scholarly journals The aging human brain: A causal analysis of the effect of sex and age on brain volume

2020 ◽  
Author(s):  
Jaime Gómez-Ramírez ◽  
Miguel A. Fernández-Blázquez ◽  
Javier González-Rosa
Keyword(s):  
Old Age ◽  
Brain Atrophy ◽  
Healthy Subjects ◽  
Brain Volume ◽  
Causal Analysis ◽  
Intracranial Volume ◽  
Volume Loss ◽  
Brain Volume Loss ◽  
Mri Scans ◽  
The Brain

AbstractThe goal of this work is to study how brain volume loss at old age is affected by factors such as age, APOE gene, sex, and school level. The study of brain volume loss at old age relative to young age requires at least in principle two MRI scans performed at both young and old age. There is, however, a way to address the problem by having only one MRI scan at old age. We compute the total brain loss of elderly subjects as the ratio between the estimated brain volume and the estimated total intracranial volume. Magnetic resonance imaging (MRI) scans of 890 healthy subjects aged 69 to 85 were assessed. The causal analysis of factors affecting brain atrophy was performed using Probabilistic Bayesian Modeling and the mathematics of Causal Inference. We find that healthy subjects get into their seventies with an average brain volume loss of 30% from their maximum brain volume at a young age. Both age and sex are causally related to brain atrophy, with women getting to elderly age with 1% larger brain volume relative to intracranial volume than men. How the brain ages and what are the reasons for sex differences in adult lifespan are causal questions that need to be addressed with causal inference and empirical data. The graphical causal modeling presented here can be instrumental in understanding a puzzling scientific inquiry-the biological age of the brain.

scholarly journals BrainFD: Measuring the Intracranial Brain Volume With Fractal Dimension

2021 ◽  
Vol 13 ◽  
Author(s):  
Ghulam Md Ashraf ◽  
Stylianos Chatzichronis ◽  
Athanasios Alexiou ◽  
Nikolaos Kyriakopoulos ◽  
Badrah Saeed Ali Alghamdi ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Brain Volume ◽  
Heterogeneous Data ◽  
Imaging Biomarker ◽  
Volume Loss ◽  
Imaging Data ◽  
Clinical Dementia Rating ◽  
Brain Volume Loss ◽  
Brain White Matter ◽  
The Brain

A few methods and tools are available for the quantitative measurement of the brain volume targeting mainly brain volume loss. However, several factors, such as the clinical conditions, the time of the day, the type of MRI machine, the brain volume artifacts, the pseudoatrophy, and the variations among the protocols, produce extreme variations leading to misdiagnosis of brain atrophy. While brain white matter loss is a characteristic lesion during neurodegeneration, the main objective of this study was to create a computational tool for high precision measuring structural brain changes using the fractal dimension (FD) definition. The validation of the BrainFD software is based on T1-weighted MRI images from the Open Access Series of Imaging Studies (OASIS)-3 brain database, where each participant has multiple MRI scan sessions. The software is based on the Python and JAVA programming languages with the main functionality of the FD calculation using the box-counting algorithm, for different subjects on the same brain regions, with high accuracy and resolution, offering the ability to compare brain data regions from different subjects and on multiple sessions, creating different imaging profiles based on the Clinical Dementia Rating (CDR) scores of the participants. Two experiments were executed. The first was a cross-sectional study where the data were separated into two CDR classes. In the second experiment, a model on multiple heterogeneous data was trained, and the FD calculation for each participant of the OASIS-3 database through multiple sessions was evaluated. The results suggest that the FD variation efficiently describes the structural complexity of the brain and the related cognitive decline. Additionally, the FD efficiently discriminates the two classes achieving 100% accuracy. It is shown that this classification outperforms the currently existing methods in terms of accuracy and the size of the dataset. Therefore, the FD calculation for identifying intracranial brain volume loss could be applied as a potential low-cost personalized imaging biomarker. Furthermore, the possibilities measuring different brain areas and subregions could give robust evidence of the slightest variations to imaging data obtained from repetitive measurements to Physicians and Radiologists.

