Добавил:
kiopkiopkiop18@yandex.ru t.me/Prokururor I Вовсе не секретарь, но почту проверяю Опубликованный материал нарушает ваши авторские права? Сообщите нам.
Вуз: Предмет: Файл:
Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5835_Библиотеки_им_академика_М_И_Перельмана.pdf
Скачиваний:
0
Добавлен:
10.10.2026
Размер:
8 Мб
Скачать
☆
[11] Ramm, O. T. V., and S. W. Smith, “Real Time Volumetric Ultrasound Imaging System,”
Journal of Digital Imaging, Vol. 3, 1990, pp. 261–266.
[12] Krenning, B. J., M. M. Voormolen, and J. R. T. C. Roelandt, “Assessment of Left Ventricu
-
lar Function by Three-Dimensional Echocardiography,” Cardiovasc. Ultrasound, Vol. 1,
No. 1, 2003.
[13] Bamber, J. C., and C. Daft, “Adaptive Filtering for Reduction of Speckle in Ultrasound
Pulse-Echo Images,” Ultrasonics, 1986, pp. 41–44.
[14] Bamber, J. C., and G. Cook-Martin, “Texture Analysis and Speckle Reduction in Medical
Echography,” SPIE Intl. Symp. Pattern Recog. Acous. Imaging, Vol. 768, 1987,
pp. 287–288.
[15] Bamber, J. C., and J. V. Philips, “Real-Time Implementation of Coherent Speckle Suppres-
sion in B-Scan Images,” Ultrasonics, Vol. 29, 1991, pp. 218–224.
[16] Crawford, D. C., D. S. Bell, and J. C. Bamber, “Implementation of Ultrasound Speckle Fil-
ters for Clinical Trial,” Proc. IEEE Ultrasonic Symp., 1990, pp. 1589–1592.
[17] Crawford, D. C., D. S. Bell, and J. C. Bamber, “Compensation for the Signal Processing
Characteristics of Ultrasound B-Mode Scanners in Adaptive Speckle Reduction,” Ultra-
sound Med. Biol., Vol. 19, 1993, pp. 469–485.
[18] Loupas, T., W. N. Mcdicken, and P. L. Allan, “An Adaptive Weighted Median Filter for
Speckle Suppression in Medical Ultrasonic Images,” IEEE Trans. on Circuits and Systems,
Vol. 36, 1989, pp. 129–135.
[19] Hao, X., S. Gao, and X. Gao, “A Novel Multiscale Nonlinear Thresholding Method for
Ultrasonic Speckle Suppressing,” IEEE Trans. on Medical Imaging, Vol. 18, 1999,
pp. 787–794.
[20] Zong, X., A. F. Laine, and E. A. Geiser, “Speckle Reduction and Contrast Enhancement of
Echocardiograms via Multiscale Nonlinear Processing,” IEEE Trans. on Medical Imaging,
Vol. 17, 1998, pp. 532–540.
[21] Abd-Elmoniem, K. Z., A.-B. M. Youssef, and Y. M. Kadah, “Real-Time Speckle Reduction
and CoherenceEnhancement inUltrasound Imaging Via Nonlinear Anisotropic Diffusion,”
IEEE Trans. on Biomedical Engineering, Vol. 49, 2002, pp. 997–1014.
[22] Angelini, E. D., et al., “LV Volume Quantification Via Spatiotemporal Analysis of
Real-Time 3-D Echocardiography,” IEEE Trans. on Medical Imaging, Vol. 20, 2001,
pp. 457–469.
[23] Duan, Q., E. D. Angelini, and A. Laine, “Assessment of Visual Quality and Spatial Accuracy
of Fast Anisotropic Diffusion and Scan Conversion Algorithms for Real-Time
Three-Dimensional Spherical Ultrasound,” SPIE International Symposium on Medical
Imaging, San Diego, CA, 2004.
[24] Abd-Elmoniem, K. Z., Y. M. Kadah, and A.-B. M. Youssef, “Real Time Adaptive Ultra-
sound Speckle Reduction and Coherence,” Proc. 2000 Int. Conf. Image Processing, Van-
couver, BC, Canada, 2000.
[25] Yu, Y., and S. T. Acton, “Segmentation of Ultrasound Imagery Using Anisotropic Diffu-
sion,” Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, 2001,
pp. 4–7.
[26] Yu, Y., and S. T. Acton, “Speckle Reducing Anisotropic Diffusion,” IEEE Trans. on Image
Processing, Vol. 11, 2002, pp. 1260–1270.
[27] Montagnat, J., et al., “Anisotropic Filtering for Model-Based Segmentation of 4D Cylindri-
cal Echocardiographic Images,” Pattern Recognition Letters, Vol. 24, 2003, pp. 815–828.
