Parameterization of Left Ventricular Wall Motion for Detection of Regional Ischemia

Herz, Susan L.; Ingrassia, Christopher M.; Homma, Shunichi; Costa, Kevin D.; Holmes, Jeffrey W.

doi:10.1007/s10439-005-3312-7

Cited by 47 publications

(61 citation statements)

References 23 publications

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“…For comparison, if linear quadrilateral patches were used, about 100 linear patches would be required to represent the same surface with comparable accuracy. For this reason, Hermite polynomials are widely used in cardiac biomechanics studies for surface representation [25][26][27]. A simple 8x8 finite element model (FEM) with intrinsic C 1 continuity can sufficiently represent the geometry of the endocardium [26,27].…”

Section: Geometric Function Setupmentioning

confidence: 99%

Real-time segmentation of 4D ultrasound by Active Geometric Functions

Duan

Angelini

Homma

et al. 2008

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro

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Four-dimensional ultrasound based on matrix phased array transducers can capture the complex 4D cardiac motion in a complete and real-time fashion. However, the large amount of information residing in 4D ultrasound scans and novel applications under interventional settings pose a big challenge in efficiency for workflow and computer-aided diagnostic algorithms such as segmentation. In this context, a novel formulation framework of the minimal surface problem, called Active Geometric Functions (AGF), is proposed to reach truly real-time performance in segmenting 4D ultrasound data. A specific instance of AGF based on finite element modeling and Hermite surface descriptors was implemented and evaluated on 35 4D ultrasound data sets with a total of 425 time frames. Quantitative comparison to manual tracing showed that the proposed method provides LV contours close to manual segmentation and that the discrepancy was comparable to inter-observer tracing variability. The ability of such realtime segmentation will not only facilitate the diagnoses and workflow, but also enables novel applications such as interventional guidance and interactive image acquisition with online segmentation.

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Section: Geometric Function Setupmentioning

confidence: 99%

Real-time segmentation of 4D ultrasound by Active Geometric Functions

Duan

Angelini

Homma

et al. 2008

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro

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“…Lekadir et al (10) used inter-landmark distance measurement to distinguish dysfunctional segments from a statistical shape model of myocardium. Herz et al (11) applied finite element model to identify regional ischemia. Another approach parameterized the left ventricular motion into a parametric image to extract abnormal coefficients (12)(13)(14).…”

mentioning

confidence: 99%

Automated regional wall motion abnormality detection by combining rest and stress cardiac MRI: Correlation with contrast‐enhanced MRI

Suinesiaputra

Frangi

Kaandorp

et al. 2011

Magnetic Resonance Imaging

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Purpose: To correlate an automated regional wall motion abnormality (RWMA) detection method based on combined rest and dobutamine-stress cardiac MRI with the assessment of myocardial infarction from contrastenhanced MRI (CE-MRI), and to demonstrate that adding stress data improves the detection of scar segments compared with rest data alone. Materials and Methods:An automated RWMA detection method was built based on a statistical model of normokinetic myocardium from 41 healthy volunteers. The method was adapted to detect changes in RWMA from rest to stress. Twelve patients with myocardial infarction were included in the experiment. The correlation with CE-MRI was performed on two measurements: infarct transmurality and scar detection. Results:Compared with infarct transmurality, the probability of normokinetic motion decreased progressively as infarct transmurality increased. These probability values were 0.59 for non-scar segments, for <25% transmurality was 0.4 (SE ¼ 0.04), for 25-50% was 0.33 (SE ¼ 0.03), for 50-75% was 0.21 (SE ¼ 0.03) and for !75% was 0.10 (SE ¼ 0.03). For scar tissue detection, adding stress data significantly improved the performance (P < 0.001, confidence interval ¼ 99.9%). The sensitivity, specificity, and accuracy increased by 34%, 30%, and 32%, respectively. The area under the receiver operating characteristics curve was 0.63 when rest-only data was used, but it was improved to 0.87 when stress data was added. Conclusion:The presented automated RWMA assessment was capable of detecting wall motion improvements from rest to stress. The method correlated well with infarct transmurality from CE-MRI. Detection of scar regions was more accurate when rest and stress data were combined compared with rest data alone.

