双层探测器光谱CT多参数成像鉴别局限性结直肠壁增厚良恶性的临床价值
Clinical Value of Dual-Layer Spectral Detector CT Multi-Parameter Imaging in Differentiating Benign and Malignant Localized Colorectal Wall Thickening
DOI: 10.12677/acm.2024.14123250, PDF,   
作者: 左秀琦:扬州大学医学院,江苏 扬州;王礼同*:扬州大学附属医院影像科,江苏 扬州
关键词: 光谱CT结直肠壁增厚鉴别诊断Spectral CT Thickening of the Colorectal Wall Differential Diagnosis
摘要: 目的:探讨双层探测器光谱CT动、静脉期定量参数对鉴别局限性结直肠壁增厚良恶性的临床价值。方法:回顾性分析2024年1月至2024年7月在扬州大学附属医院接受光谱CT腹部增强扫描的“局限性结直肠壁增厚(厚度 > 5 mm,长度 < 5 mm)”患者,并在1个月内接受了肠镜检查的65例患者。根据肠镜检查结果分为恶性组(n = 42)及良性组(n = 23)。纳入分析的临床特征包括年龄、性别和症状。常规CT特征包括病灶位置及肠壁厚度。测量并计算光谱CT动脉期(AP)和静脉期(VP)的碘浓度(IC)、标准化IC (NIC)、有效原子序数(Zeff)、标准化Zeff (NZeff)、动脉增强分数(AEF)和40~100 keV光谱曲线斜率(λHU)。采用SPSS 27.0软件进行统计学分析。符合正态分布的计量资料采用独立样本t检验比较组间差异,不符合正态分布的计量资料采用Mann-Whitney U检验比较组间差异。采用χ2检验比较组间各计数资料差异。采用受试者操作特征(ROC)曲线计算各参数评估局限性肠壁增厚良恶性的效能。选择曲线下面积(AUC) > 0.75的参数采用二元logistic回归建立联合参数,并评价其效能。结果:恶性组年龄、AP和VP的IC、NIC、Zeff、NZeffλvp均显著高于良性组,差异有统计学意义(p均 < 0.05),良性组AEF高于恶性组,差异有统计学意义(p < 0.05)。其余参数差异无统计学意义(p均 > 0.05)。ROC曲线显示,VP中的IC、NIC、Zeff、NZeffλHU表现出较高的诊断性能,ROC曲线下面积(AUC)值分别为0.764、0.812、0.757、0.761和0.761。将AUC > 0.75的5个参数组成联合参数,其AUC值为0.867,灵敏度为88.10%,特异度为78.26%。结论:双层探测器光谱CT定量参数在区分良性和恶性局限性结直肠肠壁增厚方面有较好的应用价值,多参数联合可提高诊断效能。
Abstract: Objective: To investigate the clinical value of quantitative parameters of dual-layer spectral detector CT in differential diagnosis of benign and malignant localized colorectal wall thickening. Methods: A retrospective analysis of 65 patients with “localized colorectal wall thickening (thickness > 5 mm, length < 5 mm)” who received spectral CT enhanced abdominal scanning in the Affiliated Hospital of Yangzhou University from January 2024 to July 2024 and underwent colonoscopy within 1 month was performed. According to the results of colonoscopy, they were divided into malignant group (n = 42) and benign group (n = 23). Clinical characteristics included in the analysis included age, sex, and symptoms. Conventional CT features included lesion location and intestinal wall thickness. Iodine concentration (IC), standardized IC (NIC), effective atomic number (Zeff), standardized Zeff (NZeff), arterial enhancement fraction (AEF), and slope of 40 to 100 keV spectral curve (λHU) were measured and calculated for the arterial phase (AP) and venous phase (VP) of spectral CT. SPSS 27.0 software was used for statistical analysis. Independent sample t test was used to compare the differences between groups for measurement data conforming to normal distribution, and Mann-Whitney U test was used to compare the differences between groups for measurement data not conforming to normal distribution. χ2 test was used to compare the difference of counting data between groups. The receiver operating characteristic (ROC) curve was used to calculate the parameters to evaluate the efficacy of local intestinal wall thickening. Parameters with area under the curve (AUC) > 0.75 were selected to establish joint parameters by binary logistic regression, and their efficiency was evaluated. Results: The IC, NIC, Zeff, NZeff and λvp of AP and VP in malignant group were significantly higher than those in benign group (p < 0.05), and the AEF in benign group was higher than that in malignant group (p < 0.05). There was no significant difference in other parameters (all p > 0.05). ROC curve showed that IC, NIC, Zeff, NZeff and λHU in VP showed high diagnostic performance, with area under ROC curve (AUC) values of 0.764, 0.812, 0.757, 0.761 and 0.761, respectively. The 5 parameters with AUC > 0.75 were combined with the AUC value of 0.867, the sensitivity of 88.10%, and the specificity of 78.26%. Conclusion: The quantitative parameters of dual-layer spectral detector CT have good application value in distinguishing benign and malignant localized colorectal wall thickening, and the combination of multiple parameters can improve the diagnostic efficiency.
