Construction of database and exploratory trial for performance evaluation of artificial intelligence model to support ultrasonic diagnosis of liver mass
Not Applicable
Recruiting
- Conditions
- iver Mass
- Registration Number
- JPRN-UMIN000052695
- Lead Sponsor
- The Japan Society of Ultrasonics in Medicine
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Recruiting
- Sex
- All
- Target Recruitment
- 20
Inclusion Criteria
Not provided
Exclusion Criteria
Participants in the construction of database for B-mode US video images of liver mass include: 1) Cases where a definitive diagnosis of liver mass could not be established. 2) Cases where modification of imaging findings is anticipated due to treatment of liver tumors. 3) Cases where consent from the patient has been withdrawn. 4) Cases where obtaining consent from the individual is difficult. 5) Other cases deemed inappropriate by the attending physician.
Study & Design
- Study Type
- Interventional
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Evaluation of improvement for accuracy, sensitivity, specificity, and Matthews correlation coefficient in the discrimination of malignant tumors in B-mode US examination under the support of AI
- Secondary Outcome Measures
Name Time Method 1) Evaluation of improvement for the accuracy of liver tumor differentiation among four types of liver lesions (hepatocellular carcinoma, metastatic liver cancer, hepatic hemangioma, and hepatic cyst) under the support of AI. 2) Evaluation of improvement for disease-specific sensitivity and specificity in the differentiation of liver mass among four types of liver lesions under the support of AI. 3) Evaluation for precision, recall, and F-value in the detection of liver mass under the support of AI. 4) Stratified analysis of skilled (Board certified fellows and registered medical sonographers of the Japan Society of Ultrasonics in Medicines) vs. non-Skilled (non-certified fellows and non-registered medical sonographer) in primary and secondary outcomes 5) Construction of database of US video images for the clinical trial of AI-aided US diagnosis of liver tumor