Current Applications and Future Development of Magnetic Resonance Fingerprinting in Diagnosis, Characterization, and Response Monitoring in Cancer

Abstract

Magnetic resonance imaging (MRI) has enabled non-invasive cancer diagnosis, monitoring, and management in common clinical settings. However, inadequate quantitative analyses in MRI continue to limit its full potential and these often have an impact on clinicians’ judgments. Magnetic resonance fingerprinting (MRF) has recently been introduced to acquire multiple quantitative parameters simultaneously in a reasonable timeframe. Initial retrospective studies have demonstrated the feasibility of using MRF for various cancer characterizations. Further trials with larger cohorts are still needed to explore the repeatability and reproducibility of the data acquired by MRF. At the moment, technical difficulties such as undesirable processing time or lack of motion robustness are limiting further implementations of MRF in clinical oncology. This review summarises the latest findings and technology developments for the use of MRF in cancer management and suggests possible future implications of MRF in characterizing tumour heterogeneity and response assessment.

Emerging Trends in Magnetic Resonance Fingerprinting for Quantitative Biomedical Imaging Applications: A Review

“…MRF offers a framework to quantify tissue properties accurately and rapidly. In [ 7 , 16 ], reviews of recent technical and clinical developments for the application of MRF in radiotherapy are presented. In [ 80 ], the authors proposed and demonstrated the feasibility of quantitative CEST-based MRF to measure the tissue properties of a brain tumor (the and for water and fat and the exchange rate between the solid-state pool and the liquid pool).…”

“…In [ 16 ], the authors discussed challenges and recent developments in integrating MRF into the radiotherapy pipeline. In [ 7 ], the authors summarized the latest findings and technological developments for the use of MRF in cancer management and suggested possible future implications of MRF in characterizing tumor heterogeneity and response assessment.…”

Systematic review of reconstruction techniques for accelerated quantitative MRI

“…Furthermore, the reconstruction techniques are usually introduced using different terminologies, which complicates their comparison. Review studies on qMRI reconstruction techniques are typically specific to a class of techniques such as compressed sensing, 3 MR fingerprinting [4][5][6] or deep-learning. 7,8 Alternatively, they are specific to a particular class of parameters of interest, such as relaxometry, 7,[9][10][11][12] or diffusion 13 parameters, or to a particular application domain, such as the knee, 14 or cardiac and abdominal imaging.…”

SMoRe ParS: A novel methodology for bridging modeling modalities and experimental data applied to 3D vascular tumor growth

“…ABMs provide a logical structure for capturing the multiple time and spatial scales associated with cancer growth and progression because they allow for the characterization of tumor heterogeneity at an individual cell level that better reflects the complexity seen in vivo (Bergman et al, 2022). One major advantage of ABMs over traditional continuum ODE/PDE models is that they can generate realistic 3-dimensional virtual tumors that current state-ofart imaging technologies cannot infer from patient scans [for a discussion on limitations of imaging in cancer, see for instance (Bogdanovic et al, 2021;Ding et al, 2021;Martinez-Heras et al, 2021)]. However, to make useful, reliable quantitative predictions, ABMs need to relate to real-world data through model parameterization and calibration (Byrne, 2010;Eisenberg and Jain, 2017).…”