从深度学习的多参数MRI完全自动识别淋巴结转移和淋巴血管入侵在子宫内膜癌
Yida Wang1, Wei Liu2, Yuanyuan Lu3
1Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China.
Journal of magnetic resonance imaging : JMRI
|March 12, 2024
概括
一个深度学习模型准确地识别了使用多参数MRI (mpMRI) 的子宫内膜癌 (EC) 患者的淋巴结转移 (LNM) 和淋巴血管空间入侵 (LVSI). 这种人工智能工具显示了改善EC治疗计划的潜力.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 在瘤学瘤学.
背景情况:
- 精确识别淋巴结转移 (LNM) 和淋巴血管空间入侵 (LVSI) 对于子宫内膜癌 (EC) 治疗计划至关重要.
- 多参数MRI (mpMRI) 用于EC评估,但识别LNM和LVSI仍然具有挑战性.
研究的目的:
- 开发和评估一种深度学习 (DL) 模型,用于使用mpMRI在EC患者中同时识别LNM和LVSI.
- 评估模型与人类放射科医生对LNM诊断的性能.
主要方法:
- 这是一项追溯性研究,涉及来自两个机构的621名EC患者.
- 开发了一个多任务DL模型,使用mpMRI扫描中的T2WI,CE-T1WI和DWI序列.
- 该模型使用自动细分的EC病变来识别LNM和LVSI.
主要成果:
- 在EC损伤细分模型中,在内部和外部测试队列中,平均达到了大约0.70的子相似系数 (DSC).
- DL模型在识别LNM和LVSI方面表现出很高的表现,在训练队列中AUC值高达0.895和0.848.
- 该模型在外部测试队列中的LNM阳性诊断中表现优于三个放射科医生.
结论:
- 开发的DL模型显示了在帮助临床医生准确识别EC患者的LNM和LVSI方面显著的潜力.
- 这种由人工智能驱动的方法可能会增强治疗计划,并改善子宫内膜癌患者的治疗结果.
相关概念视频
01:24Magnetic Resonance Imaging
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
01:27Imaging Studies IV: Magnetic Resonance Imaging
Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...