Bas Jasperse

Progressive structural brain changes are a hallmark of neurodegenerative conditions like Alzheimer’s disease (AD), frontotemporal dementia (FTD), multiple sclerosis (MS), and Parkinson’s disease (PD). The brain-predicted age difference (brain-PAD) has emerged as a promising biomarker to quantify these alterations, yet its unique clinical contribution relative to conventional measures of global brain atrophy such as the brain parenchymal fraction (BPF) remains underexplored. In this transdiagnostic study across AD, FTD, MS, and PD, we systematically evaluated brain-PAD’s capacity to distinguish patients from controls, its cross-sectional and longitudinal associations with cognition, and its voxel-wise structural correlates. We benchmarked brain-PAD against BPF to determine its added explanatory value. Brain-PAD successfully distinguished patients from controls, adding to BPF alone, in AD, FTD, and MS, but not PD. Across disorders, higher brain-PAD correlated with worse cognition, showing clear added value beyond BPF particularly in AD and MS. Baseline brain-PAD also independently predicted subsequent cognitive changes in AD, FTD, and MS, over and above BPF. Voxel-wise analyses revealed spatial features underlying brain-PAD including, beyond global tissue loss, specific regional atrophy matching each disease’s characteristic pattern. Collectively, these findings demonstrate that brain-PAD is a clinically meaningful, transdiagnostic biomarker of neurodegeneration that complements conventional volumetric measures like the BPF.

The brain-predicted age difference (brain-PAD) is considered a marker of neurodegeneration in people with multiple sclerosis (pwMS) and is associated with greater disability and cognitive impairment. However, the impact of disease-modifying factors (DMFs) on brain-PAD remains unknown, as does the extent to which their effect on disability and cognition is mediated through brain-PAD. The goal of this study was to investigate this in pwMS using a same-age cohort to eliminate calendar age as a confounding factor. Brain age was determined using brainageR from 3-dimensional T1-weighted MRI scans, and brain-PAD was calculated as the difference between predicted and chronological age. Disability was evaluated with the Expanded Disability Status Scale (EDSS), the 9-hole peg test (9HPT), and timed 25-foot walk test (T25FWT). Cognitive function was assessed using the Minimal Assessment of Cognitive Function in MS battery and converted to Z-scores. DMFs included lifetime smoking, alcohol consumption, physical activity, diet, leisure, and educational level, as well as body mass index (BMI) at 18 years. The effect of DMFs on brain-PAD was examined using linear regression, adjusting for sex. Mediation analyses were performed to investigate to what extent brain-PAD is a mediator of DMF effects on disability and cognition. The study included 117 healthy controls (mean age 52.8 ± 1.1 years, 74.3% female) and 242 pwMS (mean age 52.8 ± 0.9 years, 70.6% female), with a median disease duration of 15.2 years (interquartile range [IQR] 8.2-24.5) and a median EDSS score of 3.5 (IQR 2.5-4.0). Smoking (β = 0.20, p = 0.002), alcohol consumption (β = 0.18, p = 0.007), and BMI at 18 years (β = 0.15, p = 0.021) were associated with a higher brain-PAD, whereas higher physical activity (β = -0.13, p = 0.041) was linked to a lower brain-PAD. Mediation analysis demonstrated an indirect effect of smoking and alcohol on EDSS score (β = 0.039, p = 0.003; β = 0.039, p = 0.009), 9HPT (β = 0.057, p < 0.0001; β = 0.055, p = 0.004), T25FWT score (β = 0.045, p = 0.009; β = 0.044, p = 0.013), and cognitive performance (β = -0.066, p = 0.0004; β = -0.060, p = 0.016). Physical activity demonstrated an indirect effect of better performance on EDSS score (β = -0.027, p = 0.032) and cognitive performance (β = 0.042, p = 0.034). DMFs unrelated to MS, particularly smoking, alcohol use, and BMI at 18 years, accelerate brain aging. Brain-PAD mediates these effects and contributes to worsening disability and cognition, underscoring the potential of lifestyle interventions to mitigate neurodegeneration and preserve function in pwMS.

The brain-predicted age difference (brain-PAD) is a novel marker of neurodegeneration in multiple sclerosis (MS). Brain-PAD has been associated with clinical disability in heterogeneous MS patient cohorts of varying ages and disease durations. In this study, we investigate the relation between clinical disability and brain-PAD in a unique birth-year cohort of people with MS (pwMS) and healthy controls (HCs) of the same age all born in 1966, eliminating age as a confounding factor. This was a cross-sectional cohort study conducted in the Netherlands. Disability was quantified using the expanded disability status scale (EDSS), 9-hole peg test (9HPT), and the timed 25-foot walk test (T25FWT). Cognition was assessed using the Minimal Assessment of Cognitive Function in MS battery. The brain-PAD was calculated by subtracting the person's chronological age from the predicted brain age derived from 3-dimensional T1-weighted brain MRI scans using machine learning (brainageR software). Brain-PAD for HCs and MS subtypes (relapsing remitting, secondary progressive, and primary progressive) were compared using a generalized linear model. The relation between brain-PAD and disease duration and disability and cognitive measures were tested using univariate linear regression. In addition, the clinical explanatory value added by brain-PAD to those of brain parenchymal fraction (BPF) and T2 lesion volume was investigated. The study included 116 HC (mean age 52.9 ± 1.1 years, 61% female) and 237 pwMS (mean age 52.9 ± 0.9 years, median disease duration 16.3 years [interquartile range 8.2-24.4] and a median EDSS of 3.5 [interquartile range 2.5-4.0]). Brain-PAD was higher in pwMS compared with HC by 9.7 years (SE = 0.82, p < 0.0001). Longer disease duration was associated with a higher brain-PAD (β = 0.21, p < 0.001). A higher brain-PAD was associated with worse performance on the T25FWT (β = 0.0063, p < 0.05), 9HPT (β = 0.0074, p < 0.001), and EDSS (β = 0.028, p < 0.05). Brain-PAD was higher for cognitively impaired people with MS, compared with cognitively preserved pwMS and HC (p < 0.0001). Brain-PAD had added explanatory value over BPF in clinical outcome measures. In a cohort unbiased by age differences, greater brain ageing was associated with worse performance on disability and cognitive tests, underscoring the potential of brain-PAD as a marker for neurodegeneration and disease severity in MS.

