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Ultrasonic tissue characterization of infarcted myocardium by transesophageal echocardiography
Journal o f the American Society o f Echocardiography Volume 8 Number 3
34D
ANALYSIS A N D C L A S S I F I C A T I O N O F MYOCARDIAL TISSUE AFTER MYOCARDIAL INFARCTION USING WAVELET IMAGE DECOMPOSITION Aleksandra Mojsihivic, MSe, *Aleksandar D. Popovic, MD, PhD, *Aleksandar N. Neskovic, MD, Miodrag Popnvic, PhD. Faculty o f Electrical Engineering and Noninvasive Cardiology Laboratory, *ClinicalHospital Center Zemun, Belgrade University, Belgrade, Yugoslavia
Abstracts
36D
Xl -- x2
C2 +-n2
(rib n2 : number of samples from infarcted and normal myocardium, respectively; 2 I, 22, Cb C2: corresponding feature vector mean values and cnvariance matrices). RESULTS: Significant difference in myocardial texture was detected between infarcted and normal tissue in pts with occluded IRA (t=14+4), whereas no difference was detected in pts with patent IRA (t-2+0.5). CONCLUSION: These data indicate that our method for tissue characterization may be used for prediction of successful reperfusion in the early post-infarction period.
35D
TISSUE C H A R A C T E R I Z A T I O N B Y I N T E G R A T E D BACKSCATTER USING NEW COMMERCIALLY PRODUCED SOFTWARE I N T R A N S P L A N T E D AND C A R D I O M Y O P A T H I C H E A R T S Marc A. Kates DO, Hector O. Ventura MD, Mandeep R. Mehra MD, Mario F. Meza MD, Susan Revall, Dwight D. Stapleton MD,FrankW. Smart MD, Joseph P. Murgo MD, Jorge Cheirif MD, Ochsner Medical Institutions, New Orleans, L A Investigators have long marched for a safe and noninvasive means to identify and follow changes in abnormal myocardium. Cardiac cycle-dependent variation of the integrated backscatter (IB) signal, which has been shown to be reduced in pathologic states, including ischemia, infarction, hypertrophy, allograft rejection, and cardiomyopathy, has shown promise but is limited by lack of standardized equipment to analyze IB. To validate a new commercially produced software package (Hewlett-Packard) which may standardize future investigation with online analysis oflB, we studied 8 controls (normal LV structure and function), 18 heart transplant recipients (HTx) (normal LV function), and 10 patients with endstage cardiomyopathy (DCM). The septum and posterior walls in the parastemal long axis, and 12, 3,6 and 9 o'clock regions in the short axis were analyzed. Results are shown as mean cyclic variation in decibels (*p<0.02 and "~p<0.05). control pts (C} Septum 5.04 • ~ost. Wall 5.01 • 12 4.68• 4.93 +9,45 5.85 • 5.31 •
HXx pts 3,31+-1.67 3.92• 3.23 • 2.95• 4.42+9.13 3.42•
DCM pts C vs HTx C vs DCM 3.03 5:1.47 4.15 • ns ns I 2.95• ~" 1. 2.50 • " * 3.78• ns 1 2.54• * *
Diastolic-to-systolic variation of IB was reduced in every region of myocardium studied in HTx and DCM groups as compared to controls. No region showed significant difference between the HTx and DCM groups, lntraobserver and interobserver variability were 6.5% and 5.7%, respectively. Reproducibility over a 3-monthinterval was 7.5%. We conclude that 1) cyclic variation of IB is reduced in heart transplant recipients and patients with end-stage cardiomyopathy; 2) myocardialtissue characterization can be performed using commercially produced software that allows onqine analysis of IB, this may be a significant step leading to the standardization of results among Investigators;and 3) results are obtained with a low intra- and interobserver variability, and are reproducible over time.
