Perfusion MRI techniques-including dynamic susceptibility contrast (DSC) MRI, dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL) MRI, and intravoxel incoherent motion (IVIM) MRI-hold strong potential as imaging techniques for diagnosing, staging, and monitoring disease across a range of clinical applications. However, clinical adoption, especially of quantitative parameters, remains variable across techniques. Key barriers to broader implementation include a lack of standardized acquisition and analysis protocols, leading to poor reproducibility and reduced clinical confidence. Additionally, limited awareness and understanding of certain techniques among radiologists contribute to underutilization in practice. This work provides practice recommendations to support radiologists in integrating perfusion MRI into routine clinical workflows. It includes guidance on technique selection, acquisition, and analysis, supported by a flowchart outlining typical imaging pathways. These efforts align with ongoing initiatives such as the Quantitative Medical Imaging Coalition (formerly QIBA) and the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI), which are developing standards and tools to enhance reproducibility and clinical utility. Ultimately, the successful adoption of state-of-the-art perfusion MRI depends on close collaboration between clinicians, researchers, and industry stakeholders to ensure robust, standardized, and clinically meaningful application. KEY POINTS: Perfusion MRI parameters hold great promise as imaging biomarkers, but their clinical adoption, especially of quantitative parameters, remains variable across perfusion MRI techniques. An overview of perfusion MRI techniques, explaining the physics, illustrating clinical applications, and addressing common technical challenges, is provided to support perfusion MRI use in clinical practice. Successful adoption of state-of-the-art perfusion MRI depends on close collaboration between clinicians, researchers, and industry stakeholders to ensure robust, standardized, and clinically meaningful applications for patient care.
Houdt et al. (Tue,) studied this question.