Parenchymal disease of the liver, known as diffuse liver disease, led to 1.4% of the total deaths in the United States in 2013. It causes impaired liver functioning and may lead to portal hypertension, encephalopathy, or hepatocellular carcinoma. Current methods of diagnosing diffuse liver disease are often invasive, subject to heterogeneous variation, and fail to distinguish between intermediate disease stages. Ultrasound imaging has long been used to monitor changes in tissue structure, and it is known that sound attenuation changes with disease progression. Tissue is acoustically nonlinear, meaning that propagating sound waves are distorted due to tissue properties and generate higher order harmonics. Since fatty deposits and fibrosis change with disease progression, we hypothesize that associated attenuation changes may be detected by changes in the nonlinear signal distortion and can be quantified as a marker of disease. We have designed a methodology based in Tissue Harmonic Imaging to use a quantified marker of attenuation to specifically detect diffuse liver disease. This project comprises of (1) a theoretical and experimental investigation of the influence of sound attenuation on harmonic content in tissue, (2) clinical patient data collection and development of MATLAB analysis tools utilizing the disease marker developed in Phase I, and (3) development of new imaging sequences capable of grading diffuse liver disease when coupled with the analysis tools. The noninvasive, easy to use, sensitive, and clinically usable methodology developed in this project has the potential for aiding in diagnosis of diffuse liver disease and enhancing quality of patient care.