Effects of fatty infiltration of the liver on the shannon entropy of ultrasound backscattered signals

Po Hsiang Tsui*, Yung Liang Wan

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

37 Scopus citations

Abstract

This study explored the effects of fatty infiltration on the signal uncertainty of ultrasound backscattered echoes from the liver. Standard ultrasound examinations were performed on 107 volunteers. For each participant, raw ultrasound image data of the right lobe of liver were acquired using a clinical scanner equipped with a 3.5-MHz convex transducer. An algorithmic scheme was proposed for ultrasound B-mode and entropy imaging. Fatty liver stage was evaluated using a sonographic scoring system. Entropy values constructed using the ultrasound radiofrequency (RF) and uncompressed envelope signals (denoted by HR and HE, respectively) as a function of fatty liver stage were analyzed using the Pearson correlation coefficient. Data were expressed as the median and interquartile range (IQR). Receiver operating characteristic (ROC) curve analysis with 95% confidence intervals (CIs) was performed to obtain the area under the ROC curve (AUC). The brightness of the entropy image typically increased as the fatty stage varied from mild to severe. The median value of HR monotonically increased from 4.69 (IQR: 4.60-4.79) to 4.90 (IQR: 4.87-4.92) as the severity of fatty liver increased (r = 0.63, p < 0.0001). Concurrently, the median value of HE increased from 4.80 (IQR: 4.69-4.89) to 5.05 (IQR: 5.02-5.07) (r = 0.69, p < 0.0001). In particular, the AUCs obtained using HE (95% CI) were 0.93 (0.87-0.99), 0.88 (0.82-0.94), and 0.76 (0.65-0.87) for fatty stages ≥mild, ≥moderate, and ≥severe, respectively. The sensitivity, specificity, and accuracy were 93.33%, 83.11%, and 86.00%, respectively (≥mild). Fatty infiltration increases the uncertainty of backscattered signals from livers. Ultrasound entropy imaging has potential for the routine examination of fatty liver disease.

Original languageEnglish
Article number341
JournalEntropy
Volume18
Issue number9
DOIs
StatePublished - 21 09 2016

Bibliographical note

Publisher Copyright:
© 2016 by the authors.

Keywords

  • Entropy imaging
  • Fatty liver
  • Information theory
  • Steatosis
  • Ultrasound

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