Feasibility study of dark-field imaging for colon cancer liver metastases in mice based on a laboratory X-ray grating-based imaging system
Abstract
MethodsThree male BALB/c mice were injected via the spleen with CT26 colon cancer cells to establish liver metastasis models. The excised liver specimens were fixed in formalin and then scanned using the laboratory X-ray grating-based integrated imaging system to obtain digital radiography (DR) and computed tomography (CT) images. Four radiologists (two junior and two senior) independently evaluated the overall image quality, tumor edge sharpness, and artifacts of the three CT modes using a Likert scale, and the contrast-to-noise ratio (CNR) was calculated. Given that this was a preliminary exploratory experiment with a limited effective sample size, no intergroup hypothesis testing was performed; results are presented as descriptive statistics showing numerical trends.ResultsSample 1 could not undergo CT reconstruction because of deformation during imaging, and only DR images were obtained; Samples 2 and 3 both yielded DR and CT images. On absorption DR/CT images, liver metastases showed iso- or slightly high density relative to normal liver parenchyma, with unclear boundaries. On dark-field DR/CT images, liver metastases showed low signal, while normal liver parenchyma showed high signal, with clear contrast between them. On phase-contrast DR images, normal liver parenchyma showed high-low mixed signal, and liver metastases showed relatively uniform signal; On phase-contrast CT images, liver metastases were poorly visualized. The overall image quality score (3.63±0.52) and tumor margin clarity score (3.75±0.46) of dark-field CT showed a numerical trend higher than those of absorption CT (1.25±0.71; 1.63±0.52) and phase-contrast CT (0.38±0.74; 0.38±0.52), while the artifact score (1.13±0.35) showed a numerical trend lower than those of absorption CT (2.63±0.74) and phase-contrast CT (3.38±0.74). Inter-observer agreement was moderate to good (between the two junior radiologists, κ=0.709, 95% CI: 0.512-0.950; between the two senior radiologists, κ=0.750, 95% CI: 0.613-0.887; between radiologists of different seniority, κ=0.527, 95% CI: 0.400–0.655). The CNR of dark-field CT in Sample 2 (0.5128) was higher than that of absorption CT (0.2904) and phase-contrast CT (0.3241); the CNR of dark-field CT in Sample 3 (0.5260) was also higher than that of absorption CT (0.1980) and phase-contrast CT (0.0259).ConclusionThis study successfully achieved dark-field CT imaging in ex vivo models of colon cancer liver metastases, demonstrating for the first time that it can clearly distinguish liver metastasis from normal parenchyma. Although limited by sample size, dark-field images consistently showed numerical advantages in overall image quality, tumor edge sharpness, and artifact control, suggesting its potential to overcome the soft-tissue resolution limitations of conventional absorption imaging. This provides key experimental evidence for parameter optimization and effect size estimation in future in vivo imaging studies.Background and purposeConventional X-ray imaging based on absorption has limitations in identifying soft-tissue tumors in the liver. Dark-field and phase-contrast imaging, utilizing X-ray scattering and refraction, can provide additional information on tissue microstructure. This study, based on a laboratory X-ray grating-based integrated imaging system, preliminarily explored the image features and contrast differences among absorption, dark-field, and phase-contrast imaging modes in ex vivo mouse models of colon cancer liver metastases, aiming to assess the feasibility and potential application value of this technique.
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BibTeX
@article{ying2026feasibility,
title = {{Feasibility study of dark-field imaging for colon cancer liver metastases in mice based on a laboratory X-ray grating-based imaging system}},
author = {SHAN Ying and LU Jincheng and WU Honglin and HUANG Yan and PENG Qin and WANG Zhentian and ZHANG Xi},
journal = {Zhongguo aizheng zazhi},
year = {2026},
month = sep,
url = {http://www.china-oncology.com/zh/article/doi/10.19401/j.cnki.1007-3639.2026.09.007/},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Feasibility study of dark-field imaging for colon cancer liver metastases in mice based on a laboratory X-ray grating-based imaging system
AU - SHAN Ying
AU - LU Jincheng
AU - WU Honglin
AU - HUANG Yan
AU - PENG Qin
AU - WANG Zhentian
AU - ZHANG Xi
PY - 2026
DA - 2026/09/01
JO - Zhongguo aizheng zazhi
UR - http://www.china-oncology.com/zh/article/doi/10.19401/j.cnki.1007-3639.2026.09.007/
AB - MethodsThree male BALB/c mice were injected via the spleen with CT26 colon cancer cells to establish liver metastasis models. The excised liver specimens were fixed in formalin and then scanned using the laboratory X-ray grating-based integrated imaging system to obtain digital radiography (DR) and computed tomography (CT) images. Four radiologists (two junior and two senior) independently evaluated the overall image quality, tumor edge sharpness, and artifacts of the three CT modes using a Likert scale, and the contrast-to-noise ratio (CNR) was calculated. Given that this was a preliminary exploratory experiment with a limited effective sample size, no intergroup hypothesis testing was performed; results are presented as descriptive statistics showing numerical trends.ResultsSample 1 could not undergo CT reconstruction because of deformation during imaging, and only DR images were obtained; Samples 2 and 3 both yielded DR and CT images. On absorption DR/CT images, liver metastases showed iso- or slightly high density relative to normal liver parenchyma, with unclear boundaries. On dark-field DR/CT images, liver metastases showed low signal, while normal liver parenchyma showed high signal, with clear contrast between them. On phase-contrast DR images, normal liver parenchyma showed high-low mixed signal, and liver metastases showed relatively uniform signal; On phase-contrast CT images, liver metastases were poorly visualized. The overall image quality score (3.63±0.52) and tumor margin clarity score (3.75±0.46) of dark-field CT showed a numerical trend higher than those of absorption CT (1.25±0.71; 1.63±0.52) and phase-contrast CT (0.38±0.74; 0.38±0.52), while the artifact score (1.13±0.35) showed a numerical trend lower than those of absorption CT (2.63±0.74) and phase-contrast CT (3.38±0.74). Inter-observer agreement was moderate to good (between the two junior radiologists, κ=0.709, 95% CI: 0.512-0.950; between the two senior radiologists, κ=0.750, 95% CI: 0.613-0.887; between radiologists of different seniority, κ=0.527, 95% CI: 0.400–0.655). The CNR of dark-field CT in Sample 2 (0.5128) was higher than that of absorption CT (0.2904) and phase-contrast CT (0.3241); the CNR of dark-field CT in Sample 3 (0.5260) was also higher than that of absorption CT (0.1980) and phase-contrast CT (0.0259).ConclusionThis study successfully achieved dark-field CT imaging in ex vivo models of colon cancer liver metastases, demonstrating for the first time that it can clearly distinguish liver metastasis from normal parenchyma. Although limited by sample size, dark-field images consistently showed numerical advantages in overall image quality, tumor edge sharpness, and artifact control, suggesting its potential to overcome the soft-tissue resolution limitations of conventional absorption imaging. This provides key experimental evidence for parameter optimization and effect size estimation in future in vivo imaging studies.Background and purposeConventional X-ray imaging based on absorption has limitations in identifying soft-tissue tumors in the liver. Dark-field and phase-contrast imaging, utilizing X-ray scattering and refraction, can provide additional information on tissue microstructure. This study, based on a laboratory X-ray grating-based integrated imaging system, preliminarily explored the image features and contrast differences among absorption, dark-field, and phase-contrast imaging modes in ex vivo mouse models of colon cancer liver metastases, aiming to assess the feasibility and potential application value of this technique.
SN - 1007-3639
ER -