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由一组临床神经放射学家应用 fMRI 的计算机语言侧化指数。

Application of a computerized language lateralization index from FMRI by a group of clinical neuroradiologists.

机构信息

Division of Neuroradiology, Imaging Institute, Cleveland Clinic, Cleveland Ohio, USA.

出版信息

AJNR Am J Neuroradiol. 2013 Mar;34(3):564-9. doi: 10.3174/ajnr.A3271. Epub 2012 Sep 13.

Abstract

BACKGROUND AND PURPOSE

Deriving accurate language lateralization from fMRI studies in the clinical context can be difficult, with 10%-20% incorrect conclusions. Most interpretations are qualitative, performed by neuroimaging experts. Quantitative lateralization has been widely described but with little implementation in the clinical setting and is disadvantaged by the use of arbitrary threshold techniques. We investigated the application and utility of a nonthreshold CLI, in a clinical setting, as applied by a group of practicing neuroradiologists.

MATERIALS AND METHODS

Twenty-two patients with known language lateralization (11 left and 11 nonleft dominant) had their images reviewed by 8 neuroradiologists in 2 settings, all randomized, once by using a CLI and once without using a CLI. For each review, neuroradiologists recorded their impressions of lateralization for each language sequence, the overall lateralization conclusion, their impression of scan quality and noise, and the subjective confidence in their conclusion.

RESULTS

The inter-rater κ for lateralization was 0.64, which increased to 0.70 with the use of CLI. The group accuracy of overall lateralization was 78%, which increased to 81% with the use of a CLI. Using a CLI removed 2 instances of significant errors, with a neuroradiologist's impression of left lateralization in a patient with known right lateralization. Using a CLI had no effect on examinations with conclusions formed with either high confidence or no confidence.

CONCLUSIONS

Although the overall clinical benefit of a CLI is modest, the most significant impact is to reduce the most harmful misclassification errors, particularly in fMRI examinations that are suboptimal.

摘要

背景与目的

在临床环境中,从 fMRI 研究中得出准确的语言侧化结果可能较为困难,有 10%-20%的结论可能不正确。大多数解释是定性的,由神经影像学专家进行。定量侧化已被广泛描述,但在临床环境中实施较少,并且由于使用任意阈值技术而处于不利地位。我们研究了一种非阈值 CLI 在临床环境中的应用和实用性,由一组实践中的神经放射科医生进行应用。

材料与方法

22 名已知语言侧化的患者(11 名左侧,11 名非左侧优势)的图像由 8 名神经放射科医生在 2 种设置下进行了回顾,均为随机分组,一次使用 CLI,一次不使用 CLI。每次检查,神经放射科医生记录他们对每种语言序列的侧化印象、整体侧化结论、对扫描质量和噪声的印象,以及对结论的主观信心。

结果

侧化的组内 κ 为 0.64,使用 CLI 后增加到 0.70。整体侧化的组准确率为 78%,使用 CLI 后增加到 81%。使用 CLI 消除了 2 例明显的错误,即一位神经放射科医生在已知右侧侧化的患者中对左侧侧化的印象。使用 CLI 对那些具有高置信度或无置信度的检查结果没有影响。

结论

尽管 CLI 的整体临床获益不大,但最重要的影响是减少最有害的分类错误,特别是在 fMRI 检查不理想的情况下。

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