| 马芳芳,贾晶,王志军,张莉萍,胡靖波,徐奋玲,田兆荣.能谱增强CT定量参数预测食管癌[STHX]p53基因突变[J].中国医学影像技术,2025,41(12):2001~2005 |
| 能谱增强CT定量参数预测食管癌[STHX]p53基因突变 |
| Quantitative parameters of spectral enhanced CT for predicting p53 gene mutation of esophageal cancer |
| 投稿时间：2025-03-04 修订日期：2025-12-07 |
| DOI：10.13929/j.issn.1003-3289.2025.12.014 |
| 中文关键词: 食管肿瘤 体层摄影术,X线计算机 基因 突变 |
| 英文关键词:esophageal neoplasms tomography, X-ray computed genes mutation |
| 基金项目:宁夏自然科学基金(2023AAC03548、2023AAC03684)。 |
|
| 摘要点击次数: 86 |
| 全文下载次数: 30 |
| 中文摘要: |
| 目的 探讨能谱增强CT定量参数预测食管癌 p53 基因突变的价值。方法 回顾性收集77例经病理证实的单发食管癌,包括47例 p53 基因突变型(突变型组)、30例 p53 基因野生型(野生型组);比较组间术前能谱增强CT定量参数,包括动、静脉期病灶碘浓度(IC)、有效原子序数(Eff-Z)、标准化IC(NIC)及能谱曲线斜率(λ)。基于组间差异有统计学意义的能谱增强CT定量参数预测食管癌 p53 基因突变;绘制受试者工作特征曲线,计算曲线下面积(AUC),评估其预测效能。结果 突变型组IC动、Eff-Z动、λ动,以及IC静、Eff-Z静、NIC静及λ静均大于野生型组(P均＜0.05),组间NIC动差异无统计学意义(P=0.794)。以IC动、Eff-Z动、λ动,以及IC静、Eff-Z静、NIC静及λ静预测食管癌 p53 基因突变的AUC分别为0.644、0.637、0.706、0.816、0.842、0.694及0.764。结论 能谱增强CT定量参数能有效预测食管癌 p53 基因突变。 |
| 英文摘要: |
| Objective To explore the value of quantitative parameters of spectral enhanced CT for predicting p53 gene mutation in esophageal cancer. Methods A total of 77 patients with solitary esophageal cancer confirmed by pathology were retrospectively enrolled, including 47 cases of p53 gene mutation type (mutation type group) and 30 cases of p53 gene wild type (wild type group).Quantitative parameters of spectral enhanced CT before surgery, including iodine concentration (IC), effective atomic number (Eff-Z), normalized IC (NIC) and spectral curve slope (λ) of lesions in arterial and venous phases were compared between groups. Spectrally enhanced CT quantitative parameters being statistically different between groups were used to predict p53 gene mutations in esophageal cancer, the receiver operating characteristic (ROC) curve was drawn, and the area under the curve (AUC) was calculated to evaluate the predictive performance of each parameter. Results ICa, Eff-Za, λa, as well as ICv, Eff-Zv, NICv and λv in mutant type group were all higher than those in wild type group (all P＜0.05), while NICa was not different between groups (P=0.794). AUC for predicting p53 gene mutations in esophageal cancer of ICa, Eff-Za, λa, ICv, Eff-Zv, NICv and λv was 0.644, 0.637, 0.706, 0.816, 0.842, 0.694 and 0.764, respectively. Conclusion Quantitative parameters of spectral enhanced CT could effectively predict p53 gene mutation in esophageal cancer. |
| 查看全文 查看/发表评论 下载PDF阅读器 |
|
|
|
