Hepatocellular Carcinoma (HCC)HCC-MVI-CADNCT07170345
Computer-Aided Diagnosis for Hepatocellular Carcinoma Microvascular Invasion
An observational study of Hepatocellular Carcinoma (HCC) and Microvascular Invasion (MVI), run by Chinese Academy of Sciences at 19 sites in China.
Trial summary
Hepatocellular carcinoma (HCC) is a common malignancy in China with a high mortality rate. Its early recurrence and long-term prognosis are closely associated with tumor aggressiveness. Read more about this study
- Who is it for?
- Ages 18 to 18 years
- Conditions the study is for
- Hepatocellular Carcinoma (HCC), Microvascular Invasion (MVI)
- What is being tested?
- Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC
- How many people
- 400 participants
- Where
- 19 sitesChina
- Study dates
- 1 Sep 2025to 1 Sep 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 18 years
- All sexes
- No healthy volunteers
- Adult
Study population: The study population consists of adult patients (≥18 years) with hepatocellular carcinoma who undergo curative-intent surgical treatment, including hepatic resection or liver transplantation, at participating clinical centers. Approximately 5,000 retrospective cases and 400 prospective cases will be included. All participants will have preoperative multiphase CT imaging and postoperative pathological evaluation with documented microvascular invasion (MVI) status.
Who may be able to join
- Age ≥ 18 years.
- Confirmed diagnosis of hepatocellular carcinoma (HCC) according to the Chinese Clinical Practice Guidelines for Primary Liver Cancer.
- Eligible for surgical intervention (hepatic resection or liver transplantation) according to the Chinese Clinical Practice Guidelines for Cancer, including stages Ia, Ib, and IIa.
- Preoperative imaging examination performed within 1 month before surgery.
- Availability of histopathological evaluation with documented microvascular invasion (MVI) status.
Who cannot join
- History of prior antitumor treatment, including preoperative surgical intervention, transarterial chemoembolization (TACE), radiofrequency ablation (RFA), systemic therapy, or any other preoperative intervention.
- Presence of major vascular invasion, bile duct invasion/thrombosis, extrahepatic metastasis, or lymph node involvement.
- Diffuse hepatocellular carcinoma or tumor rupture with hemorrhage.
- Lack of key data required for primary analysis.
- Poor image quality that prevents reliable qualitative or radiomics analysis.
Trial locations and contacts
19 sites in 1 country. Contact the study team or a site near you to ask about taking part.
19 sites in 1 country
China19 sites, 19 recruiting
- Recruiting
Beijing Tsinghua Changgeng Hospital
Beijing
Zhuozhao Zheng
- Recruiting
Beijing YouAn Hospital
Beijing
Hongjun Li
- Recruiting
Peking Union Medical College Hospital
Beijing
Yilei Mao
- Recruiting
West China Hospital
Chengdu, Sichuan
Hanyu Jiang
- Recruiting
Dazhou Central Hospital
Dazhou, Sichuan
Jie Liu
- Recruiting
Meng Chao Hepatobiliary Hospital of Fujian Medical University
Fuzhou, Fujian
Xiaolong Liu
- Recruiting
Guangdong Provincial Hospital of Traditional Chinese Medicine
Guangzhou, Guangdong
Junming He
- Recruiting
Zhujiang Hospital
Guangzhou, Guangdong
Shihua Fang
- Recruiting
Guizhou Provincial People's Hospital
Guiyang, Guizhou
Rongpin Wang
- Recruiting
First Affiliated Hospital of Kunming Medical University
Kunming, Yunnan
Bo He
- Recruiting
The First People's Hospital of Yunnan Province
Kunming, Yunnan
Yun Jin
- Recruiting
Yunnan Cancer Hospital
Kunming, Yunnan
Yong Zha
- Recruiting
First Affiliated Hospital of Guangxi Medical University
Nanning, Guangxi
Yidi Chen
- Recruiting
Eastern Hepatobiliary Surgery Hospital
Shanghai
Yabo Jiang
- Recruiting
Shengjing Hospital
Shenyang, Liaoning
Meng Niu
- Recruiting
First Affiliated Hospital of Wenzhou Medical University
Wenzhou, Zhejiang
Gang Chen
- Recruiting
Henan Provincial People's Hospital
Zhengzhou, Henan
Deyu Li
- Recruiting
Fifth Affiliated Hospital, Sun Yat-Sen University
Zhuhai, Guangdong
Jian Li
- Recruiting
Zhuhai People's Hospital
Zhuhai, Guangdong
Sirui Fu
About this study
Official title: Development of a Computer-Aided Diagnosis System for Hepatocellular Carcinoma Microvascular Invasion Based on Preoperative Image Analysis
Hepatocellular carcinoma (HCC) is a common malignancy in China with a high mortality rate. Its early recurrence and long-term prognosis are closely associated with tumor aggressiveness. Microvascular invasion (MVI), defined as the presence of tumor cells within small branches of the portal or hepatic veins, is a key indicator of malignant biological behavior in HCC. Clinically, MVI is strongly correlated with postoperative early recurrence and serves as an important factor in determining surgical margin extension, adjuvant therapy, and postoperative management strategies.