文章引用:左秀琦, 王礼同. 双层探测器光谱CT多参数成像鉴别局限性结直肠壁增厚良恶性的临床价值[J]. 临床医学进展, 2024, 14(12): 1530-1538. https://doi.org/10.12677/acm.2024.14123250

参考文献

[1] Daniel, F., Alsheikh, M., Ghieh, D., Hosni, M., Tayara, Z., Tamim, H., et al. (2020) Bowel Wall Thickening on Computed Tomography Scan: Inter-Observer Agreement and Correlation with Endoscopic Findings. Arab Journal of Gastroenterology, 21, 219-223. [Google Scholar] [CrossRef] [PubMed]
[2] 王雪莹, 刘庭玮, 徐森, 等. 肠壁增厚CT影像学评估及其临床意义研究进展[J]. 临床军医杂志, 2022, 50(12): 1223-1225, 1229.
[3] Ormeci Bas, B. (2020) Endoscopic Evaluation of Patients with Colonic Wall Thickening Detected on Computed Tomography. Acta Clinica Croatica, 59, 463-468. [Google Scholar] [CrossRef] [PubMed]
[4] Chandrapalan, S., Tahir, F., Sinha, R. and Arasaradnam, R. (2016) Colonic Thickening on Computed Tomography—Does It Correlate with Endoscopic Findings? A Protocol for Systematic Review. Systematic Reviews, 5, 213-216. [Google Scholar] [CrossRef] [PubMed]
[5] Franco, P.N., Spasiano, C.M., Maino, C., De Ponti, E., Ragusi, M., Giandola, T., et al. (2023) Principles and Applications of Dual-Layer Spectral CT in Gastrointestinal Imaging. Diagnostics, 13, 1740-1752. [Google Scholar] [CrossRef] [PubMed]
[6] 陈琰, 文自强, 马钰茹, 等. 双层探测器光谱CT诊断结直肠癌区域转移淋巴结的价值[J]. 中华放射学杂志, 2021, 55(12): 1253-1258.
[7] 刘思佳, 赵卫, 胡继红, 等. 光谱CT多参数成像术前预测结肠癌神经及脉管侵犯状态的价值[J]. 放射学实践, 2024, 39(1): 83-89.
[8] Jia, Z., Guo, L., Yuan, W., Dai, J., Lu, J., Li, Z., et al. (2024) Performance of Dual-Layer Spectrum CT Virtual Monoenergetic Images to Assess Early Rectal Adenocarcinoma T-Stage: Comparison with MR. Insights into Imaging, 15, Article No. 11. [Google Scholar] [CrossRef] [PubMed]
[9] Wang, Q., Shi, G., Qi, X., Fan, X. and Wang, L. (2014) Quantitative Analysis of the Dual-Energy CT Virtual Spectral Curve for Focal Liver Lesions Characterization. European Journal of Radiology, 83, 1759-1764. [Google Scholar] [CrossRef] [PubMed]
[10] Xu, X.Q., Zhou, Y., Su, G.Y., Tao, X., Ge, Y., Si, Y., et al. (2022) Iodine Maps from Dual-Energy CT to Predict Extrathyroidal Extension and Recurrence in Papillary Thyroid Cancer Based on a Radiomics Approach. American Journal of Neuroradiology, 43, 748-755. [Google Scholar] [CrossRef] [PubMed]
[11] Pelgrim, G.J., van Hamersvelt, R.W., Willemink, M.J., Schmidt, B.T., Flohr, T., Schilham, A., et al. (2017) Accuracy of Iodine Quantification Using Dual Energy CT in Latest Generation Dual Source and Dual Layer CT. European Radiology, 27, 3904-3912. [Google Scholar] [CrossRef] [PubMed]
[12] Zhang, R., Yao, Y., Gao, H. and Hu, X. (2024) Mechanisms of Angiogenesis in Tumour. Frontiers in Oncology, 14, Article 1359069. [Google Scholar] [CrossRef] [PubMed]
[13] 贾萍, 郑阳, 王晓明. 光谱CT碘浓度值相关参数诊断胃腺癌区域淋巴结转移的效能[J]. 中华放射学杂志, 2022, 56(12): 1326-1331.
[14] Li, R., Li, J., Wang, X., Liang, P. and Gao, J. (2018) Detection of Gastric Cancer and Its Histological Type Based on Iodine Concentration in Spectral CT. Cancer Imaging, 18, Article No. 42. [Google Scholar] [CrossRef] [PubMed]
[15] Feng, F., Jiang, F., Liu, Y., Sun, Q., Hong, R., Hu, C., et al. (2024) Radiomics Analysis of Dual-Layer Spectral-Detector CT-Derived Iodine Maps for Predicting Tumor Deposits in Colorectal Cancer. European Radiology, 35, 105-116. [Google Scholar] [CrossRef] [PubMed]
[16] Wang, G., Fang, Y., Wang, Z. and Jin, Z. (2021) Quantitative Assessment of Radiologically Indeterminate Local Colonic Wall Thickening on Iodine Density Images Using Dual-Layer Spectral Detector Ct. Academic Radiology, 28, 1368-1374. [Google Scholar] [CrossRef] [PubMed]
[17] 严福华, 金征宇. 开辟双能量CT临床应用的新时代[J]. 中华放射学杂志, 2020, 54(6): 505-507.
[18] Rassouli, N., Etesami, M., Dhanantwari, A. and Rajiah, P. (2017) Detector-Based Spectral CT with a Novel Dual-Layer Technology: Principles and Applications. Insights into Imaging, 8, 589-598. [Google Scholar] [CrossRef] [PubMed]