Computational fluid dynamics using in vivo ultrasound blood flow measurements

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2012

Documents

View graph of relations

This paper presents a model environment for construction of patient-specific computational fluid dynamic (CFD) models for the abdominal aorta (AA). Realistic pulsatile velocity waveforms are employed by using in vivo ultrasound blood flow measurements. Ultrasound is suitable for acquisition of blood
velocity profiles, but these are influenced by noise, which will cause convergence problems in CFD simulations. Therefore, physiological smoothing of the velocity profiles is needed. This paper uses the Womersley-Evans model for physiological smoothing of measured blood velocity profiles in the AA. The geometry for the CFD simulation model was obtained by segmentation of MRI scans using a 3 Tesla scanner (Magnetom Trio, Siemens Healthcare, Erlangen, Germany). Spectral velocity data were obtained from a BK Medical ProFocus scanner using a research interface. All data were obtained from healthy volunteers. The estimated and smoothed velocity profiles were quantitatively compared. The energy contained in the velocity profile after smoothing is 65% larger relative to the noise contaminated estimated profiles. In conclusion, a model environment that produces realistic patient-specific CFD simulation models without
convergence issues has been developed. The data processing for the model environment can be performed within six hours which is fast enough to be used in the clinical setting.
Original languageEnglish
Title of host publicationProceedings of IEEE International Ultrasonics Symposium
Number of pages4
PublisherIEEE
Publication date2012
StatePublished

Conference

Conference2012 IEEE International Ultrasonics Symposium
CountryGermany
CityDresden
Period07/10/1210/10/12
Internet addresshttps://ius2012.ifw-dresden.de
Download as:
Download as PDF
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
PDF
Download as HTML
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
HTML
Download as Word
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
Word

Download statistics

No data available

ID: 12344800