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

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

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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 (C_PPM)] 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 C_PPM 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

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

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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 (C_SV/PP), 2) by the PP method (C_PPM) (34), and 3) by the area method: C_AM = A_{t(1) – t(2)}/{SVR[P(t₁) – P(t₂)]} (17). The PP method is an iterative method (based on a 2-element windkessel model), where C_PPM 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 [A_{t(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 (P_es) was taken as the aortic pressure corresponding to the onset of the diastolic interval. Effective arterial elastance was calculated as P_es/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 [Z_0(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.

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 A_max, P₀, and P₁ model parameters following from the curve-fitting procedure: A_max 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.

	RESULTS

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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).

0(P-)

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, stiffness index, and Z_0(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 A_max 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.

	DISCUSSION

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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, C_AM is more than three times higher than C_PPM and about two times higher than C_SV/PP (Table 2). In agreement with earlier findings, we found a close correlation between C_SV/PP and C_PPM (C_SV/PP = 0.05 + 1.66C_PPM, 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 and power 1- in DC and CC for ascending and descending aorta due to SNP infusion

Our data further allowed assessment of the relation between global (e.g., C_PPM) 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 CC_desc = 0.0033 + 0.0041C_PPM. The difficulties in measuring the ascending aorta elastic properties also contribute to the relatively poor (but significant) relation between Z_0(P-) and Z_0(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.

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

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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.

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