ISSN 1004-4140
CN 11-3017/P
LI Y G, LI J, XUE T Y, et al. Assessment of the Image Quality of Virtual Non-Contrast Dual-energy CT Liver Scans Using Both PSNR and SSIM Methods[J]. CT Theory and Applications, 2025, 34(1): 51-57. DOI: 10.15953/j.ctta.2024.151. (in Chinese).
Citation: LI Y G, LI J, XUE T Y, et al. Assessment of the Image Quality of Virtual Non-Contrast Dual-energy CT Liver Scans Using Both PSNR and SSIM Methods[J]. CT Theory and Applications, 2025, 34(1): 51-57. DOI: 10.15953/j.ctta.2024.151. (in Chinese).

Assessment of the Image Quality of Virtual Non-Contrast Dual-energy CT Liver Scans Using Both PSNR and SSIM Methods

More Information
  • Received Date: July 25, 2024
  • Revised Date: September 05, 2024
  • Accepted Date: September 11, 2024
  • Available Online: October 14, 2024
  • The purpose of this study was to investigate the feasibility of replacing true non-contrast (TNC) dual-energy computed tomography (DECT) images with virtual non-contrast (VNC) DECT images by comparing their quality on the basis of both the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). Methods: A prospective analysis was conducted on TNC and enhanced three-phase DECT images of the livers of 33 patients. Post-processing was used to obtain the arterial-phase (VNCa), venous-phase VNC (VNCv), and delayed-phase VNC (VNCd) images. Both the PSNR and SSIM methods were used to compare the overall and local TNC and three-phase VNC images. The CT numbers and noise values (standard deviation) of the liver and erector spinae muscle were measured, and the SNR and contrast-to-noise ratio (CNR) were calculated. The dose length product values of the TNC and enhanced three-phase VNC scans were recorded, and the objective evaluation indicators and radiation doses of the three-phase VNC and TNC images were compared. Bland-Altman scatter plots were drawn to analyze the consistency of the liver CT numbers, SNRs, and CNRs. Results: The overall comparison of the three-phase VNC and TNC images showed PSNR values of (18.01±1.06), (18.33±0.99), and (18.20±1.04) and SSIM values of (0.76±0.04), (0.77±0.03), and (0.78±0.04), with the differences being not statistically significant. The local comparison of these images showed PSNR values of (29.90±2.50), (30.97±2.34), and (30.61±2.76) and SSIM values of (0.75±0.04), (0.77±0.03), and (0.77±0.04), and the differences were also not statistically significant. The CT number of the liver in the three-phase VNC image was higher than that in the TNC image. The CNR of the three-phase VNC image and the SNR of the VNCv image were not statistically different from those of the TNC image, and the liver CT numbers, SNRs, and CNRs in the three-phase VNC and TNC images were highly consistent. Using the VNC+three-phase enhancement scheme can reduce the radiation dose by approximately 29.63% by removing the TNC part. Conclusion: The VNC DECT image of the liver is of good quality and can accurately reproduce the TNC image, meeting clinical diagnostic needs.

  • [1]
    杨志安, 闵小红, 徐俏宇, 等. 能谱CT虚拟平扫及水基图定量参数在诊断颅脑血管内治疗术后颅内出血的研究[J]. 临床放射学杂志, 2024, 43(6): 872-877. DOI: 10.13437/j.cnki.jcr.2024.06.004.

    YANG Z A, MIN X H, XU Q Y, et al. The value of quantitative parameters on virtual non-contrast and water-based images of brain spectral CT in early diagnosing intracranial hemorrhage after endovascular treatment[J]. Journal of Clinical Radiology, 2024, 43(6): 872-877. DOI: 10.13437/j.cnki.jcr.2024.06.004. (in Chinese).
    [2]
    尹娇, 魏茜, 彭超, 等. 双层探测器光谱CT虚拟平扫联合40keV虚拟单能量成像用于降低小肠CT造影辐射剂量[J]. 中国医学影像技术, 2023, 39(12): 1883-1887. DOI: 10.13929/j.issn.1003-3289.2023.12.032.

    YIN J, WEI Q, PENG C, et al. Virtual non-contrast images combined with 40 keV virtual monoenergetic images for reducing radiation dose of CT enterography based on dual-layer spectral detector CT[J]. Chinese Journal of Medical Imaging Technology, 2023, 39(12): 1883-1887. DOI: 10.13929/j.issn.1003-3289.2023.12.032. (in Chinese).
    [3]
    CHEN M, DING L, DENG S, et al. Differentiating the invasiveness of lung adenocarcinoma manifesting as ground glass nodules: Combination of dual-energy CT parameters and quantitative-semantic features[J]. Academic Radiology, 2024, 31(7): 2962-2972. DOI: 10.1016/j.acra.2024.02.011.
    [4]
    CATANIA R, JIA L, HAGHSHOMAR M, et al. Detection of moderate hepatic steatosis on contrast-enhanced dual-source dual-energy CT: Role and accuracy of virtual non-contrast CT[J]. European Journal of Radiology, 2024, 172: 111328. DOI: 10.1016/j.ejrad.2024.111328.
    [5]
    RAJIAH P, PARAKH A, KAY F, et al. Update on multienergy CT: Physics, principles, and applications[J]. Radiographics, 2020, 40(5): 1284-1308. DOI: 10.1148/rg.2020200038.
    [6]
    BORHANI A A, KULZER M, IRANPOUR N, et al. Comparison of true unenhanced and virtual unenhanced (VUE) attenuation values in abdominopelvic single-source rapid kilovoltage-switching spectral CT[J]. Abdominal Radiology (NY), 2017, 42(3): 710-717. DOI: 10.1007/s00261-016-0991-5.
    [7]
    孙嘉晨, 景梦园, 刘宏, 等. 能谱CT虚拟平扫技术在化疗相关性脂肪肝中的应用[J]. 中国医学影像学杂志, 2023, 31(5): 509-514. DOI: 10.3969/j.issn.1005-5185.2023.05.015.

