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胃黏膜下肿瘤:应用 CT 实用评分方法对胃肠道间质瘤的识别。

Gastric sub-epithelial tumors: identification of gastrointestinal stromal tumors using CT with a practical scoring method.

机构信息

Department of Radiotherapy, Fudan University Shanghai Cancer Center, Shanghai, China.

Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.

出版信息

Gastric Cancer. 2019 Jul;22(4):769-777. doi: 10.1007/s10120-018-00908-6. Epub 2018 Dec 9.

Abstract

OBJECTIVES

To determine CT features that can identify gastrointestinal stromal tumors (GISTs) among gastric sub-epithelial tumors (SETs) and to explore a practical scoring method.

METHODS

Sixty-four patients with gastric SETs (51 GISTs and 13 non-GISTs) from hospital I were included for primary analyses, and 92 (67 GISTs and 25 non-GISTs) from hospital II constituted a validation cohort. Pre-operative CT images were reviewed for imaging features: lesion location, growth pattern, lesion margin, enhancement pattern, dynamic pattern, attenuation at each phasic images and presence of necrosis, superficial ulcer, calcification, and peri-lesion enlarged lymph node (LN). Clinical and CT features were compared between the two groups (GISTs versus non-GISTs) and a GIST-risk scoring method was developed; then, its performance for identifying GISTs was tested in the validation cohort.

RESULTS

Seven clinical and CT features were significantly suggestive of GISTs rather than non-GISTs: older age (> 49 years), non-cardial location, irregular margin, lower attenuation on unenhanced images (≤ 43 HU), heterogeneous enhancement, necrosis, and absence of enlarged LN (p < 0.05). At validation step, the established scoring method with cut-off score dichotomized into ≥ 4 versus < 4 for identifying GISTs revealed an AUC of 0.97 with an accuracy of 92%, a sensitivity of 100% and a negative predictive value (NPV) of 100%.

CONCLUSIONS

Gastric GISTs have special CT and clinical features that differ from non-GISTs. With a simple and practical scoring method based on the significant features, GISTs can be accurately differentiated from non-GISTs.

摘要

目的

确定能够在胃黏膜下肿瘤(SET)中识别胃肠道间质瘤(GIST)的 CT 特征,并探索一种实用的评分方法。

方法

对 I 医院的 64 例胃 SET 患者(51 例 GIST 和 13 例非 GIST)进行了初步分析,对 II 医院的 92 例(67 例 GIST 和 25 例非 GIST)进行了验证队列分析。对术前 CT 图像进行了影像学特征的回顾:病变位置、生长模式、病变边缘、强化模式、动态模式、各时相图像的衰减以及坏死、浅表溃疡、钙化和病变周围增大的淋巴结(LN)的存在。比较两组(GIST 与非 GIST)之间的临床和 CT 特征,并建立 GIST 风险评分方法;然后在验证队列中测试其识别 GIST 的性能。

结果

有 7 个临床和 CT 特征强烈提示 GIST 而非非 GIST:年龄较大(>49 岁)、非贲门位置、不规则边缘、平扫时的低衰减(≤43 HU)、不均匀强化、坏死和无增大的 LN(p<0.05)。在验证步骤中,采用截断值为≥4 与<4 的建立的评分方法,对识别 GIST 的 AUC 为 0.97,准确率为 92%,敏感度为 100%,阴性预测值(NPV)为 100%。

结论

胃 GIST 具有与非 GIST 不同的特殊 CT 和临床特征。基于显著特征建立的简单实用的评分方法,能够准确地区分 GIST 和非 GIST。

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