Validating Artificial Intelligence Effectiveness Defined Lung Nodule Malignancy Score in Patients With Pulmonary Nodule.

Study Overview
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Brief Summary
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Artificial intelligence (AI) based algorithms have demonstrated increased accuracy in predicting the risk of Lung Cancer among patients with an incidental pulmonary nodule (IPN) on chest radiographs. Qure.ai, an AI company specializing in the reading of chest X- Rays (CXRs) by a proprietary algorithm and has developed a new model, qXR, that can report the lung nodule malignancy score (LNMS) based on lung nodule features. Our study aims to prospectively validate the lung nodule malignancy score against radiologist assessment of CT scans and Lung CT Screening Reporting and Data System score (Lung-RADS).(lung RADS score explained below) Thus, lung nodule malignancy score (interpreted by qXR as a high or low category) will be compared with radiologist-based assessment probability of CT scan and Lung-RADS assessment. The results of this prospective observational study will pave the way for improved nodule management, leading to better clinical outcomes in patients with incidental pulmonary nodule (IPNs), especially concerning malignancy assessment.

Detailed Description
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A multicentric, multinational, prospective, observational study to validate qXR-Lung nodule malignancy score as a binary categorization of the risk of Lung cancer as high or low among patients with an incidental pulmonary nodule (IPN) on chest radiographs. The study will be implemented across selected countries in the AstraZeneca International Region (e.g., Philippines, Malaysia, Saudi Arabia, United Arab Emirates, Kuwait, Thailand, Taiwan, Hong Kong, India, Brazil, Argentina, Colombia). Patients coming to the facility for x-rays for any reason will undergo x-rays as ordered by their treating clinician. Adult patients diagnosed with incidental pulmonary nodule( IPN) on Chest X-ray (CXR) with nodule size ≥8 and ≤30 mm, will be invited to participate in the study and enrolled after obtaining their written informed consent. In case of any nodule detection by qXR, it will be classified either as low-risk Lung nodule malignancy score (LNMS) or high-risk LNMS. The X-ray reporting physician will decide the qXR report for the presence of a nodule. CT scan will be performed after obtaining consent for the low-dose CT scan from patients.The clinical site's radiologist and an independent radiologist not associated with the clinical site will report the CT scan and the qXR-LNMS category. Radiologists' interpretation will be based on examining a nodule on a CT scan film (naked eye examination). Radiologists will first rate their CT scan interpretation of the nodule on the Likert scale as: non-malignant: 1; probable non-malignant: 2; uncertain: 3; probable malignant: 4; malignant: 5. In addition, the radiologists will assign a Lung-RADS and then give an overall assessment of the risk of malignancy as high or low. . This study is minimal to no risk to the patient. The study duration for a participant will be approximately 30 months from the enrolment. The study will have 2 phases. Phase 1 will be from enrolment until CT data collection. The CT data collection day will end Phase 1 (End of Phase-1). Phase 2 will be from CT data collection until 24 months from CT which is the end of Phase 2. The study visits in this period will be per clinical follow-up and will not be mandatory.

Official Title
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Prospective Realworld Cohort Study to Validate Effectiveness of an Artificial Intelligence Defined Lung Nodule Malignancy Score in Patients With Pulmonary Nodule Multicentric, Multinational, Prospective, Observational Study.

Conditions
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Lung Malignancy

Intervention / Treatment
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* Other: Participant Cohort


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Male or female patients aged >35 years Patients diagnosed with incidental pulmonary nodule (IPN) on CXR (chest x-ray) by qXR and confirmed by the radiologist at the site with nodule size ≥8 and ≤30 mm. Exclusion Criteria: Any medical or other contraindications for a CT scan Nondigital (chest x-ray)CXR CT scan is done more than 6 months after (chest x-ray) CXR Patients with already diagnosed lung cancer The patients referred for an X-Ray for a suspicious Lung cancer A patient who already participated in the study.

Ages Eligible for Study
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Minimum Age: 35 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Computed tomography Cohort<br>In case of any nodule detection by qXR, it will be classified either as low-risk LNMS(lung nodule malignancy score ) or high-risk LNMS confirmed by radiologist. The patient will be requested to get a CT scan after enrolment in the study. | Other: Participant Cohort<br>* Patients coming to the facility for chest x-rays for any reason, will undergo x-rays as ordered by their treating clinician. In case of any nodule detection by qXR, it will be classified either as low-risk (Lung nodule malignancy score ) LNMS or high-risk LNMS confirmed by radiologist. Then if patient is eligible will be included in the study and a CT Scan will be requested upon enrolment of the patient.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| To estimate the positive and negative predictive values of qXR LNMS (lung nodule malignancy score ) in a multi-centre real-world setting. | PPV( positive predictive value) of qXR-LNMS using a panel of radiologists assigning high-risk based on CT (done within 180 days from Xray) as the reference standard The PPV here is the number of nodules rated as high risk as assessed by a reference standard (a panel of radiologists) on CT divided by the total number of high-risk nodules as reported by qXR-LNMS (lung nodule malignancy score ) (n = 500) NPV( negative predictive value) of qXR-LNMS using panel of radiologists assigning low-risk based on CT (done within 180days from X-ray) as reference standard. The NPV here is number of nodules rated as low risk as assessed by a reference standard (a panel of radiologists) on CT divided by total number of low-risk nodules as reported by qXR-LNMS (lung nodule malignancy score ) (n = 200) | 6 months from the Last subject In. | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Demographic and clinical factors associated with high or low predictive values association of qXR LNMS with the Mayo score model. | PPV (positive predictive value) of qXR-LNMS (lung nodule malignancy score) using panel of radiologists assigning Lung-RADS (lung RADS score explained in description )>4A based on CT as reference standard. The PPV here is number of nodules rated as Lung-RADS>4A as assessed by a reference standard (a panel of radiologists) on CT divided by total number of high-risk nodules as reported by qXR-LNMS (n = 500) NPV ( negative predictive value) of qXR-LNMS using a panel of radiologists assigning Lung-RADS<4A based on CT as the reference standard The NPV here is the number of nodules rated as Lung-RADS<4A as assessed by a reference standard (a panel of radiologists) on CT divided by the total number of low-risk nodules as reported by qXR-LNMS (n = 200) | 2 and half years from Last subject In. | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Artificial Intelligence, Lung malignancy nodule score, Pulmonary Nodule, qXR-LNMS, Lung Cancer, Lung RADS, CT scan