Quantitative and Qualitative Comparison of Single-Source Dual-Energy Computed Tomography and 120-kVp Computed Tomography for the Assessment of Pancreatic Ductal Adenocarcinoma

被引:47
|
作者
Bhosale, Priya [1 ]
Le, Ott [1 ]
Balachandran, Aprana [1 ]
Fox, Patricia [2 ]
Paulson, Eric [1 ]
Tamm, Eric [1 ]
机构
[1] Univ Texas MD Anderson Canc Ctr, Dept Diagnost Radiol, Houston, TX 77030 USA
[2] Univ Texas MD Anderson Canc Ctr, Dept Biostat, Houston, TX 77030 USA
关键词
pancreatic ductal adenocarcinoma; 120; kVp; DECT; CNR and SNR; SPECTRAL MULTIDETECTOR CT; LOW TUBE VOLTAGE; CONTRAST ENHANCEMENT; SECONDARY SIGNS; IMAGE QUALITY; DIAGNOSIS; MDCT;
D O I
10.1097/RCT.0000000000000295
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose The aim of this study was to compare contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) between pancreatic-phase dual-energy computed tomography (DECT) and 120-kVp CT for pancreatic ductal adenocarcinoma (PDA). Materials and Methods Seventy-eight patients underwent multiphasic pancreatic imaging protocols for PDA (40, DECT; 38, 120-kVp CT [control]). Using pancreatic phase, CNR and SNR for PDA were obtained for DECT at monochromatic energies 50 through 80 keV, iodine material density images, and 120-kVp images. Using a 5-point scale (1, excellent; 5, markedly limited), images were qualitatively assessed by 2 radiologists in consensus for PDA detection, extension, vascular involvement, and noise. Wilcoxon signed rank and 2-sample tests were used to compare the qualitative measures, CNR and SNR, for DECT and 120-kVp images. Bonferroni correction was applied. Results Iodine material density image had significantly higher CNR and SNR for PDA than any monochromatic energy images (P < 0.0001) and the 120-kVp images. Qualitatively, 70-keV images were rated highest in the categories of tumor extension and vascular invasion and were similar to 120-kVp images. Conclusions Our results indicate that DECT improves PDA lesion conspicuity compared with routine 120-kVp CT, which may allow for better detection of PDA.
引用
收藏
页码:907 / 913
页数:7
相关论文
共 50 条
  • [12] Deep learning radiomics of dual-energy computed tomography for predicting lymph node metastases of pancreatic ductal adenocarcinoma
    Chao An
    Dongyang Li
    Sheng Li
    Wangzhong Li
    Tong Tong
    Lizhi Liu
    Dongping Jiang
    Linling Jiang
    Guangying Ruan
    Ning Hai
    Yan Fu
    Kun Wang
    Shuiqing Zhuo
    Jie Tian
    European Journal of Nuclear Medicine and Molecular Imaging, 2022, 49 : 1187 - 1199
  • [13] Deep learning radiomics of dual-energy computed tomography for predicting lymph node metastases of pancreatic ductal adenocarcinoma
    An, Chao
    Li, Dongyang
    Li, Sheng
    Li, Wangzhong
    Tong, Tong
    Liu, Lizhi
    Jiang, Dongping
    Jiang, Linling
    Ruan, Guangying
    Hai, Ning
    Fu, Yan
    Wang, Kun
    Zhuo, Shuiqing
    Tian, Jie
    EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2022, 49 (04) : 1187 - 1199
  • [14] Single source dual-energy computed tomography in the diagnosis of gout: Diagnostic reliability in comparison to digital radiography and conventional computed tomography of the feet
    Kiefer, Tobias
    Diekhoff, Torsten
    Hermann, Sandra
    Stroux, Andrea
    Mews, Jurgen
    Blobel, Jorg
    Hamm, Bernd
    Hermann, Kay-Geert A.
    EUROPEAN JOURNAL OF RADIOLOGY, 2016, 85 (10) : 1829 - 1834
  • [15] Dual-energy computed tomography in a multiparametric regression model for diagnosing lymph node metastases in pancreatic ductal adenocarcinoma
    Li, Sheng
    Jiang, Dongping
    Jiang, Linling
    Yan, Shumei
    Liu, Lizhi
    Ruan, Guangying
    Zhou, Xuhui
    Zhuo, Shuiqing
    CANCER IMAGING, 2024, 24 (01)
  • [16] Dual-energy computed tomography in a multiparametric regression model for diagnosing lymph node metastases in pancreatic ductal adenocarcinoma
    Sheng Li
    Dongping Jiang
    Linling Jiang
    Shumei Yan
    Lizhi Liu
    Guangying Ruan
    Xuhui Zhou
    Shuiqing Zhuo
    Cancer Imaging, 24
  • [17] Feasibility of Single-Source Dual-Energy Computed Tomography for Urinary Stone Characterization and Value of Iterative Reconstructions
    Morsbach, Fabian
    Wurnig, Moritz C.
    Mueller, Daniel
    Krauss, Bernhard
    Korporaal, Johannes Georg
    Alkadhi, Hatem
    INVESTIGATIVE RADIOLOGY, 2014, 49 (03) : 125 - 130
  • [18] Determination of Renal Stone Composition in Phantom and Patients Using Single-Source Dual-Energy Computed Tomography
    Kulkarni, Naveen M.
    Eisner, Brian H.
    Pinho, Daniella F.
    Joshi, Mukta C.
    Kambadakone, Avinash R.
    Sahani, Dushyant V.
    JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 2013, 37 (01) : 37 - 45
  • [19] Ex Vivo Renal Stone Characterization with Single-Source Dual-Energy Computed Tomography: A Multiparametric Approach
    Kriegshauser, J. Scott
    Silva, Alvin C.
    Paden, Robert G.
    He, Miao
    Humphreys, Mitchell R.
    Zell, Steven I.
    Fu, Yinlin
    Wu, Teresa
    ACADEMIC RADIOLOGY, 2016, 23 (08) : 969 - 976
  • [20] Indirect Computed Tomography Venography of the Lower Extremities Using Single-Source Dual-Energy Computed Tomography: Advantage of Low-Kiloelectron Volt Monochromatic Images
    Kulkarni, Naveen M.
    Sahani, Dushyant V.
    Desai, Gaurav S.
    Kalva, Sanjeeva P.
    JOURNAL OF VASCULAR AND INTERVENTIONAL RADIOLOGY, 2012, 23 (07) : 879 - 886