ULTRASONIC TISSUE CHARACTERIZATION OF INFARCTED MYOCAROIUM BY TRANSESOPHAGEAL ECHOCARDIOGRAPHY Scott D. Solomon MD, Luis Maas SM, Ann Cell AB, John Fox MD, Stanton Shernan MD. Hard Kytomaa PhD, Richard T. Lee MD. Brigham and Women's Hospital, Harvard Medical School & Massachusetts Institute of Technology, Boston and Cambridge, MA Objectives: To prospectively test an approach to myocardial tissue characterization based on two-dimensional autocorrelation, which mathematically characterizes the prominence and spacing between textural elements that comprise an image. Methods: Echoeardiographic backseatter data were obtained by Transesophageal Echocardiography (TEE) from 19 patients undergoing coronary bypass surgery. Echo images were obtained using linear post-processing from the anterior and posterior left ventricular walls in the transgastric short axis view. The twodimensional autocorrelation was calculated from 64x64 pixel regions of interest from digitized images for all frames of 3 consecutive cardiac cycles. Myocardial segments were categorized as infarcted if they were in the distribution of an occluded major coronary artery by angiography and demonstrated akinesis by echocardiography. Results: In a blinded analysis, three statistical parameters providing topographical representations of the autoeorrelations derived from echocardiographic images were significantly different in 8 regions of normal myocardium compared with 11 infarcted regions: Full width at half maximum (FWHM), Area under curve/Maximum (Area/Max), and Area under the Normalized Frequ~ ,ncy Spectrum (A Normals (n=8) infarcts ( n = l f ) p-value Mean + sd Mean + sd FWHM 0.44• mm 0.35+0.06 mm 0.003 Area/Max 0.37• mm 0.27• mm 003 AuNorm 33.5 • 10.5 49.3r 0.02 Conclusions: This study suggests that by characterizing the spatial distribution of eehocardiographic backscatter data, autocorrelation of TEE based images may be a useful statistical technique to distinguish normal from infarcted myonardium.
In order to investigate the relationship of texture properties of the infarcted myocardium and the patency of the infarct-related artery" (IRA), we have developed a new multiresohition approach to texture characterization. The method was applied 14 pts after myocardial infarction (7 pts with patent IRA and 7 pts with occluded IRA) before discharge. M E T H O D : Our method pertbrrns an image decomposition with filter banks derived from wavelet functions. In the first step, the tissue sample is decomposed into four spatially oriented channels, representing t) low frequency data, 2) vertical high frequencies (horizontal edges), 3) horizontal high frequencies (vertical edges), and 4) high frequencies in both directions (corners). This procedure is repeated for different image resolutions. In the second step, several texture energy measurements arecothputed for each decomposed image. These values are used as feature vector components in the classification phase. We have proposed the following modification of T-test as a classification criterion:
t= ~
393
37D
AUTOMATIC MEASUREMENT OF FORWARD FLOW USING C O L O R DOPPLER FLOW INTEGRATION: IN VITRO VALIDATION IN A PULSATILE MODEL Min Pu, MD, Phi), Hiroyuki Tsujino*, BSE, Pieter M. Vandervoort, MD, James D. Thomas, MD. Cardiovascular Imaging Center, Cleveland Clinic Foundation, Cleveland, OH, and *Toshiba Corp., Nasu, Japan Quantification of volumetric flow remains an important goa~ in echocardiography. Flow can be calculated from the product of flow velocity and cross sectional area, assuming a fiat velocity profile, hut this requires 2 separate tmaging windows for these components and angle correction for the PW measurement. A new technique, assummg neither a fiat profile nor collinearity of flow to the scan line, has been developed (Toshiba SSA-380A) for automated cardiac output measurement (ACOM). Using digital color Doppler velocities and perfoninng spatiotempora~ flow integration across a selected velocity profile, cardiac output can be calculated in 5 to 10 seconds of computational time. Methods: To validate this method, data were gathered from an in vitro flow model with a sinusoidat pulsatile velocity time course (EchoCal), known to have a fiat velocity profile across a 1.0 cm tube. Stroke volume was calculated using ACOM by double integration of digital color Doppler velocities in space (across the tube) and in time (through the flow period), assuming hemiaxial symmetry: ff~ r v(r,t) dr dt, where v(r,t) is the velocity at a distance r from the centerline of the tube and at time t during the forward flow cycle. Stroke volume (SV) and peak flow (Q) from ACOM were compared with measurements obtained using pulsed Doppler velocity and the known area of the tube. Results: Peak flow by PW ranged from 33 to 79 ml/sec with a stroke volume (relatively fixed by design of the model, mean~+S.D.) of 31.3_+0.7 ml. There was excellent agreement between ACOM (y) and PW (x) measurements of stroke volume (ASV (ACOM - PW) = -0A_+I 2 ml); and peak flow (y = 10x + 1.9, r = 0.986, p<0.0001, AQ (ACOM - PW) = 2.0+~.6 ml/see). Conclusions: 1) Automatic integration of color Doppler digital velocities with ACOM is a feasible new method for quantitating flow. 2) It is simpler, faster, and uses fewer imaging windows than the conventional PW method. 3) Compared with PW flow estimation, ACOM yields accurate flow and stroke volume measurements.
