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Journal of Biomechanics 41 (2008) 2906–2911

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Journal of Biomechanics

0021-92

doi:10.1

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Measurement of the transverse strain tensor in the coronary arterial wallfrom clinical intravascular ultrasound images

Yun Liang a, Hui Zhu a, Thomas Gehrig b, Morton H. Friedman a,�

a Department of Biomedical Engineering, Duke University, Box 90281, Durham, NC 27708, USAb Department of Medicine—Cardiovascular Medicine, Duke University Medical Center, Durham, NC, USA

a r t i c l e i n f o

Article history:

Accepted 1 August 2008Atherosclerotic plaque rupture is the major cause of acute coronary syndromes. Currently, there is no

reliable diagnostic tool to predict plaque rupture. Knowledge of plaque mechanical properties based on

Keywords:

Cardiac phase

Coronary artery

Image registration

Intravascular ultrasound

Transverse strain tensor

Vulnerable plaque

90/$ - see front matter & 2008 Elsevier Ltd. A

016/j.jbiomech.2008.08.004

esponding author. Tel.: +1919 660 5154.

ail addresses: mhfriedm@duke.edu, mort.fried

iedman).

a b s t r a c t

local artery wall strain measurements would be useful for characterizing its composition and predicting

its vulnerability. Due to cardiac motion, strain estimation in clinical intravascular ultrasound (IVUS)

images is extremely challenging. A method is presented to estimate cross-sectional coronary artery wall

strain in response to cardiac pulsatile pressure using clinically acquired IVUS images, which are

acquired in continuous pullback mode. First, cardiac phase information is retrieved retrospectively from

an IVUS image sequence using an image-based gating method, and image sub-sequences at systole and

diastole are extracted. Then, images at branch sites are used as landmarks to align the two image sub-

sequences. Finally, the paired images at each site are registered to measure the 2D strain tensor of the

coronary artery cross-section. This method has been successfully applied to IVUS images of a left

anterior descending (LAD) coronary artery acquired clinically during a standard procedure. Such

complete strain information should be useful for identifying vulnerable plaque.

& 2008 Elsevier Ltd. All rights reserved.

1. Introduction

Atherosclerotic plaque rupture is the most frequent cause ofacute coronary syndromes (ACS), which include sudden death,acute myocardial infarction, or unstable angina (Falk et al., 1995;Naghavi et al., 2003; Virmani et al., 2006). In a broad sense, anyatherosclerotic plaque that has a propensity to cause thrombosisand clinical consequences is defined as a vulnerable plaque. Themost accepted features of the vulnerable plaques are a large lipidcore, a thin fibrous cap, and an increased inflammation level (Falk,2006; Richardson, 2002). The composition and morphometry ofthe vulnerable plaque are thought to be more crucial determi-nants of ACS likelihood than the extent of stenosis (Cheng et al.,1993; Finet et al., 2004). Specific characteristics of the vulnerableplaques have been proposed mostly on the basis of pathologicalstudies. There is an urgent need to improve diagnostic methodsfor prospectively identifying vulnerable plaque in susceptiblepatients, as a primary prevention goal.

Intravascular ultrasound (IVUS) is a catheter-based, minimallyinvasive high-resolution imaging technique. It is widely availableclinically and provides real-time cross-sectional images of arteries

ll rights reserved.

man@duke.edu

with the best spatial representation of the vessel wall andatherosclerotic plaque morphometry (Potkin et al., 1990; Teo,2005). The equipment required to perform IVUS imaging are acatheter with a miniaturized transducer, a catheter pullbackdevice, and a console to reconstruct the image. Radio frequency(RF) ultrasonic echo signals are received by the transducer andsent through multiple stages of processing, including amplifica-tion, bandpass filtering, envelope detection, and scan conversion,to generate a 3601 cross-sectional image of the artery wall.

In clinical use, the IVUS catheter is pulled back through a vesselsegment by a motorized pullback device at a fixed speed between0.25 and 1.0 mm/s while images are continuously acquired at arate of 30 frames/s. The motorized pullback and continuousacquisition of images generate a volume scan of the vesselsegment.

