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Clinical Trials in China / NCT07582419
Starting soon Observational

Hybrid Deep Learning Integrating Multimodal CEUS and Enhanced MRI to Optimize Early-Stage HCC Treatment Decisions

NCT07582419 · tracked via the Priya Life Science China tracker
Sponsor
The First Hospital of Jilin University
Phase
Observational
Started
2026-04-30
Last updated
2026-05-12

Condition(s) studied

Hepatocellular Carcinoma (HCC)

Investigational drug(s) / intervention(s)

surgeryablation

surgery: The surgery was performed in supine position under general anesthesia with open/laparoscopic liver resection (LH), and the main and secondary incisions were made based on the tumor location. Intraoperative ultrasound was routinely used to assess the tumor, remnant liver volume, and the feasibility of negative margins. The type of liver resection followed established guidelines.

ablation: Ablation is performed under ultrasound guidance and intravenous anesthesia, using the KY-2000 treatment device with disposable ablation needles and monitoring software. For tumors with a diameter of less than 2cm, a single needle is used; for tumors of 2cm or more, dual needles (needle spacing ≤ 2cm) are used. The ablation parameters are set to a power of 40-65W and a duration of 1-15 minutes, with immediate post-operative ultrasound (contrast) assessment of the ablation range.

Study summary

This study aims to address the issue of a lack of individualized basis for selecting liver resection (LH) or microwave ablation (MWA) in early-stage hepatocellular carcinoma (HCC) patients to reduce the early recurrence rate (≤2 years). Given that existing machine learning-based recurrence prediction studies have failed to guide the optimal treatment plan selection, and that multidisciplinary consultations rely on guidelines (universality) and experience (subjectivity) which have their limitations, we propose to utilize artificial intelligence (AI), specifically the advantages of multimodal deep learning technology (which outperforms traditional machine learning by integrating complementary information to provide more accurate predictions), to establish a hybrid deep learning model that integrates contrast-enhanced ultrasound (CEUS) and enhanced magnetic resonance imaging (MRI) features. This model will predict the probability of early recurrence (ER≤2 years) in patients and, based on this, recommend LH or MWA as the optimal first treatment option for newly diagnosed early HCC patients to optimize individualized treatment decisions.

Eligibility

Sex
ALL
Min age
18 Years
Max age
85 Years
Healthy volunteers
No
Inclusion Criteria: 1. Preoperative enhanced imaging examination or pathological diagnosis is HCC; 2. CNLC Stage I, IIa, Child-Pugh Class A/B; 3. A single tumor with a diameter ≤ 5 cm or 2-3 tumors, with the maximum diameter ≤ 3 cm; 4. Perform liver resection surgery or MWA surgery treatment; 5. MRI and/or CEUS examinations performed within one month before surgery Exclusion Criteria: 1:There is already extrahepatic metastasis or the presence of other malignant tumors; 2: History of other treatments prior to surgery; 3: Incomplete preoperative ultrasound contrast and/or MRI imaging data, with images missing or unclear; 4: Missing postoperative follow-up data

Primary outcome measure(s)

Trial sites (1)

FacilityCityRegionStatus
The First Hospital of jilin University Changchun Jilin

More The First Hospital of Jilin University trials in China

Other trials for the same condition

Official registry record

This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.

View NCT07582419 on ClinicalTrials.gov ↗ ← All trials in China