34D
ANALYSIS A N D C L A S S I F I C A T I O N O F MYOCARDIAL TISSUE AFTER MYOCARDIAL INFARCTION USING WAVELET IMAGE DECOMPOSITION Aleksandra Mojsihivic, MSe, *Aleksandar D. Popovic, MD, PhD, *Aleksandar N. Neskovic, MD, Miodrag Popnvic, PhD. Faculty o f Electrical Engineering and Noninvasive Cardiology Laboratory, *ClinicalHospital Center Zemun, Belgrade University, Belgrade, Yugoslavia
Abstracts
36D
Xl -- x2
C2 +-n2
(rib n2 : number of samples from infarcted and normal myocardium, respectively; 2 I, 22, Cb C2: corresponding feature vector mean values and cnvariance matrices). RESULTS: Significant difference in myocardial texture was detected between infarcted and normal tissue in pts with occluded IRA (t=14+4), whereas no difference was detected in pts with patent IRA (t-2+0.5). CONCLUSION: These data indicate that our method for tissue characterization may be used for prediction of successful reperfusion in the early post-infarction period.
35D
TISSUE C H A R A C T E R I Z A T I O N B Y I N T E G R A T E D BACKSCATTER USING NEW COMMERCIALLY PRODUCED SOFTWARE I N T R A N S P L A N T E D AND C A R D I O M Y O P A T H I C H E A R T S Marc A. Kates DO, Hector O. Ventura MD, Mandeep R. Mehra MD, Mario F. Meza MD, Susan Revall, Dwight D. Stapleton MD,FrankW. Smart MD, Joseph P. Murgo MD, Jorge Cheirif MD, Ochsner Medical Institutions, New Orleans, L A Investigators have long marched for a safe and noninvasive means to identify and follow changes in abnormal myocardium. Cardiac cycle-dependent variation of the integrated backscatter (IB) signal, which has been shown to be reduced in pathologic states, including ischemia, infarction, hypertrophy, allograft rejection, and cardiomyopathy, has shown promise but is limited by lack of standardized equipment to analyze IB. To validate a new commercially produced software package (Hewlett-Packard) which may standardize future investigation with online analysis oflB, we studied 8 controls (normal LV structure and function), 18 heart transplant recipients (HTx) (normal LV function), and 10 patients with endstage cardiomyopathy (DCM). The septum and posterior walls in the parastemal long axis, and 12, 3,6 and 9 o'clock regions in the short axis were analyzed. Results are shown as mean cyclic variation in decibels (*p<0.02 and "~p<0.05). control pts (C} Septum 5.04 • ~ost. Wall 5.01 • 12 4.68• 4.93 +9,45 5.85 • 5.31 •
HXx pts 3,31+-1.67 3.92• 3.23 • 2.95• 4.42+9.13 3.42•
DCM pts C vs HTx C vs DCM 3.03 5:1.47 4.15 • ns ns I 2.95• ~" 1. 2.50 • " * 3.78• ns 1 2.54• * *
Diastolic-to-systolic variation of IB was reduced in every region of myocardium studied in HTx and DCM groups as compared to controls. No region showed significant difference between the HTx and DCM groups, lntraobserver and interobserver variability were 6.5% and 5.7%, respectively. Reproducibility over a 3-monthinterval was 7.5%. We conclude that 1) cyclic variation of IB is reduced in heart transplant recipients and patients with end-stage cardiomyopathy; 2) myocardialtissue characterization can be performed using commercially produced software that allows onqine analysis of IB, this may be a significant step leading to the standardization of results among Investigators;and 3) results are obtained with a low intra- and interobserver variability, and are reproducible over time.
