Synopsis

Keywords: Contrast mechanisms: Perfusion, Cross-organ: Cancer

Contrast-based perfusion MRI is used to assess tissue perfusion and permeability. Dynamic susceptibility-contrast (DSC-) MRI is mainly applied in the brain, whereas dynamic contrast-enhanced (DCE-) MRI has applications throughout the body, mostly related to oncology . For example, in cervical cancer it has been shown that DCE-MRI can be used to identify patients with hypoxic tumors, which is related to tumor aggression and resistance toradiation treatment. Clinical adoption of DSC- and DCE-MRI is currently hindered by the lack of reproducibility, non-standardized terminology, and requirements of expert imaging scientists.

Perfusion magnetic resonance imaging (MRI) is a family of imaging techniques used to measure the delivery of blood to tissues in any part of the body. In this talk we will focus on the contrast-based perfusion techniques, dynamic susceptibility-contrast (DSC-) MRI and dynamic contrast-enhanced (DCE-) MRI. DSC-MRI is mainly used in the brain, whereas DCE has applications throughout the body.

Currently, in clinical practice the data is most frequently assessed visually. For example DCE-MRI is increasingly being used in several lung diseases, such as COPD or pulmonary hypertension [1]. In the diagnosis of prostate cancer, DCE-MRI can be used to increase the likelihood of detecting clinically significant cancer when an intermediate risk (PIRADS 3) is observed based on T2-weighed imaging and DWI alone [2].

More quantitative analysis of the enhancement curves can provide imaging biomarkers of tissue perfusion and vascular permeability. The simplest approach, i.e. semi-quantitative analysis, describes signal time curves using model-free metrics such as time-to-peak, area-under-the-curve, and peak enhancement. Tracer kinetic analysis, also called pharmacokinetic modeling or quantitative DCE-MRI, helps to address variability caused by patient-specific factors and aims to derive more physiologically meaningful metrics compared to semi-quantitative analysis [3].

Over the past 30 years, parameters derived from DCE-MRI have found potential as imaging biomarkers in a wide range of research applications (e.g. oncology and brain, cardiac, lung, and renal diseases). For example, in the brain DCE-MRI has been used to assess damage to the blood-brain barrier (BBB) in multiple sclerosis, stroke, or neurodegenerative diseases [4-6]. Oncology is the most well-established of the research applications. DCE-MRI metrics have shown utility as surrogate endpoints in trials of anti-vascular and anti-angiogenic therapies [7-8], and hold value as predictive biomarkers of early tumor response to chemotherapy and/or radiotherapy [9-11]. Promising evidence in cervical tumors, has shown that DCE-MRI can be used to identify patients with hypoxic tumors which are related to resistance of radiation treatment [12-13].

Many of these applications are ongoing areas of research, but current clinical adoption is hindered by the lack of reproducibility, non-standardized terminology and requirements of expert imaging scientists for the analysis. Efforts to translate imaging biomarkers derived from DCE-MRI are ongoing through a number of international standardization initiatives. The quantitative imaging biomarker alliance (QIBA) focusses on the standardization of data acquisition [14], whereas the ISMRM open science initiative for perfusion imaging (ISMRM OSIPI) focuses more on the analysis of the perfusion data.

Acknowledgements

thanks to Ben Dickie from The University of Manchester

References

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