[28] Perona, P., and J. Malik, “Scale Space and Edge Detection Using Anisotropic Diffusion,”
IEEE Workshop on Computer Vision, 1987.
[29] Perona, P., and J. Malik, “Scale-Space and Edge Detection Using Anisotropic Diffusion,”
IEEE Trans. on Pattern Anal. Machine Intell., Vol. 12, 1990, pp. 629–639.
[30] Weickert, J., B. M. T. H. Romeny, and M. A. Viergever, “Efficient and Reliable Schemes for
Nonlinear Diffusion Filtering,” IEEE Trans. on Image Processing, Vol. 7, 1998,
pp. 398–410.
244 Cardiac Motion Analysis Based on Optical Flow of Real-Time 3-D Ultrasound Data
[31] Herz, S., et al., “Parameterization of Left Ventricular Wall Motion for Detection of
Regional Ischemia,” Annals of Biomedical Engineering, Vol. 33, 2005, pp. 912–919.
[32] Duan, Q., et al., “Tracking of LV Endocardial Surface on Real-Time Three-Dimensional
Ultrasound with Optical Flow,” 3rd International Conference on Functional Imaging and
Modeling of the Heart 2005, Barcelona, Spain, 2005.
[33] Tsuruoka, S., et al., “Regional Wall Motion Tracking System for High-Frame Rate Ultra-
sound Echocardiography,” Proc. 4th Int. Workshop on Advanced Motion Control, Part 1,
Tsu, Japan, 1996.
[34] Mikic, I., S. Krucinski, and J. D. Thomas, “Segmentation and Tracking in
Echocardiographic Sequences: Active Contours Guided by Optical Flow Estimates,” IEEE
Trans. on Medical Imaging, Vol. 17, 1998, pp. 274–284.
[35] Boukerroui, D., J. A. Noble, and M. Brady, “Velocity Estimation in Ultrasound Images: A
Block Matching Approach,” Lecture Notes in Computer Science, Vol. 2732, 2003,
pp. 586–598.
[36] Yu, W., et al., “Motion Analysis of 3-D Ultrasound Texture Patterns,” Lecture Notes in
Computer Science, Vol. 2674, 2003, pp. 252–261.
[37] Paragios, N., “A Level Set Approach for Shape-Driven Segmentation and Tracking of the
Left Ventricle,” IEEE Trans. on Medical Imaging, Vol. 22, 2003, pp. 773–776.
[38] Bardinet, E., L. D. Cohen, and N. Ayache, “Tracking and Motion Analysis of the Left Ven-
tricle with Deformable Superquadratics,” Medical Image Analysis, Vol. 1, 1996,
pp. 129–149.
[39] Behar, V., et al., “The Combined Effect of Nonlinear Filtration and Window Size on the
Accuracy of Tissue Displacement Estimation Using Detected Echo Signals,” Ultrasonics,
Vol. 41, 2004, pp. 743–753.
[40] Bang, J., et al., “A New Method for Analysis of Motion of Carotid Plaques from RF Ultra-
sound Images,” Ultrasound in Medicine and Biology, Vol. 29, 2003, pp. 967–976.
[41] Rabben, S. I., et al., “Ultrasound-Based Vessel Wall Tracking: An Auto-Correlation Tech-
nique with RF Center Frequency Estimation,” Ultrasound in Medicine and Biology,
Vol. 28, 2002, pp. 507–517.
[42] D’Hooge, J., et al., “Deformation Imaging by Ultrasound for the Assessment of Regional
Myocardial Function,” 2003 IEEE Ultrasonics Symposium, Honolulu, HI, 2003.
[43] Konofagou, E. E., et al., “Myocardial Elastography—Comparison to Results Using MR
Cardiac Tagging,” IEEE Ultrasonics Symposium, Honolulu, HI, 2003.
[44] Gutierrez, M. A., et al., “Computing Optical Flow in Cardiac Images for3-D MotionAnal-
ysis,” Proc. Conf. Computers in Cardiology, London, U.K., 1993.
[45] Shin, I.-S., et al., “Left Ventricular Volume Estimation from Three-Dimensional
Echocardiography,” Proc. SPIE: Ultrasonic Imaging and Signal Processing, San Diego, CA,
2004.
[46] Lucas, B. D., and T. Kanade, “An Iterative Image Registration Technique with an Applica-
tion to Stereo Vision,” International Joint Conference on Artificial Intelligence (IJCAI),
Vancouver, Canada, April 1981, pp. 674–679.
