## 5 Clinical Applications
### Quantitative Mapping  
Cardiac MRI can also be used to non-invasively and quantitatively measure fat concentration in the heart, which can assist in diagnosing pathologies characterized by the abnormal development of adipose cells [54; 55]. Fat fraction quantification also has the potential to characterize the complex metabolic role of adipose tissues in obesity and diabetes, where increased amounts of epicardial, pericardial, and peri-coronary fat alter the cardiovascular disease risk profile [56; 57]. Fat fraction quantification is typically performed using a multi-echo gradient-echo sequence that acquires images at different echo times [55].  
In 2023, [PERSON] et al. extended the FRF to 6D to enable multi-echo sampling and multi-peak fitting for fat-water separation and quantification at 1.5 T (x-y-z-cardiac-respiratory-echo, Figure 9) [58]. The aforementioned PT technique was added to obtain cardiac and respiratory signals [36; 37]. In vivo results in 10 healthy volunteers demonstrated the feasibility of pericardial fat imaging and quantification throughout the cardiac cycle, and the motion-resolved end-diastolic 3D fat fraction maps showed a good correlation with ECG-triggered measurements (bias of \(-\)1.1%).  
Figure 8: Panel (**A**) Magnitude images and phase-difference images for all three velocity-encoding directions (V\({}_{x}\), V\({}_{y}\), and V\({}_{z}\)) in a transversal (TRA), coronal (COR), and sagittal (SAG) view for a specific time point during systole of a 41-year-old man with bicuspid aortic valve disease. Panel (**B**) Peak systolic velocity maximum intensity projections (MIPs) and streamlines show good agreement between conventional navigator-gated 4D flow and free-running 5D flow imaging, with some overestimation in the ascending aorta (AAo) and underestimation in the arch and descending aorta (DAo) as indicated by the white arrows. Panel (**C**) Flow curves at three locations in the aorta, as indicated by the red lines in panel (**B**), demonstrate good agreement between the two techniques. The underestimation in the arch and DAo for 5D flow can be observed. LV = left ventricle, SVC = superior vena cava. Figure created using the original source images by [PERSON] et al. [52] with author permission.  
Later in 2024, [PERSON] et al. further built upon the work of [PERSON] et al. and evaluated it on 3 T [59]. Although benefitting from increased signal-to-noise to achieve higher spatial resolution, gradient correction using the gradient impulse response function (GIRF) was implemented to overcome distortions between odd and even echoes [60; 61]. Their in vitro results in a water-fat phantom showed that fat fraction quantification was reliable and accurate using bipolar readout gradient with the GIRF correction, while it suffered from artefacts without correction (bias of 0.4% vs. 4.9%). In vivo measurements in 10 healthy volunteers and three diabetic patients demonstrated a significantly lower fat fraction of epicardial adipose tissue compared to subcutaneous fat. These studies showed that fat-fraction mapping using the FRF is feasible at both 1.5 and 3 T, enabling the investigation of epicardial adipose tissue in metabolic diseases.  
Apart from fat-fraction mapping, quantitative T\({}_{1}\) and T\({}_{2}\) mapping in a free-running approach have been proposed [18; 62; 63; 64; 65]. However, since a different framework and different acquisition strategy were used for these, we will not further discuss these in this review.