Application of computer‐aided detection for NCCN‐based follow‐up recommendation in subsolid nodules: Effect on inter‐observer agreement
Rationale and Objectives Computer‐aided detection (CAD) of pulmonary nodules reduces the impact of observer variability, improving the reliability and reproducibility of nodule assessments in clinical practice. Therefore, this study aimed to assess the impact of CAD on inter‐observer agreement in th...
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Veröffentlicht in: | Cancer medicine (Malden, MA) MA), 2024-01, Vol.13 (2), p.e6967-n/a |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Rationale and Objectives
Computer‐aided detection (CAD) of pulmonary nodules reduces the impact of observer variability, improving the reliability and reproducibility of nodule assessments in clinical practice. Therefore, this study aimed to assess the impact of CAD on inter‐observer agreement in the follow‐up management of subsolid nodules.
Materials and Methods
A dataset comprising 60 subsolid nodule cases was constructed based on the National Cancer Center lung cancer screening data. Five observers independently assessed all low‐dose computed tomography scans and assigned follow‐up management strategies to each case according to the National Comprehensive Cancer Network (NCCN) guidelines, using both manual measurements and CAD assistance. The linearly weighted Cohen’s kappa test was used to measure agreement between paired observers. Agreement among multiple observers was evaluated using the Fleiss kappa statistic.
Results
The agreement of the five observers for NCCN follow‐up management categorization was moderate when measured manually, with a Fleiss kappa score of 0.437. Utilizing CAD led to a notable enhancement in agreement, achieving a substantial consensus with a Fleiss kappa value of 0.623. After using CAD, the proportion of major and substantial management discrepancies decreased from 27.5% to 15.8% and 4.8% to 1.5%, respectively (p |
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ISSN: | 2045-7634 2045-7634 |
DOI: | 10.1002/cam4.6967 |