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

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

712 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-04-20

Study Completion Date

2026-12-06

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.

Conditions

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Lung Malignancy

Keywords

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Artificial Intelligence Lung malignancy nodule score Pulmonary Nodule qXR-LNMS Lung Cancer Lung RADS CT scan

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Computed tomography Cohort

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.

Participant Cohort

Intervention Type OTHER

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.

Interventions

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Participant Cohort

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.

Intervention Type OTHER

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.

Minimum Eligible Age

35 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Responsible Party

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Responsibility Role SPONSOR

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D133FR00178

Identifier Type: -

Identifier Source: org_study_id

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

Study Results

Basic Information

Brief Summary

Detailed Description

Conditions

Keywords

Study Design

Study Groups

Computed tomography Cohort

Participant Cohort

Interventions

Participant Cohort

Eligibility Criteria

Inclusion Criteria

Exclusion Criteria

Sponsors

AstraZeneca

Responsible Party

Locations

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Other Identifiers

D133FR00178