AJP - Heart Fuel your research with LabChart
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Am J Physiol Heart Circ Physiol 288: H2504-H2511, 2005. First published December 16, 2004; doi:10.1152/ajpheart.00368.2004
0363-6135/05 $8.00
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
288/5/H2504    most recent
00368.2004v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (4)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Heerman, J. R.
Right arrow Articles by Poelaert, J. I.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Heerman, J. R.
Right arrow Articles by Poelaert, J. I.

Echocardiographic assessment of aortic elastic properties with automated border detection in an ICU: in vivo application of the arctangent Langewouters model

Jan R. Heerman,1 Patrick Segers,2 Carl D. Roosens,1 Frank Gasthuys,3 Pascal R. Verdonck,2 and Jan I. Poelaert1

1Intensive Care Department, Ghent University Hospital, 2Hydraulics Laboratory, Institute of Biomedical Technology, and 3Department of Surgery and Anesthesiology of Domestic Animals, Ghent University, Ghent, Belgium

Submitted 13 May 2004 ; accepted in final form 14 December 2004


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
We studied whether combined pressure and transesophageal ultrasound monitoring is feasible in the intensive care unit (ICU) setting for global cardiovascular hemodynamic monitoring [systemic vascular resistance (SVR) and total arterial compliance (CPPM)] and direct estimation of local ascending and descending aortic mechanical properties, i.e., distensibility and compliance coefficients (DC and CC). Pressure-area data were fitted to the arctangent Langewouters model, with aortic cross-sectional area obtained via automated border detection. Data were measured in 19 subjects at baseline, during infusion of sodium nitroprusside (SNP), and after washout. SNP infusion lowered SVR from 1.15 ± 0.40 to 0.80 ± 0.32 mmHg·ml–1·s (P < 0.05), whereas CPPM increased from 0.87 ± 0.46 to 1.02 ± 0.42 ml/mmHg (P < 0.05). DC and CC increased from 0.0018 ± 0.0007 to 0.0025 ± 0.0009 l/mmHg (P < 0.05) and from 0.0066 ± 0.0028 to 0.0083 ± 0.0026 cm2/mmHg (P < 0.05), respectively, at the descending, but not ascending, aorta. The Langewouters model fitted the descending aorta data reasonably well. Assessment of local mechanical properties of the human ascending aorta in a clinical setting by automated border detection remains technically challenging.

afterload; large artery function; nitroprusside; coronary artery bypass grafting; intensive care unit

LEFT VENTRICULAR SYSTOLIC function and cardiac output are determined by left ventricular preload, contractility, afterload, and heart rate (HR). Therefore, assessment of cardiovascular hemodynamic function should include these determinants. Transesophageal echocardiography is increasingly being used for patient monitoring in the operating room and intensive care unit (ICU). Interestingly, these patients often have a pressure catheter in the aorta for pressure monitoring. The simultaneous availability of ultrasound imaging modalities and intra-arterial pressure potentially allows for the online and in situ assessment of most determinants of cardiovascular function.

The main determinants of arterial afterload are systemic vascular resistance (SVR) and total arterial compliance, reflecting the steady and main pulsatile component of arterial load, respectively (18, 21, 24). Both are derived from aortic pressure and flow; therefore, they can be monitored in the clinical setting as described above.

In addition to the aforementioned global afterload parameters, transesophageal echocardiography in conjunction with arterial pressure monitoring has the potential to assess local mechanical characteristics of central vessels via the construction and analysis of pressure-area or pressure-diameter curves (3, 4). It is well established that large artery elastic dysfunction is an important cardiovascular risk factor (1, 28). Reduced arterial compliance leads to an increased systolic pressure and pulse pressure (PP) and, consequently, an increased load to the heart. Because >60% of the total arterial compliance resides in the ascending and thoracic aorta, determining the regional compliance of the thoracic aorta and its changes can be useful in determining left ventricular afterload with regard to the pulsatile nature of the circulation (15, 16, 34).

In this study, we aimed to obtain pressure and area data simultaneously. These data were then fitted to the so-called arctangent model described by Langewouters et al. (15, 16) to determine static and dynamic elastic properties of the thoracic aorta in vivo. To the best of our knowledge, this is the first time that the Langewouters model has been applied in vivo. To induce changes in elastic properties, we infused sodium nitroprusside (SNP), which is known to change elastic properties of the thoracic aorta. In this study, all analysis was done offline. The measurements were done at baseline (BL), after infusion of SNP, and after washout (WO) of SNP.


