Dual-layer spectral detector computed tomography-derived virtual non-contrast images in breast cancer patients: a promising alternative to true non-contrast images.

Background: Dual-layer spectral detector computed tomography (SDCT) is extensively used in the diagnosis of various clinical diseases. Virtual non-contrast (VNC) images are a frequently utilized spectral parameter in clinical practice, the process of which simulates the creation of iodine-free images akin to traditional plain scans. This study explored the feasibility of using VNC images derived from SDCT to replace true non-contrast (TNC) images in breast cancer patients. Methods: The clinical and imaging data of 62 breast cancer patients who underwent dual-energy spectrum computed tomography (CT) scanning preoperatively from January 2021 to May 2022 were retrospectively analyzed. Mean Hounsfield units (HU), standard deviation (SD), signal-to-noise ratio (SNR), and contrast-noise-ratio (CNR) of tissues (including tumors, vessels, contralateral gland tissue) on TNC and VNC images were measured and compared by Kruskal-Wallis H test. A Bland-Altman scatter plot was constructed to evaluate the consistency of CT values between the image sets. The Friedman test was used to compare the subjective scores among the three images. Results: No statistically significant difference in CT values of the lesion tissue and the glands was found between TNC and VNC images (Z=4.259, P=0.119; Z=1.881, P=0.390). The Bland-Altman scatter plot demonstrated good consistency between the image sets. No statistically significant difference was found in the SD of the lesion tissue and the vessel among the three images (Z=4.080, P=0.130; Z=4.094, P=0.129); however, a statistically significant difference was observed in the SD of the contralateral gland tissue (Z=7.994, P=0.018). SNR and CNR were higher in VNC than they were in TNC images, with the CNR of venous-phase VNC (VNC-V) exhibiting the highest value (P<0.05). No significant differences in CT values, SD, SNR, and CNR of lesions and contralateral gland tissues were found between arterial-phase VNC (VNC-A) and VNC-V images (P>0.05), with CT values showing excellent consistency. The subjective scores of the three images were relatively consistent, with scores ≥4 indicating better image quality. When TNC was used as the standard, the overall detection rate of VNC for calcification was 87.5% (21/24). Conclusions: The image quality of VNC was significantly higher than that of TNC. The reconstruction for VNC based on arterial or venous phases did not affect the images. Therefore, VNC images may have the potential to replace TNC images in breast cancer.