Cerebral small vessel disease (CSVD) is a group of age-related cerebrovascular diseases that affect the small arteries, micro-arteries, waning valves, micro-vessels, and small veins in the brain. The diagnosis of CSVD can be clinically difficult because the manifestations are highly inconsistent, which may include stroke events, cognitive decline, gait and balance abnormalities, emotional changes, urinary incontinence and decreased vitality. So far our understanding of CSVD is still limited but the advanced neuroimaging methods, such as fMRI, CT, PET-CT/MRI have shown great potential to deepen our understanding of the pathophysiologic mechanisms of CSVD. For example, in spite of distinctive pathogenesis, neuroimaging technology reveals similarity in CSVD related imaging features, such as recent small subcortical infarct, lacune of presumed vascular origin, white matter hyperintensity of presumed vascular origin, perivascular space, cerebral microbleeds, and brain atrophy. Therefore the development of novel imaging markers in CSVD diagnosis as well as in evaluation and management strategies is a direction worth further exploration.
The aims of this Research Topic is to gain an improved understanding of CSVD in terms of the physiologies and pathologies, neurological mechanism, potential markers, and assessing or diagnostic techniques, using neuroimaging methods (e.g. CT, MRI, PET-CT/MRI), from basic to clinical research, from population/patient-based studies to animal models.
The sub-topics within the scope include, but are not limited to the following:
1) Imaging and quantifying the structural and functional alterations in the brain;
2) Developing imaging markers in improving early diagnoses and differential diagnoses,
3) Understanding of pathophysiologic mechanisms of CSVD and how its association with Stroke, Cognitive impairment, gait and balance disorders, and etc.
4) Neuroimaging assessment and prediction of the progression and severity of CSVD
5) Evaluation of pharmacological/non-pharmacological interventions, and treatment efficacy via neuroimaging approaches
6) improvement and refinement of neuroimaging techniques and data analysis, e.g. multimodal approaches, machine-learning based approaches
Original articles, Review articles, case reports, protocols, clinical trials, systematic reviews and meta-analyses are welcome.
Cerebral small vessel disease (CSVD) is a group of age-related cerebrovascular diseases that affect the small arteries, micro-arteries, waning valves, micro-vessels, and small veins in the brain. The diagnosis of CSVD can be clinically difficult because the manifestations are highly inconsistent, which may include stroke events, cognitive decline, gait and balance abnormalities, emotional changes, urinary incontinence and decreased vitality. So far our understanding of CSVD is still limited but the advanced neuroimaging methods, such as fMRI, CT, PET-CT/MRI have shown great potential to deepen our understanding of the pathophysiologic mechanisms of CSVD. For example, in spite of distinctive pathogenesis, neuroimaging technology reveals similarity in CSVD related imaging features, such as recent small subcortical infarct, lacune of presumed vascular origin, white matter hyperintensity of presumed vascular origin, perivascular space, cerebral microbleeds, and brain atrophy. Therefore the development of novel imaging markers in CSVD diagnosis as well as in evaluation and management strategies is a direction worth further exploration.
The aims of this Research Topic is to gain an improved understanding of CSVD in terms of the physiologies and pathologies, neurological mechanism, potential markers, and assessing or diagnostic techniques, using neuroimaging methods (e.g. CT, MRI, PET-CT/MRI), from basic to clinical research, from population/patient-based studies to animal models.
The sub-topics within the scope include, but are not limited to the following:
1) Imaging and quantifying the structural and functional alterations in the brain;
2) Developing imaging markers in improving early diagnoses and differential diagnoses,
3) Understanding of pathophysiologic mechanisms of CSVD and how its association with Stroke, Cognitive impairment, gait and balance disorders, and etc.
4) Neuroimaging assessment and prediction of the progression and severity of CSVD
5) Evaluation of pharmacological/non-pharmacological interventions, and treatment efficacy via neuroimaging approaches
6) improvement and refinement of neuroimaging techniques and data analysis, e.g. multimodal approaches, machine-learning based approaches
Original articles, Review articles, case reports, protocols, clinical trials, systematic reviews and meta-analyses are welcome.