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Patients

The subject group consisted of postoperative patients after coronary artery bypass grafting. None of the patients suffered from any form of valvular pathology. The aortic valve was carefully examined for aortic valve area determination. Patients with minimal aortic insufficiency or stenosis (maximal pressure gradient >10 mmHg), as well as patients suffering from overt regional wall motion abnormalities or hemodynamic instability, were excluded. In the presence of symptomatic peripheral vascular disease, it was considered too dangerous to perform catheterization of the femoral artery with a wide-bore sheath; therefore, these patients were excluded. The institutional Ethics Committee on Human Research approved the study protocol, and written informed consent was obtained on the day before surgery in every case.

Data Acquisition

After the patients were admitted to the ICU, a sheath was introduced into the femoral artery, through which a 6-Fr fluid-filled pigtail catheter was advanced in the aorta for blood pressure measurements. Transesophageal echocardiography was performed with an omniplane 6-MHz echoprobe connected to an echocardiograph (Sonos 2500, Hewlett-Packard, Andover, MA). Positioning of the catheter was verified by means of echocardiography. Custom-made software (Vision Bloodflow) enabled simultaneous acquisition of echo images and blood pressure.

Recordings were made in three consecutive hemodynamic situations: 1) at BL, representing the postoperative hemodynamic condition of the patient, 2) after 20% reduction of mean arterial pressure by continuous infusion of SNP, and 3) after cessation of SNP infusion and restoration of mean blood pressure to BL levels or higher (WO).

Each recording sequence consisted of four images. 1) From a transgastric midpapillary short axis (26) plane, at least four beats were recorded simultaneously with blood pressure measurements at the level of the aortic valve. 2) With use of continuous-flow Doppler, blood flow over the aortic valve was acquired from a deep transgastric long-axis view (26) while blood pressure was recorded simultaneously in the proximal ascending aorta. 3) With use of automated border detection (also termed acoustic quantification), area changes of the ascending aorta in a midesophageal short-axis plane (26) were recorded. Acoustic quantification permits the automatic delineation of the aortic intima vs. blood. This technique was validated in humans in 1994 by Lang et al. (14). The pressure catheter was pulled back until it disappeared from the scanning plane to avoid interference with the area measurements. 4) By rotating the probe ~180°, without changing the depth of the probe, the descending aorta could be visualized. The tip of the probe was flipped up and down to ensure visualization of the minimal cross-sectional area of the descending aorta, measured with automated border detection. As a consequence, visualization occurred perpendicular to the long axis of the descending aorta. The area changes of the descending aorta in a short-axis plane (26) were again recorded by means of automated border detection. Blood pressure was recorded simultaneously after the catheter was pulled back until it disappeared from the imaging plane. All recordings were made in apnea to avoid respiratory variation of stroke volume (SV) and blood pressure. All patients were curarized with cis-atracurium (Nimbex) to ensure apnea. All data were stored in a spreadsheet file format for further offline analysis.

Data Analysis

Indexes derived from aortic pressure and flow data. Echographic data were saved as Windows bitmap files and analyzed offline with customized applications written in Matlab (Mathworks, Natick, MA). The bitmaps were calibrated using the time and velocity information displayed in the echocardiographic image, and maximal velocity contours were manually traced and resampled at 200 Hz to match the pressure-sampling frequency. The velocities were multiplied by the mean aortic valve cross-sectional area to obtain aortic flow or SV. These flow traces were then aligned in time with the simultaneously measured aortic pressure, with the onset of systolic upstroke used as a reference (23). Three successive beats were analyzed for the assessment of several arterial and heart-arterial interaction parameters.

Cardiac output was calculated as the product of SV and HR (10). SVR was calculated as the ratio of mean aortic pressure to mean aortic flow. Total arterial compliance was estimated using three methods: 1) as the ratio of SV to PP (CSV/PP), 2) by the PP method (CPPM) (34), and 3) by the area method: CAM = At(1) – t(2)/{SVR[P(t1) – P(t2)]} (17). The PP method is an iterative method (based on a 2-element windkessel model), where CPPM is modified until the PP that is predicted by the two-element windkessel model (with measured flow as an input) equals the measured PP (25). The area method uses the area under the diastolic portion of the pressure curve [At(1) – t(2)] between the first maximum after the aortic incisura (t1) and end systole (t2), with P(t1) and P(t2) representing the pressures at these moments (17). End-systolic pressure (Pes) was taken as the aortic pressure corresponding to the onset of the diastolic interval. Effective arterial elastance was calculated as Pes/SV (11). Furthermore, linear regression analysis on the linear portion of the early systolic pressure-flow relation yielded a pressure-flow (P-)-based estimate of aortic characteristic impedance [Z0(P-)] (6).

