Noninvasive Diagnosis of Liver Fibrosis: Utility of Data Mining of Both Ultrasound Elastography and Serological Findings to Construct a Decision Tree

Abstract

Objective: Although liver biopsy is the gold standard for viral liver disease management, it is invasive and the sampling error rate is problematic. Real-time tissue elastography (RTE), a recently developed method of ultrasound elastography, can be used to assess liver fibrosis noninvasively but the overlap between fibrosis stages limits its ability to assess liver fibrosis adequately when used alone. Methods: A multicenter collaborative study involving 542 patients with chronic viral hepatitis and cirrhosis who were scheduled to undergo liver biopsy compared the image features obtained from RTE image analysis, the liver fibrosis index (LFI), and pathological diagnosis. RTE and a blood test were performed on the same day as the liver biopsy. Data mining was also performed to construct a decision tree, and its diagnostic performance for assessing liver fibrosis was evaluated. Results: The LFI was higher in patients with chronic hepatitis C (CHC) than in those with chronic hepatitis B (CHB). When a decision tree was constructed by data mining of RTE and serological findings, the diagnostic accuracy was very high for all fibrosis stages, with respective rates at F1, F2, F3, and F4 of 94.4, 54.1, 38.7, and 81.3% for patients with CHC and of 97.1, 50.0, 43.8, and 80.6% for patients with CHB. Conclusions: The variation in LFI values between the different etiologies appears to reflect the difference in the development style of liver fibrosis. The decision tree for assessing liver fibrosis constructed by data mining of both RTE and serological findings had a high diagnostic performance in assessing liver fibrosis and shows promising clinical utility.

A Newly Developed Shear Wave Elastography Modality: With a Unique Reliability Index

“…They have been reported to be useful in the decision of the clinical treatment of hepatic disease, or in the diagnosis of noninvasive liver fibrosis [1,2,3,4,5]. Using elastography, it is also possible to noninvasively predict hepatocarcinogenesis [6,7].…”

Data Mining and Machine Learning Algorithms Using <i>IL28B</i> Genotype and Biochemical Markers Best Predicted Advanced Liver Fibrosis in Chronic Hepatitis C

“…Patients with minimal or no liver fibrosis progress slowly over a long period of time, while those with advanced fibrosis will eventually progress to cirrhosis within 10 years, carrying the risk of liver-related complications and eventually death. Whilst there have been many non-invasive biomarkers investigated and proposed, an ideal serological test for liver fibrosis that reduces the need to perform liver biopsy is still awaited (29).…”

Prospective Risk Analysis of Hepatocellular Carcinoma in Patients with Chronic Hepatitis C by Ultrasound Strain Elastography

“…RTE was performed after overnight fasting with ultrasound (EUB-8500 or HI VISION Ascendus; Hitachi, Tokyo, Japan) and EUP-L52 linear type probe (3-7 MHz; Hitachi, Tokyo, Japan), by a previously reported method [14,15]. Another analyst calculated the liver fibrosis index (LFI) as the median LFI from 10 still RTE images [12,13,14,15].…”

“…Another analyst calculated the liver fibrosis index (LFI) as the median LFI from 10 still RTE images [12,13,14,15]. …”

“…Liver stiffness measured by shear wave imaging is useful not only in diagnosing severe liver fibrosis but also for liver carcinogenesis risk assessment [8,9,10]. We had also found real-time tissue elastography (RTE), a type of strain imaging, to be useful for diagnosing liver fibrosis [11,12,13,14,15,16], but its use in predicting liver cancer prediction has not been reported.…”