Patient-individual local SAR determination: In vivo measurements and numerical validation

2011 ◽  
Vol 68 (4) ◽  
pp. 1117-1126 ◽  
Author(s):  
T. Voigt ◽  
H. Homann ◽  
U. Katscher ◽  
O. Doessel
Keyword(s):  
Numerical Validation ◽  
In Vivo Measurements ◽  
Local Sar

scholarly journals Simulating a Ground Truth for Transit Time Analysis of Indicator Dilution Curves

2020 ◽  
Vol 6 (3) ◽  
pp. 268-271
Author(s):  
Michael Reiß ◽  
Ady Naber ◽  
Werner Nahm
Keyword(s):  
Transit Time ◽  
Sampling Rate ◽  
Ground Truth ◽  
Indicator Dilution ◽  
Cross Sectional ◽  
In Vivo Measurements ◽  
Multiple Indicator Dilution ◽  
Transit Times ◽  
Dilution Curves

AbstractTransit times of a bolus through an organ can provide valuable information for researchers, technicians and clinicians. Therefore, an indicator is injected and the temporal propagation is monitored at two distinct locations. The transit time extracted from two indicator dilution curves can be used to calculate for example blood flow and thus provide the surgeon with important diagnostic information. However, the performance of methods to determine the transit time Δt cannot be assessed quantitatively due to the lack of a sufficient and trustworthy ground truth derived from in vivo measurements. Therefore, we propose a method to obtain an in silico generated dataset of differently subsampled indicator dilution curves with a ground truth of the transit time. This method allows variations on shape, sampling rate and noise while being accurate and easily configurable. COMSOL Multiphysics is used to simulate a laminar flow through a pipe containing blood analogue. The indicator is modelled as a rectangular function of concentration in a segment of the pipe. Afterwards, a flow is applied and the rectangular function will be diluted. Shape varying dilution curves are obtained by discrete-time measurement of the average dye concentration over different cross-sectional areas of the pipe. One dataset is obtained by duplicating one curve followed by subsampling, delaying and applying noise. Multiple indicator dilution curves were simulated, which are qualitatively matching in vivo measurements. The curves temporal resolution, delay and noise level can be chosen according to the requirements of the field of research. Various datasets, each containing two corresponding dilution curves with an existing ground truth transit time, are now available. With additional knowledge or assumptions regarding the detection-specific transfer function, realistic signal characteristics can be simulated. The accuracy of methods for the assessment of Δt can now be quantitatively compared and their sensitivity to noise evaluated.

In vivo measurements of glenohumeral distraction technique performed in three different joint positions

2021 ◽  
pp. 1-7
Author(s):  
Diego Guerra-Rodríguez ◽  
Liliana Rozo ◽  
Daniel Basilio ◽  
Juan Guerrero-Henriquez
Keyword(s):  
In Vivo Measurements

In Vivo Measurements On Human Lens Using Quasielastic Light Scattering

1987 ◽  
Author(s):  
Peter C. Magnante ◽  
Leo T. Chylack ◽  
George B. Benedek ◽  
Teodosio Libondi ◽  
Stephen N. Joffe ◽  
...  
Keyword(s):  
Light Scattering ◽  
Human Lens ◽  
Quasielastic Light Scattering ◽  
In Vivo Measurements

Numerical simulation of humidification and heating during inspiration within an adult nose

2012 ◽  
Vol 50 (2) ◽  
pp. 157-164
Author(s):  
F. Sommer ◽  
R. Kroger ◽  
J. Lindemann
Keyword(s):  
Numerical Simulations ◽  
High Speed ◽  
Middle Turbinate ◽  
Multislice Ct ◽  
Respiratory Cycle ◽  
In Vivo Measurements ◽  
Airflow Distribution ◽  
The Impact ◽  
Human Nose

Background: The temperature of inhaled air is highly relevant for the humidification process. Narrow anatomical conditions limit possibilities for in vivo measurements. Numerical simulations offer a great potential to examine the function of the human nose. Objective: In the present study, the nasal humidification of inhaled air was simulated simultaneously with temperature distribution during a respiratory cycle. Methods: A realistic nose model based on a multislice CT scan was created. The simulation was performed by the Software Fluent(r). Boundary conditions were based on previous in vivo measurements. Inhaled air had a temperature of 20(deg)C and relative humidity of 30%. The wall temperature was assumed to be variable from 34(deg)C to 30(deg)C with constant humidity saturation of 100% during the respiratory cycle. Results: A substantial increase in temperature and humidity can be observed after passing the nasal valve area. Areas with high speed air flow, e.g. the space around the turbinates, show an intensive humidification and heating potential. Inspired air reaches 95% humidity and 28(deg)C within the nasopharynx. Conclusion: The human nose features an enormous humidification and heating capability. Warming and humidification are dependent on each other and show a similar spacial pattern. Concerning the climatisation function, the middle turbinate is of high importance. In contrast to in vivo measurements, numerical simulations can explore the impact of airflow distribution on nasal air conditioning. They are an effective method to investigate nasal pathologies and impacts of surgical procedures.

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