| 黄豆豆,陈峻帆,韦鑫,罗银灯,刘欣杰.双能CT定量参数联合CT特征预测结直肠腺癌周围神经浸润[J].中国医学影像技术,2023,39(12):1827~1832 |
| 双能CT定量参数联合CT特征预测结直肠腺癌周围神经浸润 |
| Dual-energy CT quantitative parameters combined with CT features for predicting perineural invasion of colorectal adenocarcinoma |
| 投稿时间：2023-05-05 修订日期：2023-10-27 |
| DOI：10.13929/j.issn.1003-3289.2023.12.019 |
| 中文关键词: 结直肠肿瘤 能谱成像 周围神经浸润 |
| 英文关键词:colorectal neoplasms spectral imaging perineural invasion |
| 基金项目:重庆市科卫联合医学科研项目（2021MSXM220）。 |
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| 中文摘要: |
| 目的 观察双能CT定量参数联合CT特征预测结直肠腺癌周围神经浸润（PNI）的价值。方法 回顾性分析79例经手术病理确诊结直肠腺癌患者的术前全腹CT资料，分为PNI组（n=31）和无PNI组（n=48）。采用单因素分析2组间CT特征及双能CT定量参数，将具有统计学差异的变量纳入二元logistic回归分析构建联合模型，绘制受试者工作特征（ROC）曲线，计算曲线下面积（AUC），评价单一CT参数和联合模型预测结直肠腺癌PNI阳性的效能。结果 2组间CT所示原发病灶位置、病变肠壁最大厚度及有无肠周淋巴结转移、瘤周肠系膜条索影、肿瘤沉积差异均有统计学意义（P均<0.05），双能CT定量参数中动脉期能谱曲线斜率（λHU）、碘浓度（IC）、标准IC （NIC）、双能指数及静脉期NIC差异均有统计学意义（P均<0.05）。上述参数预测结直肠腺癌PNI阳性的AUC为0.615~0.698，联合模型的AUC为0.864。结论 双能CT定量参数联合CT特征能有效预测结直肠腺癌PNI状态。 |
| 英文摘要: |
| Objective To investigate the value of dual-energy CT quantitative parameters combined with CT features for predicting perineural invasion (PNI) of colorectal adenocarcinoma. Methods Preoperative whole-abdominal CT data of 79 patients with colorectal adenocarcinoma confirmed by postoperative pathology were retrospectively analyzed. The patients were divided into PNI group (n=31) or no PNI group (n=48). Univariate analysis was used to compare CT features and dual-energy CT quantitative parameters between groups, and the variables with significant differences were included in binary logistic regression analysis to construct a combined model. Receiver operating characteristic (ROC) curves were drawn and area under the curve (AUC) were calculated, the efficacy of single CT parameters and combined model for predicting PNI of colorectal adenocarcinoma were evaluated. Results There were significant differences of the location of the primary lesion, the maximum thickness of the diseased intestinal wall, the presence or absence of peritumoral lymph node metastases, peritumoral mesenteric streak shadow and tumor deposits shown on CT between groups (all P<0.05). Significant differences of the arterial phase slope of energy spectrum curve (λHU), iodine concentration (IC), normalized IC (NIC), dual energy index and the venous phase NIC of dual energy index were found between groups (all P<0.05). AUC of the above single parameters for predicting PNI of colorectal adenocarcinoma ranged from 0.615 to 0.698, while of the combined model was 0.864. Conclusion Dual-energy CT quantitative parameters combined with CT features could be used to effectively predict PNI of colorectal adenocarcinoma. |
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