基于增强CT的列线图术前辅助性预测胃癌患者的EB病毒状态

doi:10.3877/cma.j.issn.2095-2015.2026.05.006

中华消化病与影像杂志(电子版) ›› 2026, Vol. 16 ›› Issue (05) : 422 -429. doi: 10.3877/cma.j.issn.2095-2015.2026.05.006

论著

基于增强CT的列线图术前辅助性预测胃癌患者的EB病毒状态

郑月¹^,²^,³^,⁴, 刘译阳¹^,²^,³^,⁴, 袁梦晨¹^,²^,³^,⁴, 尤亚茹¹^,²^,³^,⁴, 李莉明¹, 张哲⁵, 陈俣菘¹^,²^,³^,⁴, 范松梅¹^,²^,³^,⁴, 高剑波¹^,²^,³^,⁴^,^†(

)

¹450052　郑州大学第一附属医院放射科
⁵450052　郑州大学第一附属医院病理科
²450052　郑州，河南省医学影像国际联合实验室
³450052　郑州，河南省消化肿瘤影像重点实验室
⁴450052　郑州，河南省CT影像重点实验室

收稿日期:2025-02-21 出版日期:2026-10-01
通信作者: 高剑波
基金资助:
国家自然科学基金(81971615); "科创中原"青年人才托举工程项目(2023HYTP039)

Preoperative adjuvant prediction of Epstein-Barr virus status in patients with gastric cancer based on the nomogram of enhanced CT

Yue Zheng¹^,²^,³^,⁴, Yiyang Liu¹^,²^,³^,⁴, Mengchen Yuan¹^,²^,³^,⁴, Yaru You¹^,²^,³^,⁴, Liming Li¹, Zhe Zhang⁵, Yusong Chen¹^,²^,³^,⁴, Songmei Fan¹^,²^,³^,⁴, Jianbo Gao¹^,²^,³^,⁴^,^†()

¹Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
⁵Department of Pathology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
²Henan International Joint Laboratory of Medical Imaging, Zhengzhou 450052, China
³Henan Key Laboratory of Image Diagnosis and Treatment for Digestive System Tumor, Zhengzhou 450052, China
⁴Henan Key Laboratory of CT Imaging, Zhengzhou 450052, China

Received:2025-02-21 Published:2026-10-01
Corresponding author: Jianbo Gao

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引用本文：

郑月, 刘译阳, 袁梦晨, 尤亚茹, 李莉明, 张哲, 陈俣菘, 范松梅, 高剑波. 基于增强CT的列线图术前辅助性预测胃癌患者的EB病毒状态[J/OL]. 中华消化病与影像杂志(电子版), 2026, 16(05): 422-429.

Yue Zheng, Yiyang Liu, Mengchen Yuan, Yaru You, Liming Li, Zhe Zhang, Yusong Chen, Songmei Fan, Jianbo Gao. Preoperative adjuvant prediction of Epstein-Barr virus status in patients with gastric cancer based on the nomogram of enhanced CT[J/OL]. Chinese Journal of Digestion and Medical Imageology(Electronic Edition), 2026, 16(05): 422-429.

目的

建立一个基于增强CT的个体化列线图，用于辅助性诊断胃癌EB病毒（EBV）的状态。

方法

回顾性分析2016年12月至2023年12月郑州大学第一附属医院经大体病理组织学证实EBV状态的胃癌患者临床及CT资料，分为EBV阳性组（n=36）与EBV阴性组（n=95）。由两名放射科医生在增强CT上获得病变的定性和定量资料，采用Bland-Altman分析定量资料的一致性。采用单因素分析和多因素Logistic回归筛选独立预测因子并建立联合模型，并用列线图可视化。采用受试者工作特征（ROC）曲线的曲线下面积（AUC）评估列线图和单独的预测因子的区分度，利用DeLong检验比较AUC间的差异。

结果

Bland-Altman分析显示两名医生所测得两组资料一致性较好。病灶动脉期CT值与同层腹主动脉CT值百分比（Ra）、强化均匀性、肿瘤最大长径为术前预测胃癌EBV表达状态的独立预测因子，三者AUC值分别为0.620、0.722、0.713。联合模型的列线图AUC为0.817，准确度为0.748。DeLong检验显示三个单一参数的AUC值之间无统计学差异（P均>0.05），联合模型的AUC值均明显优于任一独立预测因子（P<0.05）。

结论

基于增强CT定量及定性特征建立的个性化列线图，能够在术前无创性辅助诊断胃癌患者EBV状态，可作为病理检测的补充工具。

关键词: 胃癌, EB病毒, 列线图, 计算机断层扫描

Objective

To develop an individualized nomogram based on contrast-enhanced CT for adjuvant diagnosis of the status of Epstein-Barr virus(EBV) in gastric cancer.