At present, definitive diagnosis of MVI still relies on postoperative pathological examination, and stable, effective preoperative assessment methods are lacking. Although some studies have attempted to predict MVI using preoperative imaging features, their clinical translation remains limited by poor generalizability, weak interpretability, and insufficient cross-center adaptability.
This study aims to leverage multiphase preoperative CT imaging, artificial intelligence techniques, and clinical prior knowledge to develop a high-performance, generalizable, and interpretable computer-aided diagnostic system for preoperative prediction of HCC-MVI. An observational, prospective evaluation will be conducted to assess system performance and to facilitate the clinical translation of intelligent diagnostic technologies in real-world practice.
Read the detailed description
Hepatocellular carcinoma (HCC) is a common malignancy in China with a high mortality rate. Early recurrence and long-term prognosis are closely linked to tumor aggressiveness. Microvascular invasion (MVI), defined as the presence of tumor cells within small branches of the portal or hepatic veins, is a critical marker of malignant biological behavior. Clinically, MVI is strongly associated with early postoperative recurrence and serves as an important reference for determining surgical margin extension, adjuvant treatment, and postoperative management strategies. At present, definitive diagnosis of MVI still relies on postoperative pathological examination, and reliable preoperative assessment methods are lacking. Although prior studies have attempted to predict MVI using preoperative imaging, their clinical application remains limited by poor generalizability, weak interpretability, and insufficient cross-center adaptability.
This study aims to develop a high-performance, generalizable, and interpretable computer-aided diagnostic (CAD) system for preoperative prediction of HCC-MVI using multiphase CT imaging, artificial intelligence techniques, and clinical prior knowledge. The system will be evaluated prospectively in an observational, multicenter clinical study to assess its diagnostic value and clinical applicability.
The CAD system integrates three categories of imaging features: (1) high-level representations automatically extracted by deep neural networks; (2) predefined radiomics features such as tumor morphology, texture, and intensity distributions; and (3) structured prior features derived from radiological expertise, including tumor margin blurriness and spatial relationships with adjacent portal veins. Sparse constraints and redundancy suppression mechanisms will be applied to identify stable and efficient MVI-related representations. In addition, the system adopts a spatial domain strategy covering tumor, peritumoral, and distant regions, in order to capture invasion patterns from both local morphology and microenvironmental context, thereby constructing reproducible and clinically interpretable imaging biomarkers.
To overcome the limitations of single-domain models, the system employs a multi-source heterogeneous fusion strategy that integrates morphological-textural features, dynamic enhancement patterns, and spatial graph structures. The model architecture combines convolutional neural networks (CNNs) to capture fine-grained textures, Transformer modules to model long-range dependencies, and graph neural networks (GNNs) to represent tumor-vascular topological relationships. This hybrid approach enables comprehensive understanding of both local details and global structures. Furthermore, the model incorporates uncertainty quantification and attention-like mechanisms to dynamically adjust prediction confidence and generate saliency heatmaps. These outputs are designed to enhance clinicians' interpretability and trust in the system. An interactive visualization interface will also be developed to support risk interpretation and surgical planning.
