Original Article
Application value of single source dual-energy CT technique in improving pancreatic image quality
Yin Wei, Wang Tiegong, Jia Zijun, Zhao Binghui, Hu Xinxin, Shao Chengwei, Bian Yun, Wang Minjie
Published 2021-12-20
Cite as Chin J Pancreatol, 2021, 21(6): 433-440. DOI: 10.3760/cma.j.cn115667-20211016-00186
Abstract
ObjectiveTo explore the application value of single source dual energy CT (DECT) scanning technique in improving the image quality of the pancreas.
MethodsImaging data of 21 patients with normal pancreas and 36 patients with pancreas related diseases in the First Affiliated Hospital of Naval Medical University from July 2021 to August 2021 were collected. All the patients first underwent multi-slice CT (MDCT) scan with no-contrast, and then dynamic enhanced MDCT scan. And the DECT scan was used in the delay period. Virtual single energy images (VMI, 40~100keV) of normal pancreas and mixed energy images of pancreatic lesions (PI, 80 and 140kVp) were obtained. The regions of interest (ROI) of fat on abdominal wall, normal pancreas and abdominal aorta were delineated, the CT values and standard deviation (SD) of each ROI were measured and recorded, and the pancreatic signal-to-noise ratio (SNR) and contrast-to-noise ratio (SNR) of each energy image were calculated. The objective index and subjective score of VMI(40-100keV) and PI (80kVp and 140kVp) with iodine (water) base map and VMI best CNR were compared between groups. The correlation between VMI(40-100keV) and PI(80, 140kVp) with iodine (water) base map and VMIbest CNR was analyzed by univariate regression.
ResultsIn VMI(40-100keV) of normal pancreas, the highest SNR value was VMI best CNR and iodine (water) base map, and the highest CNR values were VMI 60keV and iodine (water) base map. There were significant differences on SNR and CNR values between different energy VMI and iodine (water) base map (P<0.05). Among the four images of PI 80kVp, PI 140kVp, VMI best CNR and iodine (water) base map for pancreatic lesions, the SNR and CNR values of iodine (water) base map were the highest. The SNR and CNR values of VMI best CNR were higher than those of PI 80kVp, and the differences were statistically significant (P<0.05). The lesion significance and edge sharpness score of iodine (water) base map was the highest, which was better than other groups; the lesion significance and edge sharpness score of VMI best CNR was better than PI 140kVp, and the differences were statistically significant (P<0.05). The results of univariate regression analysis showed that the SNR values of PI 80kVp, PI 140kVp and VMI best CNR for pancreatic lesions were positively correlated with those of the iodine (water) base map (P<0.05), the CNR values of PI 140kVp and VMI best CNR images were positively correlated with the iodine (water) base map (P<0.05), and the SNR and CNR values of PI 140kVp were positively correlated with VMI best CNR (P<0.05).
ConclusionsVMI with different energy and iodine (water) base maps can be obtained by single source DECT enhanced scanning of pancreas related diseases. The VMI best CNR was the best among all VMIs, while the SNR and CNR values of iodine (water) base maps were the highest in all images. The VMI best CNR and iodine (water) base maps can improve the image quality of pancreas related diseases.
Key words:
Pancreas; Dual-energy scanned; Energy spectrum image; Tomography, X-ray computed
Contributor Information
Yin Wei
Department of Radiology, First Affiliated Hospital of Naval Medical University, Shanghai 200433, China
Wang Tiegong
Department of Radiology, First Affiliated Hospital of Naval Medical University, Shanghai 200433, China
Jia Zijun
Department of Radiology, First Affiliated Hospital of Naval Medical University, Shanghai 200433, China
Zhao Binghui
Department of Radiology, First Affiliated Hospital of Naval Medical University, Shanghai 200433, China
Hu Xinxin
Department of Radiology, First Affiliated Hospital of Naval Medical University, Shanghai 200433, China
Shao Chengwei
Department of Radiology, First Affiliated Hospital of Naval Medical University, Shanghai 200433, China
Bian Yun
Department of Radiology, First Affiliated Hospital of Naval Medical University, Shanghai 200433, China
Wang Minjie
Department of Radiology, First Affiliated Hospital of Naval Medical University, Shanghai 200433, China