Ultrasound characterization of acute myocardial ischemia by quantitative texture analysis

LTRASONIC

IMAGING

8,

227-240

(1986)

ULTRASOUND CHARACTERIZATION BY QUANTITATIVE David D. McPherson 1,* Richard E. Kerberl,'

OF ACUTE MYOCARDIAL ISCHEMIA TEXTURE ANALYSIS

Philip E. Aylward' Steve M. Collins2,4:5,

Boyd M. Knosp2 Judy A. Bean3, and David J: Skorton1*2'5

Cardiovascular

Image Processing and Ultrasonic Imaging Laboratories Cardiovascular Center Departments of Internal Medicine', Electrical and Computer Engineering', Preventive Medicine and Environmental Health3, Radiology4, and Biomedical Engineering5 The University of Iowa and Veterans Administration Medical Center Iowa City, IA 52242

In this study we tested the efficacy of quantitative texture analysis in the identification of acute myocardial ischemia using an ultrasound data acquisition system that digitizes and stores echocardiographic data in polar format. In nine closed-chest dogs, data were acquired before and after coronary occlusion using a 2.4 MHz echocardiographic system. Regions of interest were analyzed at end-diastole and end-systole from the ischemic area and normal area at the same depth of field. Ultrasound data were evaluated using previously reported quantitative gray level texture measures. After occlusion, texture changes indicative of ischemia were found in systolic images. The directional component of the data analysis was important; analysis in the azimuthal direction was more accurate than in the axial direction. Six texture measures exhibited significant changes in region from control to occlusion when analyzing data in the the ischemic azimuthal direction. One false positive result occurred (significant texture change in the normal region from control to occlusion) in the azimuthal direction. Several false positive alterations in the normal regions from control to occlusion were found when the texture was evaluated in the axial direction. For accurate assessment of ischemic changes, preocclusion image data were required. We conclude that quantitative echocardiographic subtle changes in texture analysis using polar format data can identify myocardial texture such as that due to acute ischemia, using data acquired through the chest wall. @ 1986 Academic Press. Inc. Key words: I.

Echocardiography; ultrasound tissue

myocardial ischemia; characterization.

texture

analysis;

INTRODUCTION

Ultrasound has gained widespread acceptance as a reliable tool in the clinical evaluation and characterization of cardiac structure and function. An expanding field in the use of cardiac ultrasound is myocardial tissue characterization of fibrosis, ischemia or other processes that alter the composition of the myocardium. Mimbs et al. [l] and Miller et al. [2] have utilized radio frequency analysis to identify myocardial infarction in animal models by demonstrating changes in ultrasound attenuation and backscatter. The use of radio frequency data necessitates a large amount of

*

Address for correspondence and Department of Internal Medicine, Hospital, Calgary, Alberta, Canada

reprints: University TZN-2T9.

David of

D. McPherson, M.D., Calgary - Foothills 0161-7346186

227

$3.00

Copyright 0 1986 by Academic Press, Inc. All rights of reproduction in any form reserved.

MCPHERSON ET AL.

