Abstract
Simple SummaryMagnetic resonance fingerprinting (MRF) is a framework for acquiring co-registered multiparametric magnetic resonance mapping with increased scan efficiency. Many studies have explored the use of MRF for cancer management. A review on the current developments in this area has not yet been written but is needed to keep both clinicians and researchers updated. This review summarises recent studies detecting and characterising tumours using MRF, with a focus on brain tumours, prostate cancers, and abdominal/pelvic cancers. Advances in MRF for radiotherapy planning are also mentioned. The principles and limitations of MRF have been simplified to increase accessibility to clinicians with minimal radiological backgrounds. Future oncological applications of MRF are explored, including integrating MRF and deep learning, as well as the use of MRF in assessing disease heterogeneity. We propose further research that needs to take place before MRF can provide a credible means for assessing tumour biomarkers or be accepted by clinicians.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.
Highlights
Magnetic resonance imaging (MRI) is a rapidly developing imaging modality with an established and expanding role in the detection and characterisation of many malignancies
Cao et al have shown that 3D Magnetic resonance fingerprinting (MRF), multi-axis spiral projection imaging is more motion-robust compared with stack-of-spiral (SOS) imaging [107]
We described advances made by conventional MRI and how quantitative MRI parameters are potential biomarkers for many cancer types
Summary
Magnetic resonance imaging (MRI) is a rapidly developing imaging modality with an established and expanding role in the detection and characterisation of many malignancies. TrueFISP is susceptible to B0 inhomogeneity artefacts on high field MRI scanners [15], while MPME has visibly noisy parameter maps in vivo due to propagated noise from successive processing steps Another example of simultaneous multiparametric quantitative imaging is MR Multitasking [16], a continuous-acquisition framework that provides multiparametric motion resolved images. Due to the lack of large multicentre studies or readily implementable imaging protocols/sequences, none of the methods mentioned above has achieved widespread clinical acceptance yet. Due otof 20 the lack of large multicentre studies or readily implementable imaging protocols/sequences, none of the methods mentioned above has achieved widespread clinical acceptance yet. We propose further research that needs to take place before MRF can provide a credible means for assessing tumour biomarkers or be accepted by clinicians
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