title: Prediction of tissue composition from ultrasonic measurements and mixture rules.
abstract: A methodology is presented for predicting the composition of tissues from measurements of the density, sound velocity, and acoustic nonlinear parameter, using mixture laws for the density, compressibility, and nonlinear parameter. It is shown that the mixture law for the nonlinear parameter plays an essential part in this methodology, which leads to the prediction of the volume fractions of water, protein, and fat in a given tissue. Data from the literature for solutions, blood, normal tissue, and cancerous tissue are investigated, and predicted fractions are consistent with tissue compositional information available in handbooks. More experimental work is needed with tissues of known composition in order to more fully test the proposed methodology.
mesh_terms: D000273:Adipose Tissue / Q000473:pathology; D000818:Animals; D001834:Body Water / Q000378:metabolism; D006801:Humans; D008433:Mathematics; D008953:Models, Anatomic; D009369:Neoplasms / Q000473:pathology; D011506:Proteins / Q000378:metabolism; D051381:Rats; D014463:Ultrasonography / Q000379:methods*
chemical_list: D011506:Proteins