| 刘梦茹,梁盼,吕东博,程铭,朱兵兵,高剑波.脾脏CT表现用于预测进展期胃腺癌分化程度[J].中国医学影像技术,2024,40(3):392~396 |
| 脾脏CT表现用于预测进展期胃腺癌分化程度 |
| CT findings of spleen for predicting differentiation degree of advanced gastric adenocarcinoma |
| 投稿时间：2023-12-18 修订日期：2024-01-21 |
| DOI：10.13929/j.issn.1003-3289.2024.03.015 |
| 中文关键词: 胃肿瘤 体层摄影术,X线计算机 细胞分化 |
| 英文关键词:stomach neoplasms tomography, X-ray computed cell differentiation |
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| 中文摘要: |
| 目的 观察脾脏CT表现用于预测进展期胃腺癌分化程度的价值。方法 回顾性分析182例经术后病理证实的进展期胃腺癌患者,根据病理结果将其分为低分化组(n=89)及中-高分化组(n=93),比较2组临床资料,以及肿瘤及脾脏CT表现。采用多因素logistic回归分析筛选进展期胃腺癌分化程度的独立影响因素;绘制受试者工作特征(ROC)曲线,计算曲线下面积(AUC),评估各单一独立影响因素及其联合预测进展期胃腺癌分化程度的效能。结果 组间患者年龄、性别、肿瘤厚度、肿瘤最长径、Borrmann分型、cT分期、cN状态、cTNM分期及动脉期脾脏CT值差异均有统计学意义(P均＜0.05)。多因素logistic回归分析显示,患者年龄、性别、Borrmann分型、cT分期、cTNM分期及动脉期脾脏CT值均为进展期胃腺癌分化程度的独立影响因素(P均＜0.05);以之单一及联合预测进展期胃腺癌分化程度的AUC分别为0.639、0.577、0.621、0.690、0.714、0.606及0.861。结论 脾脏CT表现有助于预测进展期胃腺癌分化程度,动脉期脾脏CT值为有效预测指标;联合临床及肿瘤CT特征可进一步提高预测效能。 |
| 英文摘要: |
| Objective To explore the value of CT finding of spleen for predicting differentiation degrees of advanced gastric adenocarcinoma. Methods Data of 182 patients with advanced gastric adenocarcinoma confirmed by pathology were retrospectively analyzed. The patients were divided into poorly differentiation group (n=89) and moderate-well differentiation group (n=93) according to pathological results. Clinical data and CT finding of both tumor and spleen were compared between groups. Multivariate logistic regression analysis was used to screen the independent impact factors of differentiation degrees of advanced gastric adenocarcinoma. Receiver operating characteristic (ROC) curves were drawn, and the area under the curve (AUC) was calculated to evaluate the efficacy of independent impact factors alone and combination for predicting differentiation degrees of advanced gastric adenocarcinoma. Results Significant differences of patients' age, gender, tumor thickness, tumor maximum diameter, Borrmann classification, clinical T (cT) stage, clinical N (cN) state, clinical TNM (cTNM) stage and splenic CT value on arterial phase were found between poorly differentiation group and moderate-well differentiation group (all P＜0.05). Multivariate logistic regression analysis revealed that patients' age, gender, Borrmann classification, cT stage, cTNM stage and splenic CT value in arterial phase were all independent impact factors of differentiation degrees of advanced gastric adenocarcinoma. AUC of above independent impact factors alone and combination for differentiation degrees of advanced gastric adenocarcinoma was 0.639, 0.577, 0.621, 0.690, 0.714, 0.606 and 0.861, respectively. Conclusion CT finding of spleen could be used to predict differentiation degrees of advanced gastric adenocarcinoma, and arterial phase splenic CT value was an useful indicator. Combination of clinical and CT findings might improve the predictive efficacy. |
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