Purpose: To assess the potential of virtual monoenergetic images in assessing colorectal liver metastasis (CRLM) compared with conventional CT images.
Methods: This single-center, retrospective study included 173 consecutive patients (mean age, 65.5 ± 10.6 years; 106 men) who underwent dual-layer spectral CT (DLSCT) between November 2016 and April 2021. Portal venous phase images were reconstructed using hybrid iterative reconstruction (iDose) and virtual monoenergetic imaging at 50 keV. Four radiologists independently and randomly reviewed the de-identified iDose and 50 keV images. Lesion detection, CRLM conspicuity, and CRLM diagnosis were compared between these images using a generalized estimating equation analysis. The reference standards used were histopathology and follow-up imaging findings.
Results: The study included 797 focal liver lesions, including 463 CRLMs (median size, 18.1 mm [interquartile range, 10.9-37.7 mm]). Lesion detection was better with 50 keV images than with iDose images (45.0% [95% confidence interval [CI]: 39-50] vs 40.0% [95% CI: 34-46], P = 0.003). CRLM conspicuity was higher in the 50 keV images than in the iDose images (3.27 [95% CI: 3.09-3.46] vs 3.09 [95% CI: 2.90-3.28], P < 0.001). However, the specificity for diagnosing CRLM was lower with 50 keV images than with iDose images (94.5% [95% CI: 91.6-96.4] vs 96.0% [95% CI: 93.2-98.1], P = 0.022), whereas sensitivity did not differ significantly (77.6% [95% CI: 70.3-83.5] vs 76.9% [95% CI: 70.0-82.7], P = 0.736). Indeterminate lesions were more frequently noted in 50 keV images than in iDose images (13% [445/3188] vs 9% [313/3188], P = 0.005), and 56% (247/445) of the indeterminate lesions at 50 keV were not CRLMs.
Conclusion: The 50 keV images obtained from DLSCT were better than the iDose images in terms of CRLM conspicuity and lesion detection. However, 50 keV images did not improve CRLM diagnosis but slightly increased the reporting of indeterminate focal liver lesions associated with CRLMs.
Keywords: Colorectal liver metastasis; Dual-layer spectral computed tomography; Virtual monoenergetic imaging.
© 2024. The Author(s).