Washington University in Saint Louis School of Medicine, (A. Schroeder), Washington University in Saint Louis School of Medicine, St. Louis, Missouri.
Departments of Ophthalmology and Visual Sciences (G.V.S., L.S.), Washington University in Saint Louis School of Medicine, St. Louis, Missouri.
AJNR Am J Neuroradiol. 2021 Jun;42(6):1130-1135. doi: 10.3174/ajnr.A7068. Epub 2021 Mar 18.
At times, there is a clinical need for using routine brain MR imaging performed close to the time of onset of patients' visual symptoms to firmly establish the diagnosis of optic neuritis. Our aim was to assess the diagnostic performance of radiologists in detecting optic neuritis on routine brain MR images and whether this performance could be enhanced using a postprocessing algorithm.
In this retrospective case-control study of 60 patients (37 women, 23 men; mean age, 47.2 [SD, 17.9] years), 2 blinded neuroradiologists evaluated T2-weighted FLAIR and contrast-enhanced T1WI from brain MR imaging for the presence of imaging evidence of optic neuritis. Images were processed using an image-processing algorithm that aimed to selectively accentuate the signal intensity of diseased optic nerves. We assessed the effect of image processing on the contrast-to-noise ratio between the optic nerves and normal-appearing white matter and on the diagnostic performance of the neuroradiologists, including the interobserver reliability.
The average sensitivity of readers was 55%, 56.5%, and 30.0% on FLAIR, coronal contrast-enhanced T1WI, and axial contrast-enhanced T1WI, respectively. Sensitivities were lower in the absence of fat saturation on FLAIR ( = .001) and coronal contrast-enhanced T1WI ( = .04). Processing increased the contrast-to-noise ratio of diseased ( value range = .03 to <.001) but not of control optic nerves. Processing did not improve the sensitivity but improved the specificity and positive predictive value. Interobserver agreement improved from slight to good.
Detection of optic neuritis on routine brain MR imaging is challenging. Specificity, positive predictive value, and interobserver agreement can be improved by postprocessing of MR images.
有时，临床需要使用患者视觉症状发作后接近发病时间的常规脑部磁共振成像（MRI）来明确视神经炎的诊断。我们的目的是评估放射科医生在常规脑部 MRI 图像上检测视神经炎的诊断性能，以及使用后处理算法是否可以提高这种性能。
在这项回顾性病例对照研究中，纳入了 60 名患者（37 名女性，23 名男性；平均年龄 47.2 [标准差 17.9] 岁）。两名盲法神经放射科医生评估了 T2 加权液体衰减反转恢复（FLAIR）和对比增强 T1 加权成像（T1WI）脑部 MRI 图像上是否存在视神经炎的影像学证据。使用一种图像处理算法对图像进行处理，旨在选择性地突出病变视神经的信号强度。我们评估了图像处理对视神经与正常外观白质之间的对比噪声比的影响，以及对神经放射科医生的诊断性能的影响，包括观察者间的可靠性。
在 FLAIR、冠状位对比增强 T1WI 和轴位对比增强 T1WI 上，读者的平均敏感度分别为 55%、56.5%和 30.0%。在 FLAIR 上缺乏脂肪饱和（ =.001）和冠状位对比增强 T1WI （ =.04）时，敏感度较低。处理增加了病变（ 值范围为.03 至 <.001）但未增加对照视神经的对比噪声比。处理并未提高敏感度，但提高了特异性和阳性预测值。观察者间的一致性从轻微提高到良好。
在常规脑部 MRI 图像上检测视神经炎具有挑战性。通过对 MRI 图像进行后处理，可以提高特异性、阳性预测值和观察者间的一致性。
