Lung Cancer
Conditions
Keywords
subtype, artificial intelligence, diagnosis
Brief summary
PET/CT imaging and clinical information (age, gender, smoking history, family history of cancer, history of present illness, and several tumor biomarkers, etc.) were used to establish a hierarchical multi-modal AI framework for pathological and genetic subtyping of lung cancer
Detailed description
The multi-modal AI framework is developed to facilitate a hierarchical and precise stratification process. The first level involves the accurate differentiation between small cell lung cancer and non-small cell lung cancer (NSCLC) in patients diagnosed with lung cancer. The second level entails the further categorization of NSCLC patients into adenocarcinoma, squamous cell carcinoma, and other less prevalent subtypes. The third level involves predicting the mutation status of the EGFR driver gene, which is most-commonly observed in patients with lung adenocarcinoma. The whole cohort was divided into the training cohort (retrospective), validation cohort (retrospective), test cohort (retrospective), and prospective cohort.
Interventions
OTHERPET imaging analysis, data mining, and AI model developing
PET imaging analysis, data mining, and AI model developing
Sponsors
Second Affiliated Hospital, School of Medicine, Zhejiang University
First Hospital of China Medical University
West China Hospital
Zhongnan Hospital
Zhejiang Cancer Hospital
Guangdong Second Provincial General Hospital
The First Affiliated Hospital of Zhejiang Chinese Medical University
Wuhan TongJi Hospital
Northern Jiangsu People's Hospital
Study design
Observational model
COHORT
Time perspective
OTHER
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Newly diagnosed NSCLC confirmed pathologically * Age ≥18 y * Underwent pre-treatment 18F-FDG PET/CT scan * No prior anti-tumor treatments * No history of other malignancies
Exclusion criteria
▪ Pure ground-glass nodules with no FDG uptake
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Accurate differentiation between small cell lung cancer and non-small cell lung cancer | 1 year |
Secondary
| Measure | Time frame |
|---|---|
| Histological subtyping of NSCLC, including adenocarcinoma, squamous cell carcinoma, and other NSCLC subtypes | 1 year |
Countries
China
Contacts
CONTACTHong Zhang
CONTACTXiaohui Zhang
PRINCIPAL_INVESTIGATORHong Zhang
Department of Nuclear Medicine and PET/CT Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University
Outcome results
None listed