Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, No.321, Zhongshan Road, Nanjing, 210008, Jiangsu Province, China.
Department of Ultrasound, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, 210008, China.
Abdom Radiol (NY). 2022 Nov;47(11):3698-3711. doi: 10.1007/s00261-022-03635-w. Epub 2022 Aug 16.
This study aimed to analyze the clinicopathological and computed tomography (CT) findings of papillary gastric adenocarcinoma and to evaluate the feasibility of the multivariate model based on clinical information and CT findings for discriminating papillary gastric adenocarcinomas.
This retrospective study included 22 patients with papillary gastric adenocarcinoma and 88 patients with tubular adenocarcinoma. The demographic data, tumor markers, histopathological information, CT morphological characteristics, and CT value-related parameters of all patients were collected and analyzed. The multivariate model based on regression analysis was performed to improve the diagnostic efficacy for discriminating papillary gastric adenocarcinomas preoperatively. The diagnostic performance of the established nomogram was evaluated by receiver operating characteristic curve analysis.
The distribution of age, carcinoembryonic antigen, differentiation degree, neural invasion, human epidermal growth factor receptor 2 overexpression, P53 mutation status, 4 CT morphological characteristics, and 10 CT valued-related parameters differed significantly between papillary gastric adenocarcinoma and tubular adenocarcinoma groups (all p < 0.05). The established multivariate model based on clinical information and CT findings for discriminating papillary gastric adenocarcinomas preoperatively achieved the area under the curve of 0.920.
There existed differences in clinicopathological features and CT findings between papillary gastric adenocarcinomas and tubular adenocarcinomas. The combination of demographic data, tumor markers, CT morphological characteristics, and CT value-related parameters could discriminate papillary gastric adenocarcinomas preoperatively with satisfactory diagnostic efficiency.
本研究旨在分析胃乳头状腺癌的临床病理和计算机断层扫描(CT)表现,并评估基于临床信息和 CT 表现的多变量模型在鉴别胃乳头状腺癌方面的可行性。
本回顾性研究纳入了 22 例胃乳头状腺癌患者和 88 例管状腺癌患者。收集并分析了所有患者的人口统计学数据、肿瘤标志物、组织病理学信息、CT 形态学特征以及与 CT 值相关的参数。通过回归分析建立基于多变量模型,以提高术前鉴别胃乳头状腺癌的诊断效能。通过接受者操作特征曲线分析评估建立的列线图的诊断性能。
胃乳头状腺癌和管状腺癌组在年龄、癌胚抗原、分化程度、神经浸润、人表皮生长因子受体 2 过表达、P53 突变状态、4 种 CT 形态学特征和 10 种与 CT 值相关的参数分布方面差异有统计学意义(均 p<0.05)。基于临床信息和 CT 表现建立的多变量模型可用于术前鉴别胃乳头状腺癌,其曲线下面积为 0.920。
胃乳头状腺癌和管状腺癌在临床病理特征和 CT 表现方面存在差异。结合人口统计学数据、肿瘤标志物、CT 形态学特征和与 CT 值相关的参数可以提高术前鉴别胃乳头状腺癌的诊断效能。