IDEAL - prospective

• Research type

  Research Study

• Full title

  IDEAL: Artificial Intelligence and Big Data for Early Lung Cancer Diagnosis Prospective Study (Phase 2)

• IRAS ID

  241486

• Contact name

  Fergus Gleeson

• Contact email

  fergus.gleeson@ouh.nhs.uk

• Sponsor organisation

  University of Oxford (Clinical Trials and Research Governance)

• Duration of Study in the UK

  2 years, 3 months, 1 days

• Research summary

  This study aims to test the use of novel CT image analysis techniques to enable a better characterisation of small pulmonary nodules. The study will incorporate solid and predominantly solid nodules of 5-15 mm scanned using a variety of scanner types, imaging protocols and patient populations. We hope that our new image processing techniques will improve the accuracy of lung nodule analysis which will in turn reduce the number of unnecessary investigations for benign nodules and may increase the accuracy of the early diagnosis of lung cancer in malignant nodules. This study aims to test this novel analysis software to subsequently allow validation.

• REC name

  South Central - Oxford C Research Ethics Committee

• REC reference

  18/SC/0321

• Date of REC Opinion

  6 Aug 2018

• REC opinion

  Further Information Favourable Opinion