[47] Horn, B. K. P., and B. G. Schunck, “Determining Optical Flow,” Artificial Intelligence,
Vol. 17, 1981, pp. 185–203.
[48] Nagel, H., “Displacement Vectors Derived from Second-Order Intensity Variations in
Image Sequences,” Computer Vision Graphics Image Processing, Vol. 21, 1983,
pp. 85–117.
[49] Anandan, P., “A Computational Framework and an Algorithm for the Measurement of
Visual Motion,” International journal of Computer Vision, Vol. 2, 1989, pp. 283–310.
[50] Singh, A., “An Estimation-Theoretic Framework for Image-Flow Computation,” Interna
-
tional Conference on Computer Vision, Osaka, Japan, 1990, pp. 168–177.
[51] Barron, J. L., D. Fleet, and S. Beauchemin, “Performanceof Optical Flow Techniques,” Int.
Journal of Computer Vision, Vol. 12, 1994, pp. 43–77.
Acknowledgments 245
[52] Duan, Q., et al., “Evaluation of Optical Flow Algorithms forTracking Endocardial Surfaces
on Three-Dimensional Ultrasound Data,” SPIE International Symposium on Medical Imag
-
ing 2005, San Diego, CA, 2005.
[53] Ingrassia, C. M., et al., “Impact of Ischemic Region Size on Regional Wall Motion,” Proc.
2003 Annual Fall Meeting of the Biomedical Engineering Society, Nashville, TN, Octo-
ber 1–4, 2003.
[54] Angelini, E. D., et al., “Comparison of Segmentation Methods for Analysis of Endocardial
Wall Motion with Real-Time Three-Dimensional Ultrasound,” Computers in Cardiology,
Memphis, TN, 2002.
[55] Herz, S., et al., “Novel Technique for Quantitative Wall Motion Analysis Using Real-Time
Three-Dimensional Echocardiography,”Proc. 15th Annual Scientific Sessions of the Ameri-
can Society of Echocardiography, San Diego, CA, June 26–30, 2004.
[56] Schiller, N. B., et al., “Left Ventricular Volume from Paired Biplane Two-Dimensional
Echocardiography,” Circulation, Vol. 60, 1979, pp. 547–555.
[57] Folland, E. D., et al., “Assessment of Left Ventricular Ejection Fraction and Volumes by
Real-Time, Two-Dimensional Echocardiography. A Comparison of Cineangiographic and
Radionuclide Techniques,” Circulation, Vol. 60, 1979, pp. 760–766.
[58] Duan, Q., et al., “Dynamic Cardiac Information from Optical Flow Using Four Dimen-
sional Ultrasound,” 27th Annual International Conference IEEE Engineering in Medicine
and Biology Society (EMBS), Shanghai, China, 2005.
[59] Baxter, B. J. C., “The Interpolation Theory of Radial Basis Functions,” Ph.D. thesis,Trinity
College, 1992.
[60] Humphrey, J. D., Cardiovascular Solid Mechanics: Cells, Tissues, and Organs, New York:
Springer, 2002.
[61] Buchalter, M. B., et al., “Noninvasive Quantification of Left Ventricular Rotational Defor-
mation in Normal Humans Using Magnetic Resonance Imaging Myocardial Tagging,” Cir-
culation, Vol. 81, 1990, pp. 1236–1244.
[62] Duan, Q., et al., “Comparing Optical-Flow Based Methods for Quantification of Myocar-
dial Deformations on RT3-D Ultrasound,” IEEE International Symposium on Biomedical
Imaging (ISBI), Arlington, VA, 2006, pp. 173–176.
[63] Waldman, L. K., Y. C. Fung, and J.W. Covell, “Transmural Myocardial Deformation in the
Canine Left Ventricle. Normal In Vivo Three-Dimensional Finite Strains,” Circ. Res.,
Vol. 57, 1985, pp. 152–163.
[64] Nieminen, M., et al., “Serial Evaluation of Myocardial Thickening and Thinning in Acute
Experimental Infarction: Identification and Quantification Using Two-Dimensional
Echocardiography,” Circulation, Vol. 66, 1982, pp. 174–180.
246 Cardiac Motion Analysis Based on Optical Flow of Real-Time 3-D Ultrasound Data
CHAPTER 10
Echocardiography: A Tool for LVSD
Identification
Manivannan Jayapalan