Indexes derived from aortic pressure and cross-sectional area data. Acoustic quantification data were saved as Windows bitmap files and analyzed offline with customized software written in Matlab (Fig. 1). The bitmaps were calibrated using the time and area information displayed in the image. After selection of a region of interest and binary conversion of the images, the area was automatically extracted from the image and resampled at 200 Hz. These area traces were then aligned with the simultaneously measured corresponding aortic pressure, with the onset of systolic upstroke used as a reference. This procedure was done for the data measured at the ascending and descending aorta.



View larger version (29K):
[in this window]
[in a new window]
  		Fig. 1. Area data extracted from the acoustic quantification image with use of customized software. Area and pressure data are aligned in time, area is plotted as a function of pressure, and the arctangent model of Langewouters is fitted through the data.

 
Systolic and diastolic cross-sectional areas (As and Ad) were given by the maximum and minimum aortic cross-sectional area. Compliance coefficient (CC) and distensibility coefficient (DC) were calculated as {Delta}A/PP (with {Delta}A = As – Ad) and ({Delta}A/Ad)/PP, respectively (24). The {beta} stiffness index was calculated as ln[(Ps/Pd)/({Delta}A/Ad)], where ln is the natural logarithm and Ps and Pd represent aortic systolic and diastolic pressure, respectively (8). Local characteristic impedance [Z0(P-A)] was derived from pressure-area (P-A) data as follows:

Local pulse wave velocity (PWV) was calculated as follows:

(19).

In addition to parameters based on systolic and diastolic dimensions alone, cross-sectional area was plotted as a function of pressure, yielding pressure-area loops. These data were fitted to the arctangent model as derived by Langewouters et al. (15, 16) to describe the mechanical characteristics of (in vitro) thoracic and abdominal aortas

where P is aortic pressure and Amax, P0, and P1 model parameters following from the curve-fitting procedure: Amax is the maximally attainable cross-sectional area, P0 is the aortic pressure where compliance is maximal, and P1 is a measure of compliance "band width"; i.e., at P0 ± P1, vessel compliance is reduced to 50% of its maximal value at P0, as described by Langewouters et al. (15, 16).

Parameters were derived for the ascending and descending aorta. For each location, at least three successive cardiac cycles were analyzed, and an average value was obtained per patient.

Statistical Analysis

Statistical analysis was achieved using a personal computer-based package (SPSS 10.0, SPSS, Chicago, IL). After assessment of the patients, a statistical power analysis was performed (see Table 3) (5). Values are means ± SD. All paired hemodynamic data were compared using repeated-measures ANOVA with post hoc polynomial contrasts and comparison of successive differences. Wilcoxon signed ranks test with Bonferroni's correction was applied to compare the results more closely. Statistical significance was accepted at P < 0.05.


View this table:
[in this window]
[in a new window]
  		Table 3. Regional mechanical properties of the ascending aorta

 
Linear regression analysis was performed using the Matlab "robustfit" linear regression algorithm, which gives lower weight to points that do not fit well, making the regression line less sensitive to outliers in the data than ordinary least-squares regression.


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 GRANTS
 REFERENCES
 
In total, 19 patients (15 men and 4 women) with a mean age of 62 ± 10 yr entered the study.

Indexes Derived From Aortic Pressure and Flow Data

There was a borderline increase in cardiac output and HR and a nonsignificant trend toward higher SV. All measures of blood pressure decreased significantly after infusion of SNP (Table 1).


View this table:
[in this window]
[in a new window]
  		Table 1. Global hemodynamic parameters

 
All results indicated a reduction of left ventricular afterload secondary to SNP infusion, as anticipated. SVR and Z0(P-) decreased as a result of SNP infusion, whereas total arterial compliance (for all 3 methods) increased. Arterial elastance, integrating the effects of HR, SVR, and total arterial compliance, decreased with SNP infusion (Table 2).


View this table:
[in this window]
[in a new window]
  		Table 2. Global characteristics of arterial load

 
Indexes Derived From Aortic Pressure and Cross-Sectional Area Data

Ascending aorta. There was considerable variability in all indexes derived for the ascending aorta, resulting only in nonsignificant trends toward a reduction in stiffness after SNP administration (Fig. 2). Changes of DC, CC, {beta} stiffness index, and Z0(P-A) induced by SNP infusion did not reach statistical significance (Table 3). Changes in PWV were borderline significant. The Langewouters model could be fitted to 38 of the 57 pressure-area traces (67%). However, model parameters could be assessed at BL, SNP, and WO for only five patients. For these patients, there was no statistically significant difference in Amax and P1 before, during, and after SNP infusion. The only parameter reaching statistical significance was P0 (P = 0.032), where the difference between SNP and WO was significantly different (Table 3). The pressure-area curves, constructed with these mean parameter values, are given in Fig. 3. SNP infusion shifts the pressure-area curves to the left.



