  Objectives- Several ultrasound measures have shown promise for assessment of
steatosis compared to traditional B-scan, however clinicians may be required to
integrate information across the parameters. Here, we propose an integrated
multiparametric approach, enabling simple clinical assessment of key
information from combined ultrasound parameters. Methods- We have measured 13
parameters related to ultrasound and shear wave elastography. These were
measured in 30 human subjects under a study of liver fat. The 13 individual
measures are assessed for their predictive value using independent magnetic
resonance imaging-derived proton density fat fraction (MRI-PDFF) measurements
as a reference standard. In addition, a comprehensive and fine-grain analysis
is made of all possible combinations of sub-sets of these parameters to
determine if any subset can be efficiently combined to predict fat fraction.
Results- We found that as few as four key parameters related to ultrasound
propagation are sufficient to generate a linear multiparametric parameter with
a correlation against MRI-PDFF values of greater than 0.93. This optimal
combination was found to have a classification area under the curve (AUC)
approaching 1.0 when applying a threshold for separating steatosis grade zero
from higher classes. Furthermore, a strategy is developed for applying local
estimates of fat content as a color overlay to produce a visual impression of
the extent and distribution of fat within the liver. Conclusion- In principle,
this approach can be applied to most clinical ultrasound systems to provide the
clinician and patient with a rapid and inexpensive estimate of liver fat
content.
