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Water exchange rate (Kw) across the blood–brain barrier (BBB) is an important physiological parameter that may provide new insight into ageing and neurodegenerative disease. Recently, two non‐invasive arterial spin labelling (ASL) MRI methods have been developed to measure Kw, but results from the different methods have not been directly compared. Furthermore, the association of Kw with age for each method has not been investigated in a single cohort. Thirty participants (70% female, 63.8 ± 10.4 years) were scanned at 3 T with Diffusion‐Prepared ASL (DP‐ASL) and Multi‐Echo ASL (ME‐ASL) using previously implemented acquisition and analysis protocols. Grey matter Kw, cerebral blood flow (CBF) and arterial transit time (ATT) were extracted. CBF values were consistent; approximately 50 ml/min/100 g for both methods, and a strong positive correlation in CBF from both methods across participants (r = 0.82, p < 0.001). ATT was significantly different between methods (on average 147.7 ms lower when measured with DP‐ASL compared to ME‐ASL) but was positively correlated across participants (r = 0.39, p < 0.05). Significantly different Kw values of 106.6 ± 19.7 min−1 and 306.8 ± 71.7 min−1 were measured using DP‐ASL and ME‐ASL, respectively, and DP‐ASL Kw and ME‐ASL Kw were negatively correlated across participants (r = −0.46, p < 0.01). Kw measured using ME‐ASL had a significant linear relationship with age (p < 0.05). In conclusion, DP‐ASL and ME‐ASL provided estimates of Kw with significantly different quantitative values and inconsistent dependence with age. We propose future standardisation of modelling and fitting methods for DP‐ASL and ME‐ASL, to evaluate the effect on Kw quantification. Also, sensitivity and bias analyses should be performed for both approaches, to assess the effect of varying acquisition and fitting parameters. Lastly, comparison with independent measures of BBB water transport, and with physiological and clinical biomarkers known to be associated with changes in BBB permeability, are essential to validate the ASL methods, and to demonstrate their clinical utility. [ABSTRACT FROM AUTHOR]

The article discusses the impairment of emotion recognition in frontotemporal dementias, focusing on subtypes such as behavioral variant frontotemporal dementia (bvFTD) and primary progressive aphasia (PPA). It highlights the challenges in diagnosing these conditions due to varying behavioral symptoms and the importance of social cognition in distinguishing between different types of dementia. The study by Gressie et al. examines error patterns in facial emotion recognition among FTD subtypes and Alzheimer's disease, emphasizing the potential for improved diagnostic accuracy and disease management through a better understanding of emotional recognition deficits. [Extracted from the article]

Background: White matter hyperintensities (WMHs) are common in normally functioning older adults. While greater WMH volume may be associated with an increased risk of cognitive dysfunction and dementia, the impact of the location of WMHs is less well understood. We investigated whether WMH burden in specific white matter (WM) tracts is associated with clinical classification and global cognitive scores in at‐risk groups for Alzheimer's disease (AD). Method: Participants from Dementia Prevention Research Clinics, New Zealand, were classified as control, subjective cognitive decline, single‐domain amnestic mild cognitive impairment (MCI), multiple‐domain amnestic MCI, or early AD by a multidisciplinary team (Table 1). Several tract‐WMH "overlap scores" (the percentage of total tract voxels containing WMHs) were calculated for each participant's binarised WMH map (Lesion Segmentation Toolbox, SPM) using seven tract probability templates from a 140‐subject tract atlas (www.megatrackatlas.org). Tract templates were of the superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF), inferior fronto‐occipital fasciculus (IFOF), uncinate fasciculus (UF), cingulum (CB), fornix, and corpus callosum (CC). Between‐group differences in overlap scores were tested with ANOVAs. Pearson's correlations examined associations between tract‐WMH overlap and global cognitive scores. Result: Figure 1 shows WMH overlap with one tract, the IFOF, in a representative participant. Considering the whole sample, the highest tract‐WMH overlap scores can be seen in the IFOF and CC. Significant between‐group differences were found for the SLF, ILF, IFOF, UF, and CC (p <.05), but not the CB or fornix (Fig. 2), with significant linear trends describing the relationship between overlap scores and clinical classification. Post‐hoc tests confirmed significant pairwise comparisons for overlap scores in all aforementioned tracts except the SLF (Fig. 2). We found Addenbrooke's Cognitive Examination‐III scores negatively correlated with overlap scores in the ILF (r = ‐0.19), IFOF(r = ‐0.22), UF(r = ‐0.22), and CC(r = ‐0.19) (all p <.01), but not the SLF, CB, or fornix (p >.05). Conclusion: Our findings highlight that WMH burden within specific WM tracts is associated with degree of clinical impairment in groups at‐risk of AD. Future research will investigate relationships between overlap scores in specific WM tracts and executive functioning, episodic memory, and processing speed performance. [ABSTRACT FROM AUTHOR]

The New Zealand Genetic Frontotemporal Dementia Study (FTDGeNZ) is an emerging longitudinal study of a large New Zealand pedigree with genetic frontotemporal dementia (FTD). Natural history studies of genetic FTD cohorts provide a unique opportunity to identify biomarkers of pre-symptomatic dementia, as carriers can be identified and studied decades before expected symptom onset. FTDGeNZ was established in 2016 with the aim of identifying the earliest pre-symptomatic biomarkers of FTD, in collaboration with international multi-centre cohorts. We enrolled 25 participants from a single family between April 2016 and August 2018. Participants were genotyped to determine whether they were pre-symptomatic carriers of the mutation (MAPT IVS 10 + 16 C > T), or non-carrier controls. Participants have undergone clinical assessments including neuropsychological and mood assessment; olfactory testing; assessment of social cognition; and blood collection for analyses of microRNA and protein fluid biomarkers annually. We have also performed structural and functional MRI of the brain and assessment of autobiographical memory biennially, and retinal imaging at baseline. Here, we describe the full study protocol and the baseline demographic and clinical characteristics of the FTDGeNZ cohort, and we highlight the latest findings in the field. [ABSTRACT FROM AUTHOR]