Background: Artificial intelligence (AI)-powered platforms may be used to ensure that clinically significant lung nodules receive appropriate management. We studied the impact of a commercially available AI natural language processing tool on detection of clinically significant indeterminate pulmonary nodules (IPNs) based on radiology reports and provision of guideline-consistent care.
Study design: All computed tomography (CT) scans performed at a single tertiary care center in the outpatient or emergency room setting between 20-Feb-2024 and 20-March-2024 were processed by the AI natural language processing algorithm. CT radiology reports mentioning a lung nodule or focal indeterminate lesion were flagged. All flagged reports were reviewed by a lung nodule expert two weeks after nodule identification. IPNs were classified as "appropriately followed" if follow-up imaging, referral to a nodule clinic, or other guideline-consistent care was ordered. IPNs were classified as "not appropriately followed" if no acknowledgement of the reported nodule was documented in the electronic health record within two weeks of being flagged.
Results: The AI software processed 76,507 unique radiology reports, identified 2,585 CT scans with chest imaging, and found 389 IPNs. Review determined that 272 (70%) nodules were appropriately followed while 117 (30%) were not appropriately followed. Of the 117 nodules without documented follow-up, 67 (57%) were > 8mm and 24 (20.5%) were > 15mm. IPNs that would not have received follow-up in the absence of the AI software generated 43 additional clinical appointments and 3 procedures.
Conclusion: At a large tertiary care center, 30% of clinically significant incidental pulmonary nodules that would have otherwise been missed were brought to the attention of lung nodule clinicians by an AI software, allowing for initiation of appropriate follow-up.
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