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1.
J Clin Med ; 10(19)2021 Sep 24.
Artigo em Inglês | MEDLINE | ID: mdl-34640371

RESUMO

Deficits in maximal and explosive knee extensor strength, which are usually assessed with unilateral tasks, are substantial in patients with knee osteoarthritis (KOA). The aim of this study was to investigate the clinical relevance of unilateral vs. bilateral tasks for assessing knee extensor strength in patients with KOA. This was achieved primarily by comparing unilateral and bilateral inter-limb strength asymmetries and secondarily by examining the relationship between unilaterally and bilaterally measured strength, and performance-based and self-reported function. Twenty-four patients with unilateral KOA (mean age: 65 ± 7 years) performed isometric gradual and explosive maximal voluntary contractions to assess, respectively their maximal and explosive strength. Performance-based and self-reported function were also evaluated with standard functional tests and questionnaires, respectively. Inter-limb asymmetries of maximal and explosive strength did not differ significantly between unilateral (mean asymmetry: 26 ± 15%) and bilateral tasks (22 ± 21%). In the same way, the relationships between knee extensor strength-measured either unilaterally or bilaterally-and performance-based or self-reported function were not influenced by the type of task. In conclusion, it does not seem to make a difference in terms of clinical relevance whether maximal and explosive knee extensor strength are evaluated with unilateral or bilateral tasks in KOA patients.

2.
Front Cardiovasc Med ; 8: 804565, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-35097022

RESUMO

The development of turbulence after transcatheter aortic valve (TAV) implantation may have detrimental effects on the long-term performance and durability of the valves. The characterization of turbulent flow generated after TAV implantation can provide fundamental insights to enhance implantation techniques. A self-expandable TAV was tested in a pulse replicator and the three-dimensional flow field was extracted by means of tomographic particle image velocimetry. The valve was fixed inside a silicone phantom mimicking the aortic root and the flow field was studied for two different supra-annular axial positions at peak systole. Fluctuating velocities and turbulent kinetic energy were compared between the two implantations. Velocity spectra were derived at different spatial positions in the turbulent wakes to characterize the turbulent flow. The valve presented similar overall flow topology but approximately 8% higher turbulent intensity in the lower implantation. In this configuration, axial views of the valve revealed smaller opening area and more corrugated leaflets during systole, as well as more accentuated pinwheeling during diastole. The difference arose from a lower degree of expansion of the TAV's stent inside the aortic lumen. These results suggest that the degree of expansion of the TAV in-situ is related to the onset of turbulence and that a smaller and less regular opening area might introduce flow instabilities that could be detrimental for the long-term performance of the valve. The present study highlights how implantation mismatches may affect the structure and intensity of the turbulent flow in the aortic root.

3.
PLoS Comput Biol ; 15(6): e1007079, 2019 06.
Artigo em Inglês | MEDLINE | ID: mdl-31206515

RESUMO

The multiple-breath washout (MBW) is a lung function test that measures the degree of ventilation inhomogeneity (VI). The test is used to identify small airway impairment in patients with lung diseases like cystic fibrosis. However, the physical and physiological factors that influence the test outcomes and differentiate health from disease are not well understood. Computational models have been used to better understand the interaction between anatomical structure and physiological properties of the lung, but none of them has dealt in depth with the tracer gas washout test in a whole. Thus, our aim was to create a lung model that simulates the entire MBW and investigate the role of lung morphology and tissue mechanics on the tracer gas washout procedure. To this end, we developed a multi-scale lung model to simulate the inert gas transport in airways of all size. We then applied systematically different modifications to geometrical and mechanical properties of the lung model (compliance, residual airway volume and flow resistance) which have been associated with VI. The modifications were applied to distinct parts of the model, and their effects on the gas distribution within the lung and on the gas concentration profile were assessed. We found that variability in compliance and residual volume of the airways, as well as the spatial distribution of this variability in the lung had a direct influence on gas distribution among airways and on the MBW pattern (washout duration, characteristic concentration profile during each expiration), while the effects of variable flow resistance were negligible. Based on these findings, it is possible to classify different types of inhomogeneities in the lung and relate them to specific features of the MBW pattern, which builds the basis for a more detailed association of lung function and structure.


