Liver Research (Dec 2023)

Sequential ultrasound molecular imaging for noninvasive identification and assessment of non-alcoholic steatohepatitis in mouse models

  • Tingting Sha,
  • Yujia You,
  • Xiaoyan Miao,
  • Huan Deng,
  • Wei Zhang,
  • Huolin Ye,
  • Ping Wang,
  • Rongqin Zheng,
  • Jie Ren,
  • Tinghui Yin

Journal volume & issue
Vol. 7, no. 4
pp. 342 – 351

Abstract

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Background and objective: Noninvasive non-alcoholic steatohepatitis (NASH) assessment is a clinical challenge to the management of non-alcoholic fatty liver disease. We aim to develop diagnostic models based on sequential ultrasound molecular imaging (USMI) for the noninvasive identification of NASH in mouse models. Methods: Animal experiments were approved by the Animal Ethics Committee of South China Agricultural University. Forty-nine C57BL/6 mice were divided into normal control, non-alcoholic fatty liver, NASH, and hepatitis groups. Sequential USMI was implemented using CD36-targeted microbubbles (MBs-CD36) and intercellular adhesion molecule-1 (ICAM-1)-targeted microbubbles (MBs-ICAM-1) to visualize hepatic steatosis and inflammation. The targeting signal of USMI was quantified as the normalized intensity difference (NID) with the destruction-replenishment method. Correlation analysis was conducted between the NID-MBs-CD36 and pathological steatosis score and between the NID-MBs-ICAM-1 and pathological inflammation score. Finally, diagnostic models combining NID-MBs-CD36 with NID-MBs-ICAM-1 were established for NASH diagnosis. Results: MBs-CD36 and MBs-ICAM-1 were successfully prepared and used for sequential USMI in all mice. NID-MBs-CD36 values increased with the progression of steatosis, while NID-MBs-ICAM-1 values increased in parallel with the progression of inflammation. A strong positive correlation was identified between NID-MBs-CD36 and pathological steatosis grade (rs = 0.9078, P < 0.0001) and between NID-MBs-ICAM-1 and pathological inflammation grade (rs = 0.9071, P < 0.0001). Among various sequential USMI-based diagnostic models, the serial testing model showed high diagnostic performance in detecting NASH, with 95% sensitivity, 97% specificity, 95% positive predictive values, 97% negative predictive values, and 96% accuracy. Conclusions: Sequential USMI using MBs-CD36 and MBs-ICAM-1 allows noninvasive grading of hepatic steatosis and inflammation. Sequential USMI-based diagnostic models hold great potential in the noninvasive identification of NASH.

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