View larger version (23K):
[in this window]
[in a new window]
  		Fig. 2. Distensibility (DC; A and B) and compliance coefficients (CC; C and D) measured at ascending and descending aortas. BL, baseline; SNP, sodium nitroprusside; WO, washout. +P < 0.05 vs. BL; *P < 0.05 vs. WO.

 


View larger version (24K):
[in this window]
[in a new window]
  		Fig. 3. Pressure-area (A and B) and pressure-compliance (C and D) curves constructed using the arctangent Langewouters model and average parameter values. SNP infusion shifts pressure-area curve to the left.

 
Descending aorta. In contrast to the ascending aorta, DC and CC increased with SNP infusion (Fig. 2): DC increased 39%, whereas CC increased 26% as a result of SNP infusion. The SNP-induced changes of the {beta} stiffness index did not reach statistical significance. Z0(P-A) decreased by 18% as a result of SNP infusion and increased again by 25% after WO, and PWV decreased by 15% after SNP infusion and increased again by 25% after WO (BL, SNP, and WO values differ significantly). Pressure-area data could be fit in 44 of 57 datasets (77%), and data were complete for 8 subjects. Amax was changed minimally after SNP infusion. P0 decreased by 35% after infusion of SNP and recovered during WO, and P1 increased by 100% secondary to SNP infusion. There was a trend toward a lower P0 (P = 0.06) and a higher P1 (P = 0.07) during SNP administration. Pressure-area and pressure-compliance traces, calculated with these average model parameters, are given in Fig. 3. For the ascending aorta, the pressure-area curve is shifted toward lower P0 values, with a clear widening of the compliance curve (Table 4).


View this table:
[in this window]
[in a new window]
  		Table 4. Regional mechanical properties of the descending aorta

 

   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
We have demonstrated that the combined use of the various imaging modalities of transesophageal echocardiography and intra-arterial pressure monitoring allows for quantification of most components of arterial load. In particular, the properties of the arterial system can be assessed with significant specificity for the descending aorta. The technique allows assessment of global arterial function parameters (SVR and total arterial compliance) as well as description of local pressure-area curves and derivation of structural and functional parameters quantifying large artery function after application of the arctangent model of arterial function as described by Langewouters et al. (15, 16).

Large artery function is the result of the organization and architecture of the arterial wall, which is composed of elastic and collagen fibers and smooth muscle cells. Arterial properties depend on arterial pressure in a nonlinear manner (2). Smooth muscle tone modulates these parameters. This pressure-dependent behavior generally complicates the interpretation of hemodynamic data, inasmuch as arterial function changes may simply be due to variations in arterial pressure. This is certainly the case in this study, where a vasodilator was used to induce hemodynamic changes. The interpretation of arterial compliance data is further complicated by the method-dependent results. We applied three well-known methods to estimate total arterial compliance. As reported in earlier studies, the area method yields significantly higher estimates than the PP method or the ratio of SV to PP, especially in conditions where wave reflections are low (25): during SNP infusion, CAM is more than three times higher than CPPM and about two times higher than CSV/PP (Table 2). In agreement with earlier findings, we found a close correlation between CSV/PP and CPPM (CSV/PP = 0.05 + 1.66CPPM, r2 = 0.976) (25).

The problems of interpretation of arterial compliance changes (i.e., compliance changes due to structural changes or pressure variations) are overcome with a direct and "continuous" measure (i.e., with properties known over a wide pressure range) of arterial compliance, such as obtained from pressure-area relations. These measurements and derived indexes (CC and DC) are well established for superficial arteries such as the carotid, radial, or femoral artery, where ultrasound techniques are combined with noninvasive pressure recordings (e.g., applanation tonometry) to construct pressure-diameter curves. It has been demonstrated in large population studies that carotid artery stiffness increases with age, in hypertension, and in patients with diabetes. Inasmuch as >60% of total arterial compliance resides in the proximal aorta, large area stiffness is probably best studied on the aorta (25).