data storage and nonstandard equipment configurations. However, the utilization of two-dimensional echocardiographic image data (as opposed to radio frequency data) to evaluate myocardial acoustic properties has been considerably more difficult due to a variety of technical problems. These problems include alteration of two-dimensional images caused by operator adjustments, by the physical characteristics of the ultrasound/tissue interaction [3], and by artifactual regional echo amplitude variability produced in the imaging system itself [4,5]. Nonetheless, alterations in echo image brightness and average gray level may accompany acute ischemia We have used a standard two-dimensional ultrasound imaging system to [61. detect acute myocardial infarction in a closed-chest animal preparation by evaluating the overall distribution of echo intensities within myocardial regions of interest [7]. In addition to evaluation of the average intensity and overall distribution of echo intensities in a region of interest, the two-dimensional spatial pattern or visual "texture" of the myocardium has been useful in identifying structural abnormalities of cardiac tissue. Standard, clinical two-dimensional echocardiograms commonly demonstrate abnormal image texture in such conditions as hypertrophic cardiomyopathy [8] and amyloid heart disease [9]. We have developed methods of quantifying the regional spatial pattern of echo image data (terming this technique "quantitative texture analysis") and have shown using data from standard two-dimensional echocardiographic systems that texture analysis can be used to distinguish normal from pathologic tissue in a model of myocardial contusion [lo] and in human cardiomyopathy [ll]. These initial data demonstrated the feasibility of quantitative texture analysis, but this technique was still encumbered by the problems inherent to the imaging system itself. One such problem common to standard two-dimensional ultrasonic imaging systems is that data initially acquired in polar format (as a set of radial ultrasound lines-of-sight emanating from the transducer) are subsequently converted to rectangular coordinates for display, storage and image processing. During scan conversion, ultrasonic data undergoes interpolation and this further adds nonbiologic variability to information anaThe artifactual regional variability lyzed from the displayed images [12]. in image texture related to the characteristics of the imaging system is visually as well as when evaluating texture quantitatively. We apparent have developed an ultrasound data acquisition system (UDAS) [13] that cirof polar-to-rectangular conversion of data by digicumvents the problem tizing and storing echocardiographic data in polar format (in the format in Data acquired with UDAS and which the data were originally acquired). analyzed in polar coordinates exhibit significantly less regional variability in quantitative texture properties than do data acquired in polar conversion) format but analyzed in rectangular format (i.e., after scan Since the echocardiographic data in all standard echocardiographic [131. some point in the image acquisition systems exist in polar format at this approach to ultrasound data analysis, if proved efficacious, process, to should be easily implementable in commercial systems, and may be able detect more subtle degrees of myocardial injury than present systems. It was our purpose in the present study to evaluate ultrasound identification of acutely ischemic myocardium tissue characterization technique. Specifically, applicable hypothesis that quantitative analysis of image texture in acquired and analyzed in polar coordinates would images tion of myocardial changes in a closed-chest canine model occlusion and myocardial ischemia.

228

the feasibility of using a clinically we tested the echocardiographic permit identificaof acute coronary

TEXTURE ANALYSIS IN ISCHEMIA

II.

METHODS Animal

Preparation

Nine adult, mongrel dogs were studied (weight 18-25 kg). Each animal was anesthetized with intravenous sodium pentobarbital, 20-30 mglkg, and ketamine, 300 mg, intubated with a cuffed endotracheal tube and ventilated artificially with a mechanical respirator. Femoral arterial and venous catheters were inserted for hemodynamic monitoring and vascular access. The thorax and pericardium were opened via a left thoracotomy and the proximal circumflex coronary artery was dissected free. A balloon occluder was placed around the proximal circumflex artery. A Doppler velocity probe was positioned on the coronary artery proximal to the balloon occluder and held in place by a suction device [14]. This probe was utilized to measure coronary flow velocity in the artery before and during balloon occlusion. After the animal preparation was completed, the pericardium and thorax were closed. Echocardiographic

Evaluation

Each animal was placed in the right lateral decubitus position on a table with a cutout to allow the echocardiographic transducer to be applied from below to the right parasternal chest wall area near the point of maximal impulse [15]. A phased-array system (Toshiba SSH-1OA Sonolayergraph) with a 2.4 MHz transducer was used to obtain the images. Instrument adjustments were set for each animal using the following format: the transducer focus was set at 7.5 cm; and the dynamic range was set at 50 dB. The gain controls were adjusted in order to make the apparent myocardial brightness as uniform as possible down the center line of sight and were not changed for any animal once the control recordings had been obtained. Image Acquisition

