A Study of the COherence of Scatter Identification and Exclusion Algorithm: The COSIE Study

Non-alcoholic fatty liver disease (NAFLD) is currently the most common liver condition worldwide; approximately 55% of the world population will have NAFLD by 2040. NAFLD is an unwanted side effect of common cancer therapies, such as chemotherapy. Ultrasound can detect NAFLD via measurement of the backscatter coefficient (BSC). It is an attractive technique because of its low cost and availability, potentially enabling earlier detection of NAFLD in a larger population through screening. This approach has shown promise in detecting NAFLD but is limited by variability in measurement due to several factors. Measurement of the BSC requires assumptions about the nature of the tissue being measured; if these assumptions are incorrect, they can lead to inaccurate BSC measurements. To improve accuracy, an algorithm (COSIE) was developed to quantify the suitability of tissue for BSC analysis. The investigators believe COSIE will enable more reliable BSC measurements by selecting the optimal regions of tissue to measure. By measuring the BSC in the livers of healthy volunteers and patients with evidence of fatty liver, the algorithm can be evaluated against liver fat percentage values obtained from MRI imaging. This study will assess whether applying the COSIE algorithm enhances the reliability of BSC measurements, bringing them closer in quality to MRI imaging.