The interpretation of pressure-area data may be facilitated by fitting the data to a biomechanical model, representing the data with a limited number of parameters. We fitted our measurements to the so-called arctangent model, which describes static and dynamic elastic properties of the human aorta (15, 16). This model, assessed on in vitro data measured on thoracic and abdominal aortas, has, to the best of our knowledge, not been used previously to study the aorta in vivo. The model could be fit to the data in 67% and 77% of the cases for the ascending and descending aorta, respectively. We could discriminate clearly between the different states utilizing Wilcoxon's signed ranks test with Bonferroni's correction. Overall, the model fitted the data very well, especially for the descending thoracic aorta data. Pressure-area data, constructed with average parameter values, are given in Fig. 3. Our results indicate that the increase in arterial compliance with SNP is only in part due to blood pressure-lowering effects. SNP shifts the pressure-diameter curve to lower pressures and changes the slope (i.e., the compliance) of the rising limb (Fig. 3). These effects are most likely due to an attenuation of smooth muscle tone by SNP. This also explains why the effect is predominantly seen at the descending aorta, where the smooth muscle content is higher than at the ascending aorta. After WO, the pressure-diameter curve shifts back to the right, but in our dataset, the slope has not yet fully returned to BL. It is possible that our WO period was too short. Also, the patients in the study are postoperative patients recovering in the ICU. It is expected that overall cardiac function improves with time, so that the condition attained after WO of SNP is probably different from BL.

Variations of elastic properties (DC and CC) with SNP infusion were most pronounced for the descending thoracic aorta. The difference in behavior between the two anatomic sites might be attributed to anatomic differences (smooth muscle cell contents) but also, in part, to the imaging difficulties of the short axis of the ascending aorta. Also, acoustic quantification is notoriously dependent on factors such as the gain of the acquired images, image quality, and plane of visualization. Even small changes can add considerable variability, particularly with respect to aortic area, because the measured changes are small. Certainly the window for visualizing the ascending aorta in the short axis is relatively small because of interference of bronchial structures, and the recent surgical procedure that these patients underwent could also be responsible for aggravating visualization. The cardiac movements in an environment that was recently surgically dissected are certainly more accentuated, making acoustic quantification of the ascending aorta short axis difficult, if not nearly impossible. Another common imaging difficulty was the temporary invasion of the region of interest by the adjacent superior caval vein and pulmonary artery, which made it even more demanding to provide reliable acoustic quantification of the ascending aorta in a short-axis image. These imaging difficulties probably contributed to the uncertainty associated with the ascending aorta data. Although the shape of the fitted pressure-area curve seems acceptable, the slope of the curve is very steep for the ascending aorta, and P1, indicating the compliance band width, is too low. The variability for all elasticity indexes is large for the ascending aorta, making the methodology rather unattractive from a statistical perspective. To illustrate this point, we performed a power analysis for DC and CC (Table 5). Given a pressure drop of 21 mmHg (difference between SNP infusion and WO) and a desired power of 0.8 to demonstrate a statistical difference with P < 0.05, 64 and 99 patients would be required to show an effect on DC and CC, respectively, for the ascending aorta. From this point of view, the descending aorta performs much better, requiring only 33 and 45 patients for DC and CC, respectively (Table 5).


View this table:
[in this window]
[in a new window]
  		Table 5. Number of subjects required to demonstrate changes with a statistical significance {alpha} and power 1-{beta} in DC and CC for ascending and descending aorta due to SNP infusion

 
Besides the arctangent model, we also fitted an exponential model through the pressure-area data (the exponential factor yielding an alternative stiffness index), but without success. The values for this stiffness index for the descending and ascending aorta varied greatly, yielding inconsistent results. Other authors also encountered major problems in fitting the exponential model to their pressure-area data and concluded that a linear model fitted better to their data (7, 12). Lacombe et al. (13), on the other hand, concluded that an exponential model applied better to their data than a linear model. However, also for the arctangent model, the outcome of the fitting procedure is largely determined by the data (pressure-area) range that is available for the fitting. Especially with SNP infusion, pressures are low, and the pressure-area relation takes a sigmoidal shape, which is better described by the arctangent model than by an exponential model. This was also recently described by Pasipoularides et al. (22), who state in their discussion that, especially in the lower pressure ranges, the pressure-dimension relation of the large arteries is sigmoidal, rather than exponential. Because we performed a blood pressure-lowering infusion of SNP in this study, it is not surprising that the pressure-area relation fitted better to the sigmoidal Langewouters model than to an exponential model. Stefanadis et al. (27) used a polynomial regression line to fit to their pressure-diameter data, which they also call a sigmoidal relation. Because in their former studies they did not record the lower pressure ranges, they could easily fit a simple regression line to their pressure-diameter data. In our study, the patients typically had low blood pressures as a consequence of the sedation and the recent coronary artery bypass grafting, and SNP infusion further lowered blood pressure (30–33).

