| 1. |
- Andersson, Magnus, et al.
(författare)
-
Correction: Quantitative Assessment of Turbulence and Flow Eccentricity in an Aortic Coarctation: Impact of Virtual Interventions (vol 6, pg 281, 2015)
- 2015
-
Ingår i: Cardiovascular Engineering and Technology. - : SPRINGER. - 1869-408X .- 1869-4098. ; 6:4, s. 577-589
-
Tidskriftsartikel (refereegranskat)abstract
- Turbulence and flow eccentricity can be measured by magnetic resonance imaging (MRI) and may play an important role in the pathogenesis of numerous cardiovascular diseases. In the present study, we propose quantitative techniques to assess turbulent kinetic energy (TKE) and flow eccentricity that could assist in the evaluation and treatment of stenotic severities. These hemodynamic parameters were studied in a pre-treated aortic coarctation (CoA) and after several virtual interventions using computational fluid dynamics (CFD), to demonstrate the effect of different dilatation options on the flow field. Patient-specific geometry and flow conditions were derived from MRI data. The unsteady pulsatile flow was resolved by large eddy simulation (LES) including non-Newtonian blood rheology. Results showed an inverse asymptotic relationship between the total amount of TKE and degree of dilatation of the stenosis, where the pre-stenotic hypoplastic segment may limit the possible improvement by treating the CoA alone. Spatiotem-poral maps of TKE and flow eccentricity could be linked to the characteristics of the post-stenotic jet, showing a versatile response between the CoA dilatations. By including these flow markers into a combined MRI-CFD intervention framework, CoA therapy has not only the possibility to produce predictions via simulation, but can also be validated pre-and immediate post treatment, as well as during follow-up studies.
|
|
| 2. |
- Andersson, Magnus, 1983-, et al.
(författare)
-
Quantitative Assessment of Turbulence and Flow Eccentricity in an Aortic Coarctation - Impact of Virtual Interventions
- 2015
-
Ingår i: Cardiovascular Engineering and Technology. - : Springer. - 1869-408X .- 1869-4098. ; 6:6, s. 281-293
-
Tidskriftsartikel (refereegranskat)abstract
- Turbulence and flow eccentricity can be measured by magnetic resonance imaging (MRI) and may play an important role in the pathogenesis of numerous cardiovascular diseases. In the present study, we propose quantitative techniques to assess turbulent kinetic energy (TKE) and flow eccentricity that could assist in the evaluation and treatment of stenotic severities. These hemodynamic parameters were studied in a pre-treated aortic coarctation (CoA) and after several virtual interventions using computational fluid dynamics (CFD), to demonstrate the effect of different dilatation options on the flow field. Patient-specific geometry and flow conditions were derived from MRI data. The unsteady pulsatile flow was resolved by large eddy simulation (LES) including non-Newtonian blood rheology. Results showed an inverse asymptotic relationship between the total amount of TKE and degree of dilatation of the stenosis, where turbulent flow proximal the constriction limits the possible improvement by treating the CoA alone. Spatiotemporal maps of TKE and flow eccentricity could be linked to the characteristics of the jet, where improved flow conditions were favored by an eccentric dilatation of the CoA. By including these flow markers into a combined MRI-CFD intervention framework, CoA therapy has not only the possibility to produce predictions via simulation, but can also be validated pre- and immediate post treatment, as well as during follow-up studies.
|
|
| 3. |
|
|
| 4. |
- Gharehbaghi, Arash, et al.
(författare)
-
A Novel Method for Screening Children with Isolated Bicuspid Aortic Valve
- 2015
-
Ingår i: Cardiovascular Engineering and Technology. - : Springer Science and Business Media LLC. - 1869-408X .- 1869-4098. ; 6:4, s. 546-556
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents a novel processing method for heart sound signal: the statistical time growing neural network (STGNN). The STGNN performs a robust classification by merging supervised and unsupervised statistical methods to overcome non-stationary behavior of the signal. By combining available preprocessing and segmentation techniques and the STGNN classifier, we build an automatic tool for screening children with isolated BAV, the congenital heart malformation which can lead to serious cardiovascular lesions. Children with BAV (22 individuals) and healthy condition (28 individuals) are subjected to the study. The performance of the STGNN is compared to that of a time growing neural network (CTGNN) and a conventional support vector (CSVM) machine, using balanced repeated random sub sampling. The average of the accuracy/sensitivity is estimated to be 87.4/86.5 for the STGNN, 81.8/83.4 for the CTGNN, and 72.9/66.8 for the CSVM. Results show that the STGNN offers better performance and provides more immunity to the background noise as compared to the CTGNN and CSVM. The method is implementable in a computer system to be employed in primary healthcare centers to improve the screening accuracy.
|
|
| 5. |
- Lantz, Jonas, et al.
(författare)
-
Improving Blood Flow Simulations by Incorporating Measured Subject-Specific Wall Motion
- 2014
-
Ingår i: Cardiovascular Engineering and Technology. - : Springer. - 1869-408X .- 1869-4098. ; 5:3, s. 261-269
-
Tidskriftsartikel (refereegranskat)abstract
- Physiologically relevant simulations of blood flow require models that allow for wall deformation. Normally a fluid–structure interaction (FSI) approach is used; however, this method relies on several assumptions and patient-specific material parameters that are difficult or impossible to measure in vivo. In order to circumvent the assumptions inherent in FSI models, aortic wall motion was measured with MRI and prescribed directly in a numerical solver. In this way is not only the displacement of the vessel accounted for, but also the interaction with the beating heart and surrounding organs. In order to highlight the effect of wall motion, comparisons with standard rigid wall models was performed in a healthy human aorta. The additional computational cost associated with prescribing the wall motion was low (17%). Standard hemodynamic parameters such as time-averaged wall shear stress and oscillatory shear index seemed largely unaffected by the wall motion, as a consequence of the smoothing effect inherent in time-averaging. Conversely, instantaneous wall shear stress was greatly affected by the wall motion; the wall dynamics seemed to produce a lower wall shear stress magnitude compared to a rigid wall model. In addition, it was found that if wall motion was taken into account the computed flow field agreed better with in vivo measurements. This article shows that it is feasible to include measured subject-specific wall motion into numerical simulations, and that the wall motion greatly affects the flow field. This approach to incorporate measured motion should be considered in future studies of arterial blood flow simulations.
|
|
| 6. |
- Rasooli, Reza, et al.