and Display

All images were recorded directly onto 314" videotape for continuous real-time imaging and selected images were acquired in digital form using our ultrasound digital acquisition system (UDAS). Using a 280 microcomputer for control, UDAS was interfaced with the Toshiba echocardiograph and provided image data acquisition and storage [13]. With UDAS, each of the 112 lines of sight making up each video frame were digitized into 512 pixels (each pixel was approximately 0.3 mm in size). Echo amplitude was Digitized echo data were obtained quantized to 8 bits (256 gray levels). at end-systole (smallest apparent cavity area) and end-diastole (ECG R-wave) and were stored in polar format in one of the UDAS digital memories. Digitized image data were then stored on floppy disks and transferred to a PDP 11/34 computer (Digital Equipment Corporation) for further analysis. Images acquired by UDAS were reconstructed into rectangular form and displayed on a standard video monitor. The reconstruction program employs a geometric reconstruction technique similar in concept to digital scan conversion procedures employed in standard echocardiographs; the approach has been previously described [13]. Each image was displayed on a monitor screen using a Gould IP8500 image array processor. Experimental

Protocol

ultrasonic images were collected in long- and shortIn each animal, axis orientations at multiple levels throughout the left ventricle with concentration on data collection at the papillary muscle level in shortaxis views. Cross-sectional data were obtained not only in real-time on videotape, but also using UDAS at end-systole and end-diastole as described

229

MCPHERSON ET AL.

Fig.

1 This illustration shows a control systolic short-axis image on the left with the corresponding postocclusion image on the right. With occlusion, there was loss of normal wall motion in the right-hand image in the area from 6:00 to 8:00 (as identified by the real-time ultrasound images). The regions of interest in the area at risk were taken from this area in control and postocclusion images (regions 1 and 2). Regions of interest for normal areas were taken at the same depth but distant from the ischemic area in pre- and postocclusion images (regions 3 and 4). In general, the ischemic area did not have visually identifiable texture patterns distinct from the surrounding myocardium in the postocclusion images.

above. Images were first obtained in the control state. Subsequently, 2 of lidocaine and 5 mg/kg of bretylium were given intravenously prior mgk to circumflex coronary artery occlusion. Once the animal had stabilized after antiarrhythmic drug administration (5-15 minutes), the circumflex occluder was tightened. Arterial occlusion was documented by a demonstrated drop in Doppler velocity in the proximal circumflex artery to zero and by abnormal posterior left ventricular wall motion using real-time echocardiography. At two hours postocclusion, images were again taken in real time and with UDAS at anatomical levels similar to the control recordings. The animals were subsequently sacrificed with intravenous potassium chloride. Identification

of Regions

of Interest

for

Texture

Analysis

the ischemic area was initially For region of interest placement, identified in the postocclusion, real-time images as that area with abnormal wall motion (i.e., dyskinesis or akinesis); all regions of interest in the area at risk in the control and postocclusion images were taken from the center of this region, but away from the papillary muscle region. All regions of interest from the normal myocardium were taken from myocardium distant to the area at risk, but at the same distance from the transducer (Fig. 1). The identified at-risk (ischemic) and normal myocardial regions of interest were similar in anatomical position in control and postocclusion images. Regions of interest were identified as the largest rectangular area that could be placed between the endocardium and epicardium, carefully excluding epicardial and endocardial reflections. The region of but were by interest size varied from 10 to 30 pixels in each direction definition as large as possible for that image. Using cardiographic

the coordinates identified from texture was analyzed using the

230

the reconstructed corresponding

image, echounreconstructed

TEXTURE ANALYSIS IN ISCHEMIA

(polar coordinate) image data stored in the disk files. That reconstructed rectangular format images were used to identify of interest, only polar (unreconstructed) data were used for analysis of texture changes. Texture

