Unleashing the potential of saturation-transfer MR fingerprinting (ST-MRF) in neuro-oncology: quantitative molecular CEST and MTC mapping.
Authors
Affiliations (10)
Affiliations (10)
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Park 336, Baltimore, MD, 21287, USA.
- Department of Artificial Intelligence, Korea University, Seoul, Republic of Korea.
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
- School of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel.
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Park 336, Baltimore, MD, 21287, USA. [email protected].
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA. [email protected].
Abstract
Neuro-oncology biomarkers allow probing tissues beyond anatomical or relaxation contrast. However, new techniques are needed to achieve mechanistic elucidation and effective therapeutic interventions. Quantitative MRI techniques, such as T<sub>1</sub>, T<sub>2</sub>, diffusion, and perfusion imaging, provide insights into tumor biology, infiltration, microstructure, and hemodynamics, and have been implemented clinically, but are limited in probing cellular and molecular changes. Saturation transfer (ST) MRI methods, including magnetization transfer contrast (MTC) and chemical exchange saturation transfer (CEST), exhibit enhanced sensitivity to semisolid macromolecular content, mobile proteins, tissue metabolites, and acidosis. Despite these advantages, ST-MRI techniques typically have been qualitative or semi-quantitative, time-consuming, and impractical for clinical implementation. However, emerging ST-MR fingerprinting (ST-MRF) represents a significant analytical advancement by integrating RF saturation preparation into a pseudo-randomized MRF acquisition framework with a deep learning-based reconstruction. This approach enables simultaneous, clinically realistic, quantitative mapping of bulk water relaxation properties (e.g., T<sub>1</sub> and T<sub>2</sub>), semisolid macromolecular parameters, and exchangeable solute dynamics (e.g., pool size ratios and exchange rates). We provide a comprehensive background, methodological principles, and evolving clinical applications of ST-MRF in neuro-oncology. We explore current advancements, strengths, limitations, and future possibilities for clinical translation into neuro-oncology workflows, including tumor characterization, treatment response monitoring, infiltration mapping, and biomarker development.