Methods

A retrospective analysis was conducted on the clinical and CT data of gastric cancer patients at the First Affiliated Hospital of Zhengzhou University, who were confirmed to have EBV status by gross pathological histology from December 2016 to December 2023. The patients were divided into the EBV-positive group (n=36) and the EBV-negative group (n=95). Two radiologists assessed qualitative and quantitative features of lesions on the enhanced CT. Consistency of the quantitative data was evaluated using Bland-Altman tests. Univariate and multivariate logistic regression were used to screen out independent predictive factors and establish a combined model, which was then visualized using a nomogram. Discriminative ability of the nomogram and individual predictors was assessed using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve, and the differences in AUC values were compared using the DeLong test.

Results

Good consistency was found between the two radiologists' measurements using the Bland-Altman analysis. The ratio of arterial phase lesion CT value to abdominal aorta CT value (Ra), enhancement homogeneity, and maximum tumor length were identified as independent predictors for predicting the EBV expression status of gastric cancer before surgery. Their AUC values were 0.620, 0.722, and 0.713, respectively. The nomogram combining these factors had an AUC of 0.817 and accuracy of 0.748. DeLong test showed no significant differences among individual predictors (P>0.05), but the combined model significantly outperformed any single factor (P<0.05).

Conclusion

The personalized nomogram established based on the quantitative and qualitative characteristics of enhanced CT can non-invasively assist in the diagnosis of EBV status in patients with gastric cancer and can be used as a supplementary tool for pathological detection.

Key words: Gastric cancer, Epstein-Barr virus, Nomogram, Computed tomography

图1 胃癌患者病灶CT图像　1A：EBVaGC患者；1B：EBVnGC患者，均为病灶最大层面（轴位）CT图像（动脉期）

图2 两组数据进行Bland-Altman分析

表1 两组胃癌患者临床、病理资料比较

变量	EBVnGC组(n=95)	EBVaGC组(n=36)	χ²/t值	P值	变量	EBVnGC组(n=95)	EBVaGC组(n=36)	χ²/t值	P值
年龄(岁,±s)	59.695±10.818	57.917±10.882	0.838	0.403	pT[例(%)]			2.725	0.436
性别[例%)]			4.768	0.029	1	13(13.7)	8(22.2)
女	28(29.5)	4(11.1)			2	21(22.1)	10(27.8)
男	67(70.5)	32(88.9)			3	45(47.4)	12(33.3)
脉管侵犯[例(%)]			5.434	0.020	4	16(16.8)	6(16.7)
否	44(46.3)	25(69.4)			pN[例(%)]			1.461	0.691
是	51(53.7)	11(30.6)			0	47(49.5)	22(61.1)
神经侵犯[例(%)]			11.123	0.001	1	19(20.0)	6(16.7)
否	30(31.6)	23(63.9)			2	11(11.6)	3(8.3)
是	65(68.4)	13(36.1)			3	18(18.9)	5(13.9)

表1 两组胃癌患者临床、病理资料比较

变量	EBVnGC组(n=95)	EBVaGC组(n=36)	χ²/t值	P值	变量	EBVnGC组(n=95)	EBVaGC组(n=36)	χ²/t值	P值
年龄(岁,±s)	59.695±10.818	57.917±10.882	0.838	0.403	pT[例(%)]			2.725	0.436
性别[例%)]			4.768	0.029	1	13(13.7)	8(22.2)
女	28(29.5)	4(11.1)			2	21(22.1)	10(27.8)
男	67(70.5)	32(88.9)			3	45(47.4)	12(33.3)
脉管侵犯[例(%)]			5.434	0.020	4	16(16.8)	6(16.7)
否	44(46.3)	25(69.4)			pN[例(%)]			1.461	0.691
是	51(53.7)	11(30.6)			0	47(49.5)	22(61.1)
神经侵犯[例(%)]			11.123	0.001	1	19(20.0)	6(16.7)
否	30(31.6)	23(63.9)			2	11(11.6)	3(8.3)
是	65(68.4)	13(36.1)			3	18(18.9)	5(13.9)

表2 两组胃癌患者CT资料比较

变量	EBVnGC组(n=95)	EBVaGC组(n=36)	χ²/t/Z值	P值
肿瘤最大厚度[mm,M(P25,P75)]	18.210(14.295,23.305)	16.505(13.328,18.867)	5.301	0.116
肿瘤最大长径(mm,±s)	53.874±22.598	40.735±19.077	3.094	0.002
病灶CT值(HU,±s)
nCT	39.085±6.584	39.670±9.091	-0.407	0.685
APCT	81.738±24.157	82.010±24.030	-0.057	0.954
VPCT	90.264±19.879	87.209±19.574	0.788	0.432
病灶同层腹主动脉CT值(HU,±s)
APCT_ao	306.013±62.450	266.127±60.442	3.292	0.001
VPCT_ao	154.662±33.510	140.421±25.068	2.314	0.022
Ra⁽%,±s)	27.179±7.282	31.861±11.514	-2.77	0.006
Rv(%,±s)	59.632±12.940	62.889±14.016	-1.257	0.211
动脉期强化率[M(P25,P75)]	0.996(0.686,1.424)	1.002(0.587,1.619)	-0.098	0.922
静脉期强化率[M(P25,P75)]	1.231(0.919,1.589)	1.152(0.775,1.634)	0.701	0.483
cT分期			2.525	0.471
1	13(13.7)	8(22.2)
2	24(25.3)	11(30.6)
3	41(43.2)	13(36.1)
4	17(17.9)	4(11.1)
肿瘤部位			8.022	0.046
上部1/3	29(30.5)	13(36.1)
中部2/3	11(11.6)	9(25.0)
下部1/3	35(36.8)	5(13.9)
>1/3	20(21.1)	9(25.0)
强化均匀性[例(%)]			20.584	<0.001
均匀	37(38.9)	30(83.3)
不均	58(61.1)	6(16.7)
动脉期强化程度[例(%)]			0.701	0.704
轻度强化	13(13.7)	7(19.4)
中度强化	38(40.0)	14(38.9)
明显强化	44(46.3)	15(41.7)
静脉期强化程度[例(%)]			0.453	0.501
轻度强化	0(0.0%)	0(0.0%)
中度强化	31(32.6)	14(38.9)
明显强化	64(67.4)	22(61.1)
cT_LN [例(%)]			0.956	0.328
否	49(51.6)	22(61.1)
是	46(48.4)	14(38.9)