10.1 Introduction

The human heart is a hollow, muscular, four-chamber organ that pumps blood
through the blood vessels by repeated rhythmic contractions. Ventricular dysfunc-
tion is the result of a diversity of structural and/or physiologic abnormalities of
myocardial relaxation or contraction that alters the ventricular flow. The cardiac
cycle contains two phases, diastole and systole, and both may be affected by dis-
eases of the heart.Thus, ventricular dysfunction canbe diastolicor systolic, or both.
It is essential to consider the ventricular dysfunction in the left-hand side
because the left ventricle plays an important role in circulating the blood to the
whole body. Systolic dysfunction results from a decrease in global or regional myo-
cardial contractility. The fraction of blood that is expelled in relation to the blood
volume in the heart in diastole is an expression of systolic function and is called the
ejection fraction (EF). During systole, the heart empties and an impairment of con-
tractility causes less blood to be expelled. thus decreasing the stroke volume but
increasing the end-systolic volume as a whole EF that ends in progressive pump fail-
ure. The impaired capacity of the left ventricle to fill and to maintain its stroke vol-
ume without a compensatory increase of atrial filling pressures represents diastolic
dysfunction. Ejection of a lesser volume of blood because of a decrease in contractil-
ity and reduced ventricular filling because of the impairment of myocardial muscles
are shown in the Figure 10.1.
Reduced ability of the left ventricle to eject blood, called left ventricle systolic
dysfunction (LVSD), is a common predecessor of heart failure (HF). The prognosis
for heart failure is poor and the morbidity is high with frequent hospitalizations,
especially among the elderly. The prevalence of HF is increasing and threatens to
become a majorlogistic and economic burden to global health care systems. HF cur-
rently contributes to 30.9% of global mortality and 10.3% of global morbidity [1]
that can be reduced by optimal treatment, requiring objective evaluation of LV
function and cardiac anatomy. Detection and treatment of LVSD is essential to
reduce the incidence of cardiac failure and its consequences. The major cause of
247
LVSD is blockage in the coronary arteries that supply blood to the heart surface,
thus reducing the oxygen supply, which leads to necrosis followed by the impaired
contractility of cardiac muscles [2].

10.1.1 Left Ventricular Systolic Dysfunction

The inability of the LV to eject sufficient blood, referred as systolic dysfunction, is a
complex process involving improper contractions of subendocardial, midwall,
subepicardial, and papillary muscle fibers. In the presence of LVSD, the heart con-
tracts less forcefully and cannot pump out as much of the blood that is returned to it
as it normally does. As a result, more blood remains in the lower chambers of the
heart (ventricles). Blood then accumulates in the veins. The muscle fibers of the
midwall LV are arranged mainly circumferentially, whereas subepicardial,
subendocardial, and papillary fibers are arranged mainly in a longitudinal and/or
oblique fashion. The shortening of these muscle fibers results in a thickening of the
ventricular walls, as well as a movement of the mitral annulus toward the LV apex.
In addition, the oblique fibers produce a twisting movement of the LV. These events
result in a volume reduction of the LV lumen, a reduction of the stroke volume, and,
hence, a reduction in the ejection fraction. The interaction of the LV, the other car-
diac chambers, and the entire vascular system results in decreased cardiac output,
which is the product of stroke volume and heart rate.
248 Echocardiography: A Tool for LVSD Identification
Systolic
dysfunction
Diastolic
dysfunction
Normal
Diastole
(filling)
Systole
(pumping)
The ventricles fill
normally with blood
The enlarged ventricles
fill with blood
The stiff ventricles fill
with less blood than
normal
The ventricles pump
out about 60% of
the blood
The ventricles pump
out less than 40% to 50%
of the blood
The ventricles pump
out about 60% of
the blood, but the
amount may be lower
than normal
Figure 10.1 Left ventricular dysfunction.

