Abstract:Currently, the most effective non-invasive method for early diagnosis of coronary artery disease is the cardiac stress test. In this test, stress is induced by treadmill exercise or with a pharmacologic agent such as dobutamine, and myocardium with insufficient coronary flow reserve, usually caused by coronary stenosis, experiences an imbalance between oxygen supply and demand known as demand ischemia. This causes altered mechanical and electrical behavior that is often identified using cardiac imaging. The me… Show more
“…have shown that the standard deviation of volumes computed from segmentation of RT3D images by different observers is 8% of the mean end‐diastolic volume (EDV) and 13% of the mean end‐systolic volume (ESV). Using data from our previously published study of supply ischemia in a canine model, we similarly found relative standard deviations across 5 observers of 9% for EDV and 12% for ESV . Regional wall‐motion analysis is more susceptible to small, local segmentation errors that tend to cancel out in volume calculations.…”
Section: Discussionmentioning
confidence: 56%
“…Therefore, we found a somewhat higher variability of AAFs computed from the same segmentations: the standard deviation of AAF across the 5 observers was 6% of the endocardial surface for a group of occlusions with an average size of 25%. However, the average error in AAF compared to ischemic region sized assessed by microspheres ranged from 2 ± 12% to 8 ± 13% for the 5 observers, compared to 14% and 19% for visual assessment of the number of segments affected . These results suggest that user‐assisted segmentation using current commercial software is sufficient to yield consistent, accurate estimates of ischemic region size from ∆3DFS.…”
Section: Discussionmentioning
confidence: 88%
“…However, the average error in AAF compared to ischemic region sized assessed by microspheres ranged from 2 AE 12% to 8 AE 13% for the 5 observers, compared to 14% and 19% for visual assessment of the number of segments affected. 15,41 These results suggest that user-assisted segmentation using current commercial software is sufficient to yield consistent, accurate estimates of ischemic region size from Δ3DFS. In addition, semiautomatic segmentation software for 3DE continues to improve in both accuracy and ease of use, reducing the time required for clinical application of Δ3DFS.…”
Section: Application To Clinical Diagnosismentioning
confidence: 79%
“…Using data from our previously published study of supply ischemia in a canine model, 15 we similarly found relative standard deviations across 5 observers of 9% for EDV and 12% for ESV. 41 Regional wall-motion analysis is more susceptible to small, local segmentation errors that tend to cancel out in volume calculations. Therefore, we found a somewhat higher variability of AAFs computed from the same segmentations: the standard deviation of AAF across the 5 observers was 6% of the endocardial surface for a group of occlusions with an average size of 25%.…”
Section: Application To Clinical Diagnosismentioning
Background
Quantitative analysis of wall motion from three-dimensional (3D) dobutamine stress echocardiography (DSE) could provide additional diagnostic information not available from qualitative analysis. In this study we compare the effectiveness of 3D fractional shortening (3DFS), a measure of wall motion computed from 3D echocardiography (3DE), to strain and strain rate measured with sonomicrometry for detecting critical stenoses during DSE.
Methods
Eleven open-chest dogs underwent DSE both with and without a critical stenosis. 3DFS was measured from 3DE images acquired at peak stress. 3DFS was normalized by subtracting average 3DFS during control peak stress (Δ3DFS). Strains in the perfusion defect (PD) were measured from sonomicrometry, and PD size and location were measured with microspheres.
Results
A Δ3DFS abnormality indicated the presence of a critical stenosis with high sensitivity and specificity (88% and 100%, respectively), and Δ3DFS abnormality size correlated with PD size (R2=0.54). The sensitivity and specificity for Δ3DFS was similar to that for area strain (88%, 100%) and circumferential strain and strain rate (88%, 92% and 88%, 86%, respectively), while longitudinal strain and strain rate were less specific. Δ3DFS correlated significantly with both coronary flow reserve (R2=0.71) and PD size (R2=0.97), while area strain correlated with PD size only (R2=0.67), and other measures were not significantly correlated with flow reserve or PD size.