表2 两组胃癌患者CT资料比较

变量	EBVnGC组(n=95)	EBVaGC组(n=36)	χ²/t/Z值	P值
肿瘤最大厚度[mm,M(P25,P75)]	18.210(14.295,23.305)	16.505(13.328,18.867)	5.301	0.116
肿瘤最大长径(mm,±s)	53.874±22.598	40.735±19.077	3.094	0.002
病灶CT值(HU,±s)
nCT	39.085±6.584	39.670±9.091	-0.407	0.685
APCT	81.738±24.157	82.010±24.030	-0.057	0.954
VPCT	90.264±19.879	87.209±19.574	0.788	0.432
病灶同层腹主动脉CT值(HU,±s)
APCT_ao	306.013±62.450	266.127±60.442	3.292	0.001
VPCT_ao	154.662±33.510	140.421±25.068	2.314	0.022
Ra⁽%,±s)	27.179±7.282	31.861±11.514	-2.77	0.006
Rv(%,±s)	59.632±12.940	62.889±14.016	-1.257	0.211
动脉期强化率[M(P25,P75)]	0.996(0.686,1.424)	1.002(0.587,1.619)	-0.098	0.922
静脉期强化率[M(P25,P75)]	1.231(0.919,1.589)	1.152(0.775,1.634)	0.701	0.483
cT分期			2.525	0.471
1	13(13.7)	8(22.2)
2	24(25.3)	11(30.6)
3	41(43.2)	13(36.1)
4	17(17.9)	4(11.1)
肿瘤部位			8.022	0.046
上部1/3	29(30.5)	13(36.1)
中部2/3	11(11.6)	9(25.0)
下部1/3	35(36.8)	5(13.9)
>1/3	20(21.1)	9(25.0)
强化均匀性[例(%)]			20.584	<0.001
均匀	37(38.9)	30(83.3)
不均	58(61.1)	6(16.7)
动脉期强化程度[例(%)]			0.701	0.704
轻度强化	13(13.7)	7(19.4)
中度强化	38(40.0)	14(38.9)
明显强化	44(46.3)	15(41.7)
静脉期强化程度[例(%)]			0.453	0.501
轻度强化	0(0.0%)	0(0.0%)
中度强化	31(32.6)	14(38.9)
明显强化	64(67.4)	22(61.1)
cT_LN [例(%)]			0.956	0.328
否	49(51.6)	22(61.1)
是	46(48.4)	14(38.9)

图3 Ra、强化均匀性、肿瘤最大长径与联合模型的ROC曲线注：Ra表示病灶动脉期CT值与病灶同层腹主动脉CT值之比×100%

图4 基于联合模型构建的列线图注：Ra表示病灶动脉期CT值与病灶同层腹主动脉CT值之比×100%

图5 决策曲线（DCA）

图6 校准（Calibration）曲线注：横坐标为预测概率，纵坐标为实际概率，刻度0~1表示发生的可能性。Apparent为实际概率线，Ideal为理想线，Bias-corrected为纠正偏差线。

表3 胃癌EB病毒的独立预测因子

独立预测因子	回归系数/b	标准误差	Wald值	OR值	95% CI	P值
Ra	0.059	0.027	4.621	1.061	1.005~1.120	0.032
强化均匀性^a	1.86	0.512	13.181	6.421	2.353~17.523	<0.001
肿瘤最大长径	-0.031	0.013	5.897	0.97	0.946~0.994	0.015

表3 胃癌EB病毒的独立预测因子

独立预测因子	回归系数/b	标准误差	Wald值	OR值	95% CI	P值
Ra	0.059	0.027	4.621	1.061	1.005~1.120	0.032
强化均匀性^a	1.86	0.512	13.181	6.421	2.353~17.523	<0.001
肿瘤最大长径	-0.031	0.013	5.897	0.97	0.946~0.994	0.015

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Preoperative adjuvant prediction of Epstein-Barr virus status in patients with gastric cancer based on the nomogram of enhanced CT

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Preoperative adjuvant prediction of Epstein-Barr virus status in patients with gastric cancer based on the nomogram of enhanced CT