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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.
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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.
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35 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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