Bridging Gaps in Neuroimaging: Enhancing Diagnostic Precision in Cerebrovascular Disease

Cerebrovascular diseases (CVD), including stroke, represent a significant global health challenge as they are among the leading causes of disability and mortality. The early and accurate diagnosis of these conditions is crucial for effective treatment and prevention. In recent years, advanced neuroimaging techniques have emerged as vital tools in the assessment of cerebrovascular diseases. These techniques offer profound insights into the pathophysiology of CVD, assist in identifying high-risk individuals, and facilitate the customization of therapeutic strategies. However, despite these advancements, there remain numerous challenges and limitations that hinder the clinical utility and accuracy of neuroimaging. Current research highlights the need for improved diagnostic capabilities and the integration of novel technologies to address these gaps. Ongoing debates focus on the efficacy of existing imaging modalities and the potential of emerging technologies to revolutionize the field. There is a pressing need for comprehensive investigations to enhance the precision and applicability of neuroimaging in clinical settings.

This research topic aims to delve into the current research landscape of advanced neuroimaging techniques within the context of cerebrovascular diseases. It seeks to illuminate recent advancements and discuss the persistent gaps in research and practice that limit their diagnostic potential. By convening experts from various disciplines, this issue aspires to facilitate a robust exchange of knowledge and ideas, driving the development and application of innovative approaches and improvements in neuroimaging. Ultimately, the goal is to enhance the accuracy, efficiency, and clinical utility of neuroimaging in evaluating cerebrovascular diseases, thereby contributing to improved patient care and outcomes.

To gather further insights into the application and enhancement of neuroimaging techniques in cerebrovascular diseases, we welcome articles addressing, but not limited to, the following themes:

- Latest advancements in neuroimaging and their applications in diagnosing and managing cerebrovascular diseases, including the use of artificial intelligence (AI) and machine learning algorithms.
- Limitations of current imaging techniques, such as the potential for misdiagnosis and poor diagnostic/prognostic accuracy, and potential opportunities/pathways to overcome these challenges.
- Emerging and novel approaches to enhance the clinical utility of neuroimaging in cerebrovascular disease.