基于深度学习的T1加权单剂量图像的信号放大改善了脑MRI中转移的检测
Robert Haase1, Thomas Pinetz, Erich Kobler
1From the Department of Diagnostic and Interventional Neuroradiology, University Hospital Bonn, Bonn, Germany (R.H., E.K., Z.B., S.Z., A.-H.S., F.C.S., S.P., A.M.S., D.P., A.R., K.D.); Institute of Applied Mathematics, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany (T.P., A.E.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (D.P.); Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany (D.P., H.-P.S.); Department of Diagnostic and Interventional Radiology With Nuclear Medicine, Thoraxklinik at University Hospital Heidelberg, Heidelberg, Germany (M.F.-D., K.S., G.H., C.P.H.); Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany (M.F.-D.); Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany (V.W., C.P.H.); Institute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (M.H., J.H., C.D.); Translational Lung Research Center Heidelberg (TLRC), Member of the German Center of Lung Research (DZL), Heidelberg, Germany (C.P.H.); Praxisnetz, Radiology and Nuclear Medicine, Bonn, Germany (M.V.); Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany (J.A.L.); German Center for Neurodegenerative Diseases (DZNE), Helmholtz Association of German Research Centers, Bonn, Germany (A.R., K.D.); and Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA (K.D.).
深度学习增强单剂量脑MRI,以创建人工双剂量图像,改善大脑转移的检测. 这种人工智能方法增加了灵敏度,特别是对于较小的瘤,而不会影响准确度.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 在瘤学瘤学.
背景情况:
- 双剂量对比增强型MRI提高了脑瘤检测,但引发了安全问题.
- 基于加多的对比剂对患者和环境造成风险.
- 开发更安全,更有效的对比增强MRI替代品至关重要.
研究的目的:
- 评估一种深度学习 (DL) 方法,从单剂量 (T-SD) T1加权的大脑MRI中创建人工双剂量 (A-DD) 图像.
- 与T-SD图像相比,评估A-DD图像在检测大脑转移中的有效性.
主要方法:
- 一项前性多中心研究涉及30名参与者.
- 将DL模型应用于T-SD脑MRI图像,以生成A-DD图像.
- 四位读者独立审查了T-SD和A-DD图像以检测转移.
- 使用统计分析来比较性能,包括灵敏度和假阳性率.
主要成果:
- 与T-SD图像相比,所有阅读器在A-DD图像上检测到更多的转移.
- 经验丰富的读者对A-DD图像显示显著的敏感度增加 (高达12.1%).
- 经验较少的读者获得的灵敏度水平与使用A-DD图像的经验丰富的读者相美.
- 对于大小≤5毫米的转移,敏感度的提高最为显著.
- 假阳性发现没有显著增加,尽管描述性更高.
结论:
- 由深度学习产生的人工双剂量 (A-DD) 成像增强了大脑转移的检测.
- 这种由人工智能驱动的方法提供了更好的灵敏度,而不会显著地降低精度.
- A-DD成像代表了常规单剂量脑MRI协议的有希望的进步.


