Deep Learning Signature for Predicting the Novel Grading System of Clinical Stage I Lung Adenocarcinoma

Deep Learning Signature Based on PET-CT Images for Predicting the Novel Grading System of Clinical Stage I Lung Adenocarcinoma

Status

UNKNOWN

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT05736991

Enrollment

600

Registered

2023-02-21

Start date

2022-11-01

Completion date

2023-04-30

Last updated

2023-02-21

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

Conditions

Grading System, Lung Adenocarcinoma, Radiomics

Brief summary

The purpose of this study is to evaluate the performance of a PET/ CT-based deep learning signature for predicting the grade 3 tumors based on the novel grading system in clinical stage stage I lung adenocarcinoma based on a multicenter prospective cohort.

Interventions

DIAGNOSTIC_TESTPET/CT-based Radiomics Signature

Radiomics Signature Based on PET-CT for Predicting the Novel Grading System of Clinical Stage I Lung Adenocarcinoma

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

20 Years to 75 Years

Healthy volunteers

Yes

Inclusion criteria

(1) Participants scheduled for surgery for radiological finding of pulmonary lesions from the preoperative thin-section CT scans; (2) The maximum diameter of lesion less than 4 cm on CT scans; (3) The maximum short axis diameter of lymph nodes less than 1 cm on CT scan; (4) The SUVmax of hilar and mediastinal lymph nodes less than 2.5; (5) Pathological confirmation of primary lung adenocarcinoma; (5) Age ranging from 20-75 years; (6) Obtained written informed consent.

Exclusion criteria

(1) Multiple lung lesions; (2) Poor quality of PET-CT images; (3) Participants with incomplete clinical information; (4) Mucinous adenocarcinomas; (5) Participants who have received neoadjuvant therapy.

Design outcomes

Primary

Measure	Time frame	Description
Area under the receiver operating characteristic curve	2022.11-2023.4	Area under the receiver operating characteristic curve

Secondary

Measure	Time frame	Description
Sensitivity	2022.11-2023.4	Sensitivity
Specificity	2022.11-2023.4	Specificity
Positive predictive value	2022.11-2023.4	Positive predictive value
Negative predictive value	2022.11-2023.4	Negative predictive value
Accuracy	2022.11-2023.4	Accuracy

Countries

China

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026