Reversible brain atrophy following liver transplantation for biliary atresia in childhood

2020 ◽  
pp. 10.1212/CPJ.0000000000000991
Author(s):  
Aikaterini Fitsiori ◽  
Valérie McLin ◽  
Seema Toso ◽  
Maria-Isabel Vargas
Keyword(s):  
Liver Transplantation ◽  
Anorexia Nervosa ◽  
Biliary Atresia ◽  
Brain Atrophy ◽  
Early Life ◽  
Rare Case ◽  
Brain Volume ◽  
The Other ◽  
Volume Loss ◽  
Brain Volume Loss

A great deal of the brain's ultimate structure and capacity is shaped early in life, before the age of 3 years.1The influence of optimal nutrition during early life on brain development has been demonstrated by numerous studies.1–3 On the other hand, brain volume loss is accepted to be progressive with age and may be permanent. However, reversible brain atrophy has been demonstrated in adults with anorexia nervosa4 and reported in children suffering from kwashiorkor.5,6 We would like to report on a rare case of reversible brain atrophy in a child following correction of malabsorption.

Brain volume reductions in medication-naive patients with schizophrenia in relation to intelligence quotient

2012 ◽  
Vol 42 (9) ◽  
pp. 1847-1856 ◽  
Author(s):  
M. Rais ◽  
W. Cahn ◽  
H. G. Schnack ◽  
H. E. Hulshoff Pol ◽  
R. S. Kahn ◽  
...  
Keyword(s):  
White Matter ◽  
Healthy Subjects ◽  
Intelligence Quotient ◽  
Brain Volume ◽  
First Episode ◽  
Volume Loss ◽  
White Matter Volume ◽  
Matter Volume ◽  
Brain Volume Loss ◽  
First Episode Schizophrenia

BackgroundGlobal brain abnormalities such as brain volume loss and grey- and white-matter deficits are consistently reported in first-episode schizophrenia patients and may already be detectable in the very early stages of the illness. Whether these changes are dependent on medication use or related to intelligence quotient (IQ) is still debated.MethodMagnetic resonance imaging scans were obtained for 20 medication-naive patients with first-episode schizophrenia and 26 matched healthy subjects. Volume measures of total brain grey and white matter, third and lateral ventricles and cortical thickness/surface were obtained. Differences between the groups were investigated, taking into account the effect of intelligence.ResultsMedication-naive patients showed statistically significant reductions in whole-brain volume and cerebral grey- and white-matter volume together with lateral ventricle enlargement compared to healthy subjects. IQ was significantly lower in patients compared to controls and was positively associated with brain and white-matter volume in the whole group. No significant differences in cortical thickness were found between the groups but medication-naive patients had a significantly smaller surface in the left superior temporal pole, Heschl's gyrus and insula compared to controls.ConclusionsOur findings suggest that brain volume loss is present at illness onset, and can be explained by the reduced surface of the temporal and insular cortex. These abnormalities are not related to medication, but IQ.

Clinical impact of early brain atrophy in clinically isolated syndromes

2013 ◽  
Vol 19 (14) ◽  
pp. 1878-1886 ◽  
Author(s):  
F Pérez-Miralles ◽  
J Sastre-Garriga ◽  
M Tintoré ◽  
G Arrambide ◽  
C Nos ◽  
...  
Keyword(s):  
Brain Atrophy ◽  
Grey Matter ◽  
Brain Volume ◽  
First Year ◽  
Grey Matter Volume ◽  
Volume Loss ◽  
Mcdonald Criteria ◽  
Brain Volume Loss ◽  
Clinical Onset ◽  
The Impact