Brain atrophy is relevant for understanding disease progression and treatment response in people with multiple sclerosis (pwMS). Automatic brain volume-reporting tools often rely on healthy control (HC) reference curves to interpret brain volumes, whereas brain volume loss is different in pwMS. This observational study aimed to develop an MS-specific reference model for brain volumes and evaluate its performance compared with HC-based curves, as a proof-of-concept. Participants, pwMS and HCs, from the Amsterdam MS cohort were included based on the availability of T1-weighted MR scans. Normalized brain volumes (NBVs) were obtained using commercially available software. The software program also provides NBV percentiles, based on age-specific and sex-specific HC curves, grouped into NBV quartiles, describing deviation from expected NBVs. Disease severity was determined with the MS severity score (MSSS), Symbol Digit Modalities Test (SDMT), and 9-Hole Peg Test (9HPT). An MS-specific model was developed by regressing NBVs against age, sex, disease duration, and MS phenotype. The resulting MS model was also used to classify pwMS into quartiles describing deviation from expected NBV, given the modeled patient characteristics, with leave-one-out predictions. Quartile classification from HC-based and MS-based reference curves was compared with MSSS using analysis of variance (ANOVA). Regressions for NBVs from 713 pwMS and 259 HCs (mean age: 49.1 ± 9.7 and 48.3 ± 10.1, %female: 70.4% and 67.2%, respectively) were significant for age, sex, disease duration, and phenotype, which were included in the MS-specific model. MS-specific model quartile designations significantly improved associations with MSSS values (p = 2.2*10^-9, η² = 0.06) compared with HC-based quartiles. MSSS values worsened with lower NBV quartiles in the MS-specific model (difference between quartiles 1-4 = -0.84, p = 6.1*10^-3, 95% CI [-1.5 to -0.18])), which was not observed for HC-based quartiles (p = 0.98). Quartile group differences were observed for 9HPT (MS: p = 3.5*10^-3, η² = 0.02, HC: p = 6.6*10^-3, η² = 0.02) and SDMT (MS: p = 3.1*10^-4, η² = 0.05, HC: p = 5.4*10^-4, η² = 0.04) values, but MS-specific quartiles again improved quartile associations (p = 0.036, η² = 0.01 and p = 0.02, η² = 0.01, respectively). NBV values derived from an MS-specific reference model offer improved relevance for assessing disease severity compared with curves derived from age-specific and sex-specific HC reference models. Improving the model toward application in individual people could enhance clinical implementation.

Purpose: Scanning during infancy is often required in otology, preferably without general anaesthesia. This study aims to determine the success rate of MRI of the head without general anaesthesia for infants, and to identify predictors for a successful scan. Methods: Data was extracted from the electronic patient file for patients who received MRI of the head without general anaesthesia between 01-01-2019 and 31-12-2022 at an age younger than 6 months. Each MRI-session was dichotomised into success (i.e., of sufficient quality to answer the clinical question) or failure, and success percentages were calculated. A logistic regression analysis was performed to determine the association between success and variables of interest, which were selected based on interviews with medical specialists. Results: Eighty-seven patients were included, showing an overall success rate of 75.9% for MRI of the head without anaesthesia. Success rates for MRI brain were higher than for MRI cerebellopontine angle (CPA), respectively 91.2% and 66.0% (p = 0.013). For MRI CPA the odds of success decreased for infants aged 3–5 months, compared to infants under 3 months (respectively 48.1% and 84.6%, p = 0.009). For MRI CPA the success percentage was lower for boys (51.9%) than for girls (80.8%, p = 0.039). Time of day and hearing loss showed no significant effect on the success rate. Conclusion: Obtaining MRI of the head without anaesthesia for infants under six months is feasible. For MRI CPA the success rate is higher for infants scanned at a younger age, as well as for female infants compared to male infants.

Magnetic resonance imaging (MRI) is the most sensitive technique for detecting inflammatory demyelinating lesions in multiple sclerosis (MS) and plays a cr

Background: Human papillomavirus (HPV)‐positive oropharyngeal squamous cell carcinoma (OPSCC) have better prognosis and treatment response compared to HPV‐negative OPSCC. This study aims to noninvasively predict HPV status of OPSCC using clinical and/or radiological variables.Methods: Seventy‐seven magnetic resonance radiomic features were extracted from T1‐weighted postcontrast images of the primary tumor of 153 patients. Logistic regression models were created to predict HPV status, determined with immunohistochemistry, based on clinical variables, radiomic features, and its combination. Model performance was evaluated using area under the curve (AUC).Results: Model performance showed AUCs of 0.794, 0.764, and 0.871 for the clinical, radiomic, and combined models, respectively. Smoking, higher T‐classification (T3 and T4), larger, less round, and heterogeneous tumors were associated with HPV‐negative tumors.Conclusion: Models based on clinical variables and/or radiomic tumor features can predict HPV status in OPSCC patients with good performance and can be considered when HPV testing is not available.