Implementation of an Artificial Intelligence-Based Double Read System in Capturing Pulmonary Nodule Discrepancy in CT Studies
| Autor: | Lai Peng Chan, Elizabeth Hui Ting Cheong, Wei Ping Tham, Jin Rong Tan |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Lung Neoplasms Lung metastasis Early detection 030218 nuclear medicine & medical imaging 03 medical and health sciences Patient safety 0302 clinical medicine Artificial Intelligence Pulmonary nodule medicine Humans Radiology Nuclear Medicine and imaging Personal health In patient Lung cancer business.industry Solitary Pulmonary Nodule medicine.disease 030220 oncology & carcinogenesis Ct technique Multiple Pulmonary Nodules Radiology business Tomography X-Ray Computed Algorithms |
| Zdroj: | Current problems in diagnostic radiology. 50(2) |
| ISSN: | 1535-6302 |
| Popis: | Studies show that up to 80% of all radiology errors are due to errors in perception. Early detection is critical for good outcomes in patients with primary lung cancer and lung metastasis. However, pulmonary nodules can be easily missed due to their small size. We prospectively applied a machine vision algorithm to CT studies containing lung parenchyma to detect pulmonary nodules, as well as a natural language processing algorithm to the text of the report to identify documentation of pulmonary nodules. Apparent discrepancies in perception – instances where a pulmonary nodule was not reported – were flagged for a secondary review by a radiologist. Four thousand and nine hundred studies were prospectively processed, of which 450 cases with potential discrepancies were detected. Preliminary manual analysis was performed to analyze the base error rate and to optimize thresholds for the machine vision and natural language processing algorithms, and 104 cases were flagged for final review. Of these 104 cases, 50 cases contained undocumented pulmonary nodules. Among these cases, 7 cases were classified as likely to be significant, where report addendums were done and the clinicians notified. We have successfully implemented an automated double read system to detect pulmonary nodule discrepancies, with minimal disruption to the radiology workflow and while keeping personal health information on-premises. This successful implementation demonstrates the viability of using an automated and secure radiology double-read system to improve patient safety in radiology workflows, either at a health system or an independent radiology practice. |
| Databáze: | OpenAIRE |
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