The study will conduct a prospective observational validation across multiple clinical centers, with unified inclusion/exclusion criteria and standardized data collection protocols. Model predictions will be blindly compared against postoperative pathological results. In addition to conventional metrics (accuracy, sensitivity, specificity, and AUC), the study will observationally evaluate the impact of model-based predictions on preoperative risk stratification and surgical decision-making. By testing the system across diverse patient populations, the study aims to confirm its generalizability, clinical utility, and potential for real-world translation of intelligent diagnostic technologies.
- Being tested
- Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC
- Keywords
- Hepatocellular Carcinoma, Microvascular Invasion, Computer-Aided Diagnosis System, Artificial Intelligence, Medical Image, Multimodal Model
- Medical subject headings
- Carcinoma, Hepatocellular
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCDiagnostic test
This intervention is an artificial intelligence-based computer-aided diagnosis (CAD) system developed to predict microvascular invasion (MVI) in patients with hepatocellular carcinoma using preoperative multiphase CT imaging. The system integrates deep learning, radiomics, and expert-defined imaging features to provide risk assessment and visualization of MVI prior to surgery. In this study, the CAD system will be evaluated retrospectively and prospectively in an observational manner only. The results will not influence clinical decision-making or patient management, and all treatments will follow standard of care.
| Study group | Role | What they receive |
|---|---|---|
| Peking Union Medical College Hospital | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| First Affiliated Hospital of Kunming Medical University | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| Beijing YouAn Hospital | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| Zhujiang Hospital | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| Meng Chao Hepatobiliary Hospital of Fujian Medical University | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| First Affiliated Hospital of Wenzhou Medical University | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| Fifth Affiliated Hospital, Sun Yat-Sen University | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| Henan Provincial People's Hospital | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| Guangdong Provincial Hospital of Traditional Chinese Medicine | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| Shengjing Hospital | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| Beijing Tsinghua Changgeng Hospital | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| Yunnan Cancer Hospital | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| The First People's Hospital of Yunnan Province | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| Guizhou Provincial People's Hospital | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| First Affiliated Hospital of Guangxi Medical University | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| West China Hospital | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| Zhuhai People's Hospital | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| Dazhou Central Hospital | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC | |
| Eastern Hepatobiliary Surgery Hospital | patients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. Receives: Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCC |
What is being measured
The primary outcome is the main question the study is designed to answer.
Area Under the Receiver Operating Characteristic Curve (AUC)
The AUC will be calculated by comparing CAD system predictions with the reference standard of postoperative pathological diagnosis of microvascular invasion in hepatocellular carcinoma.
Measured: Within 1 month after surgery
Accuracy
Accuracy will be defined as the proportion of correctly classified cases (both MVI-positive and MVI-negative) by the CAD system compared with postoperative pathology.
Measured: Within 1 month after surgery
Secondary outcomes (3)
Sensitivity
Sensitivity will be calculated as the proportion of true positive MVI cases correctly identified by the CAD system compared with postoperative pathology.
Measured: Within 1 month after surgery
Specificity
Specificity will be calculated as the proportion of true negative MVI cases correctly identified by the CAD system compared with postoperative pathology.
Measured: Within 1 month after surgery
Calibration
Calibration performance will be assessed using calibration curves, Hosmer-Lemeshow goodness-of-fit tests, and Brier scores, to determine agreement between predicted probabilities and observed MVI outcomes.
