Computed tomography features for differentiating malignant and benign focal liver lesions in dogs: A meta-analysis

被引:3
|
作者
Burti, S. [1 ]
Zotti, A. [1 ]
Contiero, B. [1 ]
Banzato, T. [1 ]
机构
[1] Univ Padua, Dept Anim Med Prod & Hlth, Viale Univ 16, I-35020 Legnaro, Italy
来源
VETERINARY JOURNAL | 2021年 / 278卷
关键词
Diagnostic imaging; Evidence-based medicine; Liver; Meta-analysis; CONTRAST-ENHANCED ULTRASONOGRAPHY; HEPATOCELLULAR-CARCINOMA; DIAGNOSIS; CT; ASSOCIATIONS; SYSTEM;
D O I
10.1016/j.tvjl.2021.105773
中图分类号
S85 [动物医学(兽医学)];
学科分类号
0906 ;
摘要
Computed tomography (CT) is often performed to complement ultrasound following detection of focal liver lesions (FLL). There is no consensus in the literature regarding the CT features that might be helpful in the distinction between benign and malignant FLL. The aim of this meta-analysis was to identify, based on the available literature, the qualitative and quantitative CT features able to distinguish between benign and malignant FLL. Studies on the diagnostic accuracy of CT in characterising FLL were searched in MEDLINE, Web of Science, and Scopus databases. Pooled sensitivity, pooled specificity, diagnostic odds ratio (DOR), receiver operator curve (ROC) area, were calculated for qualitative features. DOR were used to determine which qualitative features were most informative to detect malignancy; quantitative features were selected/identified based on standardised mean difference (SMD). Well-defined margins, presence of a capsule, abnormal lymph nodes, and heterogeneity in the arterial, portal and delayed phase were classified as informative qualitative CT features. The pooled sensitivity ranged from 0.630 (abnormal lymph nodes) to 0.786 (well-defined margins), while pooled specificity ranged from 0.643 (well-defined margins) to 0.816 (heterogeneous in delayed phase). Maximum dimensions, ellipsoid volume, attenuation of the liver in the pre-contrast phase, and attenuation of the liver in the arterial, portal, and delayed phase were found to be informative quantitative CT features. Larger maximum dimensions and volume (positive SMD), and lower attenuation values (negative SMD) were more associated with malignancy. This meta-analysis provides the evidence base for the interpreting CT imaging in the characterization of FLL.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] Computed tomographic features for differentiating benign from malignant liver lesions in dogs
    Leela-Arporn, Rommaneeya
    Ohta, Hiroshi
    Shimbo, Genya
    Hanazono, Kiwamu
    Osuga, Tatsuyuki
    Morishita, Keitaro
    Sasaki, Noboru
    Takiguchi, Mitsuyoshi
    JOURNAL OF VETERINARY MEDICAL SCIENCE, 2019, 81 (12): : 1697 - 1704
  • [2] Differentiating malignant from benign splenic lesions: a meta-analysis and pictorial review of imaging features
    Valizadeh, Parya
    Jannatdoust, Payam
    Tahamtan, Mohammadreza
    Dorcheh, Soroush Soleimani
    Khalaj, Fattaneh
    Ghorani, Hamed
    Yazdi, Niloofar Ayoobi
    Salahshour, Faeze
    ABDOMINAL RADIOLOGY, 2024, 49 (08) : 2833 - 2857
  • [3] Diagnostic Performance of Perfusion Computed Tomography for Differentiating Lung Cancer from Benign Lesions: A Meta-Analysis
    Huang, Cuiqing
    Liang, Jianye
    Lei, Xueping
    Xu, Xi
    Xiao, Zeyu
    Luo, Liangping
    MEDICAL SCIENCE MONITOR, 2019, 25 : 3485 - 3494
  • [4] Meta-analysis of contrast-enhanced ultrasound for the differentiation of benign and malignant focal liver lesions
    Friedrich-Rust, Mireen
    Klopffleisch, Tom
    Nierhoff, Julia
    Herrmann, Eva
    Schneider, Maximilian David
    Vermehren, Johannes
    Zeuzem, Stefan
    Bojunga, Joerg
    HEPATOLOGY, 2012, 56 : 834A - 835A
  • [5] Machine learning for malignant versus benign focal liver lesions on US and CEUS: a meta-analysis
    Carlos Alberto Campello
    Everton Bruno Castanha
    Marina Vilardo
    Pedro V. Staziaki
    Martina Zaguini Francisco
    Bahram Mohajer
    Guilherme Watte
    Fabio Ynoe Moraes
    Bruno Hochhegger
    Stephan Altmayer
    Abdominal Radiology, 2023, 48 : 3114 - 3126
  • [6] Machine learning for malignant versus benign focal liver lesions on US and CEUS: a meta-analysis
    Campello, Carlos Alberto
    Castanha, Everton Bruno
    Vilardo, Marina
    Staziaki, Pedro V.
    Francisco, Martina Zaguini
    Mohajer, Bahram
    Watte, Guilherme
    Moraes, Fabio Ynoe
    Hochhegger, Bruno
    Altmayer, Stephan
    ABDOMINAL RADIOLOGY, 2023, 48 (10) : 3114 - 3126
  • [7] Contrast-Enhanced Ultrasound for the differentiation of benign and malignant focal liver lesions: a meta-analysis
    Friedrich-Rust, Mireen
    Klopffleisch, Tom
    Nierhoff, Julia
    Herrmann, Eva
    Vermehren, Johannes
    Schneider, Maximilian D.
    Zeuzem, Stefan
    Bojunga, Joerg
    LIVER INTERNATIONAL, 2013, 33 (05) : 739 - 755
  • [8] Elastography for the differentiation of benign and malignant liver lesions: a meta-analysis
    Ma, Xuelei
    Zhan, Wenli
    Zhang, Binglan
    Wei, Benling
    Wu, Xin
    Zhou, Min
    Liu, Lei
    Li, Ping
    TUMOR BIOLOGY, 2014, 35 (05) : 4489 - 4497
  • [9] Diagnostic value of computed tomography scanning in differentiating malignant from benign solitary pulmonary nodules: a meta-analysis
    Zhang, Chuan-yu
    Yu, Hua-long
    Li, Xia
    Sun, Yong-ye
    TUMOR BIOLOGY, 2014, 35 (09) : 8551 - 8558
  • [10] Benign or,malignant? Differentiating breast lesions with computed tomography attenuation values on dynamic computed tomography mammography
    Miyake, K
    Hayakawa, K
    Nishino, M
    Nakamura, Y
    Morimoto, T
    Urata, Y
    Ueda, H
    Tanikake, M
    Kanao, S
    Shiozaki, T
    Yamamoto, A
    JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 2005, 29 (06) : 772 - 779