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Thrippleton, M. J.

Publications and source records attributed to Thrippleton, M. J..

2 recordsLinked to original sources

Intracranial functional haemodynamic relationships in patients with cerebral small vessel disease

BackgroundCerebral small vessel disease (SVD) is a major cause of stroke and dementia. The underlying cerebrovascular dysfunction is poorly understood. We investigated cerebrovascular reactivity, blood flow, vascular and cerebrospinal fluid (CSF) pulsatility, and their independent relationship to SVD features, in patients with minor ischaemic stroke and MRI evidence of SVD.\n\nMethodsWe recruited patients with minor ischaemic stroke and assessed CVR using Blood Oxygen Level Dependent (BOLD) MRI during a hypercapnic challenge, cerebral blood flow, vascular and CSF pulsatility using phase contrast MRI, and structural MR brain imaging to quantify white matter hyperintensities (WMH) and perivascular spaces (PVS). We quantified CVR in seven white matter and six subcortical grey matter regions, measured blood flow in carotid and vertebral arteries, intracranial venous sinuses, internal jugular veins and CSF flow at the aqueduct and foramen magnum. We used multiple regression to identify SVD features, blood flow and pulsatility parameters associated with CVR, controlling for patient characteristics.\n\nResultsIn 53 of 60 patients with complete data (age 68.0{+/-}8.8, 74% male, 75% hypertensive), CVR in grey and white matter decreased with increasing blood pressure (BP, respectively -0.001%/mmHg, p=0.01 and -0.006%/mmHg, p=0.01, per mmHg increase in BP). After controlling for age, gender and systolic BP, white matter CVR decreased with increasing WMF volume (-0.01%/mmHg per log10 increase in WMH volume, p=0.02) and basal ganglia PVS (-0.01%/mmHg per point increase in PVS score, p=0.02). White matter CVR decreased with increasing venous pulsatility (superior sagittal sinus -0.03%/mmHg, p=0.02, per unit increase in pulsatility index) but not with cerebral blood flow (p=0.58). Lower foramen magnum CSF stroke volume was associated with worse white matter CVR (0.04%/mmHg per ml increase in stroke volume, p=0.04) and increased basal ganglia PVS.\n\nConclusionsContemporaneous assessment of CVR, intracranial vascular and CSF pulsatility demonstrates important interrelationships of these vascular functions in humans. Decreased CVR, increased venous pulsatility and reduced foramen magnum CSF stroke volume suggests that dynamic vascular dysfunctions underpin PVS dysfunction and WMH development. Improved understanding of microvascular dysfunction and CSF dynamics offers new intervention targets to reduce SVD lesion development and their impact on cognitive dysfunction and stroke.

neuroscience

Neonatal morphometric similarity mapping for predicting brain age and characterizing neuroanatomic variation associated with preterm birth

Multi-contrast MRI captures information about brain macro- and micro-structure which can be combined in an integrated model to obtain a detailed "fingerprint" of the anatomical properties of an individuals brain. Inter-regional similarities between features derived from structural and diffusion MRI, including regional volumes, diffusion tensor metrics, neurite orientation dispersion and density imaging measures, can be modelled as morphometric similarity networks (MSNs). Here, individual MSNs were derived from 105 neonates (59 preterm and 46 term) who were scanned between 38 and 45 weeks postmenstrual age (PMA). Inter-regional similarities were used as predictors in a regression model of age at the time of scanning and in a classification model to discriminate between preterm and term infant brains. When tested on unseen data, the regression model predicted PMA at scan with a mean absolute error of 0.70 {+/-} 0.56 weeks, and the classification model achieved 92% accuracy. We conclude that MSNs predict chronological brain age accurately; and they provide a data-driven approach to identify networks that characterise typical maturation and those that contribute most to neuroanatomic variation associated with preterm birth. HighlightsO_LIMultiple MRI features are integrated in a single model to study brain maturation in newborns. C_LIO_LIMorphometric similarity networks (MSNs) provide a whole-brain description of the structural properties of neonatal brain. C_LIO_LIThe information encoded in MSNs is predictive of chronological brain age in the perinatal period. C_LIO_LIMSNs provide a novel data-driven method for investigating neuroanatomic variation associated with preterm birth. C_LI

neuroscience