Measured: Within 1 month after surgery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Sep 2025
- Study start1 Sep 2025
- Primary completion1 Sep 2026 (estimated)
- Study completion1 Sep 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Hepatocellular Carcinoma (HCC)Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 400 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Chinese Academy of Sciences
- Sponsor type
- Other government
- Collaborators
- Peking Union Medical College Hospital, First Affiliated Hospital of Kunming Medical University, Beijing YouAn Hospital, Zhujiang Hospital, Meng Chao Hepatobiliary Hospital of Fujian Medical University, First Affiliated Hospital of Wenzhou Medical University, Fifth Affiliated Hospital, Sun Yat-Sen University, Henan Provincial People's Hospital, Guangdong Provincial Hospital of Traditional Chinese Medicine, Shengjing Hospital, Beijing Tsinghua Changgeng Hospital, Yunnan Cancer Hospital, The First People's Hospital of Yunnan, Guizhou Provincial People's Hospital, First Affiliated Hospital of Guangxi Medical University, West China Hospital, ZhuHai Hospital, Dazhou Central Hospital, Eastern Hepatobiliary Surgery Hospital
- Responsible party
- Principal investigator, Di Dong, Chinese Academy of Sciences
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07170345
- Sponsor's protocol ID
- CASMI008
- Acronym
- HCC-MVI-CAD
- Status last verified
- Aug 2025
- First submitted
- 28 Aug 2025
- Last updated
- 12 Sep 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 12 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of a Computer-Aided Diagnosis System for Hepatocellular Carcinoma Microvascular Invasion Based on Preoperative Image Analysis
- ClinicalTrials.gov ID
- NCT07170345
- Acronym / sponsor ID
- HCC-MVI-CAD / CASMI008
- Keywords
- Hepatocellular Carcinoma, Microvascular Invasion, Computer-Aided Diagnosis System, Artificial Intelligence, Medical Image, Multimodal Model
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 400 participants (estimated)
- Lead sponsor
- Chinese Academy of SciencesOther government
- Collaborators
- Peking Union Medical College Hospital, First Affiliated Hospital of Kunming Medical University, Beijing YouAn Hospital, Zhujiang Hospital, Meng Chao Hepatobiliary Hospital of Fujian Medical University, First Affiliated Hospital of Wenzhou Medical University, Fifth Affiliated Hospital, Sun Yat-Sen University, Henan Provincial People's Hospital, Guangdong Provincial Hospital of Traditional Chinese Medicine, Shengjing Hospital, Beijing Tsinghua Changgeng Hospital, Yunnan Cancer Hospital, The First People's Hospital of Yunnan, Guizhou Provincial People's Hospital, First Affiliated Hospital of Guangxi Medical University, West China Hospital, ZhuHai Hospital, Dazhou Central Hospital, Eastern Hepatobiliary Surgery Hospital
- Study start
- 1 Sep 2025 (actual)
- Primary completion
- 1 Sep 2026 (estimated)
- Study completion
- 1 Sep 2027 (estimated)
- First posted
- 12 Sep 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Hepatocellular carcinoma (HCC) is a common malignancy in China with a high mortality rate. Its early recurrence and long-term prognosis are closely associated with tumor aggressiveness. Microvascular invasion (MVI), defined as the presence of tumor cells within small branches of the portal or hepatic veins, is a key indicator of malignant biological behavior in HCC. Clinically, MVI is strongly correlated with postoperative early recurrence and serves as an important factor in determining surgical margin extension, adjuvant therapy, and postoperative management strategies.
At present, definitive diagnosis of MVI still relies on postoperative pathological examination, and stable, effective preoperative assessment methods are lacking. Although some studies have attempted to predict MVI using preoperative imaging features, their clinical translation remains limited by poor generalizability, weak interpretability, and insufficient cross-center adaptability.
This study aims to leverage multiphase preoperative CT imaging, artificial intelligence techniques, and clinical prior knowledge to develop a high-performance, generalizable, and interpretable computer-aided diagnostic system for preoperative prediction of HCC-MVI. An observational, prospective evaluation will be conducted to assess system performance and to facilitate the clinical translation of intelligent diagnostic technologies in real-world practice.
