Support Center for Advanced Neuroimaging - Institute for Diagnostic and Interventional Neuroradiology, University Hospital Inselspital and University of Bern, Bern, Switzerland.
Department of Radiology, Division of Diagnostic and Interventional Neuroradiology, University Hospital, Basel, Switzerland.
Eur J Radiol. 2017 Oct;95:75-81. doi: 10.1016/j.ejrad.2017.07.028. Epub 2017 Aug 2.
Current recommendations for the measurement of tumor size in glioblastoma continue to employ manually measured 2D product diameters of enhancing tumor. To overcome the rater dependent variability, this study aimed to evaluate the potential of automated 2D tumor analysis (ATA) compared to highly experienced rater teams in the workup of pre- and postoperative image interpretation in a routine clinical setting.
From 92 patients with newly diagnosed GB and performed surgery, manual rating of the sum product diameter (SPD) of enhancing tumor on magnetic resonance imaging (MRI) contrast enhanced T1w was compared to automated machine learning-based tumor analysis using FLAIR, T1w, T2w and contrast enhanced T1w.
Preoperative correlation of SPD between two rater teams (1 and 2) was r=0.921 (p<0.0001). Difference among the rater teams and ATA (p=0.567) was not statistically significant. Correlation between team 1 vs. automated tumor analysis and team 2 vs. automated tumor analysis was r=0.922 and r=0.897, respectively (p<0.0001 for both). For postoperative evaluation interrater agreement between team 1 and 2 was moderate (Kappa 0.53). Manual consensus classified 46 patients as completely resected enhancing tumor. Automated tumor analysis agreed in 13/46 (28%) due to overestimation caused by hemorrhage and choroid plexus enhancement.
Automated 2D measurements can be promisingly translated into clinical trials in the preoperative evaluation. Immediate postoperative SPD evaluation for extent of resection is mainly influenced by postoperative blood depositions and poses challenges for human raters and ATA alike.
目前胶质母细胞瘤肿瘤大小测量的推荐方法仍然采用增强肿瘤的手动测量 2D 产品直径。为了克服评估者之间的可变性，本研究旨在评估自动 2D 肿瘤分析（ATA）与高度有经验的评估者团队在常规临床环境中术前和术后图像解释中的潜在应用。
从 92 例新诊断为胶质母细胞瘤并接受手术的患者中，比较了磁共振成像（MRI）对比增强 T1w 上增强肿瘤的总和产品直径（SPD）的手动评分与基于自动机器学习的肿瘤分析，该分析使用了 FLAIR、T1w、T2w 和对比增强 T1w。
两个评估者团队（1 和 2）之间的术前 SPD 相关性为 r=0.921（p<0.0001）。评估者团队之间和 ATA（p=0.567）之间的差异无统计学意义。团队 1 与自动肿瘤分析的相关性和团队 2 与自动肿瘤分析的相关性分别为 r=0.922 和 r=0.897（均 p<0.0001）。术后评估中，团队 1 和 2 之间的组内一致性为中度（Kappa 0.53）。手动共识将 46 例患者归类为完全切除的增强肿瘤。由于出血和脉络丛增强导致的高估，自动肿瘤分析仅在 13/46（28%）例中与共识一致。
自动 2D 测量有望在术前评估中转化为临床试验。术后立即对 SPD 进行评估以确定切除范围主要受到术后血液沉积的影响，这对人类评估者和 ATA 都构成了挑战。
