人工智能算法的准确性用于检测腹部和胸部计算机断层扫描中的中度至严重的脊椎压缩骨折
Renata Fernandes Batista Pereira1, Paulo Victor Partezani Helito1,2,3, Renata Vidal Leão1,2
1Hospital Sírio-Libanês, São Paulo, SP, Brazil.
Radiologia brasileira
|July 12, 2024
概括
一个人工智能软件HealthVCF在CT扫描上准确检测中度至严重的脊椎压缩骨折 (VCF). 它具有很高的特异性,可以帮助放射科医生在机会性VCF检测中.
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:
- 脊椎压缩骨折 (VCF) 很常见,特别是在老年人中.
- 胸部和腹部CT扫描中的偶然VCF经常被遗漏.
- 早期发现风险投资基金对于及时干预和管理至关重要.
研究的目的:
- 为了评估HealthVCF的诊断准确度,一个AI软件,用于检测中度至重度的VCF.
- 评估软件在胸部和腹部CT扫描中发现的偶然VCF的性能.
- 将人工智能软件的检测能力与人类放射科医生的检测能力进行比较.
主要方法:
- 追溯分析了899个来自51至99岁患者的胸部和腹部CT扫描.
- 使用HealthVCF人工智能软件和两个肌肉骨成像专家对扫描的评估.
- 将AI软件的VCF检测与专家共识作为参考标准进行比较.
主要成果:
- 卫生VCF在中度至重度VCF的诊断准确率为89.6%.
- 该软件实现了73.8%的灵敏度和92.7%的高特异性.
- 人工智能在42.8%的阳性病例中发现了一般放射科医生错过的额外骨折.
结论:
- 卫生VCF在检测中度至严重的VCF方面表现出良好的准确性和高特异性.
- 人工智能软件可以增强对VCF的机会性检测.
- 健康VCF显示了提高非专业放射科医生中VCF检测率的潜力.
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