ArticleEmergency radiology2026
Artificial intelligence and the phantom pneumothorax: Clinical reasoning still matters.
Article in Emergency radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Artificial intelligence (AI) has become increasingly integrated into chest radiograph interpretation, demonstrating excellent diagnostic performance for several thoracic abnormalities, including pneumothorax. Nevertheless, current AI systems remain predominantly image-based and do not inherently incorporate procedural or clinical information into diagnostic interpretation. We report the case of an 81-year-old man who underwent uncomplicated left-sided dual-chamber permanent pacemaker implantation. Routine post-procedural chest radiography, analyzed by an AI-assisted interpretation system, generated a positive alert for a right apical pneumothorax, highlighting the suspected abnormality with automated visual annotation. The alert was immediately considered clinically discordant by the treating team, given the left-sided venous access, normal oxygen saturation, hemodynamic stability, and absence of respiratory symptoms. Because of this clinicoradiological discordance, chest computed tomography was performed and definitively excluded pneumothorax, confirming a false-positive AI interpretation. The patient required no additional intervention and experienced an uneventful recovery. This case highlights the importance of integrating AI-generated findings with procedural details, bedside clinical assessment, and, when clinically indicated, confirmatory imaging in the presence of clinicoradiological discordance. Although AI can accurately identify many radiographic abnormalities, accurate diagnosis ultimately depends on integrating imaging findings with procedural information, clinical presentation, and pre-test probability. This case also emphasizes that AI should be regarded as a clinical decision-support tool rather than an autonomous diagnostic system and highlights the continuing importance of physician oversight in ensuring patient safety during AI-assisted post-procedural imaging interpretation.
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