IVUS images provide some insights into plaque composition,based on the echogenic appearance of plaque and the presence orabsence of shadowing and reverberation (Di Mario et al., 1998;Nissen and Yock, 2001). IVUS has been shown to be able tocharacterize plaque broadly as calcified, fibrous, or fatty, but itsability to more precisely detect lipid-rich regions, the necroticcore, mixed plaques, and thrombus is limited (Palmer et al., 1999;Prati et al., 2000). Therefore, IVUS echo image alone cannotreliably predict the vulnerability of the plaque.

Structural analysis of atherosclerotic arteries has shown thatatherosclerotic plaque exhibits mechanical behavior consistent

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Fig. 1. An IVUS frame showing the ROI (red) for calculating average gray level

(AGL).

Y. Liang et al. / Journal of Biomechanics 41 (2008) 2906–2911 2907

with its underlying components and its location in the artery wall(Finet et al., 2004; Lee et al., 1991; Loree et al., 1992). Furthermore,there are considerable difference in mechanical propertiesbetween normal artery wall and different types of atheroscleroticplaques, which may vary by several orders of magnitude (Dobrin,1978; Vito and Dixon, 2003). This suggests that measurements ofplaque mechanical response may be useful in assessing thelikelihood of plaque rupture and estimating plaque composition.Local artery wall strain in response to luminal pressure change issuch a measurable response.

Introduced by Ophir and colleagues (Cespedes et al., 1993;Ophir et al., 1991), elastography is an imaging technique that usesultrasound to relate the deformation (strain) of a tissue to itsmechanical properties. Since then, intravascular applications havebeen developed (Brusseau et al., 2001; de Korte et al., 1997; Ryanand Foster, 1997; Shapo et al., 1996; Talhami et al., 1994; Wanet al., 2001). de Korte et al. (Cespedes et al., 1997; de Korte et al.,1997) have used IVUS elastography to obtain vascular elasticproperties; they measure radial strain by correlation analysis of RFsignals recorded under different luminal pressures.

One critical requirement in IVUS elastography is the necessityto ensure that the tissue images acquired at the two levels ofluminal pressure are at corresponding sites. It is particularlydifficult to achieve this in vivo, due to the movements of the IVUScatheter caused by cardiac motion. The IVUS catheter movesaxially during the cardiac cycle. The measured amplitude ofmovement in the absence of pullback was 1.570.8 mm by IVUS,and 2.471.4 mm by cineangiography (Arbab-Zadeh et al., 1999).Since the catheter is smaller than the lumen, there are additionalin-plane movements.

In the elastography studies of de Korte et al. (2002), minimalcatheter motion was achieved by using only RF signals acquirednear end-diastole, during which time the catheter pullback wasinterrupted. This approach has several disadvantages. First, it isone-dimensional (1D) processing. Hence, reliable strain estimatesare obtained only when the tissue motion is aligned with the RFsignal direction. Second, disregarding tissue motion componentsin a direction other than the radial direction corrupts the radialstrain estimate by introducing decorrelation noise. Third, thesmall strain during a brief end-diastolic interval is difficult tomeasure accurately due to low signal-to-noise ratio (SNR).

The goal of this study is to find a practical method to measurecross-sectional wall strain distribution in coronary arteries fromclinical IVUS images acquired in continuous pullback mode. Wehave developed a strain estimation method based on IVUS imageregistration (Liang et al., 2006, 2008). This 2D processing methodhas the ability to overcome in-plane movement of the IVUScatheter and heterogeneous tissue displacements, yielding thelocal transverse strain tensor.

To estimate strain in clinical IVUS images, one critical step is toidentify pairs of frames corresponding to a given vessel site atdifferent cardiac phases. In this study, an image-based retro-spective technique (Zhu et al., 2003) developed earlier in our lab isused to retrieve the cardiac phase. Since the axial movement ofthe catheter is periodic, we are able to identify the closest imagepair at the same vessel site with the help of the images at thebranch sites.

In the rest of this paper, we first describe the techniques usedto overcome catheter movement due to cardiac motion: theimage-based retrospective method to retrieve the cardiac phase,and the method used to pair images at the same vessel site. Wethen apply the image-registration-based strain estimation meth-od to clinical IVUS images of the left anterior descending (LAD)coronary artery. We are able to achieve high SNR, since thecoronary artery wall strain can be measured under a pressuredifference that is comparable to physiological pulse pressure.

