NCT05627297

Applying Artificial Intelligence to Optimize Early-stage Hepatocellular Carcinoma Treatment Based on Multi-modal Image

Artificial Intelligence to Optimize Early-stage Hepatocellular CarcinomaTreatment Based on Multi-modal Image

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 200 (estimated)
• Sponsor: The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School · Academic / Other
• Sex: All
• Age: —
• Healthy volunteers: Not accepted

Summary

This study intends to establish two prognostic models based on contrast-enhanced ultrasound (CEUS) and dynamic enhanced magnetic resonance (DE-MRI) multimodal images: prognostic model of liver cancer patients after hepatectomy and prognostic model of liver cancer patients after radiofrequency ablation. Combined with artificial intelligence imaging omics, traditional imaging omics and clinical information, to predict and compare the prognosis of two different treatment methods for early liver cancer, so as to realize the individual selection of treatment methods for early liver cancer patients

Conditions

• Hepatocellular Carcinoma

Interventions

Type	Name	Description
OTHER	CEUS and CEMRI	contrast-enhanced ultrasound and contrast-enhanced MRI examination

Timeline

• Start date: 2022-12-01
• Primary completion: 2024-11-01
• Completion: 2025-11-01
• First posted: 2022-11-25
• Last updated: 2022-11-25

Locations

1 site across 1 country: China