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Trial Title:
Improving the Intraoperative Diagnosis Accuracy of Invasiveness for Small-sized Lung Adenocarcinoma
NCT ID:
NCT05830812
Condition:
Lung Adenocarcinoma, Stage I
Conditions: Official terms:
Adenocarcinoma
Adenocarcinoma of Lung
Conditions: Keywords:
multi-modal information
lung adenocarcinoma
intraoperative diagnosis
invasiveness
Study type:
Observational
Overall status:
Recruiting
Study design:
Time perspective:
Retrospective
Intervention:
Intervention type:
Diagnostic Test
Intervention name:
Invasiveness diagnosis
Description:
To predict the invasiveness of patients with small-sized lung adenocarcinoma
intraoperatively based on multi-modal information.
Arm group label:
adenocarcinoma in situ
Arm group label:
invasive adenocarcinoma
Arm group label:
minimally invasive adenocarcinoma
Summary:
The goal of this observational study is to improve the intraoperative diagnosis accuracy
of invasiveness for small-sized lung adenocarcinoma by combining multi-modal information.
The main question it aims to answer is whether multi-modal information have great value
of prediction on the invasiveness for small-sized lung adenocarcinoma. Since a promising
limited resection is largely based on intraoperative frozen section diagnosis, there is a
growing demand on the high-accuracy of timely pathology diagnosis. The multi-modal
information of participants will be collected retrospectively.
Criteria for eligibility:
Study pop:
From January 2018 to December 2022, about 3000 patients with lung adenocarcinoma were
enrolled in this retrospective study.
Sampling method:
Non-Probability Sample
Criteria:
Inclusion Criteria:
CT examination within 3 months before surgery Patients with operable clinical stage I
lung cancer No previous treatment in the lungs or any other organ
≥ 20 years and ≤ 80 years old Tumor less than 3cm in diameter on thin-slice (0.625-1 mm)
CT images Lung adenocarcinoma confirmed by surgical resection and histopathological
diagnosis
Exclusion Criteria:
Marked artifacts on CT images History of preoperative treatment Incomplete clinical
information or DICOM images History of other malignant tumors Lung cancer associated with
cystic airspaces
Gender:
All
Minimum age:
20 Years
Maximum age:
80 Years
Healthy volunteers:
No
Locations:
Facility:
Name:
Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Address:
City:
Wuhan
Zip:
430022
Country:
China
Status:
Recruiting
Contact:
Last name:
Xueyun Tan, MD
Phone:
13419692313
Phone ext:
86
Email:
tanxueyun93@sina.com
Start date:
January 1, 2023
Completion date:
December 31, 2026
Lead sponsor:
Agency:
Wuhan Union Hospital, China
Agency class:
Other
Source:
Wuhan Union Hospital, China
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT05830812