Analysis

is, although the regions quantitative

Parameters

We have previously described our methods of quantitative texture analysis [10,13], which were derived from approaches used to analyze nonbiological image data [16,17]. These measures quantify the two-dimensional spatial pattern of gray levels within regions of echocardiographic images. Briefly, the ultrasound data were evaluated with gray level run length statistics and gray level difference statistics. A gray level run is defined as a set of consecutive, collinear pixels having the same gray level value or gray level values within a given range [16]. The length of the run is the number of pixels traversed before a change in gray level value occurs. Four gray level run-length variables were evaluated: 1) long run emphasis, 2) short run emphasis, 3) run length nonuniformity; and 4) gray level nonuniformity [lo]. The gray level run length statistics measure the homogeneity or heterogeneity of gray levels and the relative size of individual echocardiographic reflections within the area of interest. For example, regions with large individual echocardiographic reflections will yield large long run emphasis values, whereas regions containing small individual echocardiographic reflections will yield large short run emphasis values. The gray level difference statistics also relate to the homogeneity or heterogeneity of the size of the individual echocardiographic reflections within the region of interest. They were calculated by measuring the differences in gray level values between picture points separated by 1, 2, 4, and 8 pixels in both azimuthal and axial directions. From these differences four different statistics were derived: 1) contrast, 2) angular second moment, 3) entropy, and 4) mean [17]. The gray level run-length and gray level difference statistics were calculated along both the azimuthal and axial directions. Comparisons

of Regions

of Interest

of interest were compared in the following Data from the regions manner. The data in the area at risk (ischemic region) were compared between the control and postocclusion images (regions 1 vs. 2 in figure 1). The data in the area distant to the area of risk (normal region) were compared between the control and occlusion images (regions 3 vs. 4 in figure 1). Further, in the postocclusion image, the data in the ischemic compared to the normal data distant to the ischemic area but in area were Data were compared in both the same image (regions 2 vs. 4 in figure 1). the systolic and diastolic images. Statistical

Analysis

All numerical data were expressed as mean f standard error of the mean. Multivariate analysis of variance with a Bonferroni modification for multiple comparisons [18] was used to assess the significance of differences between texture measures calculated for the different regions of interest. The Bonferroni correction is based on the argument that the likelihood of a test statistic exceeding the cutoff for significance when, in fact, no true difference is present, is directly related to the number of comparisons made. Thus, the Bonferroni correction lowers the p value necessary for significance (making the test more stringent) based on the number of comparisons made. Thus, using the Bonferroni correction, a

231

MCPHERSON ET AL.

p-value significant III.

of

less than differences

0.008 existed

was necessary to indicate in the texture measures

that statistically between regions.

RESULTS Qualitative

Observations

With circumflex coronary arterial occlusion, in all animals there was a marked decrease in the systolic thickening of the area at risk (usually changing to dyskinesis - i.e. systolic wall thinning), but no gross visual change in the texture of the myocardium (Fig. 1). Quantitative

Analyses

In contrast to the lack of visual changes in myocardial texture with coronary occlusion, there were significant changes in quantitative texture measures (figure 2 shows two of the texture measures and Table 1 and figure 3 show all texture measures demonstrating significant changes in the azimuthal direction). Although all the above-mentioned texture measures were differences run on data from each region of interest, all the significant were found between the control and postocclusion systolic images; none were found using diastolic images. All data reported will refer to these systolic images. Figure 2 illustrates two of the texture parameters that changed significantly in the ischemic region between the control and postocclusion images (regions 1 and 2, respectively). For both of the parameters (gray level difference mean and gray level difference contrast), if the texture became more heterogeneous, large grey level differences would occur more When comparing the ischemic frequently, resulting in larger statistics. region in the control and postocclusion states (regions 1 and 2) and evaluating gray level differences in the azimuthal direction, six texture measshowed significant changes (Fig. 3). They included the gray level ures contrast and gray level mean variables. All these gray level contrast and gray level mean parameters increased from the control to postocclusion state. When comparing the normal area (distant to the risk area) between the control and postocclusion states (regions 3 and 4, respectively) and evaluating gray level differences in the azimuthal direction, there was

.lO

GRAY LEVEL DIFFERENCE MEAN

*

p<.ootl

. w

1 LEVEL DIFFERENCE CONTRAST

.05

(Ax=21

(Ax=21

0

PREOCCLUSION

Fig.

