ECG-gated cardiac cine MRI is the gold standard for the assessment of cardiac function and blood flow. To overcome the limitations of conventional cine MRI in patients suffering from arrhythmia and shortness of breath, recent developments in acquisition technology provide real-time (rt) MRI sequences. This new technique allows for the acquisition of serial images with a temporal resolution of up to 20 ms under free breathing without ECG gating [1]. Recent studies of rt-MRI datasets have shown that single heartbeats as well as the variation of the cardiac contraction over time can be inspected quantitatively [2]. However, the application of conventional analysis tools is not possible because of the different image characteristics and the number of frames to process. The functionality to assess the additional information about beat-to-beat variability of clinical parameters is generally missing. The purpose of this work was the development of a software solution which enables quantitative analysis of rt-MRI data of function and flow in a clinical environment. The proposed solution combines automatic image processing with interactive exploration techniques as shown in Figure 1. Data sent by the scanner is immediately pre-processed in a background process to analyze motion, detect heart cycles, and segment the myocardium in short-axis sequences [2,3]. The segmentation result as well as the temporal division into cardiac cycles can be corrected interactively. The exploration step is organized in such a way that analysis results can be inspected in a coarse-to-fine concept via a web browser. The slices as well as the heart cycles can be explored separately. The data to include for the calculation of overall functional parameters such as blood flow or ejection fraction adapts to the user selection. Thereby parameters can be calculated for different phases of the image series, e.g. for normal and ectopic beats separately.The installation has been tested with data from arrhythmic patients as well as volunteers performing Valsalva maneuver and physical exercise tests. The size of the complete datasets was between 0.5 and 6 GB. Depending on the workload of the server (i7, 2.7GHz, 32GB RAM), automatic image analysis took between 1 and 30 minutes per image series. The effort for interactive correction was highest (10 min) for the exercise cases with strong through-plane motion affecting the image quality of the cine sequence. Figure 2 shows the comparison of the myocardial function analysis under physical stress with a pedometer and under rest (one section). The overall ejection fraction rose from 0.77±0.0 during rest to 0.84±0.03 during exercise. The multi-cycle analysis of the cardiac function of a patient with arrhythmia showed that the average ejection fraction of the irregular cycles was 0.43±0.02, whereas the normal EF was 0.66±0.04. The blood pool volume as a function of time in Figure 3 also clearly despicts the temporal shortening of the irregular heart cycles. Figure 4 shows a multi-cycle analysis of the blood flow in the ascending aorta from real-time velocity-encoded PC-MRI during a Valsalva maneuver. In the period during the maneuver the flow rate dropped from 90.04±4.98 ml to 63.11±10.12 ml, while the maximum peak velocity decreased from 80.42±12.75 cm/s to 57.23±8.26 cm/s.We have developed a concept for the time-efficient analysis of rt-MRI datasets of cardiac function and flow. The solution has been successfully applied to compare cardiac blood flow and function under different stress levels, to measure the influence of breathing maneuvers such as Valsalva as well as to determine the influence of arrhythmia on cardiac function. The initial tests showed that cardiac variability can be quantified with the suggested acquisition and analysis pipeline with reasonable temporal effort. Future work will focus on studies to prove the clinical benefit of the provided technology.