ArticleCurrent medical imaging2026
The Quality Assessment of Virtual Unenhanced and Blending Images Derived from Dual-Energy CT for Detecting Colorectal Cancer
Article in Current medical imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
introductionThis study aimed to evaluate the image quality of virtual unenhanced and blending images from dual-energy CT for detecting colorectal cancer (CRC). MATERIALS AND
methodsA total of 72 patients with pathologically diagnosed CRC underwent abdominal dual-energy CT, following which virtual unenhanced, linear blending, and non-linear blending images were generated by post-processing reconstruction. Both subjective and objective evaluations were conducted on these images, with signal-to-noise (SNR) and contrast-to-noise ratio (CNR) calculations conducted for organs, such as the liver, pancreas, and spleen.
resultsVirtual unenhanced images of CRC, extraserosal fat of the tumor, liver, pancreas, spleen, kidney, and subcutaneous fat showed a lower signal intensity than both linear and non-linear blending images (P < 0.05), while the CNR of virtual unenhanced images was higher than linear and nonlinear blending images (P < 0.05). Except for CRC lesions, the SNR of other organs in virtual unenhanced images was higher than in linear and non-linear blending images (P < 0.05). There were no significant differences in subjective image scores and the number of conventional lesions between virtual unenhanced image, linear, and non-linear blending (P ≥ 0.05). The Kappa coefficients for evaluating extraserosal invasion were 0.722, 0.584, and 0.584 for virtual unenhanced, linear blending, and non-linear blending images, respectively, with corresponding accuracies of 86.1%, 79.2%, and 79.2%.
conclusionVirtual unenhanced images of patients with CRC can provide high-quality images for diagnostic evaluation, potentially replacing linear blending and non-linear blending images in plain scans.
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