2. Material and methods

The image sequences were taken from patients at Duke University Medical

Center. Informed consent of the patients was obtained before the procedure. The

studies were performed by using a Boston Scientific ClearView IVUS system, with a

3 French mechanical-type 40 MHz IVUS catheter (Atlantis SR, Boston Scientific

Corporation, Natick, MA, USA). The images were acquired during a standard

interventional procedure, in which the IVUS catheter was pulled through the

vessel segment by a motorized pullback device at a speed of 0.5 mm/s, while

images were acquired continuously at a rate of 30 frames/s. After image

acquisition, the branch sites were identified by the cardiologist. Image sequences

encompassing a branch site were chosen for analysis. The steps in our procedure

are described below.

2.1. Retrieval of the cardiac phase

In an IVUS image, there are three distinct regions—catheter, lumen, and

arterial wall with the surrounding tissues. The catheter region exhibits virtually no

change from frame to frame during the catheter pullback. The change of lumen

size that accompanies the pulsatile blood pressure causes the average intensity of

the IVUS images to exhibit a periodic variation during pullback.

The retrospective method is based on the cyclic average gray level (AGL)

changes inside a circular region of interest (ROI), which includes the lumen, the

arterial wall, and some surrounding tissue. The fixed size of the ROI is set so that

the entire lumen and a portion of the arterial wall are included in each frame of the

image sequence. An IVUS image with a typical ROI is shown in Fig. 1. The changes

of AGL signal along the pullback path are due to two main factors in addition to

noise: axial variation of vessel structure and the time-dependent changes of vessel

morphometry caused by cardiac motion and pulsatile blood pressure. The latter

carries cardiac phase information and has a major component at the heart rate,

which is around 1 Hz. To extract this information, the AGL signal was filtered with

a Butterworth bandpass filter centered at the frequency peak closest to 1 Hz, as

determined from a Fourier frequency analysis of the AGL. In practice, this

frequency can be verified with the clinical record.

The filtered AGL signal can be used to determine the cardiac phase of each

image in a sequence. Systolic epicardial coronary artery expansion has been

demonstrated with a sonomicrometer in animal studies (Baughman et al., 1980)

and IVUS measurements in humans (Weissman et al., 1995), although the majority

of coronary artery blood flow occurs in diastole. In this study, we have adopted the

terms ‘‘diastole’’ and ‘‘systole’’ to describe the peak and valley of the filtered AGL,

respectively. We define the image frame corresponding to the peak of the filtered

AGL as the diastolic frame since the lumen size is small; while the frame

corresponding to the valley of the filtered AGL is referred to as the systolic frame

since the lumen size is large. Viscoelastic effects in the coronary artery wall are

ignored. And it is a common assumption made in computational studies (Cheng

et al., 1993). The diastolic and systolic frames were then grouped to form the

diastolic and systolic sub-sequences, respectively.

2.2. Identification of paired images at the same site

Image pairs corresponding to a specific vessel site were identified by aligning

the diastolic and systolic sub-sequences by using frames in which branch sites

were imaged in both sub-sequences. The images closest to the center of the branch

ostium were used for this purpose. The images at the branch points are used only

for aligning the diastolic and systolic sub-sequences. Arterial wall strain is not

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Y. Liang et al. / Journal of Biomechanics 41 (2008) 2906–29112908

measured at these locations, where the geometry is complex. After the axial

registration of the two sub-sequences, the diastolic and systolic image pairs

corresponding to multiple vessel sites can be identified for analysis. The

availability of entire sub-sequences permits the study of arterial wall mechanical

properties at multiple sites along the vessel, including sites where plaque exists,

and also facilitates the measurement of axial strain.

2.3. Estimation of local artery wall strain

The cross-sectional strain between systole and diastole is estimated from the

displacement field by using a non-rigid image registration technique developed in

our laboratory. This method has been validated by using synthetic motion IVUS

images, and evaluated by using a homogeneous phantom, as described by Liang

et al. (2008). Here, the technique is applied to a pair of IVUS images of the same

site; the reference image is obtained in diastole and the target image is at systole.

Briefly, non-rigid image registration is formulated as an optimization problem,

whose goal is to minimize an associated cost function. In this study, the cost

function is a combination of a term that characterizes the similarity between the

reference and target images, and a weighted term that adds robustness to motion

estimation by incorporating a strain smoothness constraint. Multi-resolution

registration is adopted to save computation time and avoid local minima.

