Generative learning approach for radiation dose reduction in X-ray guided cardiac interventions.
Generative learning approach for radiation dose reduction in X-ray guided cardiac interventions.
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DOI：
10.1002/mp.15654
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发表时间：
2022-06
期刊：
影响因子：
3.8
通讯作者：
Duong, Luc
中科院分区：
文献类型：
--
作者：
Azizmohammadi, Fariba;Castellanos, Inaki Navarro;Miro, Joaquim;Segars, Paul;Samei, Ehsan;Duong, Luc
心脏介入治疗中的导航指导是通过X射线血管造影术提供的。累积辐射暴露是儿科心脏干预的一个严重问题。提出了一种基于产生式学习的方法来预测X射线血管造影帧，以减少儿科心脏介入治疗中的辐射暴露，同时保持图像质量。帧预测基于使用长短期记忆体系结构的无模型运动估计方法和使用卷积神经网络结构的内容预测器。因此，提出的模型估计了对比剂增强的血管结构，如冠状动脉及其在端到端系统中的X射线序列中的运动。这项工作通过56个模拟序列和52个患者的X射线血管成像序列进行了验证。使用预测图像可以在不影响图像质量的情况下最多减少三个新帧的脉冲数。对于15 fps的采集，平均每秒所需的采集量可能会下降30%。模拟数据集的平均结构相似指数为97%，患者数据集的平均结构相似指数为82%。使用基于学习的方法的帧预测在最小化辐射剂量暴露方面是有希望的。在保持帧速率和图像质量的同时，降低了所需的脉率。在X射线血管成像系统中进行适当的集成，这种方法可以为改进剂量管理铺平道路。
Navigation guidance in cardiac interventions is provided by X-ray angiography. Cumulative radiation exposure is a serious concern for pediatric cardiac interventions. A generative learning-based approach is proposed to predict X-ray angiography frames to reduce the radiation exposure for pediatric cardiac interventions while preserving the image quality. Frame predictions are based on a model-free motion estimation approach using a long short-term memory architecture and a content predictor using a convolutional neural network structure. The presented model thus estimates contrast-enhanced vascular structures such as the coronary arteries and their motion in X-ray sequences in an end-to-end system. This work was validated with 56 simulated and 52 patients’ X-ray angiography sequences. Using the predicted images can reduce the number of pulses by up to three new frames without affecting the image quality. The average required acquisition can drop by 30% per second for a 15 fps acquisition. The average structural similarity index measurement was 97% for the simulated dataset and 82% for the patients’ dataset. Frame prediction using a learning-based method is promising for minimizing radiation dose exposure. The required pulse rate is reduced while preserving the frame rate and the image quality. With proper integration in X-ray angiography systems, this method can pave the way for improved dose management.
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