A scoping review of automatic and semi-automatic MRI segmentation in human brain imaging

Radiography, Journal Year: 2025, Volume and Issue: 31(2), P. 102878 - 102878

Published: Jan. 31, 2025

Language: Английский

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Deep learning‐based BMI inference from structural brain MRI reflects brain alterations following lifestyle intervention

Human Brain Mapping, Journal Year: 2024, Volume and Issue: 45(3)

Published: Feb. 15, 2024

Abstract Obesity is associated with negative effects on the brain. We exploit Artificial Intelligence (AI) tools to explore whether differences in clinical measurements following lifestyle interventions overweight population could be reflected brain morphology. In DIRECT‐PLUS trial, participants criterion for metabolic syndrome underwent an 18‐month intervention. Structural MRIs were acquired before and after utilized ensemble learning framework predict Body‐Mass Index (BMI) scores, which correspond adiposity‐related from MRIs. revealed that patient‐specific reduction BMI predictions was actual weight loss significantly higher active diet groups compared a control group. Moreover, explainable AI (XAI) maps highlighted regions contributing distinct age prediction. Our analysis results imply predicted its are unique neural biomarkers obesity‐related modifications loss.

Language: Английский

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Novel brain biomarkers of obesity in young adult women based on statistical measurements of white matter tracts

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(4), P. e0319936 - e0319936

Published: April 10, 2025

Objective Novel brain biomarkers of obesity were sought by studying statistical measurements on fractional anisotropy (FA) images different white matter (WM) tracts from young adult women. Methods Tract chosen that showed differences between two groups (normal weight and overweight/obese) correlated with BMI. From these measurements, a simple novel process was applied to select those would allow the creation models quantify classify state individuals. The created tract used in models. Results Positive correlations found WM integrity BMI, mainly involved motor functions. results, built status, whose regression coefficients formed proposed associated biomarkers. Conclusion A for selection proposed, such determine status subjects individually. models, created. These results generate new knowledge field, intended be future clinical environment as prevention treatment tool changes obesity. Significance After women, opposed some previous reported literature. consisted positive also precise quantification classification status. All this allows generation its probable subsequent application.

Language: Английский

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Multimodal Neuroimaging of Obesity: From Structural-Functional Mechanisms to Precision Interventions

Brain Sciences, Journal Year: 2025, Volume and Issue: 15(5), P. 446 - 446

Published: April 25, 2025

Purpose: Obesity’s metabolic consequences are well documented; however, its neurobiological underpinnings remain elusive. This systematic review addresses a critical gap by synthesizing evidence on obesity-induced neuroplasticity across structural, functional, and molecular domains through advanced neuroimaging. Methods: According to PRISMA guidelines, we systematically searched (2015–2024) PubMed/Web of Science, employing MeSH terms: (“Obesity” [Majr]) AND (“Neuroimaging” [Mesh] OR “Magnetic Resonance Imaging” [Mesh]). A total 104 studies met the inclusion criteria. The criteria required following: (1) multimodal imaging protocols (structural MRI/diffusion tensor imaging/resting-state functional magnetic resonance (fMRI)/positron emission tomography (PET)); (2) pre-/post-intervention longitudinal design. Risk bias was assessed via Newcastle-Ottawa Scale. Key Findings: 1. Structural alterations: 7.2% mean gray matter reduction in prefrontal cortex (Cohen’s d = 0.81). White integrity decline (FA β −0.33, p < 0.001) 12 major tracts. 2. Functional connectivity: Resting-state hyperactivity mesolimbic pathways (fALFF + 23%, p-FDR 0.05). Impaired fronto–striatal connectivity (r −0.58 with BMI, 95% CI [−0.67, −0.49]). 3. Interventional reversibility: Bariatric surgery restored activation (Δ +18% vs. controls, 0.002). Neurostimulation (transcranial direct current stimulation (tDCS) enhanced cognitive control (post-treatment 0.42, 0.009). Conclusion: Obesity induces multidomain neural reorganization beyond traditional reward circuits. Neuroimaging biomarkers (e.g., striatal PET-dopamine binding potential) predict intervention outcomes (AUC 0.79). Precision neuromodulation requires tripartite integration structural guidance, monitoring, profiling. Findings highlight neuroimaging’s pivotal role developing stage-specific therapeutic strategies.

Language: Английский

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Type 2 Diabetes Mellitus and Cardiometabolic Prospects: A Rapid Narrative Review

Cureus, Journal Year: 2024, Volume and Issue: unknown

Published: July 30, 2024

Cardiometabolic syndrome (CMS), type 2 diabetes mellitus (T2DM), and cardiovascular diseases are among the major altruists to international liability of disease. The lifestyle dietary changes attributable economic growth have resulted in an epidemiological transition towards non-communicable (NCDs) as leading causes death. Low- middle-income countries (LMICs) bear a more substantial disease burden due limited healthcare sector capacities address rapidly growing number chronic patients. purpose this narrative review paper was explore interrelationships between CMS, T2DM, impairments context NCDs, well preventative control interventions. role insulin resistance, hyperglycemia, dyslipidemia pathogenesis T2DM development severe highlighted. This elaborated on pivotal modifications, such healthy diets physical activity, cornerstones addressing epidemics metabolic diseases. Foods high calories, refined sugar, red meat, processed ready-to-eat meals were associated with amplified risk CMS T2DM. In contrast, based fruits, legumes, vegetables, whole grain, home-cooked foods demonstrated protective effects against Additionally, psychological behavioral approach highlighted, especially regarding its impact patient empowerment patient-centered therapeutic

Language: Английский

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