This page shows some examples of multimedia files. It is also available at: http://www.ieee-uffc.org/tr/mexample.pdf. For submission of multimedia manuscripts to TUFFC, please follow “Information for Contributors” at: http://www.ieeeuffc.org/tr/contrib.pdf. Multimedia Example Created by Jian-yu Lu, Editor-in-Chief, 07/07/03 IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society 1. Color Figure: The IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control (TUFFC) now accepts color figures online with corresponding grayscale figures in print without additional charges if authors follow the multimedia manuscript submission procedure in the “Information for Contributors”. The “color figures” icon below indicates in the print that a color version of the figure is available online. It also links to the color figure submitted originally by the authors for viewing details. Because of the sizes of color figures and the additional editorial work such as making two sets of PostScript files in which they remain identical after replacing grayscale with color, authors should request color figures online only when it is necessary. The color figure must be in JPEG (Joint Photographic Expert Group) or GIF (Graphics Interchange Format) format to reduce file size and to decrease the bandwidth usage on the TUFFC server. Fig. 1. An eight-layer printed circuit board (PCB) used primarily for multi-channel ultrasound signal reception and storage. The board was designed in the Ultrasound Lab at The University of Toledo, led by Dr. Jian-yu Lu. It is one of the many PCBs designed for a high-frame rate medical ultrasound imaging system [1], which consists of 128 linear, ±144V peak, 0.05-10MHz, and 12-bit arbitrary waveform generators for the production of ultrasound signals or for other research purposes. 2. Movies: Please click on the movie icon to see a movie. The two movies below give you an idea on the file size versus movie quality. “VCD quality” here means 1150kbits/s for video and 224kbits/s for 16-bit MP2 stereo audio at 44.1KHz sampling rate. Fig. 2. An introduction to the Ultrasound Lab at The University of Toledo. 3. Movies and Animations: Please click on the movie icons to see movies or animations. Fig. 3. Circuit design and construction of the imaging system. 4. Movies and Animation: Please click on the movie icons to see movies or animation. Movie [File size: 785KB; Format: MPEG1; Resolution: 320X240; Duration: 9 seconds]

IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control

This guidance provides a data-supported approach to the diagnostic, therapeutic, and preventive aspects of NAFLD care. A "Guidance" document is different from a "Guideline." Guidelines are developed by a multidisciplinary panel of experts and rate the quality (level) of the evidence and the strength of each recommendation using the Grading of Recommendations, Assessment Development, and Evaluation (GRADE) system. A guidance document is developed by a panel of experts in the topic, and guidance statements, not recommendations, are put forward to help clinicians understand and implement the most recent evidence. This article is protected by copyright. All rights reserved.

The Diagnosis and Management of Nonalcoholic Fatty Liver Disease: Practice Guidance from the American Association for the Study of Liver Diseases

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Medical Imaging Signals And Systems

Liver disease is increasing in prevalence across the globe. We present here a multiparametric ultrasound (mpUS) imaging approach for assessing nonalcoholic fatty liver disease (NALFD). This study was performed using rats (N = 21) that were fed either a control or methionine and choline deficient (MCD) diet. A mpUS imaging approach that includes H-scan ultrasound (US), shear wave elastography, and contrast-enhanced US measurements were then performed at 0 (baseline), 2, and 6 weeks. Thereafter, animals were euthanized and livers excised for histological processing. A support vector machine (SVM) was used to find a decision plane that classifies normal and fatty liver conditions. In vivo mpUS results from control and MCD diet fed animals reveal that all mpUS measures were different at week 6 (P < 0.05). Principal component analysis (PCA) showed that the H-scan US data contributed the highest percentage to the classification among the mpUS measurements. The SVM resulted in 100% accuracy for classification of normal and high fat livers and 92% accuracy for classification of normal, low fat, and high fat livers. Histology findings found considerable steatosis in the MCD diet fed animals. This study suggests that mpUS examinations have the potential to provide a comprehensive estimation of the main components of early stage NAFLD.

/pdf/multiparametric-ultrasound-imaging-for-the-assessment-of-4saqbz1dpu.pdf

Multiparametric ultrasound imaging for the assessment of normal versus steatotic livers.

