Peter Lysyansky

Myocardial Strain Measurement With 2-Dimensional Speckle-Tracking Echocardiography: Definition of Normal Range

The interpretation of wall motion is an important component of echocardiography but remains a source of variation between observers. It has been believed that automated quantification of left ventricular (LV) systolic function by measurement of LV systolic strain from speckle-tracking echocardiography might be helpful. This multicenter study of nearly 250 volunteers without evidence of cardiovascular disease showed an average LV peak systolic strain of -18.6 +/- 0.1%. Although strain was influenced by weight, blood pressure, and heart rate, these features accounted for only 16% of variance. However, there was significant segmental variation of regional strain to necessitate the use of site-specific normal ranges.

A new tool for automatic assessment of segmental wall motion based on longitudinal 2D strain: a multicenter study by the Israeli Echocardiography Research Group.

Background— Identification and quantification of segmental left ventricular wall motion abnormalities on echocardiograms is of paramount clinical importance but is still performed by a subjective visual method. We constructed an automatic tool for assessment of wall motion based on longitudinal strain. Methods and Results— Echocardiograms of 105 patients (3 apical views) were blindly analyzed by 12 experienced readers. Visual segmental scores (VSS) and peak systolic longitudinal strain were assigned to each of 18 segments per patient. Ranges of peak systolic longitudinal strain that best fit VSS (by receiver operating characteristic analysis) were used to generate automatic segmental scores (ASS). Comparisons of ASS and VSS were performed on 1952 analyzable segments. There was agreement of wall motion scores between both methods in 89.6% of normal, 39.5% of hypokinetic, and 69.4% of akinetic segments. Correlation between methods was r =0.63 ( P <0.0001). Interobserver and intraobserver reliability using interclass correlation for scoring segmental wall motion into 3 scores by ASS was 0.82 and 0.83 and by VSS 0.70 and 0.69, respectively. Compared with VSS (majority rule), ASS had a sensitivity, specificity, and accuracy of 87%, 85%, and 86%, respectively. ASS and VSS had similar success rates for correct identification of wall motion abnormalities in territories supplied by culprit arteries. VSS had greater specificity and positive predictive values, whereas ASS had higher sensitivity and negative predictive values for identifying the culprit artery. Conclusions— Automatic quantification of wall motion on echocardiograms by this tool performs as well as visual analysis by experienced echocardiographers, with a greater reliability and similar agreement to angiographic findings. Received December 16, 2008; accepted November 17, 2009. # CLINICAL PERSPECTIVE {#article-title-2}Background—Identification and quantification of segmental left ventricular wall motion abnormalities on echocardiograms is of paramount clinical importance but is still performed by a subjective visual method. We constructed an automatic tool for assessment of wall motion based on longitudinal strain. Methods and Results—Echocardiograms of 105 patients (3 apical views) were blindly analyzed by 12 experienced readers. Visual segmental scores (VSS) and peak systolic longitudinal strain were assigned to each of 18 segments per patient. Ranges of peak systolic longitudinal strain that best fit VSS (by receiver operating characteristic analysis) were used to generate automatic segmental scores (ASS). Comparisons of ASS and VSS were performed on 1952 analyzable segments. There was agreement of wall motion scores between both methods in 89.6% of normal, 39.5% of hypokinetic, and 69.4% of akinetic segments. Correlation between methods was r=0.63 (P<0.0001). Interobserver and intraobserver reliability using interclass correlation for scoring segmental wall motion into 3 scores by ASS was 0.82 and 0.83 and by VSS 0.70 and 0.69, respectively. Compared with VSS (majority rule), ASS had a sensitivity, specificity, and accuracy of 87%, 85%, and 86%, respectively. ASS and VSS had similar success rates for correct identification of wall motion abnormalities in territories supplied by culprit arteries. VSS had greater specificity and positive predictive values, whereas ASS had higher sensitivity and negative predictive values for identifying the culprit artery. Conclusions—Automatic quantification of wall motion on echocardiograms by this tool performs as well as visual analysis by experienced echocardiographers, with a greater reliability and similar agreement to angiographic findings.

Delineation of cardiac twist by a sonographically based 2-dimensional strain analysis method: an in vitro validation study.

