IDEAL: Artificial Intelligence and Big Data for Early Lung Cancer Diagnosis Study
IDEAL: Artificial Intelligence and Big Data for Early Lung Cancer Diagnosis Study
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. The investigators hope that the 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.
As the commonest cancer with 1.8 million cases diagnosed each year worldwide, early diagnosis
 of lung cancer is important to reduce mortality. The early diagnosis of lung cancer is
 contingent on both the detection of a small lung nodule and determining whether it is
 malignant. Whilst computed tomography (CT) has proven to be a robust way of detecting lung
 nodules, they are often discovered on routine scanning as an incidental finding or as part of
 a lung cancer screening program. Hence, determining whether they are benign or malignant is
 challenging.

 Up to 75% of smokers scanned either as part of their clinical care or in lung cancer
 screening trials have subcentimetre pulmonary nodules detected. This places a substantial
 burden on scanning facilities, staff and patients. Current methods of determining if lung
 nodules are benign or malignant are not standardised and unproven. The US National Lung
 Screening Trial (NLST) showed that up to 95% of lung nodules detected on CT scans of the
 chest were false positives i.e. they were not malignant. Detection of non-malignant nodules
 have the unwanted consequences of unnecessary cost as they require follow-up scanning or
 alternative methods of investigation, cause patient anxiety, may result in increased
 morbidity potentially by biopsy or resection, and result in increased patient radiation
 exposure due to follow-up CT scans or from PET-CT scans.

 As part of standard care at present, patients with lung nodules greater than 4mm and
 sub-centimetre are followed up with CT scan(s), up to 5 scans, for up to 24 months, according
 to the internationally accepted Fleischner guidelines. Additional investigations, such as a
 positron-emission tomography (PET-CT) scan and biopsy or resection may also be performed
 based on the size and clinical risk profile of the patient.

 Recent studies have shown that incorporating lung nodule characteristics such as size,
 texture, growth rate, contrast enhancement can improve the accuracy of predicting the risk of
 malignancy. This allows the stratification of lung nodules into different investigations
 and/or follow-up pathways based on the predicted risk of malignancy.

 This study aims to test the use of novel CT image analysis techniques incorporated into a
 clinical risk model to characterise small pulmonary nodules. The study will incorporate solid
 and predominantly solid nodules of 5-15mm scanned using a variety of scanner types, imaging
 protocols and patient populations.

 CT scans from patients referred to the Lung Nodule Clinic or for review by a specialist in
 nodule assessment as per current clinical practice will be reviewed. Patients who meet the
 inclusion/exclusion criteria will be contacted by a member of the clinical care team and
 study participation will be discussed.

 Of the nodules detected, their management will be categorised as per standard care into the
 following groups:

 GROUP 1. On review of the scans by an expert, no further follow up or investigation is
 required, as the nodule(s) has been categorised as benign. As the patient was unaware the
 scan was being reviewed and no further investigations are required. Patient is invited to
 take part in the study (by telephone).

 GROUP 2. On review, the nodule is indeterminate and further scanning at a later date is
 required. The patient is informed of this, usually via a telephone call from either the
 doctor or nurse specialist working in the Lung Nodule Clinic (LNC) or site equivalent. This
 LNC is usually a virtual clinic - no physical interaction with the patient - and the follow
 up scan is reviewed and the patient contacted again via the virtual clinic. Patient is
 invited to take part in the study (by telephone, by post or in clinic if appropriate).

 GROUP 3. On review, the nodule is regarded as potentially malignant and further scans and a
 clinic appointment is made for the patient. Patient is invited to take part in the study (in
 clinic if appropriate).

 Apart from CT images routine care clinical information about the patient (e.g. age, sex,
 smoking status, family history of lung cancer) and data on nodule characteristics derived
 from the identified CT scan (and/or prior and subsequent) will be collected and used to test
 the new software program that will stratify pulmonary nodules in terms of their probability
 of being malignant or benign. All this data is routine and is collected as part of standard
 care therefore no study visits will need to be arranged.

 As part of the health economics assessment patients will be invited to complete the EQ-5D-5L
 (quality of life), GAD-7 (anxiety), and productivity loss questionnaires. Patients will also
 be asked questions about their health utilisation. This data may also be collected from
 medical notes/electronic patient records.

 The initial questionnaires will be completed within 2 weeks (if possible) of having the first
 scan and a follow-up will be carried out after 1 year for group 1 participants. Group 2 and 3
 participants will also be invited to complete these questionnaires 3 months after their
 initial scan as they will have undergone further investigations during that time. The
 questionnaires will be completed over the phone for patients in groups 1 and over the phone
 or face to face when attending routine clinic appointments for groups 2 and 3.
Inclusion Criteria:

 -  Male or Female, aged 18 years or above

 -  CT scans identified as having pulmonary nodule(s) of 5-15mm

 -  Patients with solid or predominantly solid nodules referred to the pulmonary nodule
 clinic or for CT scan review by a specialist

 -  CT scan section thickness of 3mm and less

 Exclusion Criteria:

 -  The CT scans are technically inadequate

 -  Having received treatment for cancer in the last 5 years

 -  Patient has more than five reported qualifying nodules