESIS: Our aim was to determine whether a range of prespecified retinal vessel traits were associated with incident diabetic retinopathy in adults with type 2 diabetes. METHODS: In the prospective observational cohort Edinburgh Type 2 Diabetes Study of 1066 adults with type 2 diabetes, aged 60-75 years at recruitment, 718 were free from diabetic retinopathy at baseline. Baseline retinal traits including vessel widths, tortuosity (curvature) and fractal dimensions (network complexity), were quantified using fundus camera images and semiautomated software, and analysed using logistic regression for their association with incident diabetic retinopathy over 10 years. RESULTS: The incidence of diabetic retinopathy was 11.4% (n = 82) over 10 years. After adjustment for a range of vascular and diabetes-related risk factors, both increased venular tortuosity (OR 1.51; 95% CI 1.15, 1.98; p = 0.003) and decreased fractal dimension (OR 0.75; 95% CI 0.58, 0.96; p = 0.025) were associated with incident retinopathy. There was no evidence of an association with arterial tortuosity, and associations between measurements of vessel widths and retinopathy lost statistical significance after adjustment for diabetes-related factors and vascular disease. Adding venular tortuosity to a model including established risk factors for diabetic retinopathy (HbA1c, BP and kidney function) improved the discriminative ability (C statistic increased from 0.624 to 0.640, p = 0.013), but no such benefit was found with fractal dimension. CONCLUSIONS/INTERPRETATION: Increased retinal venular tortuosity and decreased fractal dimension are associated with incident diabetic retinopathy, independent of classical risk factors. There is some evidence that venular tortuosity may be a useful biomarker to improve the predictive ability of models based on established retinopathy risk factors, and its inclusion in further risk prediction modelling is warranted.

The Eye as a Non-Invasive Window to the Microcirculation in Liver Cirrhosis: A Prospective Pilot Study.

Microcirculatory dysfunction is associated with organ failure, poor response to vasoactive drugs and increased mortality in cirrhosis, but monitoring techniques are not established. We hypothesized that the chorioretinal structures of the eye could be visualized as a non-invasive proxy of the systemic microvasculature in cirrhosis and would correlate with renal dysfunction. Optical Coherence Tomography (OCT) was performed to image the retina in n = 55 cirrhosis patients being assessed for liver transplantation. OCT parameters were compared with established cohorts of age- and sex-matched healthy volunteers (HV) and patients with chronic kidney disease (CKD). Retinal thickness, macular volume and choroidal thickness were significantly reduced relative to HV and comparable to CKD patients (macular volume: HV vs. cirrhosis mean difference 0.44 mm3 (95% CI 0.26-0.61), p ≤ 0.0001). Reduced retinal thickness and macular volume correlated with renal dysfunction in cirrhosis (macular volume vs. MDRD-6 eGFR r = 0.40, p = 0.006). Retinal changes had resolved substantially 6 weeks following transplantation. There was an inverse association between choroidal thickness and circulating markers of endothelial dysfunction (endothelin-1 r = -0.49, p ≤ 0.001; von Willebrand factor r = -0.32, p ≤ 0.05). Retinal OCT may represent a non-invasive window to the microcirculation in cirrhosis and a dynamic measure of renal and endothelial dysfunction. Validation in different cirrhosis populations is now required.

Retinal vessel phenotype in patients with primary open-angle glaucoma.

PURPOSE: To characterize the phenotype of retinal vessels using central retinal artery equivalent (CRAE), central retinal vein equivalent (CRVE), tortuosity and fractal dimension (FD) in primary open-angle glaucoma (POAG) subjects. METHODS: This prospective case-control multicentre study included 61 POAG subjects and 61 controls matched for age, systemic hypertension and body mass index. Fundus images of the right eye were acquired using a non-mydriatic camera. Central retinal artery equivalent (CRAE), CRVE, arteriole-to-venule ratio, FD and tortuosity of the vascular network were measured using VAMPIRE software (Vessel Assessment and Measurement Platform for Images of the Retina). Primary open-angle glaucoma (POAG) patients underwent 24.2 sita-standard visual field and peri-papillary optical coherence tomography (OCT) examinations. Data were expressed as median and interquartile range (75-25th percentiles). RESULTS: The control group was comparable to the POAG group for sex ratio, refraction and intraocular pressure. The mean CRAE and the mean CRVE were significantly lower in the POAG group than in the control group [150.5 (137.9; 157.1) µm versus 161.3 (154.0; 168.4) µm and 204.8 (190.1; 218.1) µm versus 233.5 (222.3; 246.9) µm, respectively; p < 0.001] and for fractal parameters as well. No significant difference was found for tortuosity between the two groups. There was a significant correlation between CRAE and retinal nerve fibre layer (RNFL) thickness (r = 0.27; p = 0.03). VAMPIRE parameters were not correlated with visual field indices. CONCLUSION: Primary open-angle glaucoma (POAG) was associated with a narrowing of arterial and venous retinal vessels, a higher arteriole-to-venule ratio and lower values of FD. The relationship between CRAE and RNFL thickness needs further investigation.

