人工智能用于儿科肺结节检测的诊断性能,用于胸部计算机断层扫描
Rida Salman1, HaiThuy N Nguyen2, Andrew C Sher1
1Edward B. Singleton Department of Radiology, Division of Body Imaging, Texas Children's Hospital and Baylor College of Medicine, Houston, TX, USA.
Clinical imaging
|June 10, 2023
概括
一个用于检测肺结节的成人人工智能 (AI) 工具在儿科CT扫描中显示出低灵敏度. 通过更薄的切片和排除较小的结节,性能得到了改善.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 医疗成像医学成像
背景情况:
- 检测肺结节对于诊断肺部疾病至关重要.
- 人工智能 (AI) 工具越来越多地用于帮助放射科医生.
- 针对成人的人工智能工具在儿科患者群体中的有效性需要评估.
研究的目的:
- 评估商用成人肺结节检测AI工具的性能.
- 为了评估AI工具在儿科胸部CT扫描中的准确性.
主要方法:
- 三十个儿童胸部CT扫描 (12-18岁) 被追溯分析.
- 图像以1毫米和3毫米切片厚度重建.
- 应用了成人AI工具 (Syngo CT Lung CAD),结果与放射科医生的读数进行了比较.
主要成果:
- 人工智能工具检测到70个结节在1毫米切片厚度 (39%的灵敏度,62%的PPV) 和60个结节在3毫米 (26%的灵敏度,48%的PPV).
- 除了小于3毫米 (固体) 或5毫米 (亚固体) 的结节外,提高了对68% (1毫米) 和49% (3毫米) 的灵敏度,PPV变化最小.
- 人工智能工具总共识别了109个结节,其中103个是固体结节和6个是亚固体结节.
结论:
- 成年肺结节检测人工智能工具在儿科患者中表现出低灵敏度.
- 使用较薄的图像重建 (1毫米) 的性能更好.
- 排除较小的结节提高了AI在儿科胸部CT分析中的灵敏度.
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