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Proposal of New Tracer Concentration Model in Lung PCT Study Comparison with Commonly Used Gamma-variate Model
Abstrakt
Perfusion computed tomography (pCT) is one of the methods that enable non-invasive imaging of the hemodynamics of organs and tissues. On the basis of pCT measurements, perfusion parameters such as blood flow (BF), blood volume (BV), mean transit time (MTT) and permeability surface (PS) are calculated and then used for quantitative evaluation of the tissue condition. To calculate perfusion parameters it is necessary to approximate concentration-time curves using regression function. In this paper we compared three regression functions: first commonly used gamma-variate function, second and third Gauss and Rayleigh functions, not previously used for this purpose. The Gauss function showed clear advantage over the others when considering results of simulated data analysis. Actual measurements analysis confirmed conclusions from simulated data analysis. It was showed that contrary to widely accepted belief, the differences between rising and falling edge slope angles of concentration-time curves are inconsiderable. For that reason, it can be assumed that rising and falling edges are symmetrical. The main conclusion is that the Gauss function gives a more robust fit than the widely used gamma-variate function when modelling concentration-time curves in lung pCT studies.
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- Accepted albo Published Version
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Informacje szczegółowe
- Kategoria:
- Aktywność konferencyjna
- Typ:
- materiały konferencyjne indeksowane w Web of Science
- Tytuł wydania:
- PROCEEDINGS OF THE 10TH INTERNATIONAL JOINT CONFERENCE ON BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES, VOL 4: BIOSIGNALS strony 134 - 140
- Język:
- angielski
- Rok wydania:
- 2017
- Opis bibliograficzny:
- Browarczyk M., Kalicka R., Lipiński S..: Proposal of New Tracer Concentration Model in Lung PCT Study Comparison with Commonly Used Gamma-variate Model, W: PROCEEDINGS OF THE 10TH INTERNATIONAL JOINT CONFERENCE ON BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES, VOL 4: BIOSIGNALS, 2017, Science and Technology Publications, Lda,.
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.5220/0006115101340140
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 88 razy