BackgroundAortic flow parameters can be quantified using 4D flow MRI. However, data are sparse on how different methods of analysis influence these parameters and how these parameters evolve during systole.PurposeTo assess multiphase segmentations and multiphase quantification of flow‐related parameters in aortic 4D flow MRI.Study TypeProspective.Population40 healthy volunteers (50% male, 28.9 ± 5.0 years) and 10 patients with thoracic aortic aneurysm (80% male, 54 ± 8 years).Field Strength/Sequence4D flow MRI with a velocity encoded turbo field echo sequence at 3 T.AssessmentPhase‐specific segmentations were obtained for the aortic root and the ascending aorta. The whole aorta was segmented in peak systole. In all aortic segments, time to peak (TTP; for flow velocity, vorticity, helicity, kinetic energy, and viscous energy loss) and peak and time‐averaged values (for velocity and vorticity) were calculated.Statistical TestsStatic vs. phase‐specific models were assessed using Bland–Altman plots. Other analyses were performed using phase‐specific segmentations for aortic root and ascending aorta. TTP for all parameters was compared to TTP of flow rate using paired t‐tests. Time‐averaged and peak values were assessed using Pearson correlation coefficient. P < 0.05 was considered statistically significant.ResultsIn the combined group, velocity in static vs. phase‐specific segmentations differed by 0.8 cm/sec for the aortic root, and 0.1 cm/sec (P = 0.214) for the ascending aorta. Vorticity differed by 167 sec−1 mL−1 (P = 0.468) for the aortic root, and by 59 sec−1 mL−1 (P = 0.481) for the ascending aorta. Vorticity, helicity, and energy loss in the ascending aorta, aortic arch, and descending aorta peaked significantly later than flow rate. Time‐averaged velocity and vorticity values correlated significantly in all segments.Data ConclusionStatic 4D flow MRI segmentation yields comparable results as multiphase segmentation for flow‐related parameters, eliminating the need for time‐consuming multiple segmentations. However, multiphase quantification is necessary for assessing peak values of aortic flow‐related parameters.Level of Evidence2Technical Efficacy Stage3
Mechanical properties of an aneurysmatic thoracic aorta are potential markers of future growth and remodeling and can help to estimate risk of rupture. Aortic geometries obtained from routine medical imaging do not display wall stress distribution and mechanical properties. Mechanical properties for a given vessel may be determined from medical images at different physiological pressures using inverse finite element analysis. However, without considering pre-stresses, the estimation of mechanical properties will lack accuracy. In the present paper, we propose and evaluate a mechanical parameter identification technique, which recovers pre-stresses by determining the zero-pressure configuration of the aortic geometry. We first validated the method on a cylindrical geometry and subsequently applied it to a realistic aortic geometry. Verification of the assessed parameters was performed using synthetically generated reference data for both geometries. The method was able to estimate the true mechanical properties with an accuracy ranging from 98% to 99%.
Four-dimensional flow magnetic resonance imaging is an emerging technique which may play a role in diagnosis and risk-stratification of aortic disease. Some knowledge of flow dynamics and related parameters is necessary to understand and apply this technique in clinical workflows. The purpose of the current review is to provide a guide for clinicians to the basics of flow imaging, frequently used flow-related parameters, and their relevance in the context of aortic disease.Clinical relevance statement Understanding normal and abnormal aortic flow could improve clinical care in patients with aortic disease. Graphical abstract
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