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一个深度的神经网络用于MRI脊柱炎症在轴性脊柱关节炎

Yingying Lin¹, Shirley Chiu Wai Chan², Ho Yin Chung^2,3

¹Department of Diagnostic Radiology, The University of Hong Kong, LG3 Sassoon Road No. 5, Pok Fu Lam, Hong Kong.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society

|January 8, 2024

概括

一个新的深度神经网络使用MRI扫描准确地检测轴性脊柱关节炎 (axSpA) 患者的脊柱炎. 这种人工智能工具的性能与经验丰富的放射科医生相当,有助于axSpA管理.

科学领域:

放射学放射学是一门学科.
人工智能的人工智能
医疗成像医学成像

背景情况:

轴性脊柱关节炎 (axSpA) 是一种影响脊柱的慢性炎症性疾病.
早期发现脊柱炎症对于有效管理至关重要.
短陶逆转恢复 (STIR) 序列磁共振成像 (MRI) 用于识别活跃的炎症病变.

研究的目的:

开发和评估一个深度神经网络 (DNN) 用于在 axSpA 患者的 STIR MRI 上检测脊柱炎症.
为了比较DNN与人类放射科医生的性能.

主要方法:

使用了330名axSpA患者的STIRMRI扫描数据集.
感兴趣的区域 (ROI) 被绘制出来,以识别骨髓 (BME) 作为活跃的炎症病变.
在270名患者的数据上开发和训练了一个基于UNet的注意力DNN,并进行了验证.
在对60名患者的单独测试组中评估了DNN的性能,并与盲目放射科医生进行了比较.

主要成果:

该DNN实现了0.80±0.03的灵敏度和0.88±0.02的特异性.
真正阳性病变的子系数为0.55 ± 0.02.
接收机运行特征曲线 (AUC-ROC) 下的面积为0.87 ± 0.02.
DNN的表现与放射科医生的表现相当.

结论:

开发的DNN在STIRMRI对axSpA.检测脊髓炎的检测中显示出可靠的性能.
该网络为脊柱MRI解释提供了一种简单且潜在可扩展的方法.
这种人工智能工具可以增强脊柱MRI在治疗axSpA. axSpA.的临床效用.

关键词:

结性脊柱炎是一种疾病.人工智能的人工智能是人工智能.轴性脊椎关节炎 (Axial spondyloarthritis) 是一个关节性关节炎.深度学习是一种深度学习.炎症炎症是一种炎症.这就是为什么MRI是MRI.脊柱脊柱脊柱脊柱脊柱脊柱

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