2

i

250

0

POSTOCCLUSION

OCCLUSION

POSTOCCLUSION

Two of the texture parameters that changed significantly in the ischemic region between the control and postocclusion images. Ax=2 indicates that gray level difference measures were calculated for a horizontal (azimuthal) spacing of two pixels.

232

TEXTURE

ANALYSIS

IN

Fig.

CON

MEAN

MEAN

MEAN

Ax=2

CON

All=4

Ax=,

Ax=2

Ax-4

n

Risk

(ischemic)

0

Remote

CONTROL

only one significant result (gray level

ISCHEJMIA

3

LJ

region

(control)

region

This figure illustrates all the texture measures exhibiting significant differences, when comparing texture (in the azimuthal direction) between the control and postocclusion states for both the risk (ischemic) and remote (normal) regions. CON = contrast. ASM = angular second motion.

texture difference found - that is, one false-positive angular second moment) (Fig. 3) (Table 1).

When evaluating both the gray level run-length and gray level difference statistics in the axial direction, wide variability of data arose. Using the run-length statistics in the axial direction, one significant difference was noted when comparing the ischemic area between the control and postocclusion images (regions 1 and 2) and one significant difference when comparing the normal region for the two states (regions 3 was noted and 4). Using the gray level difference statistics in the axial direction, measures yielded significant differences when comparing the two texture ischemic area from control to postocclusion (regions 1 and 2), and six texture measures yielded significant differences when comparing the normal area from control to postocclusion (regions 3 and 4). Thus, seven falseresults were noted when using texture parameter changes to evalupositive ate ischemia in the axial direction as compared to three true positive results. No either

significant the azimuthal

differences were noted using any texture or axial directions between the ischemic

Significant

Table 1. Direction

Area at (Ischemic

risk area)

Normal (Nonischemic area) GL = gray

Due less

Parameter Changes and Postocclusion

Parameter

Region

+ All

Texture Control

Between

data the than

Control

in the Systolic

parameters area and

in the

Azimuthal Images

Data+ Postocclusion

P

GL GL GL GL GL GL

contrast contrast contrast mean mean mean

Ax=1 Ax=2 Ax=4 Ax=1 Ax=2 Ax=4

211.6222.93 412.8t41.05 654.Ot68.60 0.045+0.0026 0.063+0.0029 0.082+0.0048

300.0+23.81 567.1t38.47 966.9T80.60 0.052+0.0021 0.075+0.0030 0.100+0.0053

0.004 0.002 0.001 0.002 0.002 0.002

GL

moment

Ax=1

0.053+0.031

0.045~0.0015

0.005

as mean

2 SEM,

level expressed Bonferroni 0.008 was

modification considered

n=9

dogs.

for multiple to be significant

233

comparisons,

a p value

of

MCPHERSON ET AL.

area in the postocclusion images (regions 2 and 4, respectively). normal That is, ischemic myocardium could not be differentiated from normal tissue without a preocclusion (control) image. IV.

DISCUSSION

The major findings of this study are that: a) quantitative texture analysis using data acquired through the chest wall in polar format can identify acute myocardial ischemia at two hours after coronary occlusion when evaluating systolic images; b) with the present system, to identify myocardial ischemia, the regions of interest in postocclusion images must c) falsebe compared to corresponding regions in the control images; positive results frequently occur when evaluating texture parameters along the scan lines, but rarely occur when evaluating texture parameters perpendicular to the scan lines. Our discussion will center on the interpretation of our data, the relationship of our results to previous observations, factors influencing our results and potential implications of this technique for future work. Interpretation

