基于CT的纹理分析用于预测食道状癌的分化:一项观察性研究
Dawei Wang1, Zeyu Shang2, Rong Chen3
1Department of Thoracic Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, China.
Medicine
|September 23, 2024
概括
计算机断层扫描 (CT) 的纹理分析可以预测食道状细胞癌 (ESCC) 的分化. 纹理参数如标准偏差和不均性有效区分瘤等级,有助于进行非侵入性手术前评估.
科学领域:
- 放射学 放射学是一门学科.
- 在瘤学瘤学.
- 医疗成像医学成像
背景情况:
- 食道状细胞癌 (ESCC) 的分化影响预后和治疗.
- 准确的手术前评估瘤分化对于治疗规划至关重要.
- 目前评估ESCC差异化的方法可能具有侵入性.
研究的目的:
- 评估计算机断层扫描 (CT) 纹理分析的可行性和临床价值,以预测ESCC差异化.
- 为了确定CT图像的纹理参数是否可以区分差异较差和中等差异较好的ESCC.
- 评估非侵入性CT纹理分析在手术前瘤分级方面的潜力.
主要方法:
- 从48名ESCC患者的胸部对比度增强CT扫描的回顾性分析.
- 根据病理学,患者分为差异化较差 (n=24) 和中等差异化较好 (n=24) 的两种分层.
- 使用FireVoxel软件对静脉相CT图像进行纹理分析,以提取标准偏差 (SD),不均性和等参数.
- 相关性分析和ROC曲线分析,以评估纹理参数的诊断性能.
主要成果:
- 在SD,不均质性,和ESCC差异化之间观察到负相关性 (P < .05).
- 不同质性显示出最强的相关性 (r = -0.505,P < .001).
- SD,不均质和显著区分差异较低和中等差异较高的ESCC (P < .05).
- ROC分析表明,SD (AUC=0.793) 和异质性 (AUC=0.792) 是差异化的最佳预测因素.
结论:
- 静脉相图的CT纹理分析是预测ESCC差异化的可行方法.
- 质地参数,特别是SD和不均性,可以非侵入性地评估瘤分化.
- 这种方法为手术前评估提供了有价值的工具,有可能指导ESCC的治疗策略.
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