Image fusion in dual energy computed tomography for detection of various anatomic structures – Effect on contrast enhancement, contrast-to-noise ratio, signal-to-noise ratio and image quality

Abstract

The purpose of this study was to evaluate image fusion in dual energy computed tomography for detecting various anatomic structures based on the effect on contrast enhancement, contrast-to-noise ratio, signal-to-noise ratio and image quality. Forty patients underwent a CT neck with dual energy mode (DECT under a Somatom Definition flash Dual Source CT scanner (Siemens, Forchheim, Germany)). Tube voltage: 80-kV and Sn140-kV; tube current: 110 and 290 mAs; collimation-2×32×0.6 mm. Raw data were reconstructed using a soft convolution kernel (D30f). Fused images were calculated using a spectrum of weighting factors (0.0, 0.3, 0.6 0.8 and 1.0) generating different ratios between the 80- and Sn140-kV images (e.g. factor 0.6 corresponds to 60% of their information from the 80-kV image, and 40% from the Sn140-kV image). CT values and SNRs measured in the ascending aorta, thyroid gland, fat, muscle, CSF, spinal cord, bone marrow and brain. In addition, CNR values calculated for aorta, thyroid, muscle and brain. Subjective image quality evaluated using a 5-point grading scale. Results compared using paired t-tests and nonparametric-paired Wilcoxon-Wilcox-test. Statistically significant increases in mean CT values noted in anatomic structures when increasing weighting factors used (all P≤0.001). For example, mean CT values derived from the contrast enhanced aorta were 149.2±12.8 Hounsfield Units (HU), 204.8±14.4 HU, 267.5±18.6 HU, 311.9±22.3 HU, 347.3±24.7 HU, when the weighting factors 0.0, 0.3, 0.6, 0.8 and 1.0 were used. The highest SNR and CNR values were found in materials when the weighting factor 0.6 used. The difference CNR between the weighting factors 0.6 and 0.3 was statistically significant in the contrast enhanced aorta and thyroid gland (P=0.012 and P=0.016, respectively). Visual image assessment for image quality showed the highest score for the data reconstructed using the weighting factor 0.6. Different fusion factors used to create images in DECT cause statistically significant differences in CT value, SNR, CNR and image quality. Best results obtained using the weighting factor 0.6 for all anatomic structures used in this study.