Detailed description
Hepatocellular carcinoma (HCC) is a common malignancy in China with a high mortality rate. Early recurrence and long-term prognosis are closely linked to tumor aggressiveness. Microvascular invasion (MVI), defined as the presence of tumor cells within small branches of the portal or hepatic veins, is a critical marker of malignant biological behavior. Clinically, MVI is strongly associated with early postoperative recurrence and serves as an important reference for determining surgical margin extension, adjuvant treatment, and postoperative management strategies. At present, definitive diagnosis of MVI still relies on postoperative pathological examination, and reliable preoperative assessment methods are lacking. Although prior studies have attempted to predict MVI using preoperative imaging, their clinical application remains limited by poor generalizability, weak interpretability, and insufficient cross-center adaptability.
This study aims to develop a high-performance, generalizable, and interpretable computer-aided diagnostic (CAD) system for preoperative prediction of HCC-MVI using multiphase CT imaging, artificial intelligence techniques, and clinical prior knowledge. The system will be evaluated prospectively in an observational, multicenter clinical study to assess its diagnostic value and clinical applicability.
The CAD system integrates three categories of imaging features: (1) high-level representations automatically extracted by deep neural networks; (2) predefined radiomics features such as tumor morphology, texture, and intensity distributions; and (3) structured prior features derived from radiological expertise, including tumor margin blurriness and spatial relationships with adjacent portal veins. Sparse constraints and redundancy suppression mechanisms will be applied to identify stable and efficient MVI-related representations. In addition, the system adopts a spatial domain strategy covering tumor, peritumoral, and distant regions, in order to capture invasion patterns from both local morphology and microenvironmental context, thereby constructing reproducible and clinically interpretable imaging biomarkers.
To overcome the limitations of single-domain models, the system employs a multi-source heterogeneous fusion strategy that integrates morphological-textural features, dynamic enhancement patterns, and spatial graph structures. The model architecture combines convolutional neural networks (CNNs) to capture fine-grained textures, Transformer modules to model long-range dependencies, and graph neural networks (GNNs) to represent tumor-vascular topological relationships. This hybrid approach enables comprehensive understanding of both local details and global structures. Furthermore, the model incorporates uncertainty quantification and attention-like mechanisms to dynamically adjust prediction confidence and generate saliency heatmaps. These outputs are designed to enhance clinicians' interpretability and trust in the system. An interactive visualization interface will also be developed to support risk interpretation and surgical planning.
The study will conduct a prospective observational validation across multiple clinical centers, with unified inclusion/exclusion criteria and standardized data collection protocols. Model predictions will be blindly compared against postoperative pathological results. In addition to conventional metrics (accuracy, sensitivity, specificity, and AUC), the study will observationally evaluate the impact of model-based predictions on preoperative risk stratification and surgical decision-making. By testing the system across diverse patient populations, the study aims to confirm its generalizability, clinical utility, and potential for real-world translation of intelligent diagnostic technologies.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 19
| Arm | Type | Receives |
|---|---|---|
| Peking Union Medical College Hospital | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| First Affiliated Hospital of Kunming Medical University | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| Beijing YouAn Hospital | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| Zhujiang Hospital | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| Meng Chao Hepatobiliary Hospital of Fujian Medical University | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| First Affiliated Hospital of Wenzhou Medical University | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| Fifth Affiliated Hospital, Sun Yat-Sen University | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| Henan Provincial People's Hospital | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| Guangdong Provincial Hospital of Traditional Chinese Medicine | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| Shengjing Hospital | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| Beijing Tsinghua Changgeng Hospital | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| Yunnan Cancer Hospital | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| The First People's Hospital of Yunnan Province | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| Guizhou Provincial People's Hospital | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| First Affiliated Hospital of Guangxi Medical University | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| West China Hospital | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| Zhuhai People's Hospital | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| Dazhou Central Hospital | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
| Eastern Hepatobiliary Surgery Hospital | – | Diagnostic Test: Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCpatients aged 18 years and older who undergo surgical resection for hepatocellular carcinoma with available pathological evaluation of microvascular invasion. We will collect preoperative multiphase CT images, clinical characteristics, and pathological outcomes. |
Who may qualify
- Ages
- 18 to 18 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult
- Study population
- The study population consists of adult patients (≥18 years) with hepatocellular carcinoma who undergo curative-intent surgical treatment, including hepatic resection or liver transplantation, at participating clinical centers. Approximately 5,000 retrospective cases and 400 prospective cases will be included. All participants will have preoperative multiphase CT imaging and postoperative pathological evaluation with documented microvascular invasion (MVI) status.