Conclusion
Quantitative wall motion analysis using Δ3DFS is effective for detecting critical stenoses during DSE, performing similarly to 3D strain, and provides potentially useful information on the size and location of a perfusion defect.
“…have shown that the standard deviation of volumes computed from segmentation of RT3D images by different observers is 8% of the mean end‐diastolic volume (EDV) and 13% of the mean end‐systolic volume (ESV). Using data from our previously published study of supply ischemia in a canine model, we similarly found relative standard deviations across 5 observers of 9% for EDV and 12% for ESV . Regional wall‐motion analysis is more susceptible to small, local segmentation errors that tend to cancel out in volume calculations.…”
Section: Discussionmentioning
confidence: 56%
“…Therefore, we found a somewhat higher variability of AAFs computed from the same segmentations: the standard deviation of AAF across the 5 observers was 6% of the endocardial surface for a group of occlusions with an average size of 25%. However, the average error in AAF compared to ischemic region sized assessed by microspheres ranged from 2 ± 12% to 8 ± 13% for the 5 observers, compared to 14% and 19% for visual assessment of the number of segments affected . These results suggest that user‐assisted segmentation using current commercial software is sufficient to yield consistent, accurate estimates of ischemic region size from ∆3DFS.…”
Section: Discussionmentioning
confidence: 88%
“…However, the average error in AAF compared to ischemic region sized assessed by microspheres ranged from 2 AE 12% to 8 AE 13% for the 5 observers, compared to 14% and 19% for visual assessment of the number of segments affected. 15,41 These results suggest that user-assisted segmentation using current commercial software is sufficient to yield consistent, accurate estimates of ischemic region size from Δ3DFS. In addition, semiautomatic segmentation software for 3DE continues to improve in both accuracy and ease of use, reducing the time required for clinical application of Δ3DFS.…”
Section: Application To Clinical Diagnosismentioning
confidence: 79%
“…Using data from our previously published study of supply ischemia in a canine model, 15 we similarly found relative standard deviations across 5 observers of 9% for EDV and 12% for ESV. 41 Regional wall-motion analysis is more susceptible to small, local segmentation errors that tend to cancel out in volume calculations. Therefore, we found a somewhat higher variability of AAFs computed from the same segmentations: the standard deviation of AAF across the 5 observers was 6% of the endocardial surface for a group of occlusions with an average size of 25%.…”
Section: Application To Clinical Diagnosismentioning
Background
Quantitative analysis of wall motion from three-dimensional (3D) dobutamine stress echocardiography (DSE) could provide additional diagnostic information not available from qualitative analysis. In this study we compare the effectiveness of 3D fractional shortening (3DFS), a measure of wall motion computed from 3D echocardiography (3DE), to strain and strain rate measured with sonomicrometry for detecting critical stenoses during DSE.
Methods
Eleven open-chest dogs underwent DSE both with and without a critical stenosis. 3DFS was measured from 3DE images acquired at peak stress. 3DFS was normalized by subtracting average 3DFS during control peak stress (Δ3DFS). Strains in the perfusion defect (PD) were measured from sonomicrometry, and PD size and location were measured with microspheres.
Results
A Δ3DFS abnormality indicated the presence of a critical stenosis with high sensitivity and specificity (88% and 100%, respectively), and Δ3DFS abnormality size correlated with PD size (R2=0.54). The sensitivity and specificity for Δ3DFS was similar to that for area strain (88%, 100%) and circumferential strain and strain rate (88%, 92% and 88%, 86%, respectively), while longitudinal strain and strain rate were less specific. Δ3DFS correlated significantly with both coronary flow reserve (R2=0.71) and PD size (R2=0.97), while area strain correlated with PD size only (R2=0.67), and other measures were not significantly correlated with flow reserve or PD size.
Conclusion
Quantitative wall motion analysis using Δ3DFS is effective for detecting critical stenoses during DSE, performing similarly to 3D strain, and provides potentially useful information on the size and location of a perfusion defect.
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