Schubert C, Brüning J, Goubergrits L, Hennemuth A, Berger F, Kühne T, Kelm M.Sci Rep. 2020 Nov 3;10(1):18894. doi: 10.1038/s41598-020-75689-z.PMID: 33144605 Free PMC article.
Take Home Points:
- MRI ergometry in combination with Computational Flow Dynamics (CFD) can be used to noninvasively assess trans-stenotic pressure gradients, aortic flow patterns and stroke volume in patients with aortic coarctation at rest and during physical exercise.
- Therefore, no simulation of exercise using adrenergic drugs is necessary.
- This information has promising implications for clinical application and further research on the pathophysiology of aortic coarctation.
Commentary from Dr. Soha Romeih (Aswan, Egypt), section editor of ACHD Journal Watch:
Introduction
For aortic coarctation, in the current clinical decision-making process, pressure gradients across the aortic narrowing is one of the decisive factors for potential re-intervention. As pressure gradients increase during exercise due to increased cardiac output, patients with gradients below the threshold for intervention at rest may develop pathologically high gradients during exercise. In the case of a borderline indication for surgical or catheter-based treatment, stress tests can help to unmask the hemodynamic relevance of the stenosis.
Commonly used non-invasive methods for determining pressure gradients at rest or during physical exercise (e.g. echocardiography, cuff measurements) are often inaccurate. Alternatively, adrenergic drug infusions can be used during cardiac catheterization, simulating physical exercise, while measuring peak-to-peak gradients. However, the hemodynamic response during pharmacological stress is far from representing responses to actual physical exercise.
The combination of MRI-ergometry and computational fluid dynamics (CFD) could be an approach to quantitatively assess the hemodynamic response to physical exercise. Combining these two methods, would allow an accurate and non-invasive assessment of pressure gradients, aortic and left ventricular hemodynamics at rest and during physical exercise, without the need for adrenergic drugs to simulate exercise.
Patients and Methods:
This is a prospective study in patients with aortic coarctation, who underwent cardiac MRI due to elevated Doppler gradients or follow-up after an intervention, between November 2018 and September 2019.
Study design:
Figure 1. (Upper panel) Visual illustration of the study design. Cardiac MRI of 20 participants with aortic coarctation was acquired during rest and moderate exercise. An absolute increase in heart rate of 50 bpm was targeted during exercise. Using the MRI images, the participant-specific aortic geometry was reconstructed Using computational fluid dynamics, the transstenotic pressure gradient was calculated during rest and exercise.(Lower panel) Visualization of the image data used for segmentation. The participant-specific anatomy of the aorta was segmented from 3D SSFP (steady-state free precession) images (A,C). If the respective participant was treated using a stent, additional image information from black blood MR sequences (D) was used to improve the segmentation of the stented region of the aorta. An example from only 3D SSFP images is shown in panel (B), whereas a combined segmentation of a previously stented patient is shown in panel (E).
Computational fluid dynamics (CFD) simulation:
Numerical simulations for calculation of patient specific hemodynamics at rest and during exercise were performed using an approach that was previously validated against in-vivo catheter-based measurements as well as 4D-flow-MRI measurements. At the descending aorta, the maximal volume flow rate was measured using the 4D QF sequence during rest and exercise was applied as an outlet boundary condition. At the ascending aorta, the patient-specific peak systolic velocity vector profiles, which were measured using planar 4D VEC MRI at rest and during exercise, were applied.
End Points
- The primary outcome measure was the pressure gradient across the stenosis at rest and during exercise.
- Secondary outcomes were wall shear stress (WSS), secondary flow degree (SFD), normalized flow displacement (NFD), cardiac index, stroke volume index and heart rate, at rest and during exercise.
Results
The analysis was carried out in 20 patients. The baseline characteristics of the included patients are shown in Table 1.
Of the 20 patients (13 men, 7 women) included, 3 patients were untreated, 5 had undergone surgical repair by end-to-end-anastomosis, 11 were treated by stent-implantation and one stented patient was also treated surgically. The mean age of included patients was 21.5 ± 13.7 years.
No symptoms occurred during exercise. The average workload present during exercise was 83.5 ± 37.8 W.
On average, 85.79 ± 10.28% of the calculated target heart rate was reached during exercise. Patients’ systolic blood pressure, measured using cuff-measurements at the arm, significantly increased from rest to exercise (128.45 ± 21.45 to 158.65 ± 33.97 mmHg, p = 0.002).
The relative static pressure distributions at rest and during exercise that were calculated using CFD are shown in Fig. 3.
The mean trans-stenotic pressure gradient was 17.99 ± 16.61 mmHg at rest and 28.45 ± 22.56 mmHg during stress (Fig. 4).
Those patients had lower resting heart rates than the patients who featured a stroke volume increase during exercise (61.2 vs. 89.9 bpm, p < 0.001). Also, with exception of one patient, they all were in the lower part of the cardiac index distribution (3.2 vs. 4.0, p < 0.05 at rest and 4.3 vs. 5.6, p < 0.05 during exercise).
No relevant difference in the increase of the trans-stenotic pressure gradient was observed between those two groups (8.9 vs 11.1 mmHg, p = 0.55). The measured maximum volume flow rate in the ascending (rest 407.0 ± 87.3, stress 494.4 ± 225.5 ml/min, p < 0.001) and descending (rest 225.5 ± 76.7, stress 274.8 ± 83.8 ml/min, p = 0.002) aorta significantly increased during exercise.
However, the ratio of the peak-systolic volume flow rate measured in the ascending and descending aorta did not change significantly (p = 0.287). An overview of changes in hemodynamic parameters is provided in Table 2.
Conclusion
In this feasibility study, MRI-ergometry and image-based computational fluid dynamics were combined. This approach allows assessing the individual hemodynamic response to exercise under nearly physiological conditions.
As pressure gradients at rest and during physical exercise can be determined noninvasively, it has the potential to serve as an alternative to pharmacological stress testing during cardiac catheterization. While the numerical method used has been validated previously, a thorough validation of the translation towards assessment of pressure gradients during dynamic exercise is required before clinical application.
However, as currently no clinical standard for measurement of the trans-stenotic pressure gradient during dynamic exercise exists, this combined approach seems promising. In general, the method has the potential for measuring individual changes in trans-stenotic pressure gradients, aortic flow patterns, the left ventricular response to dynamic exercise, providing valuable information for studying the pathophysiology of aortic coarctation.
Currently, those parameters can only be assessed in a very limited matter or cannot be assessed at all during dynamic exercise.