10.1.2 Determinants of LV Systolic Performance

The forces acting on the myocardium during filling and contraction are important
determinants of LV systolic performance. These forces are affected by chamber size
and shape and can be described according to the concept of wall stress. The law of
Laplace states that the stress in the walls of a cylinder is directly proportional to the
transmural pressure and the radius of the cylinder and inversely proportional to the
thickness of the cylinder walls. So an increased radius of the LV, that is, dilation,
causes increased stress on the chamber walls, if the transmural pressure and wall
thickness are constant. By increasing the wall thickness (i.e., LV hypertrophy), the
wall stress can be reduced.
The wall stress acting to stretch the noncontracting muscle in diastole can be
viewed as preload. An increase in preload produces an increase in stroke volume by
lengthening the fundamental contractile units—the sarcomeres—in the myocyte (the
length–tension relationship). Frank first described this phenomenon in the frog heart
in 1895, and Starling described it in the mammalian heart in 1914. It is therefore
oftenreferredtoastheFrank-Starlingmechanism. The myocardial wall stress that
builds up during the systolic contraction can be viewed as afterload. In addition to
chamber size and wall thickness, this wall stress depends on the peripheral vascular
resistance, arterial compliance, and intraventricular pressure. An increase in afterload
reduces the myofiber shortening velocity, resulting in a decrease in stroke volume.
Last but definitely not least, contractility is the fundamental quality of cardiac
muscle that determines the systolic performance independent of loading conditions.
Increased contractility produces a greater rate of contraction to reach a greater peak
force. Figure 10.2 shows the left ventricle P-V relationship in a normal heart along
with systolic and diastolic dysfunctions.

10.2 Assessment of Left Ventricular Function—An Overview

Systolic function of the left ventricle represents a complex interaction between
preload, afterload, and contractility. Preload is the force that stretches the
10.2 Assessment of Left Ventricular Function—An Overview 249
Systolic dysfunction
Normal
Diastolic dysfunction
Pressure
Pressure
Pressure
Left ventricular volume Left ventricular volume Left ventricular volume
Figure 10.2 Left ventricle P-V relationship.
myofibrils in diastole. The balance of two opposing forces determines the end-dia-
stolic sarcomere length. These forces are end-diastolic wall stress, which is an esti-
mate of the force stretching the myocardial fibers at end diastole, and the intrinsic
myocardial stiffness or elasticity. These two opposing forces will eventually deter-
mine the left ventricular end-diastolic volume and pressure. Afterload is the force
that resists myofibril shortening in systole and varies throughout systole as blood is
ejected from the ventricles. The left ventricular systolic wall stress is the measure of
the force resisting myofibril shortening in systole in humans and, therefore, repre-
sents afterload. It is directly proportional to the radius of and the pressure inside the
chamber and is inversely proportional to the wall thickness [3].
Contractility is anintrinsic property of themyocardium and generally means the
strength of the shortening of the myofibrils when they contract. Preload, afterload,
and contractility are intimately related in vivo and alterations in any one of these
three parameters will affect the other two. For example, an increase in preload gen-
erally increases contractility according to the Frank-Starling mechanism. However,
an increase in preload may also result in anincrease in afterload because the left ven-
tricular end-diastolic volume will increase.
Therefore, the overall increase in contractility as a result of an increase in
preload is somewhat blunted because the increased afterload (that accompanies an
increase in preload) will decrease contractility. Assessment of ventricular function,
therefore, requires careful consideration of this complex interaction between
preload, afterload, and contractility, and ventricular function is not synonymous
with contractility.
In common usage, left ventricular function usually refers to left ventricular sys-
tolic function. Assessment of left ventricular function remains a vital part of man-
agement of almost all cardiovascular diseases because left ventricular function
carries important diagnostic and prognostic information. The ideal parameter of
ventricular function should be accurate; independent of loading conditions, heart
rate, cardiac chamber shape and size; easily measured; reproducible; and sensitive
only to intrinsic changes of contractile function. Numerous indices of cardiac func-
tion have been proposed and tested. However, none of the currently available indi-
ces fulfills the criteria of the ideal index. In the following sections, the rationale,
benefits, and shortcomings of the commonly used indices are discussed.

