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Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma

NCT03198975 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 40

Last updated 2017-06-26

No results posted yet for this study

Summary

Microvascular invasion (MVI) has been well demonstrated as an unfavorable prognostic factor for hepatocellular carcinoma (HCC), and patients with MVI have a high risk of tumor recurrence after curative hepatectomy. Currently, the diagnosis of MVI is determined on the postoperative histologic examination, which greatly limits its influence on preoperative decision making. Therefore, we constructed this prospective study to develop a machine learning-based model for preoperative prediction of MVI by extracting high-dimensional magnetic resonance (MR) image features.

Conditions

Interventions

DIAGNOSTIC_TEST

Magnetic resonance image

Histologically-diagnosed primary HCC after curative hepatectomy. The magnetic resonance image will be imported into the software ,and the radiomic textural features will be automatically extracted by the Analysis-Kit software.The high-throughput extracted features will be then selected and a prediction model will be developed in the training set in which patients were collected from a retrospective study. In this project, an independent validation set will be collected and used to validate the prediction accuracy of the model.

Sponsors & Collaborators

  • Ming Kuang

    lead OTHER

Principal Investigators

  • Ming Kuang, PhD · Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China

Eligibility

Min Age
18 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2017-06-23
Primary Completion
2017-07-31
Completion
2017-07-31

Countries

  • China

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT03198975 on ClinicalTrials.gov