Clinical trial · Observational
Deep Learning Model for Pure Solid Nodules Classification
Deep Learning Model Supplementary PET-CT as a More Effectively Diagnostic Method for Pure Solid Nodules Classification: a Multicenter Observational Study
NCT05542992CI-TRIAL-00060896unknownClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The purpose of this study is to compare the predictive performance of a CT-based deep learning model for pure-solid nodules classification and compared with the tumor maximum standardized uptake value on PET in a multicenter prospective cohort.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Lung Cancer | Malignant Lung Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| CT-based deep learning model | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- AUC
- timeFrame
- 2022.01-2023.12
- description
- Area under the curve of the receiver operating characteristic
Secondary outcomes (5)
- measure
- Accuracy
- timeFrame
- 2022.01-2023.12
- description
- Ratio of the number of correctly classified samples to the total number of samples
- measure
- sensitivity
- timeFrame
- 2022.01-2023.12
- description
- The probability of detecting a positive test in the population with the gold standard for disease (positive)
- measure
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
- Maximum age
- 75 Years
Show eligibility criteria text
Inclusion Criteria: * Participants scheduled for surgery for radiological finding of pulmonary pure-solid lesions from the preoperative thin-section CT scans; * The maximum short-axis diameter of lymph nodes less than 3 cm on CT scan; * Age ranging from 18-75 years; * definied pathological examination report available; * Obtained written informed consent. Exclusion Criteria: * Multiple lung lesions; * Poor quality of CT images; * Participants with incomplete clinical information; * Participants who have received neoadjuvant therapy before initial CT evaluation.
References
Publications (0)
Data not yet available
No reference posted for this study.