10.2.1 Ejection Phase Indices

10.2.1.1 Ejection Fraction and Fractional Shortening
The left ventricular ejection fraction, which is obtained from volume data only, is
the most widely used index of systolic function. It is often quoted as a measure of left
ventricular function in heart failure trials [4–6]. Fractional shortening is the
one-dimensional surrogate of EF and has the advantage of relative simplicity
because its calculation depends only on measurement of a single dimension of the
left ventricle. The velocity of circumferential fiber shortening [7] is the rate of short-
ening of a theoretical myocardial fiber in the circumferential plane at the midpoint
of the long axis of the ventricle. These ejection phase indices can be measured rela-
tively easily from either contrast left ventriculography or noninvasively using
radionuclide ventriculography or echocardiography.
250 Echocardiography: A Tool for LVSD Identification
Except for the velocity of circumferential fiber shortening, both EF and frac-
tional shortening are extremely popular. Their popularity stems from the fact that
these parameters are easily obtainable, quantitative, easy to understand, and repro-
ducible. However, ejection phase indices are very dependent on both preload and
afterload and cannot be considered a reliable index of ventricular contractility,
especially in conditions of altered loading conditions. For example, in patients with
mitral regurgitation, the ejection fraction is increased as a result of the increase in
preload and the decrease in afterload. The increase in EF is not indicative of
increased ventricular function and it can, in effect, mask the development of
ventricular dysfunction.
10.2.1.2 Myocardial Performance Index
Tei et al. [8, 9] advocated the use of a Doppler-derived myocardial performance
index, which isdefined as the sum of the isovolumetric relaxation and isovolumetric
contraction times divided by the ejection time. They studied 100 patients with dif-
ferent degrees of left ventricular dysfunction and 70 normal subjects with Doppler
echocardiography. The researchers found that the mean value of the index was sig-
nificantly different between normal and patients with moderate or severe left ven-
tricular dysfunction (0.39 ± 0.05, 0.59 ± 0.10, and 1.06 ± 0.24, respectively; p <
0.001 for all) with a small degree of overlap [8]. Furthermore, the value of the index
did not appear to be related to heart rate, mean arterial pressure, or the degree of
mitral regurgitation. In a subsequent study, the authors performed simultaneous
cardiac catheterization and Doppler echocardiography in 34 patients [9] and found
good correlations between the Doppler index and simultaneously recorded systolic
peak +dp/dt (r =0.821; p < 0.0001), diastolic peak –dp/dt (r = 0.833; p < 0.001), and
tau (τ, the relaxation time constant; r = 0.680, p < 0.0001).
The Doppler index can be measured easily and is reproducible and appears to
be promising in the assessment of global ventricular function. However, it does not
differentiate between systolic and diastolic function and its use in patients with sig-
nificant mitral regurgitation has not been validated. Moreover, in patients with sig-
nificant mitral regurgitation, the isovolumetric contraction time cannot be
measured accurately. Therefore, the index may have limited applicability in these
patients.

10.2.2 Isovolumetric Indices

The maximum rate of rise of left ventricular systolic pressure (+dp/dt) is the maxi-
mum of the first derivative of ventricular pressure and has been used as an indicator
of contractility. It was first measured by means of a catheter-tip micromanometer.
More recently, dp/dt has been successfully measured noninvasively with the use of
Doppler echocardiography [10]. Using continuous wave Doppler, Bargiggia et al.
found good correlations between catheter-derived and Doppler-derived dp/dt.
Interventions known to increase myocardial contractility, such as exercise, infusion
of adrenaline, and tachycardia also increased left ventricular dp/dt. However, left
ventricular dp/dt is not completely load independent. Studies have shown that left
ventricular dp/dt increased with a moderate increase in preload [11] and showed lit
-
10.2 Assessment of Left Ventricular Function—An Overview 251
tle change with changes in afterload [12]. Whereas changes in dp/dt reflect changes
in contractility in a given individual, its use in comparing one individual with
another is limited, especially when there has been chronic pressure or volume
overload.

