validating artificial intelligence effectiveness defined lung nodule malignancy score in patients with pulmonary nodule.

Conditions: Lung Malignancy

Summary: 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.

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.

Eligibility criteria:
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.

Keywords: artificial intelligence lung malignancy nodule score pulmonary nodule qxr-lnms lung cancer lung rads ct scan