Key inclusion criteria (5 listed)
- Age ≥ 18 years.
- Confirmed diagnosis of hepatocellular carcinoma (HCC) according to the Chinese Clinical Practice Guidelines for Primary Liver Cancer.
- Eligible for surgical intervention (hepatic resection or liver transplantation) according to the Chinese Clinical Practice Guidelines for Cancer, including stages Ia, Ib, and IIa.
- Preoperative imaging examination performed within 1 month before surgery.
- Availability of histopathological evaluation with documented microvascular invasion (MVI) status.
Key exclusion criteria (5 listed)
- History of prior antitumor treatment, including preoperative surgical intervention, transarterial chemoembolization (TACE), radiofrequency ablation (RFA), systemic therapy, or any other preoperative intervention.
- Presence of major vascular invasion, bile duct invasion/thrombosis, extrahepatic metastasis, or lymph node involvement.
- Diffuse hepatocellular carcinoma or tumor rupture with hemorrhage.
- Lack of key data required for primary analysis.
- Poor image quality that prevents reliable qualitative or radiomics analysis.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Computer-Aided Diagnosis System for Preoperative Prediction of MVI in HCCThis intervention is an artificial intelligence-based computer-aided diagnosis (CAD) system developed to predict microvascular invasion (MVI) in patients with hepatocellular carcinoma using preoperative multiphase CT imaging. The system integrates deep learning, radiomics, and expert-defined imaging features to provide risk assessment and visualization of MVI prior to surgery. In this study, the CAD system will be evaluated retrospectively and prospectively in an observational manner only. The results will not influence clinical decision-making or patient management, and all treatments will follow standard of care. | Diagnostic test | Beijing Tsinghua Changgeng Hospital, Beijing YouAn Hospital, Dazhou Central Hospital, Eastern Hepatobiliary Surgery Hospital, Fifth Affiliated Hospital, Sun Yat-Sen University, First Affiliated Hospital of Guangxi Medical University, First Affiliated Hospital of Kunming Medical University, First Affiliated Hospital of Wenzhou Medical University, Guangdong Provincial Hospital of Traditional Chinese Medicine, Guizhou Provincial People's Hospital, Henan Provincial People's Hospital, Meng Chao Hepatobiliary Hospital of Fujian Medical University, Peking Union Medical College Hospital, Shengjing Hospital, The First People's Hospital of Yunnan Province, West China Hospital, Yunnan Cancer Hospital, Zhuhai People's Hospital, Zhujiang Hospital |
Primary outcome
Area Under the Receiver Operating Characteristic Curve (AUC)
Time frame: Within 1 month after surgery
The AUC will be calculated by comparing CAD system predictions with the reference standard of postoperative pathological diagnosis of microvascular invasion in hepatocellular carcinoma.
Accuracy
Time frame: Within 1 month after surgery
Accuracy will be defined as the proportion of correctly classified cases (both MVI-positive and MVI-negative) by the CAD system compared with postoperative pathology.
3 secondary outcomes
Sensitivity
Time frame: Within 1 month after surgery
Specificity
Time frame: Within 1 month after surgery
Calibration
Time frame: Within 1 month after surgery
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Sep 2025.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
19 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Hepatocellular Carcinoma (HCC) and Microvascular Invasion (MVI), run by Chinese Academy of Sciences at 19 sites in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 12 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 19 sites in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Di Dong, Ph.D. (+86 13811833760, di.dong@ia.ac.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Area Under the Receiver Operating Characteristic Curve (AUC) (time frame: Within 1 month after surgery). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 Sep 2025.