Background: The impact of global and tissue-specific brain atrophy on conversion to multiple sclerosis (MS) after a clinically isolated syndrome (CIS) is not fully gauged. Objectives: We aimed to determine the magnitude and clinical relevance of brain volume dynamics in the first year after a CIS. Methods: We assessed 176 patients with CIS within 3 months of onset, clinically and by conventional magnetic resonance imaging (MRI) scans, at baseline and 1 year after clinical onset. We determined the percentage of brain volume change (PBVC) and the brain parenchymal (BPF), grey matter (GMF) and white matter (WMF) fractions. Results: The mean follow-up time was 53 months (SD = 16.8): 76 patients (43%) experienced a second attack, 32 (18%) fulfilled MRI-only 2005 McDonald criteria and 68 (39%) remained as CIS. Statistically significant decreases in the volume measures tested were observed in patients with a second attack, for BPF and PBVC; in both MS groups for GMF; whereas in all groups, the WMF was unchanged. Patients with a second attack had larger PBVC decreases (− 0.65% versus + 0.059%; p < 0.001). PBVC decreases below − 0.817% independently predicted shorter times to a second attack. Conclusions: Global brain and grey matter volume loss occurred within the first year after a CIS; brain volume loss predicted conversion to MS.

scholarly journals Evolution of Brain Volume Loss Rates in Early Stages of Multiple Sclerosis

2021 ◽  
Vol 8 (3) ◽  
pp. e979
Author(s):  
Tomas Uher ◽  
Jan Krasensky ◽  
Charles Malpas ◽  
Niels Bergsland ◽  
Michael G. Dwyer ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Disease Duration ◽  
Brain Volume ◽  
Brain Mri ◽  
Quantitative Mri ◽  
Volume Loss ◽  
Tissue Specific ◽  
Brain Volume Loss ◽  
Mri Scans ◽  
Treatment Escalation

ObjectiveTo describe the dynamics of brain volume loss (BVL) at different stages of relapsing-remitting multiple sclerosis (RRMS), to describe the association between BVL and clinical measures, and to investigate an effect of treatment escalation on the rate of BVL.MethodsTogether, 1903 patients predominantly with RRMS from the Avonex-Steroids-Azathioprine cohort (N = 166), the study of early IFN-β1a treatment cohort (N = 180), and the quantitative MRI cohort (N = 1,557) with ≥2 MRI scans and ≥1-year of follow-up were included. Brain MRI scans (N = 7,203) were performed using a single 1.5-T machine. Relationships between age or disease duration and global and tissue-specific BVL rates were analyzed using mixed models.ResultsAge was not associated with the rate of BVL (β = −0.003; Cohen f2 = 0.0005; adjusted p = 0.39). Although disease duration was associated with the rate of BVL, its effect on the BVL rate was minimal (β = −0.012; Cohen f2 = 0.004; adjusted p = 4 × 10−5). Analysis of association between tissue-specific brain volume changes and age (β = −0.019 to −0.011; adjusted p = 0.028–1.00) or disease duration (β = −0.028 to −0.008; adjusted p = 0.16–0.96) confirmed these results. Although increase in the relapse rate (β = 0.10; adjusted p = 9 × 10−9), Expanded Disability Status Scale (EDSS; β = 0.17; adjusted p = 8 × 10−5), and EDSS change (β = 0.15; adjusted p = 2 × 10−5) were associated with accelerated rate of BVL, their effect on the rate of BVL was minimal (all Cohen f2 ≤ 0.007). In 94 patients who escalated therapy, the rate of BVL decreased following treatment escalation by 0.29% (β = −0.29; Cohen f2 = 0.133; p = 5.5 × 10−8).ConclusionsThe rate of BVL is relatively stable throughout the course of RRMS. The accelerated BVL is weakly associated with concurrent higher disease activity, and timely escalation to high-efficacy immunotherapy helps decrease the rate of BVL.

