Texture analysis of CT colonography to develop a novel imaging biomarker for the management of colorectal cancer

Abstract Background 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). Methods Th...

Full description

Saved in:
Bibliographic Details
Main Authors: Hisashi Mamiya, Toru Tochigi, Koichi Hayano, Gaku Ohira, Shunsuke Imanishi, Tetsuro Maruyama, Yoshihiro Kurata, Yumiko Takahashi, Atsushi Hirata, Hisahiro Matsubara
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Annals of Gastroenterological Surgery
Subjects:
Online Access:https://doi.org/10.1002/ags3.12852
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850034864918626304
author Hisashi Mamiya
Toru Tochigi
Koichi Hayano
Gaku Ohira
Shunsuke Imanishi
Tetsuro Maruyama
Yoshihiro Kurata
Yumiko Takahashi
Atsushi Hirata
Hisahiro Matsubara
author_facet Hisashi Mamiya
Toru Tochigi
Koichi Hayano
Gaku Ohira
Shunsuke Imanishi
Tetsuro Maruyama
Yoshihiro Kurata
Yumiko Takahashi
Atsushi Hirata
Hisahiro Matsubara
author_sort Hisashi Mamiya
collection DOAJ
description Abstract Background 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). Methods 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). Results Tumor depth was significantly associated with FD, kurtosis, entropy, GLCM‐correlation, GLCM‐autocorrelation, GLCM‐entropy, and GLCM‐homogeneity (p = 0.001, 0.001, 0.001, 0.001, 0.018, 0.008, and 0.001, respectively); lymph node metastasis was associated with GLCM‐homogeneity (p = 0.004); lymphatic invasion was associated with GLCM‐correlation and GLCM‐homogeneity (p = 0.001 and 0.012, respectively); and venous invasion was associated with FD, entropy, GLCM‐correlation, GLCM‐autocorrelation, and GLCM‐entropy of the tumor (p = 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 (p = 0.001 and 0.04, respectively). Multivariate analyses showed that the GLCM correlation was an independent prognostic factor for the OS (p = 0.021). Conclusion CE‐CTC‐derived texture parameters may be clinically useful biomarkers for managing CRC patients.
format Article
id doaj-art-f492fda5f89a43c3886d8a121a2f6de9
institution DOAJ
issn 2475-0328
language English
publishDate 2025-01-01
publisher Wiley
record_format Article
series Annals of Gastroenterological Surgery
spelling doaj-art-f492fda5f89a43c3886d8a121a2f6de92025-08-20T02:57:40ZengWileyAnnals of Gastroenterological Surgery2475-03282025-01-019114515210.1002/ags3.12852Texture analysis of CT colonography to develop a novel imaging biomarker for the management of colorectal cancerHisashi Mamiya0Toru Tochigi1Koichi Hayano2Gaku Ohira3Shunsuke Imanishi4Tetsuro Maruyama5Yoshihiro Kurata6Yumiko Takahashi7Atsushi Hirata8Hisahiro Matsubara9Department of Frontier Surgery Chiba University Graduate School of Medicine Chiba JapanDepartment of Frontier Surgery Chiba University Graduate School of Medicine Chiba JapanDepartment of Frontier Surgery Chiba University Graduate School of Medicine Chiba JapanDepartment of Frontier Surgery Chiba University Graduate School of Medicine Chiba JapanDepartment of Frontier Surgery Chiba University Graduate School of Medicine Chiba JapanDepartment of Frontier Surgery Chiba University Graduate School of Medicine Chiba JapanDepartment of Frontier Surgery Chiba University Graduate School of Medicine Chiba JapanDepartment of Frontier Surgery Chiba University Graduate School of Medicine Chiba JapanDepartment of Frontier Surgery Chiba University Graduate School of Medicine Chiba JapanDepartment of Frontier Surgery Chiba University Graduate School of Medicine Chiba JapanAbstract Background 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). Methods 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). Results Tumor depth was significantly associated with FD, kurtosis, entropy, GLCM‐correlation, GLCM‐autocorrelation, GLCM‐entropy, and GLCM‐homogeneity (p = 0.001, 0.001, 0.001, 0.001, 0.018, 0.008, and 0.001, respectively); lymph node metastasis was associated with GLCM‐homogeneity (p = 0.004); lymphatic invasion was associated with GLCM‐correlation and GLCM‐homogeneity (p = 0.001 and 0.012, respectively); and venous invasion was associated with FD, entropy, GLCM‐correlation, GLCM‐autocorrelation, and GLCM‐entropy of the tumor (p = 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 (p = 0.001 and 0.04, respectively). Multivariate analyses showed that the GLCM correlation was an independent prognostic factor for the OS (p = 0.021). Conclusion CE‐CTC‐derived texture parameters may be clinically useful biomarkers for managing CRC patients.https://doi.org/10.1002/ags3.12852biomarkercolorectal cancerCT colonographygray level co‐occurrence matrixtexture analysis
spellingShingle Hisashi Mamiya
Toru Tochigi
Koichi Hayano
Gaku Ohira
Shunsuke Imanishi
Tetsuro Maruyama
Yoshihiro Kurata
Yumiko Takahashi
Atsushi Hirata
Hisahiro Matsubara
Texture analysis of CT colonography to develop a novel imaging biomarker for the management of colorectal cancer
Annals of Gastroenterological Surgery
biomarker
colorectal cancer
CT colonography
gray level co‐occurrence matrix
texture analysis
title Texture analysis of CT colonography to develop a novel imaging biomarker for the management of colorectal cancer
title_full Texture analysis of CT colonography to develop a novel imaging biomarker for the management of colorectal cancer
title_fullStr Texture analysis of CT colonography to develop a novel imaging biomarker for the management of colorectal cancer
title_full_unstemmed Texture analysis of CT colonography to develop a novel imaging biomarker for the management of colorectal cancer
title_short Texture analysis of CT colonography to develop a novel imaging biomarker for the management of colorectal cancer
title_sort texture analysis of ct colonography to develop a novel imaging biomarker for the management of colorectal cancer
topic biomarker
colorectal cancer
CT colonography
gray level co‐occurrence matrix
texture analysis
url https://doi.org/10.1002/ags3.12852
work_keys_str_mv AT hisashimamiya textureanalysisofctcolonographytodevelopanovelimagingbiomarkerforthemanagementofcolorectalcancer
AT torutochigi textureanalysisofctcolonographytodevelopanovelimagingbiomarkerforthemanagementofcolorectalcancer
AT koichihayano textureanalysisofctcolonographytodevelopanovelimagingbiomarkerforthemanagementofcolorectalcancer
AT gakuohira textureanalysisofctcolonographytodevelopanovelimagingbiomarkerforthemanagementofcolorectalcancer
AT shunsukeimanishi textureanalysisofctcolonographytodevelopanovelimagingbiomarkerforthemanagementofcolorectalcancer
AT tetsuromaruyama textureanalysisofctcolonographytodevelopanovelimagingbiomarkerforthemanagementofcolorectalcancer
AT yoshihirokurata textureanalysisofctcolonographytodevelopanovelimagingbiomarkerforthemanagementofcolorectalcancer
AT yumikotakahashi textureanalysisofctcolonographytodevelopanovelimagingbiomarkerforthemanagementofcolorectalcancer
AT atsushihirata textureanalysisofctcolonographytodevelopanovelimagingbiomarkerforthemanagementofcolorectalcancer
AT hisahiromatsubara textureanalysisofctcolonographytodevelopanovelimagingbiomarkerforthemanagementofcolorectalcancer