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Deep learning-based PET/CT image quality optimisation and application in precision diagnosis and treatment of lung cancer

Deep learning-based PET/CT image quality optimisation and application in precision diagnosis and treatment of lung cancer

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500107804
Enrollment
Unknown
Registered
2025-08-19
Start date
2024-04-01
Completion date
Unknown
Last updated
2025-08-25

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

Conditions

Lung lesion

Interventions

T staging group:None
N staging group:None
M staging group:None

Sponsors

Shanghai Changzheng Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Routine lung cancer patients. 2. Postoperative pathology or lymph node biopsy pathology results are available. 3. There is postoperative follow-up available.

Exclusion criteria

Exclusion criteria: 1. Pregnant and lactating women. 2. Patients with severe primary diseases such as cardiovascular, liver, kidney, and hematopoietic systems. 3. Psychiatric patients. 4. Severe claustrophobia, unable to cooperate with magnetic resonance imaging examination. 5. Elderly individuals with limited mobility, difficulty in self-care, or difficulty in reaching the experimental site.

Design outcomes

Primary

MeasureTime frame
SUVmax;Radiomics Features;—

Secondary

MeasureTime frame
SUVmean;SUVsd;—

Countries

China

Contacts

Public ContactFan Li

Shanghai Changzheng Hospital

fanli0930@163.com+86 135 4648 4699

Outcome results

None listed

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