Objective. Normal left ventricular contraction involves a twisting component that helps augment stroke volume, the unwinding of which also very usefully contributes to early diastolic filling. Abnormalities of cardiac twist have been related to abnormal cardiac function. We sought to quantify the twisting action using a new sonographically based angle‐independent motion‐detecting echo method. Methods. A twist model was developed with a variable‐speed motor to rotate a wheel in water bath. A freshly harvested pig heart was mounted on it as a twist phantom. Short axis views were acquired with a GE/VingMed Vivid 7 system (GE Healthcare, Milwaukee, WI) at 3.5 MHz and more than 100 frames/s. Eight different speeds (30–100 cycles/min of winding and unwinding) were studied at 5 degrees of rotation (10°, 20°, 30°, 40°, and 50°). Data were analyzed off‐line for twist analysis with a new 2‐dimensional speckle‐tracking–based program (2‐dimensional strain rate method [2DSR]) embedded in EchoPac software (GE Healthcare). Ten freshly harvested pig hearts were studied in this model. Results. The 2DSR program tracked the twist well (mean determination at 10° = 16.88° ± 1.81° [SD]; at 20° = 26.5° ± 1.05°; at 30° = 36.47° ± 1.31°; at 40° = 44.03° ± 1.39°; and at 50° = 54.1° ± 1.96°). Conclusions. The 2DSR program can be used to study twisting action of the heart.

A New Tool for Automatic Assessment of Segmental Wall Motion Based on Longitudinal 2D StrainCLINICAL PERSPECTIVE: A Multicenter Study by the Israeli Echocardiography Research Group

Background— Identification and quantification of segmental left ventricular wall motion abnormalities on echocardiograms is of paramount clinical importance but is still performed by a subjective visual method. We constructed an automatic tool for assessment of wall motion based on longitudinal strain. Methods and Results— Echocardiograms of 105 patients (3 apical views) were blindly analyzed by 12 experienced readers. Visual segmental scores (VSS) and peak systolic longitudinal strain were assigned to each of 18 segments per patient. Ranges of peak systolic longitudinal strain that best fit VSS (by receiver operating characteristic analysis) were used to generate automatic segmental scores (ASS). Comparisons of ASS and VSS were performed on 1952 analyzable segments. There was agreement of wall motion scores between both methods in 89.6% of normal, 39.5% of hypokinetic, and 69.4% of akinetic segments. Correlation between methods was r =0.63 ( P <0.0001). Interobserver and intraobserver reliability using interclass correlation for scoring segmental wall motion into 3 scores by ASS was 0.82 and 0.83 and by VSS 0.70 and 0.69, respectively. Compared with VSS (majority rule), ASS had a sensitivity, specificity, and accuracy of 87%, 85%, and 86%, respectively. ASS and VSS had similar success rates for correct identification of wall motion abnormalities in territories supplied by culprit arteries. VSS had greater specificity and positive predictive values, whereas ASS had higher sensitivity and negative predictive values for identifying the culprit artery. Conclusions— Automatic quantification of wall motion on echocardiograms by this tool performs as well as visual analysis by experienced echocardiographers, with a greater reliability and similar agreement to angiographic findings. Received December 16, 2008; accepted November 17, 2009. # CLINICAL PERSPECTIVE {#article-title-2}Background—Identification and quantification of segmental left ventricular wall motion abnormalities on echocardiograms is of paramount clinical importance but is still performed by a subjective visual method. We constructed an automatic tool for assessment of wall motion based on longitudinal strain. Methods and Results—Echocardiograms of 105 patients (3 apical views) were blindly analyzed by 12 experienced readers. Visual segmental scores (VSS) and peak systolic longitudinal strain were assigned to each of 18 segments per patient. Ranges of peak systolic longitudinal strain that best fit VSS (by receiver operating characteristic analysis) were used to generate automatic segmental scores (ASS). Comparisons of ASS and VSS were performed on 1952 analyzable segments. There was agreement of wall motion scores between both methods in 89.6% of normal, 39.5% of hypokinetic, and 69.4% of akinetic segments. Correlation between methods was r=0.63 (P<0.0001). Interobserver and intraobserver reliability using interclass correlation for scoring segmental wall motion into 3 scores by ASS was 0.82 and 0.83 and by VSS 0.70 and 0.69, respectively. Compared with VSS (majority rule), ASS had a sensitivity, specificity, and accuracy of 87%, 85%, and 86%, respectively. ASS and VSS had similar success rates for correct identification of wall motion abnormalities in territories supplied by culprit arteries. VSS had greater specificity and positive predictive values, whereas ASS had higher sensitivity and negative predictive values for identifying the culprit artery. Conclusions—Automatic quantification of wall motion on echocardiograms by this tool performs as well as visual analysis by experienced echocardiographers, with a greater reliability and similar agreement to angiographic findings.

