Hemodynamics of collapsible vessels with tone: the vascular waterfall

Permutt, Solbert; Riley, R. L.

doi:10.1152/jappl.1963.18.5.924

Cited by 510 publications

(231 citation statements)

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“…6 Studies of other organs have shown that the EDP can be determined by a Starling resistor located at arteriolar level. 38 These studies verified the theory of Permutt and Riley 39 showing that two forces, the extramural pressure (ICP in the case of the brain) and arteriolar wall tension determine CCP. Arteriolar wall tension arises from a combination of the stretched elastic components of the vessel wall and active contraction of vascular smooth muscle.…”

Section: Discussionsupporting

confidence: 68%

Carbon Dioxide Induced Changes in Cerebral Blood Flow and Flow Velocity: Role of Cerebrovascular Resistance and Effective Cerebral Perfusion Pressure

Grüne

Kazmaier

Stolker

et al. 2015

J Cereb Blood Flow Metab

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In addition to cerebrovascular resistance (CVR) zero flow pressure (ZFP), effective cerebral perfusion pressure (CPPe) and the resistance area product (RAP) are supplemental determinants of cerebral blood flow (CBF). Until now, the interrelationship of PaCO 2 -induced changes in CBF, CVR, CPPe, ZFP, and RAP is not fully understood. In a controlled crossover trial, we investigated 10 anesthetized patients aiming at PaCO 2 levels of 30, 37, 43, and 50 mm Hg. Cerebral blood flow was measured with a modified Kety-Schmidt-technique. Zero flow pressure and RAP was estimated by linear regression analysis of pressure-flow velocity relationships of the middle cerebral artery. Effective cerebral perfusion pressure was calculated as the difference between mean arterial pressure and ZFP, CVR as the ratio CPPe/CBF. Statistical analysis was performed by one-way RM-ANOVA. When comparing hypocapnia with hypercapnia, CBF showed a significant exponential reduction by 55% and mean V MCA by 41%. Effective cerebral perfusion pressure linearly decreased by 17% while ZFP increased from 14 to 29 mm Hg. Cerebrovascular resistance increased by 96% and RAP by 39%; despite these concordant changes in mean CVR and Doppler-derived RAP correlation between these variables was weak (r = 0.43). In conclusion, under general anesthesia hypocapnia-induced reduction in CBF is caused by both an increase in CVR and a decrease in CPPe, as a consequence of an increase in ZFP.

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Section: Discussionsupporting

confidence: 68%

Carbon Dioxide Induced Changes in Cerebral Blood Flow and Flow Velocity: Role of Cerebrovascular Resistance and Effective Cerebral Perfusion Pressure

Grüne

Kazmaier

Stolker

et al. 2015

J Cereb Blood Flow Metab

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“…Mathematical modeling of the respiratory system has been crucial to the development and advancement of a quantitative understanding of lung physiology in general, and mechanics in particular (2,(60)(61)(62). This approach has become increasingly important with the explosion of information at the cellular and molecular levels, and the integration of quantitative models of physiology at multiple scales and for multiple organ systems is the goal of the International Union of Physiological Sciences Physiome Project (63,64).…”

Section: Image-based Modelingmentioning

confidence: 99%

Computed Tomography Studies of Lung Mechanics

Simon

Christensen²,

Low³

et al. 2005

Proceedings of the American Thoracic Society

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The study of lung mechanics has progressed from global descriptions of lung pressure and volume relationships to the highresolution, three-dimensional, quantitative measurement of dynamic regional mechanical properties and displacements. X-ray computed tomography (CT) imaging is ideally suited to the study of regional lung mechanics in intact subjects because of its high spatial and temporal resolution, correlation of functional data with anatomic detail, increasing volumetric data acquisition, and the unique relationship between CT density and lung air content. This review presents an overview of CT measurement principles and limitations for the study of regional mechanics, reviews some of the early work that set the stage for modern imaging approaches and impacted the understanding and management of patients with acute lung injury, and presents evolving novel approaches for the analysis and application of dynamic volumetric lung image data. Keywords: computed tomography; mathematical modeling; physiologyThe phenomena covered by the word "respiration" are very diverse. When a person is seen to breathe, what is observed is a movement of the chest and abdomen by which air is alternately drawn into his lungs and again expelled. This constitutes the mechanical aspect of respiration.-August Krogh, 1941 In the 60-odd years since A. Krogh (1) opened his treatise on the comparative physiology of respiration with these words, an enormous amount of work has explored the relationship between lung expansion or deformation and the forces that drive such changes. Most recently, advances in imaging techniques have extended the study of lung mechanical behavior to the regional level, and currently evolving technologies permit the threedimensional characterization of dynamic lung volume changes in intact subjects. X-ray computed tomography (CT), because of its speed, widespread availability, high-resolution anatomic visualization, and unique ability to quantify regional air and tissue volumes, provides a particularly powerful tool for the noninvasive measurement of lung mechanics in experimental models as well as human subjects. This review presents relevant CT measurement principles for regional mechanics, presents examples of static and dynamic approaches to lung mechanics, and emphasizes some exciting and promising new high-resolution, vol-

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“…Various analogies can be used when teaching the interaction between cardiac output, venous return, arterial pressure, and oxygen delivery. [1][2][3] However, students may still be confused when they try to integrate these analogies into a single comprehensive mental model. Herein, we propose an ''advance organizer'', namely, gardening to teach hemodynamics to medical students.…”

Section: To the Editormentioning

confidence: 99%