Integrated physiological flow simulator and pulse sequence monitoring system for MRI

Wong, Pauline; Graves, Martin J.; Lomas, David J.

doi:10.1007/s11517-008-0319-x

Cited by 13 publications

(9 citation statements)

References 12 publications

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“…Plewes et al [11] had a RMS error that was as high as 20% on the first iteration, but improved to less than 1% over 15 iterations for a 2-Hz sinusoidal waveform. Wong et al [14] were able to achieve aortic flow waveforms with a normalized cross correlations of 0.94 after the use of the pre-compensation scheme. For a system without any feedback correction, the pump system is capable of replicating physiological waveforms.…”

Section: Discussionmentioning

confidence: 99%

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Flow pumping system for physiological waveforms

Tsai

Savaş

2010

Med Biol Eng Comput

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A pulsatile flow pumping system is developed to replicate flow waveforms with reasonable accuracy for experiments simulating physiological blood flows at numerous points in the body. The system divides the task of flow waveform generation between two pumps: a gear pump generates the mean component and a piston pump generates the oscillatory component. The system is driven by two programmable servo controllers. The frequency response of the system is used to characterize its operation.The system has been successfully tested in vascular flow experiments where sinusoidal, carotid, and coronary flow waveforms are replicated.

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Section: Discussionmentioning

confidence: 99%

“…While Plewes' pump is simpler than the dualchamber pump, it requires electronics to carry out initial iterative calibration adjustments for each new waveform. Wong et al [14] modified the design by introducing a software feedback loop using real-time velocity feedback from MRI scans.…”

Section: Introductionmentioning

confidence: 99%

Flow pumping system for physiological waveforms

Tsai

Savaş

2010

Med Biol Eng Comput

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“…This offers numerous advantages, such as the ability to pre-validate experimental prototypes before their use in the real world. In the case of the absence of infrastructure, computer simulations involving multiple variables in the healthcare area [104][105][106][107][108][109][110][111][112][113][114][115][116] play a key role. They can simulate different activity trends based on heterogeneous parameters (e.g., age, education, seasons, etc.)…”

Section: Actimetry For Chronic Patients At Homementioning

confidence: 99%

Smart Homes and Sensors for Surveillance and Preventive Education at Home: Example of Obesity

et al. 2016

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Abstract:(1) Background: The aim of this paper is to show that e-health tools like smart homes allow the personalization of the surveillance and preventive education of chronic patients, such as obese persons, in order to maintain a comfortable and preventive lifestyle at home. (2) Technologies and methods: Several types of sensors allow coaching the patient at home, e.g., the sensors recording the activity and monitoring the physiology of the person. All of this information serves to personalize serious games dedicated to preventive education, for example in nutrition and vision. (3) Results: We built a system of personalized preventive education at home based on serious games, derived from the feedback information they provide through a monitoring system. Therefore, it is possible to define (after clustering and personalized calibration) from the at home surveillance of chronic patients different comfort zones where their behavior can be estimated as normal or abnormal and, then, to adapt both alarm levels for surveillance and education programs for prevention, the chosen example of application being obesity.

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“…The tube was integrated into an existing physiological flow simulator as described by Wong et al (24). The two ends of the PVA-C tube were clamped to the inlet and outlet of a Perspex box, which was filled with water to produce MR signal outside the vessel model and avoid susceptibility artifacts caused by interfaces with air.…”

Section: Accuracy Experimentsmentioning

confidence: 99%

Accuracy and repeatability of fourier velocity encoded M‐mode and two‐dimensional cine phase contrast for pulse wave velocity measurement in the descending aorta

Taviani

Patterson

Graves

et al. 2010

Magnetic Resonance Imaging

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Purpose: To assess the accuracy and repeatability of Fourier velocity encoded (FVE) M-mode and two-dimensional (2D) phase contrast with through-plane velocity encoding (2D-PC) for pulse wave velocity (PWV) evaluation in the descending aorta using five different analysis techniques. Materials and Methods:Accuracy experiments were conducted on a tubular human-tissue-mimicking phantom integrated into a flow simulator. The theoretical PWV value was derived from the Moens-Korteweg equation after measurement of the tube elastic modulus by uniaxial tensile testing (PWV ¼ 6.6 6 0.7 m/s). Repeatability was assessed on 20 healthy volunteers undergoing three consecutive MR examinations.Results: FVE M-mode PWV was more repeatable than 2D-PC PWV independently of the analysis technique used. The early systolic fit (ESF) method, followed by the maximum of the first derivative (1st der.) method, was the most accurate (PWV ¼ 6.8 6 0.4 m/s and PWV ¼ 7.0 6 0.6 m/s, respectively) and repeatable (inter-scan withinsubject variation d ¼ 0.096 and d ¼ 0.107, respectively) for FVE M-mode. For 2D-PC, the 1st der. method performed best in terms of accuracy (PWV ¼ 6.8 6 1.1 m/s), whereas the ESF algorithm was the most repeatable (d ¼ 0.386).Conclusion: FVE M-mode allows rapid, accurate and repeatable central PWV evaluation when the ESF algorithm is used. 2D-PC requires long scan times and can provide accurate although much less repeatable PWV measurements when the 1st der. method is used.

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Integrated physiological flow simulator and pulse sequence monitoring system for MRI

Cited by 13 publications

References 12 publications

Flow pumping system for physiological waveforms

Flow pumping system for physiological waveforms

Smart Homes and Sensors for Surveillance and Preventive Education at Home: Example of Obesity

Accuracy and repeatability of fourier velocity encoded M‐mode and two‐dimensional cine phase contrast for pulse wave velocity measurement in the descending aorta

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