TL;DR
Findings suggest a systematic overestimation of predicted brain age in children, highlighting the need for caution in clinical interpretations to prevent misinterpretations in pediatric populations.
Clinical brain MRIs from pediatric health systems represent a viable resource for modeling early neurodevelopmental trajectories and studying neurodevelopmental risk in real-world populations, and a robust segmentation approach tailored to early-life clinical MRIs with variable orientation, resolution, and contrast is...
The widespread use of FreeSurfer 7 raises concern about developmental neuroimaging studies that utilize eTIV without quality control, andRecommendations for future research and considerations for past research in the field are discussed.
Brain age, an individual’s age predicted from neuroimaging data, is a promising biomarker of brain health. Yet brain age estimates may depend on methodological choices within the prediction pipeline. We used a multiverse approach to systematically investigate effects of data modality, bias-adjustment method, and brain...
Abstract Tremendous maturation in brain structure and function, underlying very rapid cognitive development, occurs in the early years of life, yet it has been difficult to obtain reliable measures of brain function over this period. A major challenge has been the difficulty of acquiring reliable neuroimaging data from...
It is suggested that these frozen neuroimaging foundation models are insufficient for fine-grained diagnostic classification in small, non-western clinical cohorts, motivating parameter-efficient adaptation and broader multi-site external validation for equitable deployment in global health settings.
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