(författare)
-
In Silico Evaluation of a Self-powered Venous Ejector Pump for Fontan Patients.
- 2023
-
Ingår i: Cardiovascular engineering and technology. - : Springer Science and Business Media LLC. - 1869-408X .- 1869-4098. ; 14:3, s. 428-446
-
Tidskriftsartikel (refereegranskat)abstract
- The Fontan circulation carries a dismal prognosis in the long term due to its peculiar physiology and lack of a subpulmonic ventricle. Although it is multifactorial, elevated IVC pressure is accepted to be the primary cause of Fontan's high mortality and morbidity. This study presents a self-powered venous ejector pump (VEP) that can be used to lower the high IVC venous pressure in single-ventricle patients.A self-powered venous assist device that exploits the high-energy aortic flow to lower IVC pressure is designed. The proposed design is clinically feasible, simple in structure, and is powered intracorporeally. The device's performance in reducing IVC pressure is assessed by conducting comprehensive computational fluid dynamics simulations in idealized total cavopulmonary connections with different offsets. The device was finally applied to complex 3D reconstructed patient-specific TCPC models to validate its performance.The assist device provided a significant IVC pressure drop of more than 3.2 mm Hg in both idealized and patient-specific geometries, while maintaining a high systemic oxygen saturation of more than 90%. The simulations revealed no significant caval pressure rise (< 0.1 mm Hg) and sufficient systemic oxygen saturation (> 84%) in the event of device failure, demonstrating its fail-safe feature.A self-powered venous assist with promising in silico performance in improving Fontan hemodynamics is proposed. Due to its passive nature, the device has the potential to provide palliation for the growing population of patients with failing Fontan.
|
|
| 7. |
- Wahlquist, Ylva, et al.
(författare)
-
Prevention of ischemic myocardial contracture through hemodynamically controlled DCD
- 2021
-
Ingår i: Cardiovascular Engineering and Technology. - : Springer Science and Business Media LLC. - 1869-408X .- 1869-4098. ; 12:5, s. 485-493
-
Tidskriftsartikel (refereegranskat)abstract
- Purpose—Ischemic myocardial contracture (IMC) or ‘‘stoneheart’’ is a condition with rapid onset following circulatory death. It inhibits transplantability of hearts donated uponcirculatory death (DCD). We investigate the effectiveness of hemodynamic normalization upon withdrawal of life-sustaining therapy (WLST) in a large-animal controlled DCD model, with the hypothesis that reduction in cardiac work delays the onset of IMC. Methods—A large-animal study was conducted comprising of a control group (n = 6) receiving no therapy upon WLST, and a test group (n = 6) subjected to a protocol for fully automated computer-controlled hemodynamic drug administration. Onset of IMC within 1 h following circulatory death defined the primary end-point. Cardiac work estimates based on pressure-volume loop concepts were developed and used to provide insight into the effectiveness of the proposed computer-controlled therapy. Results—No test group individual developed IMC within 1 h, whereas all control group individuals did (4/6 within30 min). Conclusion—Automatic dosing of hemodynamic drugs in the controlled DCD context has the potential to prevent onset of IMC up to 1 h, enabling ethical and medically safe organ procurement. This has the potential to increase the use of DCD heart transplantation, which has been widely recognized as a means of meeting the growing demand for donor hearts.
|
|
| 8. |
- Christierson, Lea, et al.
(författare)
-
Multi-Modal in Vitro Experiments Mimicking the Flow Through a Mitral Heart Valve Phantom
-
Ingår i: Cardiovascular Engineering and Technology. - 1869-408X.
-
Tidskriftsartikel (refereegranskat)abstract
- Purpose: Fluid-structure interaction (FSI) models are more commonly applied in medical research as computational power is increasing. However, understanding the accuracy of FSI models is crucial, especially in the context of heart valve disease in patient-specific models. Therefore, this study aimed to create a multi-modal benchmarking data set for cardiac-inspired FSI models, based on clinically important parameters, such as the pressure, velocity, and valve opening, with an in vitro phantom setup. Method: An in vitro setup was developed with a 3D-printed phantom mimicking the left heart, including a deforming mitral valve. A range of pulsatile flows were created with a computer-controlled motor-and-pump setup. Catheter pressure measurements, magnetic resonance imaging (MRI), and echocardiography (Echo) imaging were used to measure pressure and velocity in the domain. Furthermore, the valve opening was quantified based on cine MRI and Echo images. Result: The experimental setup, with 0.5% cycle-to-cycle variation, was successfully built and six different flow cases were investigated. Higher velocity through the mitral valve was observed for increased cardiac output. The pressure difference across the valve also followed this trend. The flow in the phantom was qualitatively assessed by the velocity profile in the ventricle and by streamlines obtained from 4D phase-contrast MRI. Conclusion: A multi-modal set of data for validation of FSI models has been created, based on parameters relevant for diagnosis of heart valve disease. All data is publicly available for future development of computational heart valve models.
|
|