Machine learning of neuroimaging for assisted diagnosis of cognitive impairment and dementia: A systematic review.

INTRODUCTION: Advanced machine learning methods might help to identify dementia risk from neuroimaging, but their accuracy to date is unclear. METHODS: We systematically reviewed the literature, 2006 to late 2016, for machine learning studies differentiating healthy aging from dementia of various types, assessing study quality, and comparing accuracy at different disease boundaries. RESULTS: Of 111 relevant studies, most assessed Alzheimer's disease versus healthy controls, using AD Neuroimaging Initiative data, support vector machines, and only T1-weighted sequences. Accuracy was highest for differentiating Alzheimer's disease from healthy controls and poor for differentiating healthy controls versus mild cognitive impairment versus Alzheimer's disease or mild cognitive impairment converters versus nonconverters. Accuracy increased using combined data types, but not by data source, sample size, or machine learning method. DISCUSSION: Machine learning does not differentiate clinically relevant disease categories yet. More diverse data sets, combinations of different types of data, and close clinical integration of machine learning would help to advance the field.

Dietary patterns and chronic kidney disease: a cross-sectional association in the Irish Nun Eye Study.

Associations between dietary patterns and chronic kidney disease are not well established, especially in European populations. We conducted a cross-sectional study of 1033 older Irish women (age range 56-100 years) with a restricted lifestyle. Dietary intake was assessed using a food frequency questionnaire. Renal function was determined by estimated glomerular filtration rate. Two dietary patterns were identified within the study population using factor analysis. A significant negative association was found between unhealthy dietary pattern adherence and renal function in both unadjusted and adjusted models controlling for potential confounding variables (p for trend <0.001), with a mean difference in estimated glomerular filtration rate of -6 ml/min/1.73 m2 between those in the highest fifth of adherence to the unhealthy dietary pattern compared to the lowest, in the fully adjusted model. Chronic kidney disease risk was significantly greater for the highest fifth, compared to the lowest fifth of unhealthy dietary pattern adherence in adjusted models (adjusted odds ratio = 2.62, p < 0.001). Adherence to the healthy dietary pattern was not associated with renal function or chronic kidney disease in adjusted models. In this cohort, an unhealthy dietary pattern was associated with lower renal function and greater prevalence of chronic kidney disease.

Evaluation of coronary artery disease as a risk factor for reticular pseudodrusen.

PURPOSE: Reticular pseudodrusen (RPD) are a risk factor for late age-related macular degeneration (AMD). Associations between RPD and coronary artery disease (CAD) have been reported from small case-control studies. This study investigated the association of RPD within a predominantly CAD cohort. METHODS: A subgroup of subjects from a multicentre randomised controlled trial of CT coronary angiography (CTCA) underwent ultrawide field (UWF) retinal imaging CAD determined by CTCA and was categorised as normal, non-obstructive or obstructive. Specific AMD features in UWF images were graded. Standardised grids were used to record the spatial location of AMD features, including RPD. Multivariate confounder adjusted regression models assessed the association between RPD and CAD. RESULTS: The 534 participants were aged 27-75 years (mean 58±9 years; 425 (80%) ≥50 years) with a male preponderance (56%). Within the study sample, 178 (33%) had no CAD, 351 (66%) had CAD. RPD was detected in 30 participants (5.6%) and bilaterally in 23. Most participants with bilateral RPD had intermediate AMD 17 (74%). After adjustment for potential confounders (age, sex, drusen >125 µm, smoking status), multivariate analysis found no significant association between CAD and RPD (OR 1.31; 95% CI (0.57 to 3.01); p=0.52). A significant association was identified between RPD and intermediate AMD (OR 3.18; 95% CI (1.61 to 6.27); p=0.001). CONCLUSION: We found no evidence to support an association between CAD and RPD. RPD was strongly associated with intermediate AMD features. TRIAL REGISTRATION NUMBER: NCT01149590, Post results.

Estimated Glomerular Filtration Rate is not Associated with Alzheimer's Disease in a Northern Ireland Cohort.

BACKGROUND: Alzheimer's disease (AD) prevalence is increasing globally and typically progresses for several years prior to clinical presentation of dementia. Renal dysfunction and vascular disease have been reported in association with dementia in several cross-sectional and longitudinal studies, and may contribute to AD risk. Experimental and observational studies suggest amyloid-ß (Aß) clearance may be impaired in chronic kidney disease (CKD) indicating a mechanism for increased AD risk. OBJECTIVE: The objective of this study was to compare estimated glomerular filtration rate (eGFR) between individuals with AD and cognitively intact controls, controlling for potential confounding factors. METHODS: A cross-sectional, case-control study was carried out in 317 cognitively normal participants and 253 cases with a clinical diagnosis of AD in a UK tertiary care dementia clinic. Associations were considered using logistic regression adjusting for confounding variables (age, APOEɛ4 genotype, systolic blood pressure, education (left school at 14), and smoking status). RESULTS: AD cases were older than cognitively intact controls, had lower MMSE scores, were more likely to have at least one APOEɛ4 allele, had higher rates of smoking, were more likely to be taking aspirin and/or clopidogrel, and had lower blood pressure. We found no significant association between eGFR and AD both before and following adjustment for appropriate confounders. CONCLUSION: This study failed to find an association between eGFR and AD in a cross-sectional sample study of elderly white individuals.

