Title: Software with artificial intelligence derived algorithms for automated detection and analysis of lung nodules from CT scan images [DAP60]
Funder: Department of Health and Social Care

Abstract: Lung cancer is one of the most common types of cancer in the UK. People in the early stages of the disease may not have symptoms and so lung cancer is often diagnosed late. Lung nodules are small abnormal areas of tissue in the lung. Many of the nodules are harmless but some of them could present early stages of lung cancer. _x000D_ _x000D_ Detecting lung nodules, examining their features, and monitoring their change in size and appearance over time on a CT (computed tomography) scan that includes the chest can help doctors identify cancer at an earlier stage and deal with it more quickly. However, detecting and monitoring lung nodules that do not develop into cancer can worry people unnecessarily. Detecting and measuring nodules in CT images can be difficult for several reasons, including the small size of the nodules, different shapes, their location, and how close they are to other lung structures. At present, most radiologists (doctors who specialise in medical imaging) or other healthcare professionals detect lung nodules on CT scan images without assistance from any computer software but may use software to measure the size of a nodule after they have spotted it._x000D_ _x000D_ Computer software capable of detecting and analysing lung nodules automatically could be used to assist the healthcare professional when reviewing CT scan images that include the chest. Such software could detect lung nodules that might have been overlooked and may measure the nodules more consistently and quickly. The software could also assess whether and how fast a previously identified nodule is growing. This might help doctors to decide whether additional investigation or follow-up imaging is needed or whether no further action is required. The software may also help the healthcare professional to recognise and record specific features of lung nodules that are important for decisions about what to do next and may enable them to complete these tasks more quickly. However, the software may detect more nodules that do not develop into cancer and lead to unnecessary investigations. Findings reported by the software are always checked by a healthcare professional before they are included in the reports but depending on their experience and speciality, their confidence to overrule the software might differ. _x000D_ _x000D_ This review will look at the evidence on how well software performs in the automated detection and analysis of lung nodules, how good it is at helping radiologists or other healthcare professionals to find, measure, and assess growth of lung nodules. It will also investigate benefits and harms of using such software and whether it offers value for money. This report will cover people who had a CT scan that includes the chest for various reasons, including those who had a CT scan due to symptoms suggestive of lung cancer; for investigating other conditions unrelated to lung cancer; or to monitor previously identified lung nodules. Depending on the upcoming recommendations to be made by the UK National Screening Committee (UK NSC), this report may additionally cover people who had a chest CT scan as part of a lung cancer screening programme.

Lay abstract: The External Assessment Group (EAG) will assess if the use of software for automated detection and analysis of lung nodules from CT scan images by radiologists and other health professionals represent a clinically and cost-effective use of National Health Service (NHS) resources.

Research activity codes: 4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS;RESPIRATORY