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


CONCLUSIONS
• 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.
Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197, Ruijin 2nd Road, Shanghai, 200025, China.|Department of Radiology, the First Affiliated Hospital of Soochow University, 188 Shizi Road, Suzhou, 215006, China.
Cen
C
Shi
Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197, Ruijin 2nd Road, Shanghai, 200025, China. huanzhangy@126.com.
Huan
H
Zhang
Siemens Medical System, Shanghai, 201318, China.
Jing
J
Yan
Department of biological statistics, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Baisong
B
Wang
Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197, Ruijin 2nd Road, Shanghai, 200025, China.
Lianjun
L
Du
Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197, Ruijin 2nd Road, Shanghai, 200025, China.
Zilai
Z
Pan
Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197, Ruijin 2nd Road, Shanghai, 200025, China.
Fuhua
F
Yan
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D055088:Early Detection of Cancer / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D013270:Stomach / Q000000981:diagnostic imaging; D013274:Stomach Neoplasms / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*
Advanced monoenergetic images; Dual-energy Computed Tomography; Early gastric cancer; Monoenergetic images; Polyenergetic images