Loading
Life sciences · Journal article
Frontiers in Neurology · November 2, 2026
No summary has been generated for this record yet. What follows is drawn from its source metadata only.
Journal article.
No findings were extractable from the material analysed.
Safety was not reported in the material analysed. Check the source before drawing any conclusion about harm.
The source did not state who this applies to in practice.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
This record has not been graded across any dimension yet. Treat the label above as provisional and read the source.
What is missing. This record has no bottom line, key findings, reported figures, evidence dimensions. That is a gap in the analysis, not a judgement about the study.
Background The corpus callosum (CC) is the largest white matter structure and is often affected in neurological and neuroimmunological disorders. However, previous studies mainly used group-level comparisons. This limits patient-level magnetic resonance imaging (MRI) assessment. Methods In this multicenter retrospective study, 3D T 1 -weighted MRI data from 24,305 healthy controls aged 4–85 years were used to construct age-,sex-, and estimated total intracranial volume (eTIV)- adjusted normative references for the whole CC and five subregions. Deviation scores were calculated and applied to 4,081 patients with multiple sclerosis (MS, n = 573), neuromyelitis optica spectrum disorder (NMOSD, n = 389), mild cognitive impairment (MCI, n = 308), Alzheimer’s disease (AD, n = 623), Parkinson’s disease (PD, n = 1,285), and cerebral small vessel disease (CSVD, n = 903). Classification, clinical correlation, and prognostic analyses were performed as exploratory applications. Results The volume of CC subregions peaked from early adulthood (central, 26.0 years) to midlife (posterior, 47.2 years; anterior, 47.5 years), forming a “centre-to-periphery” pattern. MS showed negative deviations mainly in central and mid-anterior regions (Cohen’s d = −0.28 to −0.30, p FDR<0.001), while CSVD and AD showed widespread negative deviations ( d = −0.13 to −0.49). NMOSD, MCI, and PD showed relatively small or regionally limited deviations. Deviation score based classification performance ranged from AUC = 0.598–0.775. Exploratory analyses identified weak correlations between deviation scores and processing speed in MS (Spearman’s ρ up to 0.22, p < 0.05) and cognition in CSVD ( ρ = 0.12–0.19, p < 0.05) and AD ( ρ = 0.10–0.16, p < 0.05). None survived FDR correction. Baseline deviation-based risk groups stratified subsequent relapse and disability outcomes in MS and NMOSD ( p < 0.001). An exploratory comparison suggested a nominal difference in baseline CC deviation burden between MCI converters and non-converters to AD. Conclusion Lifespan normative references of the CC provide a quantitative framework for characterizing individual structural deviations across neurological and neuroimmunological disorders. Exploratory clinical analyses suggest potential applications that require further validation.