A study to establish an intelligent system for invasive staging and prognosis of lung nodule based on multimodal imaging.

Status

Recruiting

Phases

Early Phase 1

Study type

Observational

Source

ChiCTR

Registry ID

ChiCTR2000036202

Enrollment

Unknown

Registered

2020-08-21

Start date

2020-09-01

Completion date

Unknown

Last updated

2020-09-07

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

Conditions

lung adenocarcinoma

Interventions

Case series:Nil

Eligibility

Sex/Gender

All

Age

18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1. The patient underwent preoperative CT examination. 2. The nodule size (major axis length) of the identified GGN(s) was between 5 to 30 mm. 3. The GGNs were resected and diagnosed as early-stage pulmonary adenocarcinoma by postoperative pathology with histological subtypes, namely AAH, AIS, MIA an IAC.

Exclusion criteria

Exclusion criteria: 1. Patients underwent prior invasive procedures for their GGNs, including puncture biopsy and radiofrequency ablation, before admission to our hospital. 2. Patients received cancer treatment for other tumours. 3. The CT image was poor in quality caused by respiratory motion and metal artefact.

Design outcomes

Primary

Measure	Time frame
recurrence;	—

Countries

China

Contacts

Public ContactHong Yu

Shanghai Chest Hospital, Shanghai Jiaotong University

yuhongchest@163.com+86 13816585101

Outcome results

None listed

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