Magnetic resonance imaging is used to assess white matter (WM) abnormalities including total WM volumes and WM hyperintensities (WMHs). Comparisons between several qualitative and quantitative methods to assess WM that are used in research and clinical settings are lacking in pediatric traumatic brain injury (TBI). This study 1) WM methods including Scheltens ratings, manual tracings, NeuroQuant®, and FreeSurfer; (2) compared total WM volumes and WMHs to assess potentially similar reporting of WM integrity; and (3) assessed the relationship between cognitive functions (intelligence, attention, processing speed, and language) and WM in pediatric TBI.Sixty participants (65% male) between ages 8-13 years old, had a complicated-mild (53%), moderate (15%), or severe TBI (32%) with a mean age of 2.6 at the time of injury. NeuroQuant® WMH volumes had poor agreement (ICC = .24), and did not correlate (r = .12, p = .21) with manually traced WMH volumes. Scheltens WMH ratings had good to excellent agreement and correlated with NeuroQuant® (ICC = .62; r = .29, p = .005) and manually traced WMH volumes (ICC = .82; r = .50, p = .000). NeuroQuant® and FreeSurfer total WM volumes had fair agreement and were correlated (ICC = .52; r = .38, p = .004). No significant difference in total WM volumes were found between complicated-mild and moderate-severe TBI groups, and in subgroups with and without WMHs. Processing speed was significantly associated with Scheltens WMH ratings: p = .004, manually traced WMHs: p = .002, and NeuroQuant® WMHs: p = .007. No other association between cognitive functions and WM volumes or hyperintensities were found. Correlations between NeuroQuant® and manual tracings with processing speed differed by sex, where males had significant correlations but females did not. Deciding when to use manual tracing and NeuroQuant® WMH volumes and Scheltens ratings in clinical or research settings will depend on available resources (e.g., time, technology, funding, and expertise) and purpose of assessing WMHs. Total WM volumes did not appear to capture WM pathology as assessed by WMHs, likely due to the sample being underpowered and that total WM volumes possibly included WMHs. Limitations include restricted range of injury severity, heterogeneity of lesions, and small sample size. Additional research is needed in a larger sample of pediatric TBI.

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Despite the common co-occurrence of the two main pathological processes in aging, vascular disease and Alzheimer's disease (AD), they are often examined in isolation. Increasing evidence of a mutually enhancing relation between these processes is supported by common risk factors including hypertension and diabetes. Therefore, both processes must be considered in characterizing the cognitive performance of older adults, particularly given high rates of vascular disease. The heterogeneity of cognitive deficits has not been systematically examined in older adults with vascular disease. In a large sample of older adults (N = 359, Mage= 74.7) with increased vascular risk associated with cardiac disease, classes of participants were identified using latent class analysis (LCA) based on their performance across neuropsychological measures of executive functions and episodic memory. The cognitively-defined classes were compared on neuroimaging variables including white matter lesion (WML) and hippocampal volumes in 203 participants and on vascular risk quantified by Framingham score in 187 participants. LCA on the cognitive variables supported a three-class model, with Class 3 (intact; n = 178) showing relatively intact cognitive test scores compared to the other classes and Classes 1 (mildly impaired; n = 136) and 2 (dysexecutive; n = 42) demonstrating uniformly low scores, with Class 2 showing the lowest and most impaired scores on two executive measures (Trails B and Mental Control). Follow-up analyses found that differences between classes on WML and hippocampal volumes did not reach statistical significance, although a trend was observed in WML volumes (p = .12) with greater levels of this pathology in Class 2 (dysexecutive). Significant differences between the classes on vascular risk were revealed, with Class 2 showing significantly higher Framingham scores (p =.02). These findings suggest meaningful heterogeneity in the cognitive presentation of older adults with increased vascular risk, with deficits in executive functions associated with potentially modifiable vascular risk factors/cerebrovascular disease. / Psychology

Background: Given the growing aging population, it is crucial to better understand the neurobiological underpinnings of healthy aging and how changes in structure relate to changes in function. The current study derived diffusion tensor imaging (DTI) metrics of white matter microstructure in younger and older adults to simulate the healthy aging process. Methods: The DTI metrics of fractional anisotropy (FA) and mean diffusivity (MD) as well as the cognitive domains of memory and executive function were examined in 34 healthy participants divided into older adults (17; Mean = 70.9, SD = 5.4) and younger adults (17; Mean = 28.1, SD = 2.8). Cognitive performance on the California Verbal Learning Test 2nd Edition (CVLT-II) and the trails making test (Trails-A & Trails-B) were used to evaluate memory and executive function, respectively. The differences in white matter microstructure between older and younger adults were analyzed using tract based spatial statistics (TBSS; p < 0.05, corrected for multiple comparisons) in FSL. Associations between the DTI metrics and cognition were then evaluated for each group. Results: Older adults had lower FA and higher MD in diffuse brain regions, including major tracts such as the corticospinal tract, corpus callosum and superior and inferior longitudinal fasciculi. There was a significant negative correlation between executive function and MD in the right superior and anterior corona radiata and the body of the corpus callosum of older adults. No significant relationship was detected between memory performance and DTI metrics in older adults. Furthermore, no significant relationships were detected between memory or executive function performance and FA or MD in younger adults. Conclusions: The differences in DTI metrics between groups as well as the association between MD and executive function support further examinations into the healthy aging process. Future studies should use longitudinal designs with large sample sizes to better understand changes and trajectories during healthy aging. / Graduate / 2023-08-19