of Quantitative

Texture

Analysis

in Ischemia

The purpose of using quantitative texture analysis of two-dimensional echocardiographic data was to determine if ischemia-induced alterations in visually apparent could be myocardial acoustic properties that were not Although we were able to identify ischemia identified from image data. several questions arose while interpreting our results: using this method, for the directional differences in results (i.e., What factors account differences between data calculated along axial versus azimuthal direcWhy were the differences between ischemic and normal tissue only tions)? found in systolic images and only by comparison with control (preocclusion) images? Why were more texture measurements not significantly altered by ischemia? texture Our results showed a marked directional dependence: only measures calculated in azimuth (perpendicular to the ultrasound beam direcThe use of quantitative tion) yielded consistent changes with ischemia. texture analysis assumes that there is some correspondence between myocarHowdial structure and statistical descriptors of the texture pattern. correspondence may be affected by the changing directions of ever, this myocardial muscle fibers throughout the left ventricle which is known to of ultrasound attenuation through cardiac tissues [19]. cause anisotropy This directionality of attenuation (and therefore, presumably, backscatter) would be expected to cause a similar directional dependence of echocardioAnother important contributor to the differences in graphic image texture. our results obtained along the beam axis vs. perpendicular to the beam axis is the anisotropic point spread function of the imaging system. The subdifference in axial compared to lateral resolution characteristic stantial of most diagnostic ultrasonic imaging systems contributes to a directional appearance in echocardiographic images [4,13]. nonuniformity of texture This directionality of texture due to the attributes of the imaging system would be expected to also affect the results of quantitative texture analysis. Thus, apparent anisotropy of texture due to the imaging system was in all likelihood superimposed on any acoustic anisotropy present. Although the reasons for the specific directional nature of our present results are not clear, these factors must be taken into account when analyzing studies myocardial architecture using any ultrasonic technique. Future might explore the significance of directional differences in image texture by imaging regions of interest from varying angles. Our data demonstrated significant tissue when evaluating images ischemic

234

alterations in the acquired at end-systole,

texture but not

of at

TEXTURE ANALYSIS

IN ISCHEMIA

end-diastole. Previous data have shown that myocardial acoustic properties vary with the phase of cardiac contraction. Madaras et al. noted a decrease in integrated ultrasonic backscatter with contraction; the change averaged 3.5 dB from end-diastole to end-systole [20]. In addition, these investigators noted a blunting of the normal systolic decrease with induction of ischemia and a reestablishment of cyclical variation with reperfusion 1211. Miller and coworkers showed that end-diastolic backscatter was slightly elevated after coronary occlusion (approximately 1 dB) but, due to blunting of the normal systolic decrease in backscatter, end-systolic data were more substantially elevated compared to control data (4 dB) [22]. We have previously shown that both average echocardiographic image gray level and regional quantitative texture measures also vary with cardiac contraction in normal humans [23,24]. Thus, maximal differences between the acoustic properties of normal and ischemic myocardium may best be demonstrated at end-systole. Cur texture measures were not sufficiently sensitive to detect acoustic alterations indicative of ischemia by comparison of different regions within a single (postocclusion) image (the preocclusion data were necessary for identification of myocardial ischemia). One potential explanation is that sources of regional variability in texture other than ischemia (such as artifacts due to imaging physics/instrument-related phenomena) were not completely taken into account. We have previously noted significant regional variations in quantitative image texture, even when imaging a uniformly scattering tissue-equivalent phantom One cause of the 141. in echo amplitude in standard echocardiograms is the regional differences method of gain compensation for attenuation of the ultrasound signal by tissue interposed between the transducer and the region of interest. The chest wall and other interposed tissues attenuate ultrasound as it passes through with alteration of the frequency spectrum of the beam. These alterations may be expected to alter image texture properties, and thus, a nonoptimal method of gain compensation for attenuation by the chest wall and other tissues may have contributed results. to our Future studies using quantitative texture analysis (or other methods of ultrasound tissue characterization) would benefit from the use of a system of gain compensation designed to optimally display and store regional backscatter data with minimal interference from the effects of overlying tissue [3,25]. In addition, typical regional differences in texture parameters may need to be established in a representative group of control animals (or human subjects) to develop normal regional limits for these parameters. In this study, only a relatively small number of tissue texture measures changed significantly with ischemia. It is, however, important that some quantitative texture variables did change significantly in this model of ischemia as there were no visually apparent changes in the echocardiographic image texture with ischemia. A prior study of experimental myocardial contusion, a more gross myocardial injury that produced visually apparent changes in echocardiographic image texture, demonstrated a larger number and variety of altered texture parameters [lo]. Thus, we conclude that the different texture measures vary in their sensitivity to particular pathological changes in the myocardium. As the texture measures most appropriate for identifying particular myocardial abnormalities are yet to be defined, quantitative texture analysis might best continue to be performed using the entire range of texture parameters. Relationship

