基于深度学习的伪CT合成从骨的零回声时间MR序列
Jonas M Getzmann1,2,3, Eva Deininger-Czermak4,5,6, Savvas Melissanidis4,5
1Institute of Diagnostic and Interventional Radiology, University Hospital Zurich (USZ), Zurich, Switzerland. jonas.getzmann@gmail.com.
Insights into imaging
|August 9, 2024
概括
从MRI零回声时间 (ZTE) 序列生成的伪CT (pCT) 图像与传统CT扫描显示出很好的一致性,提供准确的骨描绘和在不暴露于辐射的情况下的几何测量.
科学领域:
- 医疗成像医学成像
- 放射学 放射学是一门学科.
- 人工智能在医学中的应用
背景情况:
- 传统的CT扫描涉及辐射暴露,造成重复成像的风险.
- 核磁共振提供了优秀的软组织对比度,但缺乏CT的骨细节.
- 开发无辐射成像替代方案对于患者安全和频繁监测至关重要.
研究的目的:
- 为了从盆腔ZTE MRI序列中合成伪CT (pCT) 图像.
- 与传统CT相比,评估合成的pCT图像的准确性和质量.
- 探索pCT在减少盆腔成像中的辐射暴露方面的潜力.
主要方法:
- 预期CT和ZTEMRI扫描91名患者.
- 11个数据集因植入物或B1不均性而被排除.
- 在60个数据集上训练深度学习 (DL) 模型,用于从ZTE序列中进行pCT合成.
- 在20个个案例的单独队列上验证DL模型.
- 通过两个独立的读者对CT和pCT图像进行定性和定量评估.
主要成果:
- pCT图像表现出良好的到完美的质量评级.
- 在CT和pCT之间达成高间联运协议 (ICC=0.88).
- 对于pCT (ICC=0.91) 的优秀的读者间协议.
- 在大多数几何测量中没有显著差异,除了横横的骨盆直径和侧面中边角外.
- 在CT和pCT之间,图像质量和组织差异可比,对比度与噪声比率 (CNRs) 类似.
结论:
- 从ZTE MRI中基于DL的pCT合成对于盆腔成像是可行的和准确的.
- pCT图像提供了高骨质描绘质量和可靠的几何测量.
- pCT为评估骨提供了CT的无辐射替代方案,在退行性疾病和手术规划中具有广泛的应用.
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