Literature DB >> 11144667

Indicator dilution methods for measuring blood flow, volume, and other properties of biological systems: a brief history and memoir.

K Zierler1.   

Abstract

In 1824 Hering introduced an indicator-dilution method for measuring blood velocity. Not until 1897 was the method extended by Stewart to measure blood (volume) flow. For more than two decades, beginning in 1928, Hamilton and colleagues measured blood flow, including cardiac output. They proposed that the first-passsage indicator concentration-time curve could be recovered from observed curves that included recirculation by semilogarithmic extrapolation of the early downslope. Others followed with attempts to fit the complete first-passage curve by various forms, such as by the sum of three exponential terms (three well-stirred compartments in series). Stephenson (1948) thought of looking at indicator-dilution curves as convolutions of indicator input with a probability density function of traversal times through the system. Meier and I reached a similar conclusion, and extended it. The fundamental notion is that there exists a probability density function of transit times, h(t), through the system. We proved that mean transit time t= V/F, where V is volume in which the indicator is distributed. Thus, V, F, and t might all be calculated, or r alone might suffice if one wanted only to know relative blood flow. I extended the analysis to include residue detection of indicator remaining in the system, so that V, F, and could be calculated by external monitoring. Chinard demonstrated the value of simultaneous multiple indicator-dilution curves with various volumes of distribution. Goresky extended the technique to study cell uptake and metabolism. He also found a transform of indicator-dilution output curves (equivalent to multiplying the ordinate by tand dividing the time by t) which made congruent the family of unalike curves obtained by simultaneous injection of indicators with different volumes of distribution. Bassingthwaighte showed the same congruency with the transform of outputs of a single indicator introduced into a system with experimentally varied blood flows. We showed the same congruency for the pulmonary circulation, adding a correction for delays. Success of these transforms suggests that the architecture of the vascular network is a major determinant of the shape of density functions of transit times through the system, and that there is in this architecture, a high degree of self-similarity, implying that the fractal power function is a component in shaping the observed density of transit times. I proposed that the distribution of capillary critical opening pressures, which describes recruitment of vascular paths, may be important in shaping indicator-dilution curves, and that h(t) may be derived from flow-pressure and volume-pressure curves under some circumstances.

Entities:  

Mesh:

Year:  2000        PMID: 11144667     DOI: 10.1114/1.1308496

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  33 in total

1.  Coronary artery calcification and myocardial perfusion in asymptomatic adults: the MESA (Multi-Ethnic Study of Atherosclerosis).

Authors:  Lu Wang; Michael Jerosch-Herold; David R Jacobs; Eyal Shahar; Robert Detrano; Aaron R Folsom
Journal:  J Am Coll Cardiol       Date:  2006-08-17       Impact factor: 24.094

2.  Analysis of the influence of 4D MR angiography temporal resolution on time-to-peak estimation error for different cerebral vessel structures.

Authors:  N D Forkert; T Illies; D Möller; H Handels; D Säring; J Fiehler
Journal:  AJNR Am J Neuroradiol       Date:  2012-05-03       Impact factor: 3.825

3.  Measurement of cardiac output by use of noninvasively measured transient hemodilution curves with photoacoustic technology.

Authors:  Dongyel Kang; Qiaojian Huang; Youzhi Li
Journal:  Biomed Opt Express       Date:  2014-04-07       Impact factor: 3.732

4.  Modeling nonsteady-state metabolism from arteriovenous data.

Authors:  Erica Manesso; Gianna M Toffolo; Rita Basu; Robert A Rizza; Claudio Cobelli
Journal:  IEEE Trans Biomed Eng       Date:  2010-12-03       Impact factor: 4.538

5.  Dynamic CT Myocardial Perfusion Imaging: Detection of Ischemia in a Porcine Model with FFR Verification.

Authors:  Rachid Fahmi; Brendan L Eck; Mani Vembar; Hiram G Bezerra; David L Wilson
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2014-03-13

Review 6.  Quantification of myocardial perfusion by cardiovascular magnetic resonance.

Authors:  Michael Jerosch-Herold
Journal:  J Cardiovasc Magn Reson       Date:  2010-10-08       Impact factor: 5.364

7.  Stochasticity of flow through microcirculation as a regulator of oxygen delivery.

Authors:  Viktor V Kislukhin
Journal:  Theor Biol Med Model       Date:  2010-07-09       Impact factor: 2.432

8.  Hemodynamic effects of developmental venous anomalies with and without cavernous malformations.

Authors:  A Sharma; G J Zipfel; C Hildebolt; C P Derdeyn
Journal:  AJNR Am J Neuroradiol       Date:  2013-04-18       Impact factor: 3.825

9.  Predictive Modeling and Integrative Physiology: The Physiome Projects.

Authors:  James B Bassingthwaighte
Journal:  Open Pacing Electrophysiol Ther J       Date:  2010

Review 10.  Coronary microvascular resistance: methods for its quantification in humans.

Authors:  Paul Knaapen; Paolo G Camici; Koen M Marques; Robin Nijveldt; Jeroen J Bax; Nico Westerhof; Marco J W Götte; Michael Jerosch-Herold; Heinrich R Schelbert; Adriaan A Lammertsma; Albert C van Rossum
Journal:  Basic Res Cardiol       Date:  2009-05-26       Impact factor: 17.165

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.