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Recruiting NCT05925764
NCT05925764 WSI Based DL for Diagnosing the IASLC Grading System of Lung Adenocarcinoma
◆ AI Clinical Summary
Plain-language summary for patients
| NCT ID | NCT05925764 |
| Status | Recruiting |
| Phase | — |
| Sponsor | Shanghai Pulmonary Hospital, Shanghai, China |
| Condition | Lung Adenocarcinoma |
| Study Type | OBSERVATIONAL |
| Enrollment | 200 participants |
| Start Date | 2024-10-15 |
| Primary Completion | 2024-12-31 |
Trial Parameters
Condition Lung Adenocarcinoma
Sponsor Shanghai Pulmonary Hospital, Shanghai, China
Study Type OBSERVATIONAL
Phase N/A
Enrollment 200
Sex ALL
Min Age 18 Years
Max Age 85 Years
Start Date 2024-10-15
Completion 2024-12-31
Interventions
Whole Slide Image based Deep Learning
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Brief Summary
The purpose of this study is to evaluate the performance of a whole slide image based deep learning model for diagnosing the IASLC grading system in resected lung adenocarcinoma based on a multicenter prospective cohort.
Eligibility Criteria
Inclusion Criteria: 1. Age ranging from 18-85 years old; 2. Pathological confirmation of primary lung adenocarcinoma after surgery; 3. Obtained written informed consent. Exclusion Criteria: 1. Multiple lung lesions; 2. Poor quality of whole slide images; 3. Mucinous adenocarcinomas and variants; 4. Participants who have received neoadjuvant therapy.
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