Value of Advanced Virtual Monoenergetic Images in Evaluating Early Gastric Cancer

Objective: To evaluate the impact of advanced monoenergetic dual-energy computed tomography(DECT) datasets on detection rate and CNR of early gastric cancer(EGC). Method: Total of 29 cases of EGC who underwent two phases DECT scan were retrospectively enrolled in this study. CT findings were compared with surgical and histopathologic results. Advanced monoenergetic images(AMEIs) at 40 keV, 60 keV and 80 keV were calculated from the 100 and Sn 140 kV DE image data respectively using a monoenergetic software application(Dual energy Mono+, syngo IPIPE,Siemens). Differences in detection rates of EGC and CNR numbers were compared between different AMEIs and conventionally reconstructed polyenergetic images(PEIs) at 120 kVp. Results: AMEIs at 40 keV showed the highest detection rate(86.21%) for EGC which showed no significant difference with PEIs(<i<P</i< = 0.062). AMEIs at 40 keV revealed statistical higher CNR-AP and CNR-PP compared to other AMEIs and PEIs(all <i<P</i<〈 0.05). Conclusion: Virtual 40 keV image datasets of advanced image-based calculated monoenergetic significantly increase the CNR of early gastric cancer which was helpful to detect EGCs.