Cyclic Variation of Integrated Backscatter: Dependence of Time Delay on the Echocardiographic View Used and the Myocardial Segment Analyzed

Finch-Johnston, Ann E.; Gussak, Hiie M.; Mobley, Joel; Holland, Mark; Petrovic, Olivera; Pérez, Julio E.; Miller, James G.

doi:10.1016/s0894-7317(00)90037-3

Cited by 53 publications

(23 citation statements)

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“…Our laboratory and others have previously demonstrated the effects of anisotropic myocardial fiber structure on the intrinsic ultrasonic properties of myocardial tissue [18][19][20][21][22][23][24][25][26] and the subsequent effects on echocardiographic images. [27][28][29][30][31][32][33][34][35] These studies have shown good agreement between simulated echocardiographic images based on models of myofiber orientation incorporating previously measured anisotropic myocardial ultrasonic properties and analyses of clinically acquired echocardiographic images. 28,29 However, the inverse analysis has not been undertaken (i.e., estimates of regional myofiber orientation have not been obtained from analyses of echocardiographic images).…”

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confidence: 52%

Echocardiographic-Based Assessment of Myocardial Fiber Structure in Individual, Excised Hearts

et al. 2012

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The objective of this study was to assess the feasibility of using echocardiographic imaging as an approach for determining the myocardial fiber structure of intact, individual hearts. Seven formalin-fixed, ex vivo sheep hearts were imaged using a commercially available echocardiographic imaging system, and the intrinsic fiber structure for the reconstructed short-axis cross section was determined for a specific distance from the apex of each heart. Diffusion tensor magnetic resonance (DT-MR) images of each heart were acquired and fiber maps were created for comparison with the fiber structure obtained from the corresponding reconstructed echocardiographic images. These two methods of obtaining the fiber structure showed relatively good agreement, suggesting that measurements of fiber orientation for individual hearts can be derived from echocardiographic images. Further development of this method may provide a clinically useful approach for mapping the fiber orientation in individual patients over the heart cycle.

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Echocardiographic-Based Assessment of Myocardial Fiber Structure in Individual, Excised Hearts

et al. 2012

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“…Cardiac lesions of sarcoidosis, including sarcoid granuloma, disarrangement, myocyte hypertrophy, fragmentation of muscle bundles, interstitial edema, large mononuclear cell infiltration, and myocardial interstitial fibrosis, may well increase anisotropy of myocardial fiber orientation [1], thereby reducing cyclic variation of integrated backscatter. Because the anisotropy of the myocardium may be greater in the anterior septum than in the posterior wall [36], in keeping with the smaller magnitude of integrated backscatter cyclic variation of the anterior septum [15,16,19,20,36], the ability to detect changes in integrated backscatter cyclic variation might be less for the anterior septum than for the posterior wall. It is interesting to note that, in patients with cardiac amyloidosis, integrated backscatter cyclic variation of the left ventricular posterior wall (not at the interventricular septum) is a powerful predictor of clinical outcome and is superior to standard echocardiographic/Doppler flow indexes [20].…”

Section: Role Of Integrated Backscatter Parametersmentioning

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Detection of cardiac sarcoidosis using cardiac markers and myocardial integrated backscatter

Yasutake

Seino

Kashiwagi

et al. 2005

International Journal of Cardiology

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“…However, the use of previously established techniques has been limited by low sensitivity and specificity, particularly in the setting of poorer quality images [10]. Integrated backscatter techniques, for example, depends predominantly on mean signal values and has demonstrated variability due to random noise,[11] susceptibility to time delays arising from the application of algorithms,[12], [13] and limited correlation with the extent of myocardial fibrosis present [10]. Therefore, we assessed the ability of a modified ultrasound-based image analysis algorithm to quantify LV wall microstructural alterations using distributions of sonographic signal intensity values.…”

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Identifying Early Changes in Myocardial Microstructure in Hypertensive Heart Disease

et al. 2014

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The transition from healthy myocardium to hypertensive heart disease is characterized by a series of poorly understood changes in myocardial tissue microstructure. Incremental alterations in the orientation and integrity of myocardial fibers can be assessed using advanced ultrasonic image analysis. We used a modified algorithm to investigate left ventricular myocardial microstructure based on analysis of the reflection intensity at the myocardial-pericardial interface on B-mode echocardiographic images. We evaluated the extent to which the novel algorithm can differentiate between normal myocardium and hypertensive heart disease in humans as well as in a mouse model of afterload resistance. The algorithm significantly differentiated between individuals with uncomplicated essential hypertension (N = 30) and healthy controls (N = 28), even after adjusting for age and sex (P = 0.025). There was a trend in higher relative wall thickness in hypertensive individuals compared to controls (P = 0.08), but no difference between groups in left ventricular mass (P = 0.98) or total wall thickness (P = 0.37). In mice, algorithm measurements (P = 0.026) compared with left ventricular mass (P = 0.053) more clearly differentiated between animal groups that underwent fixed aortic banding, temporary aortic banding, or sham procedure, on echocardiography at 7 weeks after surgery. Based on sonographic signal intensity analysis, a novel imaging algorithm provides an accessible, non-invasive measure that appears to differentiate normal left ventricular microstructure from myocardium exposed to chronic afterload stress. The algorithm may represent a particularly sensitive measure of the myocardial changes that occur early in the course of disease progression.

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Cyclic Variation of Integrated Backscatter: Dependence of Time Delay on the Echocardiographic View Used and the Myocardial Segment Analyzed

Cited by 53 publications

References 53 publications

Echocardiographic-Based Assessment of Myocardial Fiber Structure in Individual, Excised Hearts

Echocardiographic-Based Assessment of Myocardial Fiber Structure in Individual, Excised Hearts

Detection of cardiac sarcoidosis using cardiac markers and myocardial integrated backscatter

Identifying Early Changes in Myocardial Microstructure in Hypertensive Heart Disease

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