Our data further allowed assessment of the relation between global (e.g., CPPM) and local arterial compliance information (CC), as illustrated in Fig. 4. The relation is weak (r = 0.25) and not significant for the ascending aorta, but this may be due to earlier described measuring uncertainties. For the descending aorta, r = 0.43 (P < 0.001), and the regression line is given as CCdesc = 0.0033 + 0.0041CPPM. The difficulties in measuring the ascending aorta elastic properties also contribute to the relatively poor (but significant) relation between Z0(P-) and Z0(P-A) data, respectively (r = 0.44, P < 0.001).



View larger version (14K):
[in this window]
[in a new window]
  		Fig. 4. Relation between global [i.e., compliance measured by pulse pressure method (CPPM)] and regional (CC) compliance indexes. For ascending aorta, linear regression yields CC = 0.015 + 0.0052CPPM, with r = 0.25 and no significant relation between local and regional compliance. For descending aorta, CC = 0.0033 + 0.0041CPPM, with r = 0.43 and P < 0.001.

 
The main goal of our work was to apply the Langewouters model to pressure-area data of the thoracic aorta obtained in vivo, subject to all limitations enforced by this environment. 1) Pressures were measured with a fluid-filled 6-Fr pigtail catheter, causing distortion of the pressure wave and a time delay in the measurement. Obviously, correcting for pressure distortion or using micro-tipped transducers will enhance the accuracy of the measurements. 2) The arterial pressure wave and the area-distension curve were manually aligned, with the rapid rising limb of both signals used as a reference. With respect to this manual intervention, we did not calculate the area enclosed by the pressure-area loop (a measure of viscoelastic damping). 3) We have no data to directly validate the accuracy of the area measurements. Such validation could consist of intra-arterial diameter measurement 1) as described by Stefanadis et al. (27, 29) using ultrasonic crystals on the aorta or 2) by means of MRI as the gold standard (9, 20). It is obvious that direct validation is practically impossible in the ICU setting, where we performed our measurements. In addition, we did a comparative study, where absolute values are not relevant.

In conclusion, we have shown that combined pressure and transesophageal ultrasound monitoring applied to the Langewouters model allows for estimating changes in aortic mechanical properties in the ICU setting. It is possible to assess global function parameters as well as directly estimate local mechanical properties of especially the descending aorta via pressure-area relations. Our descending aorta data fitted reasonably well to the arctangent model of Langewouters et al. (15, 16). Furthermore, we demonstrated the sigmoidal, rather than exponential, nature of the pressure-area relation of the thoracic aorta in vivo. Visualization difficulties aggravate the determination of regional elastic properties of the ascending aorta. SNP lowers afterload via a general pressure reduction and also actively modulates total arterial compliance, probably via attenuation of smooth muscle tone, a phenomenon predominantly seen at the descending thoracic aorta.


   GRANTS
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
REFERENCES
 
This project was funded by Exploring European Research Fund Grant 011V1898 (J. Poelaert). In addition, this study was supported by an unrestricted grant from the International Research Center (J. Poelaert and C. Roosens).


   FOOTNOTES
 

Address for reprint requests and other correspondence: J. Poelaert, Intensive Care Dept., Ghent Univ. Hospital, De Pintelaan 185, B-9000 Gent, Belgium (E-mail: jan.poelaert{at}ugent.be)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


