Cerebrovascular disease (CVD) remains a leading cause of death and adult disability in most countries. Take acute stroke as an example; despite treatment progress, 20-30% of strokes result in death within one month, and 70-80% result in significant long-term disability. Traditional assessment relies on clinic experiments and lacks a quantitative analysis method. Enormous heterogeneity within the patient population of CVD challenges the accuracy of conventional assessment, which impedes prognosis improvement. For example, low dose IV tPA in acute ischemia stroke mainly achieved positive results in Asian counties, but it is controversary in other continents. Due to the heterogeneity, CVD presentations are various in different territories. Diagnostic criteria and therapeutic strategy of CVD should be adjusted individually. With the development of neuroimage and artificial intelligence technologies, personalized and precise evaluation based on quantitative metabolic and blood flow analysis becomes a reality. It will re-build the diagnostic and therapeutic model of CVD and bring light to the patient suffering from the disease.
Risk factors of CVD induce abnormal vascular structure and blood components, subsequently cause hemodynamic disturbances, interrupt regular blood supply and metabolism, and eventually lead to brain injury. The critical pathophysiological process of CVD is hemodynamic disturbances, which bridges risk factor and brain injury. The metabolic and perfused condition results from hemodynamics; therefore, the precision of metabolic and blood flow assessment determines the accuracy of diagnosis and effectiveness of therapy for CVD. In recent years, advanced neuroimaging techniques such as Arterial spin labeling (ASL) developed. ASL cerebral blood flow (CBF)-weight MRI did not require an injection of a contrast agent. It magnetically labels blood water by radiofrequency pulse, which provides a more direct measure of CBF than the traditional method. Therefore, ASL measurement will change the CBF threshold abnormal. Recent developments in non-contrast-enhanced MRA based on ASL-like sequences have emerged as an attractive alternative to MRA. It enables the possibility of restricting the labeling to a single artery, allowing the selective depiction of the responsible vessels for CVD. Another ASL advancement, vessel selective ASL, can visualize collateralization, which helps to correct diagnosis. Except for ALS, fluorodeoxyglucose 18F PET imaging shows the reduction of glucose metabolism in patients with brain infarct. Intracranial vessel wall imaging help to differentiate the cause of vessel structural abnormality. Globule magnetic resonance spectroscopy (MRS) can quantify the whole brain's metabolism, which provides more precise information predicting the prognosis.
The Research Topic aims to advance neuroimage techniques for metabolic and blood flow assessment in cerebral diseases. Original research articles or reviews are welcome. Areas covered in this Research Topic may include, but are not limited to:
- Inventing a new neuroimage sequence for metabolic and blood flow assessment in CVD
- Setting new neuroimage scan parameters for metabolic and blood flow assessment in CVD
- Innovative applications of traditional neuroimage techniques for metabolic and blood flow assessment in CVD
- Advanced neuroimage data post-processing technology for metabolic and blood flow assessment in CVD
- Comparing CVD presentations, diagnostic criteria, and therapeutic strategies in different territories
Cerebrovascular disease (CVD) remains a leading cause of death and adult disability in most countries. Take acute stroke as an example; despite treatment progress, 20-30% of strokes result in death within one month, and 70-80% result in significant long-term disability. Traditional assessment relies on clinic experiments and lacks a quantitative analysis method. Enormous heterogeneity within the patient population of CVD challenges the accuracy of conventional assessment, which impedes prognosis improvement. For example, low dose IV tPA in acute ischemia stroke mainly achieved positive results in Asian counties, but it is controversary in other continents. Due to the heterogeneity, CVD presentations are various in different territories. Diagnostic criteria and therapeutic strategy of CVD should be adjusted individually. With the development of neuroimage and artificial intelligence technologies, personalized and precise evaluation based on quantitative metabolic and blood flow analysis becomes a reality. It will re-build the diagnostic and therapeutic model of CVD and bring light to the patient suffering from the disease.
Risk factors of CVD induce abnormal vascular structure and blood components, subsequently cause hemodynamic disturbances, interrupt regular blood supply and metabolism, and eventually lead to brain injury. The critical pathophysiological process of CVD is hemodynamic disturbances, which bridges risk factor and brain injury. The metabolic and perfused condition results from hemodynamics; therefore, the precision of metabolic and blood flow assessment determines the accuracy of diagnosis and effectiveness of therapy for CVD. In recent years, advanced neuroimaging techniques such as Arterial spin labeling (ASL) developed. ASL cerebral blood flow (CBF)-weight MRI did not require an injection of a contrast agent. It magnetically labels blood water by radiofrequency pulse, which provides a more direct measure of CBF than the traditional method. Therefore, ASL measurement will change the CBF threshold abnormal. Recent developments in non-contrast-enhanced MRA based on ASL-like sequences have emerged as an attractive alternative to MRA. It enables the possibility of restricting the labeling to a single artery, allowing the selective depiction of the responsible vessels for CVD. Another ASL advancement, vessel selective ASL, can visualize collateralization, which helps to correct diagnosis. Except for ALS, fluorodeoxyglucose 18F PET imaging shows the reduction of glucose metabolism in patients with brain infarct. Intracranial vessel wall imaging help to differentiate the cause of vessel structural abnormality. Globule magnetic resonance spectroscopy (MRS) can quantify the whole brain's metabolism, which provides more precise information predicting the prognosis.
The Research Topic aims to advance neuroimage techniques for metabolic and blood flow assessment in cerebral diseases. Original research articles or reviews are welcome. Areas covered in this Research Topic may include, but are not limited to:
- Inventing a new neuroimage sequence for metabolic and blood flow assessment in CVD
- Setting new neuroimage scan parameters for metabolic and blood flow assessment in CVD
- Innovative applications of traditional neuroimage techniques for metabolic and blood flow assessment in CVD
- Advanced neuroimage data post-processing technology for metabolic and blood flow assessment in CVD
- Comparing CVD presentations, diagnostic criteria, and therapeutic strategies in different territories