Lung Nodule Imaging Biobank for Radiomics and AI Research

Lung Nodule Imaging Biobank for Radiomics and AI Research

This study will collect retrospective CT scan images and clinical data from participants with incidental lung nodules seen in hospitals across London. The investigators will research whether machine learning can be used to predict which participants will develop lung cancer, to improve early diagnosis.

Inclusion Criteria:

• Age > 18
• Baseline CT thorax imaging reported as having pulmonary nodule(s) between 5 and 30mm in the last 10 years.
• Ground truth known (either scan data showing stability for 2 years (based on diameter) or one year (based on volumetry), complete resolution, or biopsy-proven malignancy.
• Slice thickness < 2.5mm.

Exclusion Criteria:

• • Absence of at least one technically adequate CT thorax imaging series (defined by visual inspection of presence of imaging data of the thorax in the DICOM record).

  • Slice thickness > 2.5mm.
  • Imaging > 10 years old.
  • Ground truth unknown.