## 4 Discussion
Therefore, these alterations of blood flow may be a factor in developing systolic and diastolic dysfunctions. While eight patients showed significantly impaired systolic function at CMR's time, five showed a complete response to treatment. Despite a nearly normalized LV ejection fraction, it showed similar hemodynamic values to non-responders DCM patients that were markedly different from volunteers. These results suggest a significant increase in the ratio of outflow to inflow during systole in responders DCM patients, but the volumeswere significantly smaller. Therefore, LV ejection fraction cannot reflect subtle ventricular dysfunction, which potentially can be better assessed using flow-based parameters because of the sensitivity to abnormal pumping function [36]. Therefore, the problem of using LV ejection fraction as the pivotal risk marker for DCM patients is that this single parameter does not recapitulate the complexity of the disease. The location and extent of the changes in intraventricular blood flow, for example, the depth (base to apex) of the vorticity changes or the spread of impaired flow through the ventricular cavity, can potentially be a sensitive marker of the severity of diseases or the progress of the treatment but are hard to quantify because of the 3D nature of the flow. We proposed to use the bullseye plots to depict this data. These plots allow us to display the most important regional differences and extend flow changes in a familiar way to many clinicians. These results could facilitate homogeneity among 4D Flow quantifiable analysis for clinical researchers and clinicians. The sensitivity study showed a significant relative error, particularly in helicity density, when the differences in the segmentations were greater than 1 pixel in dilation and erosion cases. We performed this sensitivity study even under the pixel resolution of the 4D Flow data. In each pixel, there were four or five elements from the mesh, whose flow values were interpolated from neighborhood pixels. When the segmentation error was lower or equal to 1 pixel, the maximum mean relative error was less than 10% in most hemodynamic parameters studied. Previous research has shown that DCM patients have a lower mean value of velocity magnitude than healthy volunteers [21; 22; 23; 24; 25]. These results were considered when the segmentation contour fell inside the LV blood pool. In general, we also observed that lower errors were obtained for almost all hemodynamic parameters when the segmentation underestimated the LV volumes. Inter-observer and intra-observer assessments showed excellent reproducibility of the results with negligible mean differences and small limits of an agreement at peak systole, e-wave, and end-diastole for all the parameters assessed. It is important to note that the high intra- e inter-observer variability was obtained because we performed an automatic segmentation process using the software Segment. Therefore, the difference in segmentations was minimal, as previously reported by [PERSON] et al. [29]. The automated process corrections were also minimal, which led to a high intra- and inter-observer variability. On the other hand, the sensitivity study was performed by modifying a reference segmentation in the entire contour by applying erosion or dilatation. This result implies a more significant volume difference concerning the reference, and, as a result, high sensitivity to the segmentation was obtained. The limited size of this proof-of-concept study did not allow us to investigate the prognostic impact, but this will be our aim in future research. Nevertheless, in this small cohort of patients, we have shown that the velocity, vorticity, kinetic energy, viscous dissipation, and energy loss revealed statistical differences between volunteers and patients. This finding could be relevant to assess changes in a longitudinal study or to study the response to a particular therapy.