Ultrasound Normalized Local Variance And Liver/Kidney Ratio To Assess Non-Alcoholic Fatty Liver Disease
Monday, March 27, 2023
2:34 PM – 2:41 PM
Location: Bonnet Creek IX
CME: 0 Hours
Authors: Lauren Hagenstein, Rocky Vista University College of Osteopathic Medicine Jing Gao, Rocky Vista University Joseph C. Jenkins, Rocky Vista College of Osteopathic Medicine
Objectives: Non-alcoholic fatty liver disease (NAFLD) affects approximately 30% of adults in the United States. With such a highly prevalent disease, there should be consideration as to what steps can be taken to improve its diagnosis and management. The current standards of diagnosis of NAFLD include biopsy and Magnetic Resonance Imaging Proton Density Fat Fraction (MRI-PDFF). These standards are invasive, expensive, and have relatively low availability compared to ultrasound. Previous studies have shown that several ultrasound (US) modalities can be used to diagnose and monitor NAFLD along with or in place of the current standards, including normalized local variance (NLV) and liver to kidney (L/K) ratio measurements. NLV is used to measure the difference in liver tissue texture in each region of interest (ROI). A healthy liver will have a significant difference in tissue echogenicity and textures (the difference between vessels and liver parenchyma) on ultrasound. In a liver with NAFLD, the liver tissue appears homogeneous, as the liver parenchyma masking the intrahepatic vessels. L/K ratio analyzes the tissue echogenicity of the liver and compares it to that of the renal cortex. The technical considerations of these two techniques which are important to consider with standardization of the measurements. The similar considerations for NLV and L/K ratio measurements include ascites and intrahepatic vessels. The aim of our study is to identify the depth at which the ROI for NLV and L/K ratio should be standardized.
Methods: The study was approved by IRB of the university (2019-0009). All participant provided written informed consent at the initial enrollment. One hundred and sixteen patient cases were reviewed for a retrospective analysis. Initially, four NLV images and four L/K ratio images were acquired for each participant using a commercial ultrasound scanner equipped with a curvilinear transducer (PVI-475BX, 1.8-6.2 MHz, Aplio i800, Canon Medical Systems USA). A senior operator with more than 30 years of experience in abdominal ultrasound and 4 years of experience measuring NLV and L/K ratio performed all initial scans. All participants underwent the ultrasound study and an MRI within 30 days for an accurate comparison between the two modalities. Re-measurements of NLV and L/K ratio were performed in 116 participants by two junior operators who had trainings for abdominal ultrasound (2 years) and how to measure NLV and L/K ratio. Three NLV and three L/K ratio images were analyzed for each patient. For NLV, the ROI, with a diameter of 3.0 cm, were at the depths of the capsule, and 6 cm, and 10 cm from the surface of the skin. The L/K ratio ROI's, with a diameter of 1.0 cm, were at depths of 6 cm, 8 cm, and 10 cm from the surface of the skin. The resulting measurements at each depth for the three scans were then averaged, providing a mean measurement at each depth. The resulting measurements at each depth for the three scans were averaged, providing a mean measurement at each depth. The mean measurement at each depth was then averaged for each patient and a standard deviation was calculated, along with one-way analysis of variance (ANOVA). Measurements were then correlated to the patients’ MRI-PDFF values. Failure rate was also calculated.
Results : The mean NLV with depths near the capsule, 6 cm., and 10 cm. were 1.1±0.14, 1.11±0.23, and 1.18±0.33, with standard deviations of 0.30±0.19, 0.34±0.23, and 0.47±0.33 respectively. ANOVA for both mean and standard deviation was < 0.001. The mean L/K ratio with depths of 6 cm., 8 cm., and 10 cm. were 3.2±2.18, 1.76±1.06, and 1.09±0.68, with standard deviations of 1.67±1.13, 0.93±0.55, and 0.57±0.35 respectively. Like the analysis of variance of NLV, ANOVA for both the mean and standard deviation for L/K ratio was also < 0.001. Where they differed was in the percentage of failure rate. The failure rate did not exceed 5.4% for NLV, which was found at a depth of 10 cm. However, the failure rate of L/K ratio was as high as 54%, found at a depth of 6 cm., and was lowest at 9%, found at 8 cm. Analysis based on linear regression showed a negative correlation between MRI-PDFF to NLV measured near the capsule (r2= -0.65), at 6cm (r2= -0.69), at 8cm (r2= -0.73) and 10cm (r2= -0.58). All values for NLV near capsule, at 6cm, at 8cm and 10cm were all significant (p < 0.001). Analysis based on linear regression between MRI-PDFF to L/K ratio showed a negative correlation at 6cm (r2= -0.29), but not significant (p = 0.27). While a positive correlation between MRI-PDFF to L/K ratio was demonstrated at 8cm (r2=0.25) and 10cm (r2=0.33) which were significant (p < 0.001).
Conclusions: The study results suggest that there are technical considerations that should be taken when diagnosing or monitoring a patient with NAFLD using ultrasound NLV and L/K ratio. One of these considerations is the selection of depth of the ROI for measuring both values. For example, L/K ratio had a problematic reliability when measured at the depth of 6 cm due to its high failure rate of 54%. When compared to MRI-PDFF, the L/K ratio at the same depth also showed the lowest correlation. However, the ROI’s at 8 cm. and 10 cm. for L/K ratio were less failure rates (9% and 16% respectively). Due to low standard deviations, low failure rates, low variance, and strong correlations to MRI-PDFF, NLV can be measured at any of the depths discussed in this study. With strong correlations to MRI-PDFF for quantifying fat content in the liver, NLV seems outperform compared to L/K ratio in the assessment of NAFLD. Due to the lower cost and higher availability of ultrasound when compared to MRI-PDFF (among other benefits of US), this could positively affect current health disparities, more quickly identify disease, and improve disease management as objective progress can be monitored for quality healthcare.