The (travel) times they are a changing : a computational framework for the diagnosis of non-alcoholic fatty liver disease (NAFLD)
Name
1003323910-MIT.pdf
Description
Full printable version
Size
5.6 MB
Format
Adobe PDF
Checksum (MD5)
5bd562aa4fcc5f53a5391313fab2e69a
Author(s)
Benjamin, Alex (Alex Robert)
Advisor(s)
Brian W. Anthony.
Alternative Title
Computational framework for the diagnosis of non-alcoholic fatty liver disease (NAFLD)
Date Issued
2017
Publisher
Massachusetts Institute of Technology
Abstract
We propose and validate a non-invasive method to diagnose Non-Alcoholic Fatty Liver Disease (NAFLD). The proposed method is based on two fundamental concepts: 1) the speed of sound in a fatty liver is lower than that in a healthy liver and 2) the quality of an ultrasound image is maximized when the beamforming speed of sound used in image formation matches the speed in the medium under examination. The proposed method uses image brightness and sharpness as quantitative image-quality metrics to predict the true sound speed and capture the effects of fat infiltration, while accounting for the transmission through subcutaneous fat. Validation using nonlinear acoustic simulations indicated the proposed method's ability to predict the speed of sound within a medium under examination with little sensitivity to the transducer's frequency (errors less than 2%). Additionally, ex vivo testing on sheep liver, mice livers, and tissue-mimicking phantoms indicated the method's ability to predict the true speed of sound with errors less than 0.5% (despite the presence of subcutaneous fat) and its ability to quantify the relationship between fat content and speed of sound. Additionally, this work starts to create a framework which allows for the determination of the spatial distribution of the longitudinal speed of sound, thereby providing a promising method for diagnosing NAFLD over time.
Description
Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 57-61).
Subjects
Computation for Design and Optimization Program.
MIT Department
Massachusetts Institute of Technology. Computation for Design and Optimization Program
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