Ultrasound-based artificial intelligence in gastroenterology and hepatology

Abstract

Artificial intelligence (AI), especially deep learning, is gaining extensive attention for its excellent performance in medical image analysis. It can automatically make a quantitative assessment of complex medical images and help doctors to make more accurate diagnoses. In recent years, AI based on ultrasound has been shown to be very helpful in diffuse liver diseases and focal liver lesions, such as analyzing the severity of nonalcoholic fatty liver and the stage of liver fibrosis, identifying benign and malignant liver lesions, predicting the microvascular invasion of hepatocellular carcinoma, curative transarterial chemoembolization effect, and prognoses after thermal ablation. Moreover, AI based on endoscopic ultrasonography has been applied in some gastrointestinal diseases, such as distinguishing gastric mesenchymal tumors, detection of pancreatic cancer and intraductal papillary mucinous neoplasms, and predicting the preoperative tumor deposits in rectal cancer. This review focused on the basic technical knowledge about AI and the clinical application of AI in ultrasound of liver and gastroenterology diseases. Lastly, we discuss the challenges and future perspectives of AI.

Preoperative and Prognostic Prediction of Microvascular Invasion in Hepatocellular Carcinoma: A Review Based on Artificial Intelligence

“…Studies based on the preoperative prediction of MVI from ultrasound images are further developing, and the usefulness of ultrasound images in predicting MVI was also confirmed by the retrospective studies of Zhang et al 42 and Hu et al 40 whose established contrast-enhanced ultrasound image radiomics nomogram had better predictive performance than the clinical data model, and multimodal enhanced ultrasound images were better than grayscale images. Deep learning methods have also been reported in ultrasound images, 55 and in addition, a deep learning–based study reported on MVI prediction metrics shows the feasibility of microscopic features of ultrasound images in this field. 44…”

Artificial Intelligence in Ultrasound Imaging: Where Are We Now?

“…The application of US-based AI in gastroenterology and hepatology is being increasingly explored with the hope of enhancing accuracy and efficiency. 19,20 For example, endoscopic US (EUS) allows high-resolution imaging for diagnosing pancreatico-biliary diseases, staging gastrointestinal tract tumors, evaluating subepithelial lesions, and sampling lymph nodes and masses. Endoscopic US-guided fine-needle aspiration and biopsy (FNB) have improved the diagnosis of malignancies, enhancing patient outcomes.…”

Diagnostic Performance of an Artificial Intelligence Model Based on Contrast-Enhanced Ultrasound in Patients with Liver Lesions: A Comparative Study with Clinicians

“…In hepatology, ultrasound-based artificial intelligence has been applied to assess diffuse liver diseases and focal liver lesions [16]. Several AI methods based on CEUS have been proposed to differentiate between benign and malignant liver lesions [17][18][19][20][21].…”