AI Detection Efficiency of Pulmonary Nodules Under Dual-source CT with Different Tube Voltages
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摘要: 目的：探讨人工智能辅助诊断系统在双源CT不同管电压下对肺结节的检测效能。方法：回顾性的搜集行双源CT的门诊患者200例，经排除最终筛选得到198例符合标准的图像，将图像进行后处理，得到100kVp，融合120kVp和140kVp下的胸部CT图像；根据结节大小、密度及位置分组，比较在不同管电压下人工智能检测肺结节的假阳性与假阴性个数。结果：AI在双源CT 100kVp下对于磨玻璃结节具有较好的分辨能力；在双源CT融合120kVp图像中，对肺结节的误诊率最高，但具有较低的漏诊率；然而，在双源CT 140kVp下对肺结节自动检出效能最差。结论：人工智能在融合120kVp下对肺结节的检测的假阴性率较低，可以降低医师诊断肺结节的漏诊率。Abstract: Objective: To explore the detection of misdiagnosis and missed pulmonary nodules by artificial intelligence assisted diagnosis system under dual-source CT with different tube voltages. Methods: a retrospective collection of 200 outpatient patients who underwent dual-source CT was conducted. Images were screened and 198 qualified images were finally obtained. The images were post-processed to obtain chest CT images under 100kVp, 120kVp and 140kVp. The number of false positives and false negatives of pulmonary nodules detected by artificial intelligence under different tube voltages were compared according to the size, density and location of the nodules. Results: AI had better resolution ability for ground glass nodule under dual-source CT 100kVp. In the dual-source CT fusion image of 120kVp, the misdiagnosis rate of pulmonary nodules was the highest, but the rate of missed diagnosis was lower. However, the automatic detection of pulmonary nodules was the least effective under dual-source CT 140kVp. Conclusion: The false negative rate of artificial intelligence detection of pulmonary nodules under 120kVp fusion is low, which can reduce the rate of missed diagnosis of pulmonary nodules by physicians.
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Keywords:
- AI /
- dual source CT /
- pulmonary nodules
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