ULTRASONIC TISSUE CHARACTERIZATION OF INFARCTED MYOCAROIUM BY TRANSESOPHAGEAL ECHOCARDIOGRAPHY Scott D. Solomon MD, Luis Maas SM, Ann Cell AB, John Fox MD, Stanton Shernan MD. Hard Kytomaa PhD, Richard T. Lee MD. Brigham and Women's Hospital, Harvard Medical School & Massachusetts Institute of Technology, Boston and Cambridge, MA Objectives: To prospectively test an approach to myocardial tissue characterization based on two-dimensional autocorrelation, which mathematically characterizes the prominence and spacing between textural elements that comprise an image. Methods: Echoeardiographic backseatter data were obtained by Transesophageal Echocardiography (TEE) from 19 patients undergoing coronary bypass surgery. Echo images were obtained using linear post-processing from the anterior and posterior left ventricular walls in the transgastric short axis view. The twodimensional autocorrelation was calculated from 64x64 pixel regions of interest from digitized images for all frames of 3 consecutive cardiac cycles. Myocardial segments were categorized as infarcted if they were in the distribution of an occluded major coronary artery by angiography and demonstrated akinesis by echocardiography. Results: In a blinded analysis, three statistical parameters providing topographical representations of the autoeorrelations derived from echocardiographic images were significantly different in 8 regions of normal myocardium compared with 11 infarcted regions: Full width at half maximum (FWHM), Area under curve/Maximum (Area/Max), and Area under the Normalized Frequ~ ,ncy Spectrum (A Normals (n=8) infarcts ( n = l f ) p-value Mean + sd Mean + sd FWHM 0.44• mm 0.35+0.06 mm 0.003 Area/Max 0.37• mm 0.27• mm 003 AuNorm 33.5 • 10.5 49.3r 0.02 Conclusions: This study suggests that by characterizing the spatial distribution of eehocardiographic backscatter data, autocorrelation of TEE based images may be a useful statistical technique to distinguish normal from infarcted myonardium.
In order to investigate the relationship of texture properties of the infarcted myocardium and the patency of the infarct-related artery" (IRA), we have developed a new multiresohition approach to texture characterization. The method was applied 14 pts after myocardial infarction (7 pts with patent IRA and 7 pts with occluded IRA) before discharge. M E T H O D : Our method pertbrrns an image decomposition with filter banks derived from wavelet functions. In the first step, the tissue sample is decomposed into four spatially oriented channels, representing t) low frequency data, 2) vertical high frequencies (horizontal edges), 3) horizontal high frequencies (vertical edges), and 4) high frequencies in both directions (corners). This procedure is repeated for different image resolutions. In the second step, several texture energy measurements arecothputed for each decomposed image. These values are used as feature vector components in the classification phase. We have proposed the following modification of T-test as a classification criterion:
t= ~
393
37D
AUTOMATIC MEASUREMENT OF FORWARD FLOW USING C O L O R DOPPLER FLOW INTEGRATION: IN VITRO VALIDATION IN A PULSATILE MODEL Min Pu, MD, Phi), Hiroyuki Tsujino*, BSE, Pieter M. Vandervoort, MD, James D. Thomas, MD. Cardiovascular Imaging Center, Cleveland Clinic Foundation, Cleveland, OH, and *Toshiba Corp., Nasu, Japan Quantification of volumetric flow remains an important goa~ in echocardiography. Flow can be calculated from the product of flow velocity and cross sectional area, assuming a fiat velocity profile, hut this requires 2 separate tmaging windows for these components and angle correction for the PW measurement. A new technique, assummg neither a fiat profile nor collinearity of flow to the scan line, has been developed (Toshiba SSA-380A) for automated cardiac output measurement (ACOM). Using digital color Doppler velocities and perfoninng spatiotempora~ flow integration across a selected velocity profile, cardiac output can be calculated in 5 to 10 seconds of computational time. Methods: To validate this method, data were gathered from an in vitro flow model with a sinusoidat pulsatile velocity time course (EchoCal), known to have a fiat velocity profile across a 1.0 cm tube. Stroke volume was calculated using ACOM by double integration of digital color Doppler velocities in space (across the tube) and in time (through the flow period), assuming hemiaxial symmetry: ff~ r v(r,t) dr dt, where v(r,t) is the velocity at a distance r from the centerline of the tube and at time t during the forward flow cycle. Stroke volume (SV) and peak flow (Q) from ACOM were compared with measurements obtained using pulsed Doppler velocity and the known area of the tube. Results: Peak flow by PW ranged from 33 to 79 ml/sec with a stroke volume (relatively fixed by design of the model, mean~+S.D.) of 31.3_+0.7 ml. There was excellent agreement between ACOM (y) and PW (x) measurements of stroke volume (ASV (ACOM - PW) = -0A_+I 2 ml); and peak flow (y = 10x + 1.9, r = 0.986, p<0.0001, AQ (ACOM - PW) = 2.0+~.6 ml/see). Conclusions: 1) Automatic integration of color Doppler digital velocities with ACOM is a feasible new method for quantitating flow. 2) It is simpler, faster, and uses fewer imaging windows than the conventional PW method. 3) Compared with PW flow estimation, ACOM yields accurate flow and stroke volume measurements.