    SUN J C, JING M Y, LIU H, et al. Application of energy spectrum CT virtual non-contrast technology in chemotherapy-related fatty liver[J]. Chinese Journal of Medical Imaging, 2023, 31(5): 509-514. DOI: 10.3969/j.issn.1005-5185.2023.05.015. (in Chinese).
    [8]
    SCHMIDT B, FLOHR T. Principles and applications of dual source CT[J]. Physica Medica, 2020, 79: 36-46. DOI: 10.1016/j.ejmp.2020.10.014.
    [9]
    KRAUSS B, GRANT K L, SCHMIDT B T, et al. The importance of spectral separation: An assessment of dual-energy spectral separation for quantitative ability and dose efficiency[J]. Investigative Radiology, 2015, 50(2): 114-118. DOI: 10.1097/RLI.0000000000000109.
    [10]
    LIANG H, DU S, YAN G, et al. Dual-energy CT of the pancreas: comparison between virtual non-contrast images and true non-contrast images in the detection of pancreatic lesion[J]. Abdominal Radiology, 2023, 48(8): 2596-2603. DOI: 10.1007/s00261-023-03914-0.
    [11]
    VOO K H B, BONG D B L. Quality assessment of stereoscopic image by 3D structural similarity[J]. Multimedia Tools and Applications, 2018, 77(2): 1-20. DOI: 10.1007/s11042-017-4361-2.
    [12]
    SHI B, LIU K. Regularization by multiple dual frames for compressed sensing magnetic resonance imaging with convergence analysis[J]. IEEE/CAA Journal of Automatica Sinica, 2023, 10(11): 2136-2153. DOI: 10.1109/JAS.2023.123543.
    [13]
    ZHAO B , LIU Z , DING S , et al. Motion artifact correction for MR images based on convolutional neural network[J]. Optoelectronics Letters, 2022, 18(1): 54-58. DOI: 10.1007/s11801-022-1084-z.
    [14]
    WANG Z, BOVIK A C, SHEIKH H R, et al. Image quality assessment: from error visibility to structural similarity[J]. IEEE Trans Image Process, 2004, 13(4): 600-612. DOI: 10.1109/TIP.2003.819861.
    [15]
    FAN M, CAO X, LÜ F, et al. Generative adversarial network-based synthesis of contrast-enhanced MR images from precontrast images for predicting histological characteristics in breast cancer[J]. Physics in Medicine & Biology, 2024, 69(9). DOI: 10.1088/1361-6560/ad3889.
    [16]
    EIDEX Z, WANG J, SAFARI M, et al. High-resolution 3T to 7T ADC map synthesis with a hybrid CNN-transformer model[J]. Medical Physics, 2024, 51(6): 4380-4388. DOI: 10.1002/mp.17079.
    [17]
    SHEIKH H R, SABIR M F, BOVIK A C. A statistical evaluation of recent full reference image quality assessment algorithms[J]. EEE Transactions on Image Processing, 2006, 15(11): 3440-3451. DOI: 10.1109/tip.2006.881959.
    [18]
    HAJI-MOMENIAN S, PARKINSON W, KHATI N, et al. Singleenergy non-contrast hepatic steatosis criteria applied to virtual non-contrast images: Is it still highly specific and positively predictive?[J]. Clinical Radiology, 2018, 73(6): 594. e7-594. e15. DOI: 10.1016/j.crad.2018.01.018.
    [19]
    de CECCO C N, DARNELL A, MACÍAS N, et al. Virtual unenhanced images of the abdomen with second-generation dual-source dual-energy computed tomography: Image quality and liver lesion detection[J]. Investigative Radiology, 2013, 48(1): 1-9. DOI: 10.1097/RLI.0b013e31826e7902.
    [20]
    ZHANG L J, PENG J, WU S Y, et al. Liver virtual non-enhanced CT with dual-source, dual-energy CT: A preliminary study[J]. European Radiology, 2010, 20(9): 2257-2264. DOI: 10.1007/s00330-010-1778-7.
    [21]
    ZHOU J, ZHOU Y, HU H, et al. Feasibility study of using virtual non-contrast images derived from dual-energy CT to replace true non-contrast images in patients diagnosed with papillary thyroid carcinoma[J]. Journal of X-ray Science and Technology, 2021, 29(4): 711-720. DOI: 10.3233/XST-210884.
    [22]
    顾芳燕, 朱晓梅, 聂芳, 等. 肝脏占位病变能谱CT成像中不同期相虚拟平扫替代真实平扫的效能及方案选择[J]. 中国医学影像学杂志, 2024, 32(8): 809-815. DOI: 10.3969/j.issn.1005-5185.2024.08.010.