Following the displacement field calculation, local 2D strain tensors are

computed. Finally, the radial and circumferential strain distributions across the

vessel wall are plotted as 2D color-coded images.

Fig. 2. (a) AGL signal before filtering; (b) frequency spectra of the AGL signal in (a);

and (c) AGL signal after filtering.

LandmarkBranch site

Diastolesubsequence

3. Results

Fig. 2 shows the AGL signal prior to filtering, the Fourierspectrum of the AGL signal, and the filtered AGL. The signal beforefiltering is noisy; however, a frame periodicity is evident. In thisimage sequence, there are a total of 962 frames, and the peakfrequency was found to be 1.3 Hz. Fig. 3 illustrates alignment ofthe diastolic and systolic sub-sequences using the branch siteimages.

Figs. 4 and 5 show the strain distributions in both the radialand circumferential directions in response to luminal pressurechange from diastole to systole at two LAD sites. In Fig. 4, theechograms show a mixed plaque: the region from 4 to 7 o’clockappears to be fibrous plaque and the rest of the cross-sectionregion appears to be fibrofatty plaque. In the radial strain map, theregion corresponding to the fibrous plaque has low strain; whilethe fibrofatty plaque region with a relatively thick lipid poolexhibits high strain.

In Fig. 5, the plaque is severely eccentric. In both the radial andcircumferential directions, the plaque cap deforms differentlythan the plaque body. The magnitude of radial strain is higher atthe plaque shoulder area. Since compressive radial strain isincreased with high circumferential tension, and finite elementanalysis of atherosclerotic arteries has suggested that circumfer-ential tensile stress concentration is associated with plaquerupture (Ohayon et al., 2001; Versluis et al., 2006), this mayindicate that this plaque is vulnerable.

It is clear from the strain distributions that when the luminalpressure increases from diastolic to systolic, the arterial wall is notalways compressed radially (negative strain) and stretchedcircumferentially (positive strain). This might be due to non-uniform forces from the surrounding tissues, local cardiac motion,or the spatial heterogeneity of the composition and mechanicalproperties of the wall.

systolesubsequence

Fig. 3. Alignment of diastolic and systolic sub-sequences with branch images.

4. Discussion and conclusions

The identification of plaque composition and the predisposi-tion of an atherosclerotic plaque to rupture are important goals incardiology. Currently, there is no clinically available techniquecapable of reliably identifying plaque that is prone to rupture.Elasticity imaging may be a valuable tool in this respect. Strictlyspeaking, the complex nature of tissue biomechanics can only be

characterized by the anisotropic elastic constants (Fung, 1993;Humphrey, 2002). In practice, a variety of limitations wouldsuggest a more pragmatic approach. The primary aim of this study

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Fig. 4. IVUS image at a LAD site at (a) diastole and (b) systole; (c) derived displacement field in the region of the vessel wall between the segmented lumen boundary and

media-adventitia interface (blue lines), in response to the luminal pressure increase from diastole to systole; color-coded (d) radial and (e) circumferential strain inside the

vessel wall. The displacement field in (c) is superimposed on the diastolic image.

Y. Liang et al. / Journal of Biomechanics 41 (2008) 2906–2911 2909

is to develop a practical method to measure strain distributionfrom conventional clinical IVUS images by using image-basedcardiac phase retrieval and non-rigid image registration methods.

The strain measurement method based on image registrationhas been validated using synthetic motion IVUS images, andevaluated using a homogeneous phantom. Arterial wall strain is infact 3D. The current formulation of our technique does notincorporate the 2D incompressibility constraint (Liang et al.,2008). Therefore, from the aspect of how the algorithm isimplemented, it is possible to obtain a result in which bothcompressive radial strain and compressive circumferential strainare present at the same location. From the biomechanics point ofview, the concurrence of compressive strain in both the radial andcircumferential directions might be caused by either the physicalstretch of the coronary artery in the axial direction or theimposition of non-uniform forces from the surrounding tissuesdue to cardiac motion.

An advantage of the retrospective image-based cardiac phaseretrieval method is its ability to determine the cardiac phase usingonly IVUS images. There is no need for new devices or changes inestablished image acquisition procedures; thus it can readily be

implemented in the current clinical environment. Electrocardio-gram (EKG)-driven frame selection is unnecessary.