Blood vessel segmentation and width estimation in ultra-wide field scanning laser ophthalmoscopy.

Features of the retinal vasculature, such as vessel widths, are considered biomarkers for systemic disease. The aim of this work is to present a supervised approach to vessel segmentation in ultra-wide field of view scanning laser ophthalmoscope (UWFoV SLO) images and to evaluate its performance in terms of segmentation and vessel width estimation accuracy. The results of the proposed method are compared with ground truth measurements from human observers and with existing state-of-the-art techniques developed for fundus camera images that we optimized for UWFoV SLO images. Our algorithm is based on multi-scale matched filters, a neural network classifier and hysteresis thresholding. After spline-based refinement of the detected vessel contours, the vessel widths are estimated from the binary maps. Such analysis is performed on SLO images for the first time. The proposed method achieves the best results, both in vessel segmentation and in width estimation, in comparison to other automatic techniques.

Carotid intima-media thickness and cerebrovascular disease in community-dwelling older people without stroke.

BACKGROUND AND PURPOSE: Carotid intima-media thickness (CIMT) is a noninvasive measure of atherosclerosis, but it is unclear whether it is a stronger risk factor for large vessel disease or small vessel disease. METHODS: One hundred seven volunteers, aged 75 to 81 years, underwent measurements of CIMT and vascular risk factors and brain MRI (structural and diffusion tensor); those with history of stroke were excluded. RESULTS: In 96 subjects without stroke, there were significant associations between CIMT and markers of large vessel disease (carotid stenosis: rho=0.28; P=0.01) and intermediary risk factors (systolic blood pressure: rho=0.34; P=0.001). However, there were no significant associations between CIMT and markers of small vessel disease (white matter lesion load and water diffusion parameters). CONCLUSIONS: CIMT was not associated with neuroimaging biomarkers of small vessel disease in older volunteers without stroke. Any association between CIMT and white matter lesion in previous studies is likely to be mediated via common intermediary risk factors like hypertension.

Birth parameters are associated with late-life white matter integrity in community-dwelling older people.

BACKGROUND AND PURPOSE: Lower birth weight is associated with increased risk of stroke, but little is known about the mechanism for this association or influence in addition to vascular risk factors. We investigated whether there was an association between birth parameters and imaging markers of white matter integrity in community-dwelling older people. METHODS: One hundred seven volunteers, age 75 to 81 years, had birth parameters (weight, length, placental weight, gestational age) extracted from archives. Neuroimaging included assessment of white matter lesions and diffusion tensor-magnetic resonance imaging parameters in normal-appearing white matter. RESULTS: Lower placental weight was correlated with increased white matter lesion load (P<0.05) and diffusion tensor-magnetic resonance imaging parameters (P<0.05). Birth weight and frontal white matter fractional anisotropy were significantly correlated (P<0.05). These associations were only slightly attenuated when corrected for gestational age, sex, age at scan, and vascular risk factors. CONCLUSIONS: Lower placental and possibly lower birth weight were associated with sensitive neuroimaging measures of white matter lesions in this cohort, independent of vascular risk factors later in life. Further studies are required to confirm these findings to explore life-long risk factors for age-related white matter changes.

B-mode compound imaging in mice.

Cross-sectional B-mode images were obtained from a dead mouse for a 360 degrees scan around the mouse using a 12-MHz linear array. For each cross-section, a set of aligned images was obtained after rotation about the isocenter, which were added to produce a single compound image. The compound images demonstrated a substantial improvement over single B-mode images, with uniform image quality, low noise and improved visualization of structures. This technique may be of interest in forming the basis for a new 3-D in vivo technique in the abdomen and pelvic regions, providing high-quality ultrasound images that are not dependent on operator skill. A further development worth pursuing for improved spatial resolution is reconstruction-based tomography.

Childhood and current cognitive function in healthy 80-year-olds: a DT-MRI study.

Diffusion tensor MR imaging (DT-MRI) yields information on early pathological changes in white matter of the ageing brain which may correlate with cognitive function. However, because individuals vary in their cognitive ability, a measurement of prior cognition from youth is required to understand fully the significance of MR imaging changes associated with ageing. Here, diffusion tensor parameters and cognitive function were measured in a cohort of 30 older subjects whose cognitive ability was measured at age 11 and 80. There was a significant correlation between diffusion anisotropy measured in the centrum semiovale at age 80 and mental ability determined at age 11 and 80. These novel results suggest, that MR imaging studies of white matter structure and its relationship to mental ability in ageing should control for early life cognition.