Sha Tingting, You Yujia, Miao Xiaoyan, Deng Huan, Zhang Wei, Ye Huolin, Wang Ping, Zheng Rongqin, Ren Jie, Yin Tinghui
Department of Medical Ultrasound, Laboratory of Novel Optoacoustic (Ultrasonic) Imaging, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Department of Medical Ultrasound, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Liver Res. 2023 Nov 21;7(4):342-351. doi: 10.1016/j.livres.2023.11.002. eCollection 2023 Dec.
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.
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.
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 (r = 0.9078, < 0.0001) and between NID-MBs-ICAM-1 and pathological inflammation grade (r = 0.9071, < 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.
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.
非侵入性非酒精性脂肪性肝炎（NASH）评估是管理非酒精性脂肪性肝病的一项临床挑战。我们旨在基于序贯超声分子成像（USMI）开发诊断模型，用于在小鼠模型中对NASH进行非侵入性识别。
动物实验经华南农业大学动物伦理委员会批准。49只C57BL/6小鼠被分为正常对照组、非酒精性脂肪肝组、NASH组和肝炎组。使用靶向CD36的微泡（MBs-CD36）和靶向细胞间黏附分子-1（ICAM-1）的微泡（MBs-ICAM-1）进行序贯USMI，以可视化肝脏脂肪变性和炎症。采用破坏-再充盈法将USMI的靶向信号量化为归一化强度差（NID）。对NID-MBs-CD36与病理脂肪变性评分以及NID-MBs-ICAM-1与病理炎症评分进行相关性分析。最后，建立结合NID-MBs-CD36与NID-MBs-ICAM-1的诊断模型用于NASH诊断。
成功制备了MBs-CD36和MBs-ICAM-1并用于所有小鼠的序贯USMI。NID-MBs-CD36值随脂肪变性进展而增加，而NID-MBs-ICAM-1值随炎症进展而平行增加。NID-MBs-CD36与病理脂肪变性分级之间存在强正相关（r = 0.9078，< 0.0001），NID-MBs-ICAM-1与病理炎症分级之间也存在强正相关（r = 0.9071,< 0.0001）。在各种基于序贯USMI的诊断模型中，串联检测模型在检测NASH方面表现出较高的诊断性能，灵敏度为95%，特异性为97%，阳性预测值为95%；阴性预测值为97%，准确率为96%。
使用MBs-CD36和MBs-ICAM-1的序贯USMI可对肝脏脂肪变性和炎症进行非侵入性分级。基于序贯USMI的诊断模型在NASH的非侵入性识别方面具有巨大潜力。