Fifty years of research on the nature of backscatter from tissues has resulted in a number of promising diagnostic parameters. We recently introduced two analyses tied directly to the biophysics of ultrasound scattering: the H-scan, based on a matched filter approach to distinguishing scattering transfer functions, and the Burr distribution for quantification of speckle patterns. Together, these analyses can produce at least five parameters that are directly linked to the mathematics of ultrasound in tissue. These have been measured in vivo in 35 rat livers under normal conditions and after exposure to compounds that induce inflammation, fibrosis, and steatosis in varying combinations. A classification technique, the support vector machine, is employed to determine clusters of the five parameters that are signatures of the different liver conditions. With the multiparametric measurement approach and determination of clusters, the different types of liver pathology can be discriminated with 94.6% accuracy.

Scattering Signatures of Normal versus Abnormal Livers with Support Vector Machine Classification.

Burr, Lomax, Pareto, and Logistic Distributions from Ultrasound Speckle.

The study of ultrasound tissue interactions in fatty livers has a long history with strong clinical potential for assessing steatosis. Recently we proposed alternative measures of first- and second-order statistics of echoes from soft tissues, namely, the H-scan, which is based on a matched filter approach, to quantify scattering transfer functions and the Burr distribution to model speckle patterns. Taken together, these approaches produce a multiparameter set that is directly related to the fundamentals of ultrasound propagation in tissue. To apply this approach to the problem of assessing steatotic livers, these analyses were applied to in vivo rat livers ( N = 21 ) under normal feeding conditions or after receiving a methionine- and choline-deficient diet that produces steatosis within a few weeks. Ultrasound data were acquired at baseline and again at weeks 2 and 6 before applying the H-scan and Burr analyses. Furthermore, a classification technique known as the support vector machine was then used to find clusters of the five parameters that are characteristic of the different steatotic liver conditions as confirmed by histologic processing of excised liver tissue samples. With the in vivo multiparametric ultrasound measurement approach and determination of clusters, steatotic can be discriminated from normal livers with 100% accuracy in a rat animal model.

Clusters of Ultrasound Scattering Parameters for the Classification of Steatotic and Normal Livers.

Purpose: Recent theories examine the role of the fractal branching vasculature as a primary site of Born scattering from soft normal tissues. These derivations postulate that the first-order statistics of speckle from soft tissue, such as the liver, thyroid, and prostate, will follow a Burr distribution with a power law parameter that can be related back to the underlying power law, which governs the branching network. However, the issue of scatterer spacing, or the number of cylindrical vessels per sample volume of the interrogating pulse, has not been directly addressed. Approach: Speckle statistics are examined with a 3D simulation that varies the number density and the governing power law parameter of an ensemble of different sized cylinders. Several in vivo liver scans are also analyzed for confirmation across different conditions. Results: The Burr distribution is found to be an appropriate model for the histogram of amplitudes from speckle regions, where the parameters track the underlying power law and scatterer density conditions. These results are also tested in a more general model of rat liver scans in normal versus abnormal conditions, and the resulting Burr parameters are also found to be appropriate and sensitive to underlying scatterer distributions. Conclusions: These preliminary results suggest that the classical Burr distribution may be useful in the quantification of scattering of ultrasound from soft vascularized tissues and as a tool in tissue characterization.

Speckle from branching vasculature: dependence on number density.

Elastography provides significant information on staging of fibrosis in patients with liver disease and may be of some value in assessing steatosis. However, there remain questions as to the role of steatosis and fibrosis as cofactors influencing the viscoelastic measurements of liver tissues, particularly shear wave speed (SWS) and shear wave attenuation (SWA). In this study, by employing the theory of composite elastic media as well as two independent experimental measurements on oil-in-gelatin phantoms and also finite element simulations, it is consistently shown that fat and fibrosis jointly influence the SWS and SWA measurements. At a constant level of fat, fibrosis stages can influence the SWA by factors of 2-4. Moreover, the rate of increase in SWA with increasing fat is strongly influenced by the stages of fibrosis; softer background cases (low fibrosis stages) have higher rate of SWA increase with fat than those with stiffer moduli (higher fibrosis stages). Meanwhile, SWS results are influenced by the presence of fat, however the degree of variability is more subtle. The results indicate the importance of jointly considering fat and fibrosis as contributors to SWS and SWA measurements in complex liver tissues and in the design and interpretation of clinical trials.

Sedigheh S. Poul

Papers

Scattering Signatures of Normal versus Abnormal Livers with Support Vector Machine Classification.

Burr, Lomax, Pareto, and Logistic Distributions from Ultrasound Speckle.

Clusters of Ultrasound Scattering Parameters for the Classification of Steatotic and Normal Livers.

Speckle from branching vasculature: dependence on number density.

Fat and fibrosis as confounding cofactors in viscoelastic measurements of the liver.