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A deep learning system for detection of tumor spread through air spaces in lung adenocarcinoma: a mulicenter cohort study

A deep learning system for detection of tumor spread through air spaces in lung adenocarcinoma: a mulicenter cohort study - STAScope

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500105680
Enrollment
Unknown
Registered
2025-07-09
Start date
2025-08-01
Completion date
Unknown
Last updated
2025-07-14

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Lung cancer

Interventions

Gold Standard:Pathological diagnosis based on FFPE WSI images, diagnosed and reviewed by three senior pathologists
Index test:STAScope developed by our research

Sponsors

Guangdong Provincial People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Age > 18 years old; 2. Complete clinical data; 3. Postoperative patients in our center with a clear STAS status reported in the pathology report; 4. Complete postoperative digital pathology WSI images and available FFPE tumor tissues; 5. Patients with lung adenocarcinoma confirmed by pathology.

Exclusion criteria

Exclusion criteria: 1. Incomplete clinical data; 2. Pathology report does not clearly state the STAS status; 3. Patients who have undergone chemotherapy and/or targeted, immunotherapy, or radiotherapy before surgery; 4. Poor image quality; 5. No evaluable lung tissue.

Design outcomes

Primary

MeasureTime frame
Sensitivity;Specificity;—

Countries

China

Contacts

Public ContactHaiyu Zhou

Guangdong Provincial People's Hospital

zhouhaiyu@gdph.org.cn+86 137 1034 2002

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026