10.2.3 Pressure-Volume Analysis

The relationship between left ventricular pressure and volume can be expressed in a
plot of left ventricular pressure versus volume. One cardiac cycle can be represented
by a complete pressure-volume loop (Figure 10.3). In Figure 10.3, segment b is
isovolumetric contraction, segment c is left ventricular ejection, and d is
isovolumetric relaxation.
10.2.3.1 End Systolic Pressure-Volume Relationships (ESPVR)
The fundamental principle underlying ESPVR is that such a relationship is unique
for a given level of contractility and is independent of loading conditions [13]. The
ratio of simultaneous pressure and volume defines the stiffness or the elastance of
the left ventricle. During the cardiac cycle, this ratio increases to a maximum during
systole and decreases to a minimum during diastole. By varying the loading condi-
tions, a series of left ventricular pressure-volume loops can be generated. The line
joining the upper left-hand corners of each individual loop is the end-systolic pres-
sure-volume line, characterized by a slope, the end-systolic elastance (E
es
), an x-axis
intercept, and an extrapolated volume at zero pressure (V
0
) (Figure 10.4).
Therefore, ESPVR is represented by:
()
PEVV
es
=−
0
(10.1)
It is generally agreed that an increase in the slope of the ESPVR line (i.e., an
increase in end-systolic elastance) is indicative of an increase in contractility and
vice versa [13, 14]. Measurement of ESPVR involves simultaneous measurements
of left ventricular pressure and volume. Left ventricular pressures can be measured
with a catheter-tip micromanometer, and measurement of left ventricular volume
252 Echocardiography: A Tool for LVSD Identification
LV pressure (mmHg)
0
0
100
100
200
200
Aortic
valve
closing
Aortic
valve
opening
ESPVR
EDPVR
db
c
a
ESV
EDV
LV volume (ml)
SV
Figure 10.3 A typical left ventricular pressure-volume loop.
can be made by contrast ventriculography, radionuclide techniques [15],
echocardiography [16], or with the use of an impedance catheter [17].
An inflatable balloon inserted into the inferior vena cava near the right atrial
junction usually achieves manipulation of loading conditions. With the use of either
contrast or radionuclide ventriculography to measure volume, alteration of loading
conditions is more commonly achieved by pharmacological means (phenylephrine
to increase afterload and sodium nitroprusside to decrease afterload and preload).
With the use of pharmacological agents, autonomic blockade [18] or temporary
pacing at a slightly higher heart rate [15] may be necessary to eliminate the reflex
changes in heart rate during such manipulations.
Whether the ESPVR is linear has been extensively investigated. A linear ESPVR
has been suggested in isolated hearts [19] and in conscious dogs [20]. It was also
supported by studies involving humans [21]. This linearity is important because,
theoretically, the ESPVR line can be constructed from only two to three pressure-
volume loops [22, 23]. This is especially important for investigators using contrast
ventriculography to measure ventricular volume, because the number of pres-
sure-volume loops that canbe generatedfrom suchmeasurements isusually limited.
Experimental and clinical studies often determined end-systolic elastance over a
limited range of loading conditions and inotropic states and, therefore, may have
failed to demonstrate the nonlinearity of such relationships. However, subsequent
investigators have suggested that the ESPVR is curvilinear at higher afterloads [24]
and that the curvilinearity of ESPVR is also contractility dependent [25]. With
increased contractility (i.e., high-end systolic elastance, E
es
), the ESPVR tended to be
concave to the volume axis. At low contractility, ESPVR tended to be convex to the
volume axis. However, over the range of end-systolic elastance values that are
encountered in normal states of contractility, a curvilinear fit was not statistically
better than a linear fit for the ventricular volumes that could be examined in the ani-
mal model [25]. This curvilinearity has been used to explain why the extrapolated
V
0
is sometimes a negative number [26]. It is important to realize that the linearity
of the ESPVR is a convenience that allows determination of such relationships to be
carried out in simple terms. Although the ESPVR is in fact curvilinear, it does not
alter the fact that such relationships define the systolic performance of the ventricle
at a given state.
End-systolic elastance has also been suggested to be influenced by heart size
[27]. In an animal model of mitral regurgitation, Berko et al. [27] found that the
end-systolic elastance decreased significantly after creation of mitral regurgitation,
10.2 Assessment of Left Ventricular Function—An Overview 253
LV volume (ml)
LV pressure (mmHg)
0
0
20 40
40
60
60
80
120
100
160
Figure 10.4 Determination of ESPVR.