Mamiya Hisashi, Tochigi Toru, Hayano Koichi, Ohira Gaku, Imanishi Shunsuke, Maruyama Tetsuro, Kurata Yoshihiro, Takahashi Yumiko, Hirata Atsushi, Matsubara Hisahiro
Department of Frontier Surgery Chiba University Graduate School of Medicine Chiba Japan.
Ann Gastroenterol Surg. 2024 Aug 26;9(1):145-152. doi: 10.1002/ags3.12852. eCollection 2025 Jan.
Recent studies have focused on evaluating the biomarker value of textural features in radiological images. Our study investigated whether or not a texture analysis of computed tomographic colonography (CTC) images could be a novel biomarker for colorectal cancer (CRC).
This retrospective study investigated 263 patients with CRC who underwent contrast-enhanced CTC (CE-CTC) before curative surgery between January 2014 and December 2017. Multiple texture analyses (fractal, histogram, and gray-level co-occurrence matrix [GLCM] texture analyses) were applied to CE-CTC (portal-venous phase), and fractal dimension (FD), skewness, kurtosis, entropy, and GLCM texture parameters, including GLCM-correlation, GLCM-autocorrelation, GLCM-entropy, and GLCM-homogeneity, of the tumor were calculated. These texture parameters were compared with pathological factors (tumor depth, lymph node metastasis, vascular invasion, and lymphatic invasion) and overall survival (OS).
Tumor depth was significantly associated with FD, kurtosis, entropy, GLCM-correlation, GLCM-autocorrelation, GLCM-entropy, and GLCM-homogeneity ( = 0.001, 0.001, 0.001, 0.001, 0.018, 0.008, and 0.001, respectively); lymph node metastasis was associated with GLCM-homogeneity ( = 0.004); lymphatic invasion was associated with GLCM-correlation and GLCM-homogeneity ( = 0.001 and 0.012, respectively); and venous invasion was associated with FD, entropy, GLCM-correlation, GLCM-autocorrelation, and GLCM-entropy of the tumor ( = 0.001, 0.033, 0.021, 0.046, respectively). In the Kaplan-Meier analysis, patients with high GLCM-correlation tumors or high GLCM-homogeneity tumors showed a significantly worse OS than others ( = 0.001 and 0.04, respectively). Multivariate analyses showed that the GLCM correlation was an independent prognostic factor for the OS ( = 0.021).
CE-CTC-derived texture parameters may be clinically useful biomarkers for managing CRC patients.
近期研究聚焦于评估放射影像中纹理特征的生物标志物价值。我们的研究调查了计算机断层结肠成像（CTC）图像的纹理分析能否成为结直肠癌（CRC）的一种新型生物标志物。
这项回顾性研究调查了2014年1月至2017年12月期间在根治性手术前接受对比增强CTC（CE-CTC）检查的263例CRC患者。对CE-CTC（门静脉期）进行多种纹理分析（分形、直方图和灰度共生矩阵[GLCM]纹理分析），计算肿瘤的分形维数（FD）、偏度、峰度、熵以及GLCM纹理参数，包括GLCM相关性、GLCM自相关性、GLCM熵和GLCM均匀性。将这些纹理参数与病理因素（肿瘤深度、淋巴结转移、血管侵犯和淋巴管侵犯）及总生存期（OS）进行比较。
肿瘤深度与FD、峰度、熵、GLCM相关性、GLCM自相关性、GLCM熵和GLCM均匀性显著相关（分别为P = .001、.001、.001、.001、.018、.008和.001）；淋巴结转移与GLCM均匀性相关（P = .004）；淋巴管侵犯与GLCM相关性和GLCM均匀性相关（分别为P = .001和.012）；静脉侵犯与肿瘤的FD、熵、GLCM相关性、GLCM自相关性和GLCM熵相关（分别为P = .001、.033、.021、.046）。在Kaplan-Meier分析中，GLCM相关性高的肿瘤患者或GLCM均匀性高的肿瘤患者的OS明显比其他患者差（分别为P = .001和.04）。多因素分析显示GLCM相关性是OS的独立预后因素（P = .021）。
CE-CTC衍生的纹理参数可能是管理CRC患者的临床有用生物标志物。
