Brain Commun.

The chronological progression of brain atrophy over decades, from pre-symptomatic to dementia stages, has never been formally depicted in Alzheimer's disease. This is mainly due to the lack of cohorts with long enough MRI follow-ups in cognitively unimpaired young participants at baseline. To describe a spatiotemporal atrophy staging of Alzheimer's disease at the whole-brain level, we built extrapolated lifetime volumetric models of healthy and Alzheimer's disease brain structures by combining multiple large-scale databases (n = 3512 quality controlled MRI from 9 cohorts of subjects covering the entire lifespan, including 415 MRI from ADNI1, ADNI2 and AIBL for Alzheimer's disease patients). Then, we validated dynamic models based on cross-sectional data using external longitudinal data. Finally, we assessed the sequential divergence between normal aging and Alzheimer's disease volumetric trajectories and described the following staging of brain atrophy progression in Alzheimer's disease: (i) hippocampus and amygdala; (ii) middle temporal gyrus; (iii) entorhinal cortex, parahippocampal cortex and other temporal areas; (iv) striatum and thalamus and (v) middle frontal, cingular, parietal, insular cortices and pallidum. We concluded that this MRI scheme of atrophy progression in Alzheimer's disease was close but did not entirely overlap with Braak staging of tauopathy, with a 'reverse chronology' between limbic and entorhinal stages. Alzheimer's disease structural progression may be associated with local tau accumulation but may also be related to axonal degeneration in remote sites and other limbic-predominant associated proteinopathies. © 2022 The Author(s). Published by Oxford University Press on behalf of the Guarantors of Brain.Apprentissage profond pour la volumétrie cérébrale : vers le BigData en neuroscienceTranslational Research and Advanced Imaging Laborator

Long-term antipsychotic and benzodiazepine use. and brain volume changes in schizophrenia : The Northern Finland Birth Cohort 1966 study

High doses of antipsychotics have been associated with loss in cortical and total gray matter in schizophrenia. However, previous imaging studies have not taken benzodiazepine use into account, in spite of evidence suggesting adverse effects such as cognitive impairment and increased mortality. In this Northern Finland Birth Cohort 1966 study, 69 controls and 38 individuals with schizophrenia underwent brain MRI at the ages of 34 and 43 years. At baseline, the average illness duration was over 10 years. Brain structures were delineated using an automated volumetry system, volBrain, and medication data on cumulative antipsychotic and benzodiazepine doses were collected using medical records and interviews. We used linear regression with intracranial volume and sex as covariates; illness severity was also taken into account. Though both medication doses associated to volumetric changes in subcortical structures, after adjusting for each other and the average PANSS total score, higher scan-interval antipsychotic dose associated only to volume increase in lateral ventricles and higher benzodiazepine dose associated with volume decrease in the caudate nucleus. To our knowledge, there are no previous studies reporting associations between benzodiazepine dose and brain structural changes. Further studies should focus on how these observations correspond to cognition and functioning.Peer reviewe

A CANDLE for a deeper in-vivo insight

A new Collaborative Approach for eNhanced Denoising under Low-light Excitation (CANDLE) is introduced for the processing of 3D laser scanning multiphoton microscopy images. CANDLE is designed to be robust for low signal-to-noise ratio (SNR) conditions typically encountered when imaging deep in scattering biological specimens. Based on an optimized non-local means filter involving the comparison of filtered patches, CANDLE locally adapts the amount of smoothing in order to deal with the noise inhomogeneity inherent to laser scanning fluorescence microscopy images. An extensive validation on synthetic data, images acquired on microspheres and in vivo images is presented. These experiments show that the CANDLE filter obtained competitive results compared to a state-of-the-art method and a locally adaptive optimized non-local means filter, especially under low SNR conditions (PSNR < 8 dB). Finally, the deeper imaging capabilities enabled by the proposed filter are demonstrated on deep tissue in vivo images of neurons and fine axonal processes in the Xenopus tadpole brain.We want to thank Florian Luisier for providing free plugin of his PureDenoise filter. We also want to thank Markku Makitalo for providing the code of their OVST. This study was supported by the Canadian Institutes of Health Research (CIHR, MOP-84360 to DLC and MOP-77567 to ESR) and Cda (CECR)-Gevas-OE016. MM holds a fellowship from the Deutscher Akademischer Austasch Dienst (DAAD) and a McGill Principal's Award. ESR is a tier 2 Canada Research Chair. This work has been partially supported by the Spanish Health Institute Carlos III through the RETICS Combiomed, RD07/0067/2001. This work benefited from the use of ImageJ.Coupé, P.; Munz, M.; Manjón Herrera, JV.; Ruthazer, ES.; Collins, DL. (2012). A CANDLE for a deeper in-vivo insight. Medical Image Analysis. 16(4):849-864. https://doi.org/10.1016/j.media.2012.01.002S84986416

Stroke

Background and Purpose: Many neurological or psychiatric diseases affect the hippocampus during aging. The study of hippocampal regional vulnerability may provide important insights into the pathophysiological mechanisms underlying these processes; however, little is known about the specific impact of vascular brain damage on hippocampal subfields atrophy. Methods: To analyze the effect of vascular injuries independently of other pathological conditions, we studied a population-based cohort of nondemented older adults, after the exclusion of people who were diagnosed with neurodegenerative diseases during the 14-year clinical follow-up period. Using an automated segmentation pipeline, 1.5T-magnetic resonance imaging at inclusion and 4 years later were assessed to measure both white matter hyperintensities and hippocampal subfields volume. Annualized rates of white matter hyperintensity progression and annualized rates of hippocampal subfields atrophy were then estimated in each participant. Results: We included 249 participants in our analyses (58% women, mean age 71.8, median Mini-Mental State Evaluation 29). The volume of the subiculum at baseline was the only hippocampal subfield volume associated with total, deep/subcortical, and periventricular white matter hyperintensity volumes, independently of demographic variables and vascular risk factors (β=−0.17, P=0.011; β=−0.25, P=0.020 and β=−0.14, P=0.029, respectively). In longitudinal measures, the annualized rate of subiculum atrophy was significantly higher in people with the highest rate of deep/subcortical white matter hyperintensity progression, independently of confounding factors (β=−0.32, P=0.014). Conclusions: These cross-sectional and longitudinal findings highlight the links between vascular brain injuries and a differential vulnerability of the subiculum within the hippocampal loop, unbiased of the effect of neurodegenerative diseases, and particularly when vascular injuries affect deep/subcortical structures