A New Tool for Automatic Assessment of Segmental Wall Motion Based on Longitudinal 2D StrainCLINICAL PERSPECTIVE

Background— Identification and quantification of segmental left ventricular wall motion abnormalities on echocardiograms is of paramount clinical importance but is still performed by a subjective visual method. We constructed an automatic tool for assessment of wall motion based on longitudinal strain. Methods and Results— Echocardiograms of 105 patients (3 apical views) were blindly analyzed by 12 experienced readers. Visual segmental scores (VSS) and peak systolic longitudinal strain were assigned to each of 18 segments per patient. Ranges of peak systolic longitudinal strain that best fit VSS (by receiver operating characteristic analysis) were used to generate automatic segmental scores (ASS). Comparisons of ASS and VSS were performed on 1952 analyzable segments. There was agreement of wall motion scores between both methods in 89.6% of normal, 39.5% of hypokinetic, and 69.4% of akinetic segments. Correlation between methods was r =0.63 ( P <0.0001). Interobserver and intraobserver reliability using interclass correlation for scoring segmental wall motion into 3 scores by ASS was 0.82 and 0.83 and by VSS 0.70 and 0.69, respectively. Compared with VSS (majority rule), ASS had a sensitivity, specificity, and accuracy of 87%, 85%, and 86%, respectively. ASS and VSS had similar success rates for correct identification of wall motion abnormalities in territories supplied by culprit arteries. VSS had greater specificity and positive predictive values, whereas ASS had higher sensitivity and negative predictive values for identifying the culprit artery. Conclusions— Automatic quantification of wall motion on echocardiograms by this tool performs as well as visual analysis by experienced echocardiographers, with a greater reliability and similar agreement to angiographic findings. Received December 16, 2008; accepted November 17, 2009. # CLINICAL PERSPECTIVE {#article-title-2}Background—Identification and quantification of segmental left ventricular wall motion abnormalities on echocardiograms is of paramount clinical importance but is still performed by a subjective visual method. We constructed an automatic tool for assessment of wall motion based on longitudinal strain. Methods and Results—Echocardiograms of 105 patients (3 apical views) were blindly analyzed by 12 experienced readers. Visual segmental scores (VSS) and peak systolic longitudinal strain were assigned to each of 18 segments per patient. Ranges of peak systolic longitudinal strain that best fit VSS (by receiver operating characteristic analysis) were used to generate automatic segmental scores (ASS). Comparisons of ASS and VSS were performed on 1952 analyzable segments. There was agreement of wall motion scores between both methods in 89.6% of normal, 39.5% of hypokinetic, and 69.4% of akinetic segments. Correlation between methods was r=0.63 (P<0.0001). Interobserver and intraobserver reliability using interclass correlation for scoring segmental wall motion into 3 scores by ASS was 0.82 and 0.83 and by VSS 0.70 and 0.69, respectively. Compared with VSS (majority rule), ASS had a sensitivity, specificity, and accuracy of 87%, 85%, and 86%, respectively. ASS and VSS had similar success rates for correct identification of wall motion abnormalities in territories supplied by culprit arteries. VSS had greater specificity and positive predictive values, whereas ASS had higher sensitivity and negative predictive values for identifying the culprit artery. Conclusions—Automatic quantification of wall motion on echocardiograms by this tool performs as well as visual analysis by experienced echocardiographers, with a greater reliability and similar agreement to angiographic findings.