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Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

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Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
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基于人工智能的软件用于检测乳腺动脉化在乳房图片上的化.

Alyssa T Watanabe1,2, Valerie Dib3, Junhao Wang2

  • 1Department of Radiology, University of Southern California Keck School of Medicine, Los Angeles, CA, USA.

Journal of breast imaging
|October 29, 2024
PubMed
概括

这项研究表明,人工智能 (AI) 软件可以准确地检测乳腺动脉化 (BAC) 在乳房影像上. 人工智能工具在识别BAC方面表现强,帮助放射科医生对女性进行心血管风险评估.

关键词:
人工智能的人工智能是人工智能.乳腺动脉化 乳腺动脉化计算机辅助检测 计算机辅助检测深度学习是一种深度学习.乳房学 乳房学 乳房学

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科学领域:

  • 放射学 放射学是一门学科.
  • 医疗成像医学成像
  • 医疗保健中的人工智能

背景情况:

  • 乳腺动脉结 (BAC) 是女性心血管风险的重要标志物.
  • 精确检测乳房图片上的BAC对风险分层至关重要.
  • 现有的BAC检测方法可能会从技术进步中受益.

研究的目的:

  • 评估基于人工智能 (AI) 的商业软件用于检测乳房图片上的BAC的性能.
  • 为了比较人工智能性能与放射学家的共识,无论是数字乳腺造影 (DM) 还是数字乳腺断层合成 (DBT).

主要方法:

  • 对来自253名和143名患者的314名DM和277名DBT检查的回顾性分析.
  • 基于AI的BAC检测被评估并与专家放射学家建立的地面真相 (GT) 相比较.
  • 计算了包括AUC,灵敏度,特异性,PPV,NPV和精度在内的关键性能指标.

主要成果:

  • 人工智能实现了高病例水平的AUC,DM为0.96和DBT为0.95.
  • 灵敏度,特异性和准确性在DM的87-92%,在DBT的88-90%之间.
  • 积极的预测值和NPV始终很高,表明可靠的AI性能用于BAC检测.

结论:

  • 人工智能软件在检测DM和DBT图像上的BAC方面表现出了有希望的表现.
  • 人工智能有可能帮助放射科医生识别和报告BACs,这是一个关键的心血管风险因素.
  • 这项技术可以提高乳房扫描对女性心血管风险评估的临床实用性.