   REFERENCES
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 

  1. Bogren HG, Mohiaddin RH, Klipstein RK, Firmin DN, Underwood RS, Rees SR, and Longmore DB. The function of the aorta in ischemic heart disease: a magnetic resonance and angiographic study of aortic compliance and blood flow patterns. Am Heart J 118: 234–247, 1989.[CrossRef][ISI][Medline]
  2. Cappello A, Gnudi G, and Lamberti C. Identification of a three-element windkessel model incorporating a pressure-dependent compliance. Ann Biomed Eng 23: 164–177, 1995.[CrossRef][ISI][Medline]
  3. Cholley B, Lang R, Berger D, Korcarz C, Payen D, and Shroff S. Alterations in systemic arterial mechanical properties during septic shock: role of fluid resuscitation. Am J Physiol Heart Circ Physiol 269: H375–H384, 1995.[Abstract/Free Full Text]
  4. Cholley B, Shroff S, Korcarz C, and Lang R. Aortic elastic properties with transoesophageal echocardiography with automated border detection: validation according to regional differences between proximal and distal descending thoracic aorta. J Am Soc Echocardiogr 9: 539–548, 1996.[CrossRef][Medline]
  5. Cohen J. Statistical Power Analysis for the Behavioral Sciences. New York: Academic, 1977.
  6. Dujardin J and Stone D. Characteristic impedance of the proximal aorta determined in the time and frequency domain: a comparison. Med Biol Eng Comput 19: 565–568, 1981.[CrossRef][ISI][Medline]
  7. Ferguson J, Miller M, Sahagian P, Aroesty J, and McKay R. Assessment of aortic pressure-volume relationships with an impedance catheter. Cathet Cardiovasc Diagn 15: 27–36, 1988.[ISI][Medline]
  8. Hayashi K. Experimental approaches on measuring the mechanical properties and constitutive laws of arterial walls. J Biomech Eng 115: 481–488, 1993.[ISI][Medline]
  9. Hundley WG, Kitzman DW, Morgan TM, Hamilton CA, Darty SN, Stewart KP, Herrington DM, Link KM, and Little WC. Cardiac cycle-dependent changes in aortic area and distensibility are reduced in older patients with isolated diastolic heart failure and correlate with exercise intolerance. J Am Coll Cardiol 38: 796–802, 2001.[Abstract/Free Full Text]
  10. Katz W, Gasior T, Quinlain J, and Gorcsan J. Transgastric continuous-wave Doppler to determine cardiac output. Am J Cardiol 71: 853–857, 1993.[CrossRef][ISI][Medline]
  11. Kelly R, Ting C, Yang T, Liu C, Maughan W, Chang M, and Kass D. Effective arterial elastance as index of arterial vascular load in humans. Circulation 86: 513–521, 1992.[Abstract/Free Full Text]
  12. Kingwell B, Arnold P, Jennings G, and Dart A. Spontaneous running increases aortic compliance in Wistar-Kyoto rats. Cardiovasc Res 35: 132–137, 1997.[Abstract/Free Full Text]
  13. Lacombe F, Dart A, Dewar E, Jennings G, Cameron J, and Laufer E. Arterial elastic properties in man: a comparison of echo-Doppler indices of aortic stiffness. Eur Heart J 13: 1040–1045, 1992.[Abstract/Free Full Text]
  14. Lang RM, Cholley BP, Korcarz C, Marcus RH, and Shroff SG. Measurement of regional elastic properties of the human aorta. A new application of transesophageal echocardiography with automated border detection and calibrated subclavian pulse tracings. Circulation 90: 1875–1882, 1994.[Abstract/Free Full Text]
  15. Langewouters G, Wesseling K, and Goedhard W. The pressure-dependent dynamic elasticity of 35 thoracic and 16 abdominal human aortas in vitro described by a five-component model. J Biomech 18: 613–620, 1985.[CrossRef][ISI][Medline]
  16. Langewouters G, Wesseling K, and Goedhard W. The static elastic properties of 45 human thoracic and 20 abdominal aortas in vitro and the parameters of a new model. J Biomech 17: 425–435, 1984.[CrossRef][ISI][Medline]
  17. Liu Z, Brin K, and Yin F. Estimation of total arterial compliance: an improved method and evaluation of current methods. Am J Physiol Heart Circ Physiol 251: H588–H600, 1986.[Abstract/Free Full Text]
  18. Milnor W. Arterial impedance as ventricular afterload. Circ Res 36: 565–570, 1975.[Free Full Text]
  19. Milnor W. Principles of hemodynamics. In: Cardiovascular Physiology. New York: Oxford University Press, 1990, p. 171–218.
  20. Mohiaddin R, Underwood S, Bogren H, Firmin D, Klipstein R, Rees R, and Longmore D. Regional aortic compliance studied by magnetic resonance imaging: the effects of age, training, and coronary artery disease. Br Heart J 62: 90–96, 1989.[Abstract/Free Full Text]
