Retinal imaging may serve as an alternative approach to monitor brain pathology in Alzheimer’s disease (AD). In this study, we investigated the association between retinal vascular and structural changes and cerebral amyloid-β (Aβ) plaque load in an elderly cohort. We studied a total of 101 participants, including 73 elderly subjects (79 ± 5 years, 22 male) with no clinical diagnosis of AD but reporting some subjective memory change and an additional 28 subjects (70 ± 9 years, 16 male) with clinically established AD. Following a complete dilated ocular examination, the amplitude of retinal vascular pulsations and dynamic response, retinal nerve fibre layer thickness and retinal ganglion cell layer (RGCL) thickness were determined in all patients. Systemic blood pressure and carotid-to-femoral pulse wave velocity were measured. The elderly cohort also underwent magnetic resonance imaging and 18F-florbetaben (FBB)-positron emission tomographic amyloid imaging to measure neocortical Aβ standardised uptake value ratio (SUVR), and this was used to characterise a ‘preclinical’ group (SUVR >1.4). The mean FBB neocortical SUVR was 1.35 ± 0.3. The amplitude of retinal venous pulsations correlated negatively with the neocortical Aβ scores (p < 0.001), whereas the amplitude of retinal arterial pulsations correlated positively with neocortical Aβ scores (p < 0.01). RGCL thickness was significantly lower in the clinical AD group (p < 0.05). The correlation between retinal vascular changes and Aβ plaque load supports the possibility of a vascular component to AD. Dynamic retinal vascular parameters may provide an additional inexpensive tool to aid in the preclinical assessment of AD.

Executive function (EF) is a set of cognitive capabilities considered essential for successful daily living, and is negatively affected by ageing and neurodegenerative conditions. Underpinning EF performance are functional nodes in the executive control network (ECN), while the structural connectivity underlying this network is not well understood. In this paper, we evaluated the structural white matter tracts that interconnect the ECN and investigated their relationship to the EF performance. Using high‐angular resolution diffusion MRI data, we performed tractography analysis of structural connectivity in a cognitively normal cohort (n = 140), specifically targeting the connectivity between ECN nodes. Our data revealed the presence of a strongly‐connected “structural core” of the ECN comprising three components: interhemispheric frontal connections, a fronto‐parietal subnetwork and fronto‐striatal connections between right dorsolateral prefrontal cortex and right caudate. These pathways were strongly correlated with EF performance (p = .003). Post‐hoc analysis of subregions within the significant ECN connections showed that these effects were driven by a highly specific subset of interconnected cortical regions. The structural core subnetwork of the functional ECN may be an important feature crucial to a better future understanding of human cognition and behaviour.

Accurate localization of the prostate and its surrounding tissue is essential in the treatment of prostate cancer. This paper presents a novel approach to fully automatically segment the prostate, including its seminal vesicles, within a few minutes of a magnetic resonance (MR) scan acquired without an endorectal coil. Such MR images are important in external beam radiation therapy, where using an endorectal coil is highly undesirable. The segmentation is obtained using a deformable model that is trained on-the-fly so that it is specific to the patient's scan. This case specific deformable model consists of a patient specific initialized triangulated surface and image feature model that are trained during its initialization. The image feature model is used to deform the initialized surface by template matching image features (via normalized cross-correlation) to the features of the scan. The resulting deformations are regularized over the surface via well established simple surface smoothing algorithms, which is then made anatomically valid via an optimized shape model. Mean and median Dice's similarity coefficients (DSCs) of 0.85 and 0.87 were achieved when segmenting 3T MR clinical scans of 50 patients. The median DSC result was equal to the inter-rater DSC and had a mean absolute surface error of 1.85 mm. The approach is showed to perform well near the apex and seminal vesicles of the prostate.

Background: Blood markers indicative of neurodegeneration (neurofilament light chain; NFL), Alzheimer’s disease amyloid pathology (amyloid-β; Aβ), and neuroinflammation (kynurenine pathway; KP metabolites) have been investigated independently in neurodegenerative diseases. However, the association of these markers of neurodegeneration and AD pathology with neuroinflammation has not been investigated previously. Therefore, the current study examined whether NFL and Aβ correlate with KP metabolites in elderly individuals to provide insight on the association between blood indicators of neurodegeneration and neuroinflammation.Methods: Correlations between KP metabolites, measured using liquid chromatography and gas chromatography coupled with mass spectrometry, and plasma NFL and Aβ concentrations, measured using single molecule array (Simoa) assays, were investigated in elderly individuals aged 65–90 years, with normal global cognition (Mini-Mental State Examination Score ≥ 26) from the Kerr Anglican Retirement Village Initiative in Ageing Health cohort.Results: A positive correlation between NFL and the kynurenine to tryptophan ratio (K/T) reflecting indoleamine 2,3-dioxygenase activity was observed (r = .451,p < .0001). Positive correlations were also observed between NFL and kynurenine (r = .364,p < .0005), kynurenic acid (r = .384,p < .0001), 3-hydroxykynurenine (r = .246,p = .014), anthranilic acid (r = .311,p = .002), and quinolinic acid (r = .296,p = .003). Further, significant associations were observed between plasma Aβ40 and the K/T (r = .375,p < .0005), kynurenine (r = .374,p < .0005), kynurenic acid (r = .352,p < .0005), anthranilic acid (r = .381,p < .0005), and quinolinic acid (r = .352,p < .0005). Significant associations were also observed between plasma Aβ42 and the K/T ratio (r = .215,p = .034), kynurenic acid (r = .214,p = .035), anthranilic acid (r = .278,p = .006), and quinolinic acid (r = .224,p = .027) in the cohort. On stratifying participants based on their neocortical Aβ load (NAL) status, NFL correlated with KP metabolites irrespective of NAL status; however, associations between plasma Aβ and KP metabolites were only pronounced in individuals with high NAL while associations in individuals with low NAL were nearly absent.Conclusions: The current study shows that KP metabolite changes are associated with biomarker evidence of neurodegeneration. Additionally, the association between KP metabolites and plasma Aβ seems to be NAL status dependent. Finally, the current study suggests that an association between neurodegeneration and neuroinflammation manifests in the periphery, suggesting that preventing cytoskeleton cytotoxicity by KP metabolites may have therapeutic potential.