to Previous

Previous work tissue characterization myocardium. Glueck

has

Observations

demonstrated the feasibility of using ultrasound techniques in the identification of. pathological and workers [21] used radio frequency tissue character-

235

MCPHERSON ET AI,.

patization in an open chest animal model to demonstrate that backscatter with ischemia and reperfusion. The cyclical variation in terns change reperfusion. backscatter was blunted with ischemia and restored by Schnittger and coworkers [26] used a transthoracic image acquisition method myocardial and radio frequency ultrasound characterization to detect acute Their data ischemia within 30 minutes after coronary artery occlusion. of the analysis relied mainly on a statistical approach to the analysis radio frequency data and showed excellent reproducibility. Problems with using radio frequency tissue characterization for evaluation of myocardial areas at risk lie mainly in the requirement for special equipment, for extensive data storage techniques and evaluation of small regions of myocardium at one time with data from single (or a few) lines of sight. Standard two-dimensional echocardiographic imaging techniques allow evaluation of large regions of myocardium for potentially more efficient myocardial mapping of acoustic abnormalities accompanying cardiac ischemia. Fraker and coworkers [6] used a standard two-dimensional echocardiographic imaging technique in a dog model of acute myocardial ischemia and demonstrated that simple gray level (pixel brightness) was altered from to occlusion. that there were easily identifiable control They showed ultrasound image parameters that change reproducibly from control to ischemia. However, problems inherent with using echo image brightness from two-dimensional video data lie primarily in the fact that image brightness can be altered by operator adjustment and structure position within the imaging plane. As mentioned above, improved methods of gain compensation for attenuation will be required to deal effectively with this problem. Rasmussen et al. [27] recently described a method involving the use of an reference calibration which compensates for the backinternal myocardial scatter influence of the chest wall, coupled with computer acquisition and enhancement of myocardial images. The further applicability of this method to all myocardial regions remains to be determined. Factors

Influencing

Results

An important variable to consider when evaluating ultrasonic tissue texture is the amplification (gain) adjustments of the ultrasonic imaging equipment. We attempted to visually adjust the overall gain and time-gain compensation to produce a uniform brightness of myocardial echoes down the center line of sight in the control state and we did not alter these settings between control and postocclusion images. Visual adjustment of gain settings may not be accurate enough to ensure uniform backscatter from different regions of the myocardium. This becomes important when identifying the region of interest for quantitative texture evaluation. If one region moved in relation to the depth of field between images, the change in texture parameters may be due to the variation in gain settings. We attempted to control for this variable by keeping the ischemic and normal regions in as similar as possible positions relative to the depth of field of the transducer. However as discussed above, this visual method of adjusting the time-gain compensation may not be sufficiently accurate to overcome all regional data characterization problems and a more accurate system of gain compensation may be required. Another important variable to consider is the fact that azimuthal resolution degrades markedly as a function of range outside of the focal zone. Although the exact influence of varying resolution cell size on echocardiographic image texture analysis has not been determined, Aylward et al. [13] demonstrated that variation in texture measures which occurred due to different azimuthal positions of regions of interest in images of a Therefore azimuphantom was greatly reduced by the use of polar analysis. thal alteration of texture parameters may be less of an issue when data are evaluated in polar format.