  21. Molino P, Cerutti C, Julien C, Cuisinaud G, Gustin M, and Paultre C. Beat-to-beat estimation of windkessel model parameters in conscious rats. Am J Physiol Heart Circ Physiol 274: H171–H177, 1998.[Abstract/Free Full Text]
  22. Pasipoularides A, Shu M, Shah A, Silvestry S, and Glower DD. Right ventricular diastolic function in canine models of pressure overload, volume overload, and ischemia. Am J Physiol Heart Circ Physiol 283: H2140–H2150, 2002.[Abstract/Free Full Text]
  23. Schmidt C, Roosens C, Struys M, Deryck Y, Van Nooten G, Colardyn F, Van Aken H, and Poelaert J. Contractility in humans after coronary artery surgery. Anesthesiology 91: 58–70, 1999.[CrossRef][ISI][Medline]
  24. Segers P and Verdonck P. Principles of vascular physiology. In: Panvascular Medicine. Integrated Clinical Management, edited by Lanzer P and Topol E. Heidelberg: Springer, 2002, p. 116–137.
  25. Segers P, Verdonck P, Deryck Y, Brimouille S, Naeije R, Carlier S, and Stergiopulos N. Pulse pressure method and the area method for the estimation of total arterial compliance in dogs: sensitivity to wave reflection. Ann Biomed Eng 27: 480–485, 1999.[CrossRef][ISI][Medline]
  26. Shanewise J, Cheung A, Aronson S, Stewart W, Weiss R, Mark J, Savage R, Sears-Rogan B, Mathew J, Quinones M, Cahalan M, and Savino J. ASE/SCA guidelines for performing a comprehensive intraoperative multiplane transesophageal echocardiography examination: recommendations of the American Society of Echocardiography Council for Intraoperative Echocardiography and the Society of Cardiovascular Anesthesiologists Task Force for Certification in Perioperative Transesophageal Echocardiography. Anesth Analg 89: 870–884, 1999.[Free Full Text]
  27. Stefanadis C, Dernellis J, Tsiamis E, Diamantopoulos L, Michaelides A, and Toutouzas P. Assessment of aortic line of elasticity using polynomial regression analysis. Circulation 101: 1819–1825, 2000.[Abstract/Free Full Text]
  28. Stefanadis C, Dernellis J, Tsiamis E, Stratos C, Diamantopoulos L, Michaelides A, and Toutouzas P. Aortic stiffness as a risk factor for recurrent acute coronary events in patients with ischaemic heart disease. Eur Heart J 21: 390–396, 2000.[Abstract/Free Full Text]
  29. Stefanadis C, Dernellis J, Tsiamis E, Stratos C, Kallikazaros I, and Toutouzas P. Aortic function in patients during intra-aortic balloon pumping determined by the pressure-diameter relation. J Thorac Cardiovasc Surg 116: 1052–1059, 1998.[Abstract/Free Full Text]
  30. Stefanadis C, Karayannacos P, Boudoulas H, Stratos C, Vlachopoulos C, Dontas I, and Toutouzas P. Medial necrosis and acute alterations in aortic distensibility following removal of the vasa vasorum of canine ascending aorta. Cardiovasc Res 27: 951–956, 1993.[Abstract/Free Full Text]
  31. Stefanadis C, Stratos C, Vlachopoulos C, Marakas S, Boudoulas H, Kallikazaros I, Tsiamis E, Toutouzas K, Sioros L, and Toutouzas P. Pressure-diameter relation of the human aorta. A new method of determination by the application of a special ultrasonic dimension catheter. Circulation 92: 2210–2219, 1995.[Abstract/Free Full Text]
  32. Stefanadis C, Tsiamis E, Dernellis J, and Toutouzas P. Effect of estrogen on aortic function in postmenopausal women. Am J Physiol Heart Circ Physiol 276: H658–H662, 1999.[Abstract/Free Full Text]
  33. Stefanadis C, Tsiamis E, Vlachopoulos C, Stratos C, Toutouzas K, Pitsavos C, Marakas S, Boudoulas H, and Toutouzas P. Unfavorable effect of smoking on the elastic properties of the human aorta. Circulation 95: 31–38, 1997.[Abstract/Free Full Text]
  34. Stergiopulos N, Segers P, and Westerhof N. Use of pulse pressure method for estimating total arterial compliance in vivo. Am J Physiol Heart Circ Physiol 276: H424–H428, 1999.[Abstract/Free Full Text]



This article has been cited by other articles:


Home page
 SEMIN CARDIOTHORAC VASC ANESTHHome page
J. Poelaert
The Failing Heart Under Stress: Echocardiography is an Essential Monitoring Tool in the Intensive Care Unit
Seminars in Cardiothoracic and Vascular Anesthesia, March 1, 2006; 10(1): 111 - 115.
[Abstract] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
288/5/H2504    most recent
00368.2004v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (4)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Heerman, J. R.
Right arrow Articles by Poelaert, J. I.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Heerman, J. R.
Right arrow Articles by Poelaert, J. I.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Visit Other APS Journals Online
Copyright © 2005 by the American Physiological Society.