The purpose of this project is to investigate if PET/MR imaging improves the accuracy in visualization and characterization of lung cancer disease, compared to PET/CT.
Lung cancer is the most frequent cancer type and the leading cause of cancer-related death worldwide. Positron emission tomography (PET) coupled with computed tomography (CT) is the standard of care for visualization and staging of lung cancer. Recent clinical introduction of hybrid PET and magnetic resonance (MR) imaging systems has shown potential to improve tumor imaging beyond the limits of PET/CT. However, knowledge about the clinical impact of this new hybrid modality is still limited. This project aims to investigate how PET/MR may improve the diagnosis and treatment of lung cancer disease, compared to PET/CT: PET/MR may allow early detection of brain and liver metastases, which strongly affects treatment outcome and survival; predictive models based on machine learning may combine image derived biomarkers from PET/MR, histology and health record data, to automatically visualize and characterize the tumor, facilitating computer aided diagnosis and personalized radiotherapy treatment.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
35
University Hospital of North Norway
Tromsø, Norway
Sensitivity and specificity of PET/MR vs. clinical routine PET/CT
Sensitivity and specificity of PET/MR scans will be compared with in clinical routine PET/CT examinations for lung cancer disease feature prediction.
Time frame: 1-2 weeks after the initial inclusion.
Prediction of treatment response and progression-free survival
We will investigate which PET/MR or PET/CT features are best suited as an imaging biomarker for treatment response evaluation and for progression-free survival 1 year after inclusion.
Time frame: 1 year after inclusion.
Prediction of treatment response and progression-free survival
We will investigate which PET/MR or PET/CT features are best suited as an imaging biomarker for treatment response evaluation and for progression-free survival 2 years after inclusion.
Time frame: 2 years after inclusion.
Prediction of treatment response and progression-free survival
We will investigate which PET/MR or PET/CT features are best suited as an imaging biomarker for treatment response evaluation and for progression-free survival 5 years after inclusion.
Time frame: 5 years after inclusion.
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.