Assuntos
Pulmão/fisiologia , Modelos Biológicos , Troca Gasosa Pulmonar/fisiologia , Testes de Função Respiratória , Adolescente , Biologia Computacional , Feminino , Humanos , Pneumopatias/fisiopatologia , Masculino
4.
PLoS One ; 13(3): e0194384, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29547668

RESUMO

The flow field past a prosthetic aortic valve comprises many details that indicate whether the prosthesis is functioning well or not. It is, however, not yet fully understood how an optimal flow scenario would look, i.e. which subtleties of the fluid dynamics in place are essential regarding the durability and compatibility of a prosthetic valve. In this study, we measured and analyzed the 3D flow field in the vicinity of a bio-prosthetic heart valve in function of the aortic root size. The measurements were conducted within aortic root phantoms of different size, mounted in a custom-built hydraulic setup, which mimicked physiological flow conditions in the aorta. Tomographic particle image velocimetry was used to measure the 3D instantaneous velocity field at various instances. Several 3D fields (e.g. instantaneous and mean velocity, 3D shear rate) were analyzed and compared focusing on the impact of the aortic root size, but also in order to gain general insight in the 3D flow structure past the bio-prosthetic valve. We found that the diameter of the aortic jet relative to the diameter of the ascending aorta is the most important parameter in determining the characteristics of the flow. A large aortic cross-section, relative to the cross-section of the aortic jet, was associated with higher levels of turbulence intensity and higher retrograde flow in the ascending aorta.


Assuntos
Aorta/fisiopatologia , Valva Aórtica/fisiopatologia , Bioprótese , Próteses Valvulares Cardíacas , Algoritmos , Aorta/patologia , Valva Aórtica/patologia , Velocidade do Fluxo Sanguíneo , Humanos , Imageamento Tridimensional/métodos , Modelos Cardiovasculares , Fluxo Pulsátil , Reologia/instrumentação , Reologia/métodos
5.
Interact Cardiovasc Thorac Surg ; 27(1): 108-115, 2018 07 01.
Artigo em Inglês | MEDLINE | ID: mdl-29481667

RESUMO

OBJECTIVES: Bioprosthetic valve thrombosis has been considered uncommon, but recent studies have shown that it is more frequent than previously thought. Insufficient washout of the aortic sinus is believed to be a risk factor for bioprosthetic valve thrombosis. The objective of this in vitro experiment was to investigate the impact of aortic root morphology on blood flow in the aortic sinus and to relate these results to in vivo data obtained in patients with a transcatheter aortic valve implant. METHODS: Two compliant aortic root phantoms with different morphologies (symmetrical and patient-specific) were fabricated with silicone. A bioprosthetic aortic valve was inserted in both phantoms. Haemodynamic measurements were performed in a pulsatile flow-loop replicating physiological flow and pressure conditions. The flow in the aortic root was visualized by injecting contrast agent (CA). The distribution of the CA was captured by a high-speed camera, and image post-processing was performed to quantify CA distribution in the aortic sinus. The results were compared with angiographic images after a transcatheter aortic valve implant. RESULTS: Blood flow in the aortic root and the washout of the sinus portion are significantly affected by aortic root morphology. CA arrives at the aortic sinus of the 2 phantoms at 0.09 s and 0.16 s after the valve opens in the symmetrical and the patient-specific phantoms, respectively. Delayed CA arrival was also observed in the patients with a transcatheter aortic valve implant. CONCLUSIONS: Aortic root morphology affects the blood flow in the aortic sinus and may be a factor in bioprosthetic valve thrombosis. Therefore, patient-specific aortic root morphology should be considered when selecting and positioning a prosthesis.


Assuntos
Valva Aórtica/patologia , Bioprótese , Próteses Valvulares Cardíacas , Trombose/etiologia , Substituição da Valva Aórtica Transcateter/instrumentação , Hemodinâmica , Humanos , Modelos Cardiovasculares , Seio Aórtico/fisiopatologia , Trombose/patologia , Trombose/fisiopatologia , Substituição da Valva Aórtica Transcateter/efeitos adversos
6.
IEEE Trans Pattern Anal Mach Intell ; 34(2): 225-39, 2012 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-21670479

RESUMO

We propose a new learning strategy for object detection. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, and instead learns a single classifier that has the inherent ability to deform based on the signal of interest. We train a detector with a standard AdaBoost procedure by using combinations of pose-indexed features and pose estimators. This allows the learning process to select and combine various estimates of the pose with features able to compensate for variations in pose without the need to label data for training or explore the pose space in testing. We validate our framework on three types of data: hand video sequences, aerial images of cars, and face images. We compare our method to a standard boosting framework, with access to the same ground truth, and show a reduction in the false alarm rate of up to an order of magnitude. Where possible, we compare our method to the state of the art, which requires pose annotations of the training data, and demonstrate comparable performance.

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