In our experience, cooperating with catheterization labora-tories in several hospitals, EKG recording is not widely usedduring clinical IVUS studies. There are two ways to incorporate theEKG into an IVUS study if it is available. One is to overlay the EKGsignal on the ultrasound record, and the other uses the EKG to gateIVUS pullback and acquisition. The EKG-based pullback procedurerequires long setup times, and considerably prolongs the acquisi-tion procedure. Furthermore, when the EKG is used in this way,IVUS images are normally acquired at only one point in the cardiaccycle, normally at the end of diastole. Images of each vessel site attwo cardiac phases (i.e., two pressures) are required to estimatestrain. Both the overlaid display of the EKG signal and externalEKG gating suffer from systematic error (Walker et al., 2002)which is absent from our method, which uses the phasic motionof the artery wall to recover the cardiac phase.

The AGL measures the variation in lumen size during thecardiac cycle. The extremes of the filtered AGL do not correspondspecifically to either systole or diastole; however, they aresufficient in our application. The two extremes of the filtered

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Fig. 5. IVUS image at a LAD site at (a) diastole and (b) systole; (c) derived displacement field in the region of the vessel wall between the segmented lumen boundary and

media-adventitia interface (blue lines), in response to the luminal pressure increase from diastole to systole; color-coded (d) radial and (e) circumferential strain inside the

vessel wall. The displacement field in (c) is superimposed on the diastolic image.

Y. Liang et al. / Journal of Biomechanics 41 (2008) 2906–29112910

AGL prescribe a pressure difference that is comparable to thepulse pressure and consistent throughout the pullback. Because ofthe size of this difference, tissue deformation, and consequentlystrain contrast are large (Ophir et al., 1991; Shapo et al., 1996).

By identifying image pairs acquired at different times at thesame vessel site, the effect of catheter movement caused bycardiac motion is essentially overcome. As a consequence, thisapproach can be applied to clinical IVUS image sequencesacquired during a continuous pullback.

The image-registration-based strain estimation method is a 2Dprocessing technique. It is unaffected by the in-plane motion ofthe catheter and can measure with improved accuracy thestructural deformation of the atherosclerotic artery wall inresponse to large luminal pressure changes. Since it measuresthe complete local 2D strain tensor, it can provide moreinformation about arterial wall mechanics than radial strainalone.

This method allows us to examine multiple sites of interestalong the artery using images from a single catheter pullback. This

is particularly useful since atherosclerosis is a multifocal disease.This method also generates multiple sub-sequences at differentpoints during the cardiac cycle, from which the phasic variation instrain can be obtained. These data may provide additionalinformation about atherosclerotic plaques.

The characterization of the plaques imaged in this study wasbased on their echogenic appearance and cannot be validated.However, the strain measurement is in principle independent ofthe echogram. The fundamental material property determiningthe strain image is the shear modulus; while the acousticproperties of soft tissue are related to its bulk modulus (Greenleafet al., 2003).

This method may also be applied to other intravascularimaging modalities, such as optical coherence tomography(OCT), which is an optical analog of IVUS with much higherspatial resolution (Fujimoto, 2003). Currently, OCT is not clinicallyavailable in the United States.

This method may not work for all clinical IVUS cases. If theplaque is relatively short axially or the axial variation of plaque

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properties is large, it may not be possible to obtain image pairswhose axial locations are close enough. One solution is to increasethe axial sampling rate by decreasing the catheter pullback speed.

In conclusion, we have examined the feasibility of a techniquebased on the retrospective image-based frame pairing and theregistration-based strain measurement to IVUS images acquiredduring a conventional IVUS procedure using instrumentationcurrently in clinical use. The major contributions of this study are:(1) the integration of (a) the image-based retrospective method toretrieve the cardiac phase and pair images at the same vessel siteand (b) registration-based strain measurement; and (2) theapplication of this combination of techniques to clinical IVUSdata obtained in a conventional setting. It is the first attempt toalign clinical images acquired at different cardiac phases during acontinuous pullback. This method yields 2D radial and circumfer-ential strain throughout the arterial cross-section and warrantsfurther investigation.

Conflicts of interest

There is no conflict of interest among the contributors to thismanuscript.

Acknowledgement

This research is supported by NIH Grant HL058856.

Appendix A. Supplementary Material

Supplementary data associated with this article can be foundin the online version at doi:10.1016/j.jbiomech.2008.08.004.

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