yes / BACKGROUND AND PURPOSE Aging of the healthy brain is characterized by focal or nonfocal white matter (WM) signal abnormality (SA) changes, which are typically detected as leukoaraiosis (LA). Hypertension is a risk factor for WM lesion formation. This study investigated whether LA might be associated with increased cerebrospinal fluid (CSF) pulsatility linked to arterial hypertension. METHODS A total of 101 individuals without neurologic diseases (53 females and 48 males) aged between 18 and 75 years underwent 3T brain MRI with cine phase contrast imaging for CSF flow estimation, after providing their informed consent. LA was defined as the presence of focal T2 WM SA changes and/or nonfocal uniform areas of signal increase termed dirty appearing white matter (DAWM). Relevant information relating to cardiovascular risk factors was also collected. RESULTS When controlled for age and hypertension, significant partial correlations were observed between: DAWM volume and: net negative flow (r = –.294, P = .014); net positive flow (NPF) (r = .406, P = .001); and peak positive velocity (r = .342, P = .004). Multiple linear regression analysis revealed DAWM volume to be significantly correlated with CSF NPF (P = .019) and hypertension (P = .007), whereas T2 WM SA volume was only significantly correlated with age (P = .002). Combined DAWM and T2 WM SA volumes were significantly related with age (P = .001) and CSF peak negative velocity (P = .041). CONCLUSIONS Rarefaction of WM leading to LA is a multifactorial process, in which formation of DAWM induced by hypertension and increased aqueductal CSF pulsatility, may play a contributory role. These two factors appear to act independently of each other in a process that is independent of age.

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INTRODUCTION: The association of Sleep-Related Movement Disorders (SRMDs) such as Restless Legs Syndrome (RLS) and Periodic Limb Movements (PLMs) with cerebrovascular disease is underexplored. Emerging evidence links them to vascular disease, for which white matter hyperintensities (WMHs) are a well-recognized biomarker. METHODS: We conducted a cross-sectional hospital-based observational study in which high-risk TIA and minor stroke patients were assessed for vascular risk factors, WMHs and polysomnography-determined sleep variables. RESULTS: Ninety-seven patients were enrolled, of whom 44 completed polysomnography. Twenty-five percent had RLS, which was associated with lower quality of life. Independent of the effect of classical vascular risk factors, PLMs (but not RLS) were associated with WMHs on linear regression analyses (p=0.016). CONCLUSIONS: SRMDs are prevalent after minor stroke/TIA. RLS is associated with poor quality of life, while PLMs are associated with WMHs. Whether PLMs are implicated in the pathogenesis of WMHs or whether WMHs exacerbate PLMs remains uncertain.

Le recalage des images du cerveau vise à réduire la variabilité anatomique entre les differentes sujets, et à créer un espace commun pour l'analyse de groupe. Les approches multi-modales essaient de minimiser les variations de forme du cortex et des structures internes telles que des faisceaux de fibres nerveuses. Ces approches nécessitent une identification préalable de ces structures, ce qui s'avère une tâche difficile en l'absence d'un atlas complet de référence. Nous proposons une extension de l'algorithme de recalage difféomorphe des Démons pour recaler conjointement des images et des faisceaux de fibres. Dans cette thèse, nous analysons différentes représentations des faisceaux de fibres comme une séquence de points, un nuage de points, les courants et les mesures. Différentes distances sont analysées et étudiées dans l'algorithme de recalage. Pour simplifier la représentation de la matière blanche nous utilisons et étendons les algorithmes de classification existants. En étendant le recalage d'images afin d'ajouter des descripteurs de la géométrie des fibres nerveuses, nous espérons améliorer les futures analyses concernant les matières grise et blanche. Nous avons démontré l'efficacité de notre algorithme en recalant conjointement des images anatomiques pondérées en T1 et des faisceaux de fibres. Nous avons comparé nos résultats à des approches concurrentes, l'une multimodale s'appuyant sur l'anisotropie fractionnaire et la pondération T1, l'autre sur les tenseurs de diffusion, et obtenu de meilleures performances à l'aide de notre algorithme. Enfin, nous mettons en évidence sur des études de groupe en IRMf que notre méthodologie et notre implémentation apportent un gain en sensibilité de détection des activations cérébrales. / Brain image registration aims at reducing anatomical variability across subjects to create a common space for group analysis. Multi-modal approaches intend to minimize cortex shape variations along with internal structures, such as fiber bundles. These approaches require prior identification of the structures, which remains a challenging task in the absence of a complete reference atlas. We propose an extension of the Diffeomorphic Demons image registration to jointly register images and fiber bundles. In this thesis we analyze differents representations of the fiber bundles such as ordered points, clouds of points, Currents and Measures. Different distances are analyzed and implemented into the registration algorithm. To simplify white matter representation we also analyze, use and extend existing clustering algorithms. By extending the image registration to include geometric fiber bundles descriptors we hope to improve future analyses regarding both, grey and white matter. We demonstrate the efficacy of our algorithm by registering simultaneously T1 images and fiber bundles and compare results with a multi-modal T1+Fractional Anisotropy (FA) and a tensor-based registration algorithms and obtain superior performance with our approach. We provide preliminary evidence that our implementation improves the sensitivity of activation detection in fMRI group studies.