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通过使用深度学习在MRI上自动检测自体主导多囊性病中的胰腺囊

Sophie J Wang¹, Zhongxiu Hu¹, Collin Li¹

¹Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA.

Tomography (Ann Arbor, Mich.)

|July 26, 2024

概括

自动化的深度学习模型可以检测自身主导多囊性病 (ADPKD) 患者的胰腺囊,改善放射科医生的同意. 为了提高诊断准确度,需要进一步提高图像质量.

科学领域:

放射学和医学成像学医学成像学
人工智能在医学中的应用
遗传学和基因组学遗传学和基因组学

背景情况:

自体主导多囊性病 (ADPKD) 的胰腺囊与PKD2突变有关.
这些囊在放射学评估中经常被忽视.
需要自动检测方法来改善识别.

研究的目的:

开发和评估一种自动化的深度学习系统,用于使用腹部MRI检测ADPKD患者的胰腺囊.
将自动检测性能与专家放射科医生的性能进行比较.

主要方法:

八个基于nnU-Net的深度学习模型 (2D/3D) 在T2加权的MRI上训练了146名ADPKD患者.
模型被训练在数据集上,只有阳性或阳性和阴性病例.
在内部,外部和测试-重新测试数据集上评估性能.

主要成果:

性能最好的2D模型实现了0.7 ± 0.5 (内部) 和0.8 ± 0.4 (外部) 的最佳子得分.
与专家观察者相比,该模型显示出更高的可重复性 (83%的同意) (77%的同意).
观察到高特异性 (94%/100%),但敏感性是有限的 (20%/24%).

结论:

自动化的深度学习模型显示出在ADPKD中检测胰腺囊的前景.
放射科医生对标签的协议是具有挑战性的,突出了需要人工智能协助的需要.
建议进一步改善MRI图像质量,以提高检测准确度.

关键词:

在 ADPKDD 中,在这里,我们可以看到AIAIAI.这就是为什么MRI是MRI.图像成像生物标志物生物标志物胰腺胰腺是什么胰腺囊是一种胰腺囊.

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