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- Ge, R, et al.
(författare)
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Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization
- 2023
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Ingår i: bioRxiv : the preprint server for biology. - : Cold Spring Harbor Laboratory.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background: Normative modeling is a statistical approach to quantify the degree to which a particular individual-level measure deviates from the pattern observed in a normative reference population. When applied to human brain morphometric measures it has the potential to inform about the significance of normative deviations for health and disease. Normative models can be implemented using a variety of algorithms that have not been systematically appraised. Methods: To address this gap, eight algorithms were compared in terms of performance and computational efficiency using brain regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) collated from 87 international MRI datasets. Performance was assessed with the mean absolute error (MAE) and computational efficiency was inferred from central processing unit (CPU) time. The algorithms evaluated were Ordinary Least Squares Regression (OLSR), Bayesian Linear Regression (BLR), Generalized Additive Models for Location, Scale, and Shape (GAMLSS), Parametric Lambda, Mu, Sigma (LMS), Gaussian Process Regression (GPR), Warped Bayesian Linear Regression (WBLG), Hierarchical Bayesian Regression (HBR), and Multivariable Fractional Polynomial Regression (MFPR). Model optimization involved testing nine covariate combinations pertaining to acquisition features, parcellation software versions, and global neuroimaging measures (i.e., total intracranial volume, mean cortical thickness, and mean cortical surface area). Findings: Statistical comparisons across models at PFDR<0.05 indicated that the MFPR-derived sex- and region-specific models with nonlinear polynomials for age and linear effects of global measures had superior predictive accuracy; the range of the MAE of the models of regional subcortical volumes was 70-520 mm3 and the corresponding ranges for regional cortical thickness and regional cortical surface area were 0.09-0.26 mm and 24-560 mm2, respectively. The MFPR-derived models were also computationally more efficient with a CPU time below one second compared to a range of 2 seconds to 60 minutes for the other algorithms. The performance of all sex- and region-specific MFPR models plateaued at sample sizes exceeding 3,000 and showed comparable MAEs across distinct 10-year age-bins covering the human lifespan. Interpretation: These results provide an empirically benchmarked framework for normative modeling of brain morphometry that is useful for interpreting prior literature and supporting future study designs. The model and tools described here are freely available through CentileBrain (https://centilebrain.org/), a user-friendly web platform.
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- Hagberg, L A, et al.
(författare)
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Importance of enjoyment when promoting physical exercise
- 2009
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Ingår i: Scandinavian Journal of Medicine and Science in Sports. - : Wiley. - 0905-7188 .- 1600-0838. ; 19:5, s. 740-747
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Tidskriftsartikel (refereegranskat)abstract
- The purpose of this study was to investigate the importance of enjoyment of exercise in a health care-based intervention aimed at promoting physical exercise in primary health care patients. In a controlled study design, the intervention group was offered a wide range of group exercises over 3 months, followed by support in designing their own exercise program. The control group received usual care. Enjoyment of exercise and exercise level were measured. Associations between enjoyment and exercise level were analyzed using Spearman's rank correlation coefficients. Changes in enjoyment between and within study groups were analyzed by the independent and paired t-test. Associations were found between enjoyment and exercise level (r=0.36, P<0.01), as well as between changes in enjoyment and changes in exercise level (r=0.34, P<0.01). At the 12-month follow-up, enjoyment of exercise was 25% higher in the intervention group than in the control group (P<0.01). In this group of primary health care patients, enjoyment of exercise was associated with exercise level. Enjoyment of exercise seems to be a mediator of exercise level. Furthermore, health care-based interventions seem to be able to affect enjoyment of exercise. Enjoyment of exercise may be important for the long-term effectiveness, of health care-based interventions.
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