Objective
The aim of the study was to compare the accuracy of quantification of iodine and Hounsfield unit (HU) values on virtual monochromatic imaging (VMI) using dual-layer computed tomography (DLCT) and fast kilovolt-switching computed tomography (FKSCT).
Materials and Methods
This study was performed in 2 phantoms (large and small) using 16 rods representing different materials (iodine, calcium, blood, and adipose tissue) with different dimensions and concentrations. The absolute percentage errors (absolute ratio of measurement error to true iodine concentration) for iodine concentration and HU value on VMI at 50, 70, and 100 keV were compared between DLCT and FKSCT. The Mann–Whitney U test was used to assess statistical significance.
Results
Overall, the absolute percentage errors for iodine concentration and HU value on VMI were smaller for DLCT than for FKSCT.
Conclusions
Overall, the accuracy of iodine and HU values was higher for DLCT than for FKSCT.
Objective: Determination of the optimal energy level of virtual monochromatic image (VMI) for brain metastases in contrast-enhanced dual-energy CT (DECT) for radiosurgery and assessment of the subjective and objective image quality of VMI at the optimal energy level. Methods: 20 patients (total of 42 metastases) underwent contrast-enhanced DECT. Spectral image analysis of VMIs at energy levels ranging from 40 to 140 keV in 1 keV increments was performed to determine the optimal VMI (VMIopt) as the one corresponding to the highest contrast-to-noise ratio (CNR) between brain parenchyma and the metastases. The objective and subjective values of VMIopt were compared to those of the VMI with 120 kVp equivalent, defined as reference VMI (VMIref, 77 keV). The objective measurement parameters included mean HU value and SD of tumor and brain parenchyma, absolute lesion contrast (LC), and CNR. The subjective measurements included five-point scale assessment of “overall image quality” and “tumor delineation” by three radiation oncologists. Results: The VMI at 63 keV was defined as VMIopt. The LC and CNR of VMIopt were significantly (p < 0.01) higher than those of VMIref (LC: 37.4 HU vs 24.7 HU; CNR: 1.1 vs 0.8, respectively). Subjective analysis rated VMIopt significantly (p < 0.01) superior to VMIref with respect to the overall image quality (3.2 vs 2.9, respectively) and tumor delineation (3.5 vs 2.9, respectively). Conclusion: The VMI at 63 keV derived from contrast-enhanced DECT yielded the highest CNR and improved the objective and subjective image quality for radiosurgery, compared to VMIref. Advances in knowledge: This paper investigated for the first time the optimal energy level of VMI in DECT for brain metastases. The findings will lead to improvement in tumor visibility with optimal VMI and consequently supplement accuracy delineation of brain metastases.
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