ArticleNeuroImage. Clinical2018
Automated versus manual segmentation of brain region volumes in former football players.
Article in NeuroImage. Clinical, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Volume-based bias in automated measurements of lateral ventricle and hippocampal volumes of mild traumatic brain injury patients.Neuroimage. Reports · 2026Article
- Regional ventricular enlargement as an in vivo biomarker of cumulative biomechanical neurodegeneration in former American football players.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Metaheuristic-driven dual-layer model for classifying Alzheimer's disease stages.Frontiers in computational neuroscience · 2026Article
- Multi - scale context U-net for breast cancer postoperative radiotherapy in patients with brachial plexus.BMC medical imaging · 2025Article
- ENIGMA's advanced guide for parcellation error identification (EAGLE-I): An implementation in the context of brain lesions.MethodsX · 2025Article
- Real-time aggression in youth and its connection to region-specific structural brain alterations.Discover mental health · 2025Article
- Improved deep canonical correlation fusion approach for detection of early mild cognitive impairment.Medical & biological engineering & computing · 2025Article
- Comparison of Inter-Method Agreement and Reliability for Automatic Brain Volumetry Using Three Different Clinically Available Software Packages.Medicina (Kaunas, Lithuania) · 2024Article
- Aging, cingulate cortex, and cognition: insights from structural MRI, emotional recognition, and theory of mind.Brain structure & function · 2024Article
- Methodological challenges of measuring brain volumes and cortical thickness in idiopathic normal pressure hydrocephalus with a surface-based approach.Frontiers in neuroscience · 2024Article
- Intimate partner violence perpetration among veterans: associations with neuropsychiatric symptoms and limbic microstructure.Frontiers in neurology · 2024Article
- Improving Cognitive Function Through High-Intensity Interval Training in Breast Cancer Patients Undergoing Chemotherapy: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2023Article
- Agreement and Reliability between Clinically Available Software Programs in Measuring Volumes and Normative Percentiles of Segmented Brain Regions.Korean journal of radiology · 2022Article
- Association of War Zone-Related Stress With Alterations in Limbic Gray Matter Microstructure.JAMA network open · 2022Article
- Clinical adaptation of synthetic MRI-based whole brain volume segmentation in children at 3 T: comparison with modified SPM segmentation methods.Neuroradiology · 2022Article
- Feasibility of FreeSurfer Processing for T1-Weighted Brain Images of 5-Year-Olds: Semiautomated Protocol of FinnBrain Neuroimaging Lab.Frontiers in neuroscience · 2022Article
- Anatomically curated segmentation of human subcortical structures in high resolution magnetic resonance imaging: An open science approach.Frontiers in neuroanatomy · 2022Article
- Differences in Structural Brain Characteristics Between Individuals with Chronic Nonspecific Neck Pain and Asymptomatic Controls: A Case-Control Study.Journal of pain research · 2022Article
- Quantifying and Examining Reserve in Symptomatic Former National Football League Players.Journal of Alzheimer's disease : JAD · 2022Article
- Intuitionistic Fuzzy C-Means Algorithm Based on Membership Information Transfer-Ring and Similarity Measurement.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
19 authors.
Funding
Abstract
Objectives: To determine whether or not automated FreeSurfer segmentation of brain regions considered important in repetitive head trauma can be analyzed accurately without manual correction. Materials and methods: 3 T MR neuroimaging was performed with automated FreeSurfer segmentation and manual correction of 11 brain regions in former National Football League (NFL) players with neurobehavioral symptoms and in control subjects. Automated segmentation and manually-corrected volumes were compared using an intraclass correlation coefficient (ICC). Linear mixed effects regression models were also used to estimate between-group mean volume comparisons and to correlate former NFL player brain volumes with neurobehavioral factors. Results: Eighty-six former NFL players (55.2 ± 8.0 years) and 22 control subjects (57.0 ± 6.6 years) were evaluated. ICC was highly correlated between automated and manually-corrected corpus callosum volumes (0.911), lateral ventricular volumes (right 0.980, left 0.967), and amygdala-hippocampal complex volumes (right 0.713, left 0.731), but less correlated when amygdalae (right -0.170, left -0.090) and hippocampi (right 0.539, left 0.637) volumes were separately delineated and also less correlated for cingulate gyri volumes (right 0.639, left 0.351). Statistically significant differences between former NFL player and controls were identified in 8 of 11 regions with manual correction but in only 4 of 11 regions without such correction. Within NFL players, manually corrected brain volumes were significantly associated with 3 neurobehavioral factors, but a different set of 3 brain regions and neurobehavioral factor correlations was observed for brain region volumes segmented without manual correction. Conclusions: Automated FreeSurfer segmentation of the corpus callosum, lateral ventricles, and amygdala-hippocampus complex may be appropriate for analysis without manual correction. However, FreeSurfer segmentation of the amygdala, hippocampus, and cingulate gyrus need further manual correction prior to performing group comparisons and correlations with neurobehavioral measures.
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