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“…Our group designed 3DFS as a 3D measure for the purpose of measuring the size of a wall motion abnormality, 78 and here we see that it measures the size of an ischemic region well. Unlike strain, ∆3DFS abnormality size does not change between -DOB and +DOB models, and therefore is not sensitive to remote contractility.…”

Section: Discussionmentioning

confidence: 71%

“…78,80 analysis is performed on a finite element model of the heart in Chapter 3, and these fitting methods are used to provide an anatomic reference for image registration in Chapter 7. Methods for performing an open-chest dog study of dobutamine stress to measure wall motion and strain will be described, as well as general wall motion analysis methods and a study of intraobserver and interobserver variability of manual endocardial segmentation of 3DE images.…”

Section: Measuring Cardiac Wall Motion From Noninvasive Imagingmentioning

confidence: 99%

“…77,78,80 The endocardial data were transformed into a cardiac coordinate system using the three anatomical landmarks selected at ED. This cardiac coordinate system has axes directed parallel to the base-apex axis (x 1 ), through the midseptum (x 2 ), and through the posterior wall (x 3 ) from an origin located 1/3 of the distance from the base to apex along the LV long axis.…”

Section: Fittingmentioning

confidence: 99%

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Regional Mechanics of Demand Ischemia During Cardiac Stress Testing

Parker

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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 mechanical movement of the left ventricular (LV) wall, characterized clinically as "wall motion", is currently assessed qualitatively to identify abnormally-moving ischemic regions which may benefit from angioplasty. Advances in ultrasound and MRI may improve diagnosis by allowing more quantitative measures such as strain, wall thickening, or endocardial fractional shortening. However, little is understood about how these measures are affected by the severity of demand ischemia, coupling to adjacent myocardium, or the presence of previously-unrecognized myocardial infarction. A greater understanding of the factors that influence regional mechanics during stress testing would help determine the best way to detect the altered mechanics that indicate demand ischemia and coronary stenosis. The goal of this dissertation is to understand how regional demand ischemia affects regional mechanics and apply that knowledge to improve clinical stress testing.A finite element model of the heart was used to examine how reduced force generation in the ischemic region, ischemic region size, and coupling to myocardium with increased contractility separately and jointly impact various measures of regional mechanics. Area strain and a measure of wall motion developed in our lab, threeiv dimensional fractional shortening (3DFS), were most sensitive to reduced force generation, while radial strain was affected most by the contractility of remote myocardium. The model also predicted that a novel measure of wall motion bulging, dyskinesia severity index (DSI), can separate infarcts from demand ischemia during stress testing. The ability of strain and 3DFS to detect a critical stenosis was evaluated in experimental canine dobutamine stress tests. The three-dimensional (3D) measures of area strain and 3DFS detected critical stenoses better than two-dimensional (2D) strain. Finally, 3DFS measured during clinical stress testing in patients at low risk for coronary artery disease displayed low variability, suggesting 3DFS may be effective for detecting demand ischemia in patients.Another application in which the cardiac mapping techniques described here could improve treatment is in evaluating cardiac resynchronization therapy (CRT) nonresponders, which compromise 30-40% of CRT patients. The relationship between LV lead location and scar or regional mechanical function measured from pre-CRT cardiac imaging likely has an important impact on CRT response. A method to reconstruct the 3D coordinates of the lead from 2D fluoroscopic i...

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Parameterization of Left Ventricular Wall Motion for Detection of Regional Ischemia

Cited by 47 publications

References 23 publications

Real-time segmentation of 4D ultrasound by Active Geometric Functions

Real-time segmentation of 4D ultrasound by Active Geometric Functions

Automated regional wall motion abnormality detection by combining rest and stress cardiac MRI: Correlation with contrast‐enhanced MRI

Regional Mechanics of Demand Ischemia During Cardiac Stress Testing

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