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Recruiting NCT05925764

WSI Based DL for Diagnosing the IASLC Grading System of Lung Adenocarcinoma

— Observational Lung Adenocarcinoma Whole Slide Image IASLC Grading System Artificial Intelligence

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: Whole Slide Image based Deep Learning.
Who it may be relevant to
Registry conditions: Lung Adenocarcinoma, Whole Slide Image, IASLC Grading System, Artificial Intelligence. Basic parameters: 18 years — 85 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
China
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

Unsure about the terms? Read our patient guide →

Official title

Whole Slide Image Based Deep Learning for Diagnosing the International Association for the Study of Lung Cancer Proposed Grading System of Lung Adenocarcinoma

Overview

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.

Interventions

  • Diagnostic test Whole Slide Image based Deep Learning
    Whole Slide Image Based Deep Learning for Diagnosing the IASLC Grading System of Lung Adenocarcinoma

Primary outcome measures

  • Agreement rate of the IASLC grading system [Time frame: 2024.11.01-2024.12.31]
Secondary outcome measures (1)
  • Agreement rate of the predominant subtypes [Time frame: 2024.11.01-2024.12.31]

Eligibility criteria

Inclusion criteria

  • Age ranging from 18-85 years old;
  • Pathological confirmation of primary lung adenocarcinoma after surgery;
  • Obtained written informed consent.

Exclusion criteria

  • Multiple lung lesions;
  • Poor quality of whole slide images;
  • Mucinous adenocarcinomas and variants;
  • Participants who have received neoadjuvant therapy.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Study design

Observational model
Cohort

Study locations

China · 3 centers
  • Affiliated Hospital of Zunyi Medical University — Zunyi
  • The First Affiliated Hospital of Nanchang University — Nanchang
  • Ningbo HwaMei Hospital — Ningbo

Identifiers

NCT: NCT05925764 · WSIGS

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