Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| Ningbo No.2 Hospital | OTHER |
| Zunyi Medical College | OTHER |
| The First Affiliated Hospital of Nanchang University | OTHER |
Not provided
Not provided
Not provided
Not provided
The purpose of this study is to evaluate the performance of a PET/ CT-based deep learning signature for predicting aggressive histological pattern in resected non-small cell lung cancer based on a multicenter prospective cohort.
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| PET/CT-based Deep Learning Signature | Diagnostic Test | Deep Learning Signature Based on PET-CT for Predicting the Aggressive Histological Pattern in Resected Non-small Cell Lung Cancer |
| Measure | Description | Time Frame |
|---|---|---|
| Area under the receiver operating characteristic curve | The area under the receiver operating characteristic curve (ROC) of the deep learning model in predicting the presence or absence of the aggressive histological pattern. The aggressive histological pattern includes spread through air space (STAS), visceral pleural invasion (VPI), and lymphovascular invasion (LVI). And the model will output all predictive values (presence or absence) of the three kinds of aggressive histological patterns. | 2023.5.1-2023.10.31 |
| Measure | Description | Time Frame |
|---|---|---|
| Sensitivity | The sensitivity of the deep learning model in predicting the presence or absence of the aggressive histological pattern. The aggressive histological pattern includes spread through air space (STAS), visceral pleural invasion (VPI), and lymphovascular invasion (LVI). And the model will output all predictive values (presence or absence) of the three kinds of aggressive histological patterns. |
| Measure | Description | Time Frame |
|---|---|---|
| Specificity | The specificity of the deep learning model in predicting the presence or absence of the aggressive histological pattern. The aggressive histological pattern includes spread through air space (STAS), visceral pleural invasion (VPI), and lymphovascular invasion (LVI). And the model will output all predictive values (presence or absence) of the three kinds of aggressive histological patterns. | 2023.5.1-2023.10.31 |
Inclusion Criteria:
(1) Participants scheduled for surgery for radiological finding of pulmonary lesions from the preoperative thin-section CT scans; (2) Pathological confirmation of primary NSCLC; (3) Age ranging from 20-75 years; (4) Obtained written informed consent.
Exclusion Criteria:
(1) Multiple lung lesions; (2) Poor quality of PET-CT images; (3) Participants with incomplete clinical information; (4) Participants who have received neoadjuvant therapy.
Not provided
Not provided
Resected Stage I-III Non-small Cell Lung Cancer
Not provided
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Affiliated Hospital of Zunyi Medical University | Recruiting | Zunyi | Guizhou | China |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| 2023.5.1-2023.10.31 |
| Positive predictive value | The positive predictive value of the deep learning model in predicting the presence or absence of the aggressive histological pattern. The aggressive histological pattern includes spread through air space (STAS), visceral pleural invasion (VPI), and lymphovascular invasion (LVI). And the model will output all predictive values (presence or absence) of the three kinds of aggressive histological patterns. | 2023.5.1-2023.10.31 |
| Negative predictive value | The negative predictive value of the deep learning model in predicting the presence or absence of the aggressive histological pattern. The aggressive histological pattern includes spread through air space (STAS), visceral pleural invasion (VPI), and lymphovascular invasion (LVI). And the model will output all predictive values (presence or absence) of the three kinds of aggressive histological patterns. | 2023.5.1-2023.10.31 |
| Accuracy | The accuracy of the deep learning model in predicting the presence or absence of the aggressive histological pattern. The aggressive histological pattern includes spread through air space (STAS), visceral pleural invasion (VPI), and lymphovascular invasion (LVI). And the model will output all predictive values (presence or absence) of the three kinds of aggressive histological patterns. | 2023.5.1-2023.10.31 |
| The First Affiliated Hospital of Nanchang University | Recruiting | Nanchang | Jiangxi | China |
|
| Ningbo HwaMei Hospital | Recruiting | Ningbo | Zhejiang | China |
|
| ID | Term |
|---|---|
| D002289 | Carcinoma, Non-Small-Cell Lung |
| ID | Term |
|---|---|
| D002283 | Carcinoma, Bronchogenic |
| D001984 | Bronchial Neoplasms |
| D008175 | Lung Neoplasms |
| D012142 | Respiratory Tract Neoplasms |
| D013899 | Thoracic Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
Not provided
Not provided