AI Models for Predicting Occult Pleural Dissemination in NSCLC

NCT ID: NCT07065422

Last Updated: 2025-08-06

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 326 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2023-12-13
• Study Completion Date: 2025-01-01

Brief Summary

Occult pleural dissemination (PD) in non-small cell lung cancer (NSCLC) patients is likely to be missed on computed tomography (CT) scans, associated with poor survival, and generally contraindicated for radical surgery. This study aimed to develop and compare the performance of radiomics-based machine learning (ML), deep learning (DL), and fusion models to preoperatively identify occult PDs in NSCLC patients. Patients from three Chinese high-volume medical centers (2016-2023) were retrospectively collected and divided into training, internal test, and external test cohorts. Ten radiomics-based ML models and eight DL models were trained using CT plain scan images at the maximum cross-sectional areas of the primary tumor. Moreover, another two fusion models (prefusion and postfusion) were developed using feature-based and decision-based methods. The receiver operating characteristic curve (ROC) and area under the curve (AUC) were mainly used to compare the predictive performance of the models.

Conditions

Non-Small Cell Lung Cancer

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: CROSS_SECTIONAL

Study Groups

non-small cell lung cancer (NSCLC) patients with or without occult pleural dissemination.

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

• pathologically confirmed primary NSCLC with malignant pleural dissemination;
• no preoperative treatment;
• clinicopathological data were complete.

Exclusion Criteria

• pleural effusion detected preoperatively;
• preoperatively diagnosed with PD;
• poor CT quality or no CT scans within 1 month before surgery.

• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

First Affiliated Hospital of Chongqing Medical University

OTHER

Sponsor Role: collaborator

Xinqiao hospital of the third military medical university

UNKNOWN

Sponsor Role: collaborator

Daping Hospital and the Research Institute of Surgery of the Third Military Medical University

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

Daping hospital

Chongqing, , China

Countries

China

Other Identifiers

GUOW

Identifier Type: -

Identifier Source: org_study_id