基于数字图像分析的内镜超声评分系统有助于预测胃肠道间质瘤。
Digital image analysis-based scoring system for endoscopic ultrasonography is useful in predicting gastrointestinal stromal tumors.
机构信息
Department of Internal Medicine, Pusan National University School of Medicine and Biomedical Research Institute, Pusan National University Hospital, 179 Gudeok-ro, Seo-Gu, Busan, 49241, South Korea.
Division of Computer Engineering, Silla University, Busan, South Korea.
出版信息
Gastric Cancer. 2019 Sep;22(5):980-987. doi: 10.1007/s10120-019-00928-w. Epub 2019 Feb 18.
BACKGROUND
When gastric mesenchymal tumors (GMTs) measuring 2-5 cm in size are found, whether to undergo further treatment or not is controversial. Endoscopic ultrasonography (EUS) is useful for the evaluation of malignant potential of GMTs, but has limitations, such as subjective interpretation of EUS images. Therefore, we aimed to develop a scoring system based on the digital image analysis of EUS images to predict gastrointestinal stromal tumors (GISTs).
METHODS
We included 103 patients with histopathologically proven GIST, leiomyoma or schwannoma on surgically resected specimen who underwent EUS examination between January 2007 and June 2018. After standardization of the EUS images, brightness values, including the mean (T), indicative of echogenicity, and the standard deviation (T), indicative of heterogeneity, in the tumors were analyzed.
RESULTS
Age, T, and T were significantly higher in GISTs than in non-GISTs. The sensitivity and specificity were almost optimized for differentiating GISTs from non-GISTs when the critical values of age, T, and T were 57.5 years, 67.0, and 25.6, respectively. A GIST-predicting scoring system was created by assigning 3 points for T ≥ 67, 2 points for age ≥ 58 years, and 1 point for T ≥ 26. When GMTs with 3 points or more were diagnosed as GISTs, the sensitivity, specificity, and accuracy of the scoring system were 86.5%, 75.9%, and 83.5%, respectively.
CONCLUSIONS
The scoring system based on the information of digital image analysis is useful in predicting GISTs in case of GMTs that are 2-5 cm in size.
背景
当发现大小为 2-5cm 的胃间质瘤（GMT）时，是否进一步治疗存在争议。内镜超声检查（EUS）有助于评估 GMT 的恶性潜能，但存在主观解读 EUS 图像等局限性。因此，我们旨在开发一种基于 EUS 图像数字图像分析的评分系统，以预测胃肠道间质瘤（GIST）。
方法
我们纳入了 2007 年 1 月至 2018 年 6 月期间经手术切除标本病理证实为 GIST、平滑肌瘤或神经鞘瘤的 103 例患者，这些患者均接受了 EUS 检查。对 EUS 图像进行标准化后，分析肿瘤的亮度值，包括平均亮度值（T），表示回声强度，以及标准偏差（T），表示异质性。
结果
GIST 的年龄、T 和 T 值显著高于非 GIST。当年龄、T 和 T 的临界值分别为 57.5 岁、67.0 和 25.6 时，区分 GIST 和非 GIST 的灵敏度和特异性几乎达到最佳。通过为 T≥67 赋值 3 分、年龄≥58 岁赋值 2 分、T≥26 赋值 1 分，创建了一个 GIST 预测评分系统。当诊断为 GMT 的 3 分或以上时，评分系统的灵敏度、特异性和准确性分别为 86.5%、75.9%和 83.5%。
结论
基于数字图像分析信息的评分系统有助于预测大小为 2-5cm 的 GMT 中的 GIST。
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