Bayesian Parameter Estimation for Characterizing the Cyclic Variation of Echocardiographic Backscatter to Assess the Hearts of Asymptomatic Type 2 Diabetes Mellitus Subjects

Anderson, Christian C.; Gibson, Allyson A.; Schaffer, Jean E.; Peterson, Linda R.; Holland, Mark; Miller, James G.

doi:10.1016/j.ultrasmedbio.2011.02.001

Cited by 3 publications

(2 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…More recent application of these studies has been to characterize diabetes [80–81]. In one study, comparisons between normal subjects and patients with type 2 diabetes demonstrated that parameterization of the ultrasonic backscatter from the myocardium could differentiate between the hearts of diabetic patients based on their diabetic control.…”

Section: Successful Applications Of Quantitative Ultrasoundmentioning

confidence: 99%

Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound

Oelze

Mamou

2016

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

296

206

View full text Add to dashboard Cite

Conventional medical imaging technologies, including ultrasound, have continued to improve over the years. For example, in oncology, medical imaging is characterized by high sensitivity, i.e., the ability to detect anomalous tissue features, but the ability to classify these tissue features from images often lacks specificity. As a result, a large number of biopsies of tissues with suspicious image findings are performed each year with a vast majority of these biopsies resulting in a negative finding. To improve specificity of cancer imaging, quantitative imaging techniques can play an important role. Conventional ultrasound B-mode imaging is mainly qualitative in nature. However, quantitative ultrasound (QUS) imaging can provide specific numbers related to tissue features that can increase the specificity of image findings leading to improvements in diagnostic ultrasound. QUS imaging techniques can encompass a wide variety of techniques including spectral-based parameterization, elastography, shear wave imaging, flow estimation and envelope statistics. Currently, spectral-based parameterization and envelope statistics are not available on most conventional clinical ultrasound machines. However, in recent years QUS techniques involving spectral-based parameterization and envelope statistics have demonstrated success in many applications, providing additional diagnostic capabilities. Spectral-based techniques include the estimation of the backscatter coefficient, estimation of attenuation, and estimation of scatterer properties such as the correlation length associated with an effective scatterer diameter and the effective acoustic concentration of scatterers. Envelope statistics include the estimation of the number density of scatterers and quantification of coherent to incoherent signals produced from the tissue. Challenges for clinical application include correctly accounting for attenuation effects and transmission losses and implementation of QUS on clinical devices. Successful clinical and pre-clinical applications demonstrating the ability of QUS to improve medical diagnostics include characterization of the myocardium during the cardiac cycle, cancer detection, classification of solid tumors and lymph nodes, detection and quantification of fatty liver disease, and monitoring and assessment of therapy.

show abstract

Section: Successful Applications Of Quantitative Ultrasoundmentioning

confidence: 99%

Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound

Oelze

Mamou

2016

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

296

206

View full text Add to dashboard Cite

show abstract

“…(Many "ultrasound" uses of Bayesian methods in the literature are really more generic post-processing or image processing algorithms (e.g. [4])). The reason for this is not clear, but in some cases it may be the lack of an appropriate, practical likelihood function.…”

Section: Introductionmentioning

confidence: 99%

2D and 3D Bayesian displacement estimation

Byram

Rotemberg

Trahey

2012

2012 IEEE International Ultrasonics Symposium

View full text Add to dashboard Cite

Bayesian displacement estimation has been previously demonstrated in 1D and shown to reduce estimation and jitter and often bias. Here it is shown that the 1D implementation is directly extendable to 2D and 3D.2D simulations are used to determine the validity of the perturbed likelihood function and empirically determine values for the scaling term α. 3D translation stage and in vivo cardiac experiments are used to examine the algorithm's performance for estimating displacements.The 2D simulations determined that a cap should be placed on the full scaling term ( SN R α ). The 3D translation stage experiments show better performance in all three dimensions, and the 3D in vivo results show significant qualitative improvements as well as improvements in estimated levels of estimation variance.

show abstract

Simulation of ultrasonic scattering from scatterer size distributions using Field II

Whitson,

Rosado-Mendez,

Hale

et al. 2024

The Journal of the Acoustical Society of America

View full text Add to dashboard Cite

Quantitative analysis of radio frequency (RF) signals obtained from ultrasound scanners can yield objective parameters that are gaining clinical relevance as imaging biomarkers. These include the backscatter coefficient (BSC) and the effective scatterer diameter (ESD). Biomarker validation is typically performed in phantoms which do not provide the flexibility of systematic variation of scattering properties. Computer simulations, such as those from the ultrasound simulator Field II, can allow more flexibility. However, Field II does not allow simulation of RF data from a distribution of scatterers with finite size. In this work, a simulation method is presented which builds upon previous work by including Faran theory models representative of distributions of scatterer size. These are systematically applied to RF data simulated in Field II. The method is validated by measuring the root mean square error of the estimated BSC and percent bias of the ESD and comparing to experimental results. The results indicate the method accurately simulates distributions of scatterer sizes and provides scattering similar to that seen in data from clinical scanners. Because Field II is widely used by the ultrasound community, this method can be adopted to aid in validation of quantitative ultrasound imaging biomarkers.

show abstract

Bayesian Parameter Estimation for Characterizing the Cyclic Variation of Echocardiographic Backscatter to Assess the Hearts of Asymptomatic Type 2 Diabetes Mellitus Subjects

Cited by 3 publications

References 36 publications

Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound

Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound

2D and 3D Bayesian displacement estimation

Simulation of ultrasonic scattering from scatterer size distributions using Field II

Contact Info

Product

Resources

About