Mallinckrodt Institute of Radiology, Washington University School of Medicine, Campus Box 8131, 510 S Kingshighway Blvd, St. Louis, MO 63110.
Acad Radiol. 2019 Apr;26(4):e1-e8. doi: 10.1016/j.acra.2018.05.007. Epub 2018 Jun 12.
To test whether an image-processing algorithm can aid in visualization of mesial temporal sclerosis on magnetic resonance imaging by selectively increasing contrast-to-noise ratio (CNR) between abnormal hippocampus and normal brain.
In this Institutional Review Board-approved and Health Insurance Portability and Accountability Act-compliant study, baseline coronal fluid-attenuated inversion recovery images of 18 adults (10 females, eight males; mean age 41.2 years) with proven mesial temporal sclerosis were processed using a custom algorithm to produce corresponding enhanced images. Average (Hmean) and maximum (Hmax) CNR for abnormal hippocampus were calculated relative to normal ipsilateral white matter. CNR values for normal gray matter (GM) were similarly calculated using ipsilateral cingulate gyrus as the internal control. To evaluate effect of image processing on visual conspicuity of hippocampal signal alteration, a neuroradiologist masked to the side of hippocampal abnormality rated signal intensity (SI) of hippocampi on baseline and enhanced images using a five-point scale (definitely abnormal to definitely normal). Differences in Hmean, Hmax, GM, and SI ratings for abnormal hippocampi on baseline and enhanced images were assessed for statistical significance.
Both Hmean and Hmax were significantly higher in enhanced images as compared to baseline images (p < 0.0001 for both). There was no significant difference in the GM between baseline and enhanced images (p = 0.9375). SI ratings showed a more confident identification of abnormality on enhanced images (p = 0.0001).
Image-processing resulted in increased CNR of abnormal hippocampus without affecting the CNR of normal gray matter. This selective increase in conspicuity of abnormal hippocampus was associated with more confident identification of hippocampal signal alteration.
通过选择性提高异常海马体与正常大脑之间的对比噪声比(CNR),测试一种图像处理算法是否有助于在磁共振成像上可视化内侧颞叶硬化。
在这项经过机构审查委员会批准且符合《健康保险流通与责任法案》的研究中,对 18 名经证实患有内侧颞叶硬化的成年患者(10 名女性,8 名男性;平均年龄 41.2 岁)的基线冠状位液体衰减反转恢复图像使用定制算法进行处理,以生成相应的增强图像。异常海马体的平均(Hmean)和最大(Hmax)CNR 相对于正常对侧白质计算。同侧扣带回作为内部对照,使用相同的方法计算正常灰质(GM)的 CNR 值。为了评估图像处理对海马信号改变的视觉显著性的影响,一位对海马异常侧不了解的神经放射科医生使用五分制量表(从绝对异常到绝对正常)对基线和增强图像上的海马信号强度(SI)进行评分。对异常海马体在基线和增强图像上的 Hmean、Hmax、GM 和 SI 评分的差异进行了统计学意义评估。
与基线图像相比,增强图像的 Hmean 和 Hmax 均显著升高(两者均 p<0.0001)。基线和增强图像之间的 GM 没有显著差异(p=0.9375)。SI 评分显示,增强图像上对异常的识别更有信心(p=0.0001)。
图像处理导致异常海马体的 CNR 增加,而不影响正常灰质的 CNR。这种异常海马体显著性的选择性增加与对海马信号改变的更有信心的识别相关。