Abstract: Objective: To evaluate image quality and the effect of metal artifact reduction with and without an iterative metal artifact reduction (iMAR) algorithm combined with virtual monoenergetic imaging (VMI) at different energy levels. Methods: Patients who had undergone internal fixation of the lumbar spine were prospectively enrolled. The VMI images were reconstructed both with and without the iMAR algorithm at energy levels of 70, 100, 120, 140, 160, and 190 keV. Axial images with an optimal visualization of the screw along its long axis (artifact layer) and those without obvious artifacts (background layer) were selected. Regions of interest (ROIs) were delineated in the vertebral body, spinal canal, erector spinae, and subcutaneous fat, and CT values and standard deviations (SD) were recorded. The difference in CT values (ΔCT) between the artifact and background layers, mean background SD, mean artifact SD, and artifact index (AI) were calculated. Subjective scoring was performed to assess the metal artifact reduction effect and its impact on diagnosis. The objective and subjective evaluation results were compared. Results: A total of 65 patients with a median age (interquartile range) of 65.00 (56.50, 72.00) years were included, including 32 males (47.76%) and 33 females (50.76%). The volume CT dose index was 16.55 (14.79, 19.14) mGy, and the dose–length product was 458.80 (410.05, 542.75) mGy·cm. For VMI images at the same energy level from 70 to 160 keV, the ΔCT (P<0.004), mean artifact SD (P < 0.001), and AI values (P<0.007) of all the anatomical sites in images reconstructed with the iMAR algorithm were significantly lower than those without the iMAR. Compared with images at 70 keV, the ΔCT, background and artifact SD, and AI values of all the anatomical structures in images at 100 to 190 keV were significantly lower (P<0.001). Subjective evaluations indicated that, at the same VMI energy level, the iMAR algorithm significantly reduced metal artifacts. VMI images acquired at higher energy levels reduced metal artifacts to a certain extent. The combination of the iMAR algorithm and VMI at higher energy levels achieved more effective artifact reduction, with the lowest artifacts observed at 120 to 140 keV. Conclusion: This study recommends VMI at 140 keV combined with the iMAR algorithm for CT image reconstruction in the postoperative evaluation of lumbar spine fixation, as it yields improved image quality and provides enhanced diagnostic information for clinical diagnosis.