Decreased stage migration rate of early gastric cancer with a new reconstruction algorithm using dual-energy CT images: a preliminary study

利用双能量CT图像的新型重建算法降低早期胃癌分期迁移率:一项初步研究

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Abstract

OBJECTIVES: To evaluate the potential value of advanced monoenergetic images (AMEIs) on early gastric cancer (EGC) using dual-energy CT (DECT). METHODS: 31 EGC patients (19 men, 12 women; age range, 38-81 years; mean age, 57.19 years) were retrospectively enrolled in this study. Conventionally reconstructed polyenergetic images (PEIs) at 120 kV and virtual monoenergetic images (MEIs) and AMEIs at six different kiloelectron volt (keV) levels (from 40 to 90 keV) were evaluated from the 100 and Sn 140 kV dual energy image data, respectively. The visibility and stage migration of EGC for all three image data sets were evaluated and statistically analyzed. The objective and subjective image qualities were also evaluated. RESULTS: AMEIs at 40 keV showed the best visibility (80.7 %) and the lowest stage migration (35.5 %) for EGC. The stage migration for AMEIs at 40 keV was significantly lower than that for PEIs (p = 0.026). AMEIs at 40 keV had statistically higher CNR in the arterial and portal phases, gastric-specific diagnostic performance and visual sharpness compared with other AMEIs, MEIs and PEIs (all p < 0.05). CONCLUSIONS: AMEIs at 40 keV with MPR increase the CNR of EGC and thus potentially lower the stage migration of EGC. KEY POINTS: • AMEIs benefits from the recombination of low-keV images and medium energies. • AMEIs could receive better CNR results than MEIs. • AMEIs at 40 keV potentially lower the stage migration of EGC.

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