Pathological cut-offs of global and regional brain volume loss in multiple sclerosis

2017 ◽  
Vol 25 (4) ◽  
pp. 541-553 ◽  
Author(s):  
Tomas Uher ◽  
Manuela Vaneckova ◽  
Jan Krasensky ◽  
Lukas Sobisek ◽  
Michaela Tyblova ◽  
...  
Keyword(s):  
Corpus Callosum ◽  
Grey Matter ◽  
Brain Volume ◽  
Healthy Controls ◽  
Volume Loss ◽  
Whole Brain ◽  
Brain Volume Loss ◽  
Regional Brain ◽  
Mri Scans ◽  
Regional Brain Volume

Background: Volumetric MRI surrogate markers of disease progression are lacking. Objective: To establish cut-off values of brain volume loss able to discriminate between healthy controls and MS patients. Methods: In total, 386 patients after first demyelinating event suggestive of MS (CIS), 964 relapsing-remitting MS (RRMS) patients, 63 secondary-progressive MS (SPMS) patients and 58 healthy controls were included in this longitudinal study. A total of 11,438 MRI scans performed on the same MRI scanner with the same protocol were analysed. Annualised percentage changes of whole brain, grey matter, thalamus and corpus callosum volumes were estimated. We investigated cut-offs able to discriminate between healthy controls and MS patients. Results: At a predefined specificity of 90%, the annualised percentage change cut-off of corpus callosum volume (−0.57%) was able to distinguish between healthy controls and patients with the highest sensitivity (51% in CIS, 48% in RRMS and 42% in SPMS patients). Lower sensitivities (22%−49%) were found for cut-offs of whole brain, grey matter and thalamic volume loss. Among CIS and RRMS patients, cut-offs were associated with greater accumulation of disability. Conclusion: We identified cut-offs of annualised global and regional brain volume loss rates able to discriminate between healthy controls and MS patients.

scholarly journals Dynamic Regional Brain Atrophy Rates in the First Year After Ischemic Stroke

Stroke ◽  
2020 ◽  
Vol 51 (9) ◽  
Author(s):  
Amy Brodtmann ◽  
Mohamed Salah Khlif ◽  
Natalia Egorova ◽  
Michele Veldsman ◽  
Laura J. Bird ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Cortical Thickness ◽  
Brain Atrophy ◽  
Brain Volume ◽  
Linear Mixed Effect Model ◽  
First Year ◽  
Intracranial Volume ◽  
Mixed Effect ◽  
Time Points ◽  
Regional Brain

Background and Purpose: Brain atrophy can be regarded as an end-organ effect of cumulative cardiovascular risk factors. Accelerated brain atrophy is described following ischemic stroke, but it is not known whether atrophy rates vary over the poststroke period. Examining rates of brain atrophy allows the identification of potential therapeutic windows for interventions to prevent poststroke brain atrophy. Methods: We charted total and regional brain volume and cortical thickness trajectories, comparing atrophy rates over 2 time periods in the first year after ischemic stroke: within 3 months (early period) and between 3 and 12 months (later period). Patients with first-ever or recurrent ischemic stroke were recruited from 3 Melbourne hospitals at 1 of 2 poststroke time points: within 6 weeks (baseline) or 3 months. Whole-brain 3T magnetic resonance imaging was performed at 3 time points: baseline, 3 months, and 12 months. Eighty-six stroke participants completed testing at baseline; 125 at 3 months (76 baseline follow-up plus 49 delayed recruitment); and 113 participants at 12 months. Their data were compared with 40 healthy control participants with identical testing. We examined 5 brain measures: hippocampal volume, thalamic volume, total brain and hemispheric brain volume, and cortical thickness. We tested whether brain atrophy rates differed between time points and groups. A linear mixed-effect model was used to compare brain structural changes, including age, sex, years of education, a composite cerebrovascular risk factor score, and total intracranial volume as covariates. Results: Atrophy rates were greater in stroke than control participants. Ipsilesional hemispheric, hippocampal, and thalamic atrophy rates were 2 to 4 times greater in the early versus later period. Conclusions: Regional atrophy rates vary over the first year after stroke. Rapid brain volume loss in the first 3 months after stroke may represent a potential window for intervention. Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT02205424.

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