Eur J Radiol. 2026 Jan 3;195:112646. doi: 10.1016/j.ejrad.2025.112646. Online ahead of print.
ABSTRACT
BACKGROUND: Accurate preoperative evaluation of rectal cancer is essential for staging and treatment planning. Low-energy virtual monoenergetic imaging (VMI) enhances iodine contrast in dual-energy computed tomography (DECT) but increases image noise. Deep learning image reconstruction (DLIR) may mitigate this issue, but its effectiveness for 40 keV VMI in rectal cancer is underexplored.
OBJECTIVE: To evaluate the impact of DLIR on 40 keV VMI image quality and its diagnostic performance in assessing extramural venous invasion (EMVI) and T staging, compared to adaptive statistical iterative reconstruction (ASIR-V).
METHODS: Sixty-two patients with rectal adenocarcinoma underwent preoperative DECT using a low-iodine contrast protocol (1 mL/kg, 300 mg iodine/mL). Images were reconstructed at 70 keV ASIR-V 40 %, 40 keV ASIR-V 40 %, and 40 keV DLIR (medium [DLIR-M] and high [DLIR-H] settings). Objective and subjective image quality were compared using repeated-measures ANOVA or Friedman tests. Pathological findings were used as the reference standard for EMVI and T staging.
RESULTS: Both 40 keV ASIR-V 40 %, DLIR-M, and DLIR-H significantly improved image quality compared to 70 keV ASIR-V, with improvements in CT attenuation, image noise, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), edge rise slope (ERS), and the area under the noise power spectrum (NPS) curve (all P < 0.001). DLIR-M and DLIR-H outperformed 40 keV ASIR-V in terms of image noise and CNR. Subjective image quality scores were highest with DLIR-H. In diagnostic performance, DLIR-H achieved slightly better results for EMVI (AUC = 0.882) and T staging (AUC = 0.592) compared to ASIR-V.
CONCLUSION: DLIR, particularly DLIR-H, significantly improves 40 keV VMI image quality but offers mild improvement in diagnostic performance for EMVI and T staging. The combination of low-keV VMI and DLIR provides high-quality imaging with reduced iodine doses, making it a promising approach for optimized DECT protocols in rectal cancer.
PMID:41520415 | DOI:10.1016/j.ejrad.2025.112646
