Synopsis

Keywords: Image acquisition: Quantification, Contrast mechanisms: Perfusion, Education Committee: Clinical MRI

In this lecture, we will dive into the clinical applications of MR perfusion quantification, encompassing both neuroimaging and body imaging. The focus will be on dynamic susceptibility contrast (DSC) imaging and dynamic contrast-enhanced (DCE) imaging techniques, highlighting their pivotal roles in improving patient diagnosis, treatment planning, and outcome prediction. Participants will gain insights into the versatile applications and inherent advantages of MR perfusion in clinical practice, enabling them to leverage this powerful tool for enhanced patient care.

Perfusion MR imaging has emerged as a powerful tool in clinical medicine, offering a non-invasive window into tissue perfusion, the rate of blood flow through organs and tissues. This lecture delves into the clinical applications of perfusion MRI techniques, focusing on how they provide valuable quantitative data for disease diagnosis, treatment planning, and monitoring.
While the prior lecture addressed the technical aspects of perfusion MRI, this session emphasizes its clinical utility. We'll explore two main techniques: Dynamic Susceptibility Contrast (DSC) imaging and Dynamic Contrast Enhanced (DCE) imaging. Each technique offers distinct advantages and limitations, but all share the ability to quantify blood flow parameters.
Quantitative perfusion MRI plays a vital role in various clinical settings. In stroke evaluation, it helps identify areas with reduced blood flow (ischemia) and potentially salvageable tissue for treatment decisions. Brain tumor characterization benefits from perfusion data, aiding in differentiating tumor types and assessing their aggressiveness. Perfusion MRI can also be used to investigate blood flow/permeability associated with Alzheimer's disease and other neurodegenerative diseases.
Perfusion MRI's quantitative capabilities extend beyond neurology. In cardiac MRI, it measures myocardial blood flow and perfusion reserve, aiding in the diagnosis of coronary artery disease. Renal MRI utilizes perfusion to assess kidney function by quantifying renal blood flow. Perfusion MRI also finds applications in oncology, where tracking changes in perfusion parameters helps monitor tumor response to treatment.
The field of quantitative perfusion MRI is constantly evolving. Researchers are developing improved data acquisition techniques to minimize artifacts and enhance data quality. Robust quantification methods are being established to ensure reliable and accurate parameter measurement. Machine learning algorithms are making significant strides in automating analysis, saving time, and potentially improving accuracy. Additionally, standardization efforts are underway to facilitate wider clinical adoption of quantitative perfusion MRI across different institutions and scanners.
In conclusion, perfusion MRI has emerged as a powerful tool for clinical diagnosis, treatment planning, and monitoring disease progression. Its ability to quantify blood flow parameters offers valuable insights into various disease processes, paving the way for a more personalized approach to patient care.

Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF) grant, funded by the Korean government (MSIP) (grant number 2020R1A2C1102896) and the Korea Health Technology R&D Project through the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number HU21C0222).