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Accuracy Evaluation of Artificial Intelligence Assisted Liver Tumor Ablation Path Planning

NCT05161624 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 160

Last updated 2021-12-17

No results posted yet for this study

Summary

CT-guided microwave ablation is one of the important treatment methods for primary or metastatic liver tumors. It has the advantages of minimally invasive, safe, and economical. For liver tumors with a diameter of less than 3 cm, it can be comparable to surgical resection. However, different doctors have different levels of experience, leading to a high risk of residues after ablation and even complications. The key is to fail to plan the needle placement reasonably. The past research on path planning was mostly conducted by the engineering team, so that the actual clinical needs were not considered comprehensively, and the sample size of verified cases was small, which limited the application of existing models in the clinical application. In previous study, we used artificial intelligence to segment the upper abdominal organs and construct the constraint function to establish the ablation path planning model, and initially verified the effectiveness of the path planning model in a small number of cases. Now it is planned to expand the number of patients enrolled to evaluate the accuracy of the ablation path planning model that we have established.

Conditions

  • Liver Tumor

Interventions

DIAGNOSTIC_TEST

Accuracy evaluation

The design of the diagnostic trial will include 160 cases of liver tumors with indications for microwave ablation after a multidisciplinary consultation with clinicians (Multiple Disciplinary Team, MDT), including primary liver cancer and metastatic liver tumors, and the tumor diameter is less than 3 cm. The test subjects consist of three groups: a. path planning model, b. junior ablation specialists, c. senior ablation specialists. The three groups will perform microwave ablation path planning on 160 selected cases of liver tumors. The attending professor of the clinical medical group of the department is responsible for scoring, evaluating whether the design of the plan is reasonable, and then comparing the scoring results by using statistical methods to evaluate the accuracy and effectiveness of the path planning model established in this study.

Sponsors & Collaborators

  • Sun Yat-sen University

    lead OTHER

Eligibility

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

Timeline & Regulatory

Start
2021-12-15
Primary Completion
2022-02-28
Completion
2022-04-30

Countries

  • China

Study Locations

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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 NCT05161624 on ClinicalTrials.gov