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CT图像纹理分析在预测胃肠道间质瘤恶性风险中的应用

Texture analysis of CT images in predicting malignancy risk of gastrointestinal stromal tumours.

作者信息

Liu S, Pan X, Liu R, Zheng H, Chen L, Guan W, Wang H, Sun Y, Tang L, Guan Y, Ge Y, He J, Zhou Z

机构信息

Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, 210008, China.

Department of Radiology, Xi'an Central Hospital, Affiliated to Xi'an Jiaotong University, Xi'an, 710004, China.

出版信息

Clin Radiol. 2018 Mar;73(3):266-274. doi: 10.1016/j.crad.2017.09.003. Epub 2017 Sep 30.

Abstract

AIM

To explore the role of texture analysis of computed tomography (CT) images in predicting the malignancy risk of gastrointestinal stromal tumours (GISTs).

MATERIALS AND METHODS

Seventy-eight patients with histopathologically confirmed GISTs underwent preoperative CT. Texture analysis was performed on unenhanced and contrast-enhanced CT images, respectively. Fourteen CT texture parameters were obtained and compared among GISTs at different malignancy risks with one-way analysis of variance or independent-samples Kruskal-Wallis test. Correlations between CT texture parameters and malignancy risk were analysed with Spearman's correlation test. Diagnostic performance of CT texture parameters in differentiating GISTs at low/very low malignancy risk was tested with receiver operating characteristic (ROC) analysis.

RESULTS

Three parameters on unenhanced images (r=-0.268-0.506), four parameters on arterial phase (r=-0.365-0.508), and six parameters on venous phase (r=-0.343-0.481) imaging correlated significantly with malignancy risk of GISTs, respectively (all p<0.05). For identifying GISTs at low/very low malignancy risk, three parameters on unenhanced images (area under ROC curve [AUC], 0.676-0.802), four parameters on arterial phase (AUC, 0.637-0.811), and six parameters on venous phase (AUC, 0.636-0.791) imaging showed significant diagnostic performance, respectively (all p<0.05), especially maximum frequency on both unenhanced and contrast-enhanced images (AUC, 0.791-0.811).

CONCLUSION

Texture analysis of CT images holds great potential to predict the malignancy risk of GISTs preoperatively.

摘要

目的

探讨计算机断层扫描(CT)图像纹理分析在预测胃肠道间质瘤(GIST)恶性风险中的作用。

材料与方法

78例经组织病理学证实的GIST患者术前行CT检查。分别对平扫及增强CT图像进行纹理分析。获取14个CT纹理参数,并采用单因素方差分析或独立样本Kruskal-Wallis检验对不同恶性风险的GIST进行比较。采用Spearman相关检验分析CT纹理参数与恶性风险之间的相关性。采用受试者工作特征(ROC)分析测试CT纹理参数在鉴别低/极低恶性风险GIST中的诊断性能。

结果

平扫图像上的3个参数(r=-0.268-0.506)、动脉期图像上的4个参数(r=-0.365-0.508)和静脉期图像上的6个参数(r=-0.343-0.481)分别与GIST的恶性风险显著相关(均p<0.05)。对于鉴别低/极低恶性风险的GIST,平扫图像上的3个参数(ROC曲线下面积[AUC],0.676-0.802)、动脉期图像上的4个参数(AUC,0.637-0.811)和静脉期图像上的6个参数(AUC,0.636-0.791)分别显示出显著的诊断性能(均p<0.05),尤其是平扫及增强图像上的最大频率(AUC,0.791-0.811)。

结论

CT图像纹理分析在术前预测GIST恶性风险方面具有巨大潜力。

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