Middlebrooks E H, Frost C J, Tuna I S, Schmalfuss I M, Rahman M, Old Crow A
From the Department of Radiology (E.H.M.), University of Alabama at Birmingham, Birmingham, Alabama
Department of Biology (C.J.F.), University of Louisville, Louisville, Kentucky.
AJNR Am J Neuroradiol. 2017 Feb;38(2):336-342. doi: 10.3174/ajnr.A4996. Epub 2016 Nov 10.
Although it is a potentially powerful presurgical tool, fMRI can be fraught with artifacts, leading to interpretive errors, many of which are not fully accounted for in routinely applied correction methods. The purpose of this investigation was to evaluate the effects of data denoising by independent component analysis in patients undergoing preoperative evaluation for glioma resection compared with more routinely applied correction methods such as realignment or motion scrubbing.
Thirty-five functional runs (both motor and language) in 12 consecutive patients with glioma were analyzed retrospectively by double-blind review. Data were processed and compared with the following: 1) realignment alone, 2) motion scrubbing, 3) independent component analysis denoising, and 4) both independent component analysis denoising and motion scrubbing. Primary outcome measures included a change in false-positives, false-negatives, score, and diagnostic rating.
Independent component analysis denoising reduced false-positives in 63% of studies versus realignment alone. There was also an increase in the score in areas of true activation in 71.4% of studies. Areas of new expected activation (previous false-negatives) were revealed in 34.4% of cases with independent component analysis denoising versus motion scrubbing or realignment alone. Of studies deemed nondiagnostic with realignment or motion scrubbing alone, 65% were considered diagnostic after independent component analysis denoising.
The addition of independent component analysis denoising of fMRI data in preoperative patients with glioma has a significant impact on data quality, resulting in reduced false-positives and an increase in true-positives compared with more commonly applied motion scrubbing or simple realignment methods.
尽管功能磁共振成像（fMRI）是一种潜在强大的术前工具，但它可能充满伪影，导致解读错误，而许多此类错误在常规应用的校正方法中并未得到充分考虑。本研究的目的是评估独立成分分析进行数据去噪对接受胶质瘤切除术前评估的患者的影响，并与更常规应用的校正方法（如重排或运动校正）进行比较。
对连续12例胶质瘤患者的35次功能扫描（运动和语言）进行回顾性双盲分析。对数据进行处理，并与以下方法进行比较：1）仅重排，2）运动校正，3）独立成分分析去噪，4）独立成分分析去噪和运动校正。主要观察指标包括假阳性、假阴性、评分和诊断评级的变化。
与仅重排相比，独立成分分析去噪在63%的研究中减少了假阳性。在71.4%的研究中，真正激活区域的评分也有所增加。与运动校正或仅重排相比，独立成分分析去噪在34.4%的病例中发现了新的预期激活区域（先前的假阴性）。在仅通过重排或运动校正被认为无法诊断的研究中，65%在独立成分分析去噪后被认为具有诊断价值。
在术前胶质瘤患者中对fMRI数据添加独立成分分析去噪对数据质量有显著影响，与更常用的运动校正或简单重排方法相比，可减少假阳性并增加真阳性。