236

TEXTURE ANALYSIS IN ISCHEMIA

With ischemia, there is lack of thickening of the myocardium and often thinning of the myocardium with systole [28]. Thus, the regions of interto est placed within the ischemic areas during systole tended to be small ensure that endocardial and epicardial reflections were avoided. Thus, less data are available to evaluate texture characteristics in small interest and these data may be less representative of all the regions of If irregularly-shaped regions could be idendata in the ischemic region. tified that encompassed the entire area at risk, then the problem of a We kept our regions rectangular small region of interest may be overcome. in shape since the effect of region shape (especially irregular regions) on texture calculations has not been studied. We attempted to control two other potentially important variables: the influence of overlap coronary flow and the acoustic properties of papillary muscle regions. Regions close to the edges of the perfusion field of one coronary artery may have a dual blood supply and thus may not become ischemic with occlusion of one coronary artery. The size of this area is variable and often the subject of debate [29]. We placed the region of interest in the center of the risk area to lessen the chance that overlap flow would influence our measurements. Secondly, due to their central position within the left ventricle, the acoustic properties of the papillary muscles must be considered in choosing regions of interest. As tisthe echo appearance of these muscles is frequently bright, myocardial sue characterization parameters might be significantly altered if these Again, identifying regions excluding regions are included in the analysis. the papillary muscles and away from regions of overlap flow requires small regions of interest in the postocclusion state for the ischemic area. This choice of small regions allowed us to obtain data that we felt was as representative as possible of the ischemic zone, allowing for the constraints of our system. Implications Two-dimensional echocardiographic tissue characterization using quantitative texture analysis in polar coordinates is a promising technique. We have identified in an in-vivo animal preparation that this technique can detect acute ischemia and to our knowledge this is the first report of this application. However, we were unable to identify textural changes indicative of ischemia without comparison with preocclusion (control) data. Thus, before widespread clinical implementation will be feasible, further and thereby investigation will need to be directed at reducing artifacts improving the sensitivity of the method. By detecting ischemia, this technique has the potential to identify areas at risk of infarction and may be able to identify changes with infarction or reperfusion. Ultimately, if noninvasive reperfusion techniques are to be widely used (e.g. tissue-type plasminogen activator), two-dimensional echocardiographic tissue characterization may have a role in evaluating the efficacy of reperfusion. One advantage of our method of tissue characterization using quantitative texture analysis is that relatively standard echocardiographic data can be used. The addition of the ultrasound data acquisition system (UDAS) to our system allowed us to evaluate texture before scan conversion (i.e., in The relatively simple application of texture analysis polar coordinates). to echocardiographic image data, if further improved and validated, would allow regional mapping of myocardial ischemia and/or infarction in an acute clinical setting. ACKNOWLEDGEMENTS This Specialized

study was supported in part by Program Project Grant HL14388, Center of Research in Ischemic Heart Disease HL32295, from

237

and the

MCPHERSON ET AL.

National Bethesda,

Lung and Blood Institute, National Heart, MD. and by a grant from the U.S. Veterans

Institutes Administration.

of

Health,

Dr. McPherson was an Alberta Heritage Foundation for Medical Research Dr. Aylward was a National Heart and a Canadian Heart Foundation Fellow. Dr. Skorton is the Foundation of Australia Overseas Research Fellow. recipient of Research Career Development Award K04HL01290 from the National National Institutes of Health, Bethesda, Heart, Lung, and Blood Institute, MD. This material was presented cal Research meetings, November, Heart Association Annual Meeting,

in part at the Central Society for Clini1984, Chicago, Illinois, and the American November 1984, Miami Beach, Florida. Ruth Hurlburt, in the preparation M.S.E.E. for their

The authors wish to thank Marlene Blakley, and Rita Yeggy for their expert help Frisbie, manuscript, and Robert Kieso M.A. and Doug Eltoft technical assistance.

Carolyn of this expert

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