    GU F Y, ZHU X Y, NIE F, et al. Feasibility and protocol selection of virtual non-contrast technology replacing true non-contrast scanning in tri-phase of liver lesions with spectral CT[J]. Chinese Journal of Medical Imaging, 2024, 32(8): 809-815. DOI: 10.3969/j.issn.1005-5185.2024.08.010. (in Chinese).
    [23]
    LACROIX M, MULÉ S, HERIN E, et al. Virtual unenhanced imaging of the liver derived from 160-mm rapid-switching dual-energy CT (rsDECT): Comparison of the accuracy of attenuation values and solid liver lesion conspicuity with native unenhanced images[J]. Chinese Journal of Medical Imaging, 2020, 133: 109387. DOI: 10.1016/j.ejrad.2020.109387.
    [24]
    林禹, 张潇潇, 张有彬, 等. 双层探测器光谱CT虚拟平扫应用于肝脏Ⅲ期增强扫描[J]. 中国医学影像技术, 2020, 36(S1): 29-33. DOI: 10.13929/j.issn.1003-3289.2020.z1.007.

    LIN Y, ZHANG X X, ZHANG Y B, et al. Application of dual-layer spectral detector CT virtual non-contrast images in hepatic triple-phase enhanced scan[J]. Chinese Journal of Medical Imaging Technology, 2020, 36(S1): 29-33. DOI: 10.13929/j.issn.1003-3289.2020.z1.007. (in Chinese).
  • Related Articles

    [1]YAN Xin, ZHAO Jianhua. Research Progress of Pericoronary Adipose Tissue Radiomics Based on Coronary Computed Tomography Angiography[J]. CT Theory and Applications, 2024, 33(4): 531-538. DOI: 10.15953/j.ctta.2023.179
    [2]HE Weihong, FANG Tingsong, FU Xi, LAO Meiling, XIAO Xiuyun. Risk Factors of Vulnerable Coronary Plaque Formation in Type 2 Diabetes[J]. CT Theory and Applications, 2023, 32(4): 523-529. DOI: 10.15953/j.ctta.2023.036
    [3]ZHU Najun, FANG Xinxin, YIN Yijun, ZHOU Shuitian. Risk Factors of Plaque Progression in Patients with Angina Pectoris and Their Relationships with Coronary CT Angiography[J]. CT Theory and Applications, 2023, 32(2): 217-222. DOI: 10.15953/j.ctta.2022.219
    [4]LIANG Yu, ZHANG Xiao-qin. Current State and Progress of Coronary Angiography in Multi-slice Spiral Computed Tomography Imaging Techniques[J]. CT Theory and Applications, 2016, 25(6): 725-735. DOI: 10.15953/j.1004-4140.2016.25.06.14
    [5]HAN Hong-cheng. The Application of Multi Slice Spiral CT Angiography in Coronary Heart Disease[J]. CT Theory and Applications, 2015, 24(6): 843-848. DOI: 10.15953/j.1004-4140.2015.24.06.10
    [6]YANG Chun-yu, SHEN Bi-xian, ZHAO Yue, HUANG Yin-ping, CHEN Sheng-ji, HUANG An-rong. Study on the Value of Dual Source CT Assessment of Correlation between Diabetes and Coronary Plaque[J]. CT Theory and Applications, 2014, 23(6): 913-921.
    [7]ZHAO Yue, SHEN Bi-xian, TAN Si-ping, YANG Chun-yu, CHEN Sheng-ji, HUANG An-rong. Study on the Value of Dual Source CT Assessment of Smoking and Coronary Plaque Correlation[J]. CT Theory and Applications, 2014, 23(4): 541-550.
    [8]TIAN Shu-ping, YANG Li, WANG Zhan-yu, WANG Shou-hai, WANG Zi-jun, ZHANG Yan-qun. The Application of “Magic Glass” Function in Coronary CTA[J]. CT Theory and Applications, 2012, 21(4): 721-726.
    [9]LIU Chao, ZHOU Xuan-ming, GONG Xiao-hong, CHEN Lun-gang. Clinical Significance of Evaluating Coronary Atherosclerotic Plaque with 64-Slice CT[J]. CT Theory and Applications, 2010, 19(2): 105-111.
    [10]XU Hui-min, HUO Jian-wei, LI Bao-ping, ZENG Qing-yu. Evaluation of Coronary Heart Disease using MDCT Coronary Angiography Combined with Ultrasound[J]. CT Theory and Applications, 2004, 13(4): 55-59.

Catalog

    Article views (116) PDF downloads (35) Cited by()
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return