Literature DB >> 24505682

Contrast-independent liver-fat quantification from spectral CT exams.

Paulo R S Mendonça1, Peter Lamb2, Andras Kriston3, Kosuke Sasaki4, Masayuki Kudo4, Dushyant V Sahani5.   

Abstract

The diagnosis and treatment of fatty liver disease requires accurate quantification of the amount of fat in the liver. Image-based methods for quantification of liver fat are of increasing interest due to the high sampling error and invasiveness associated with liver biopsy, which despite these difficulties remains the gold standard. Current computed tomography (CT) methods for liver-fat quantification are only semi-quantitative and infer the concentration of liver fat heuristically. Furthermore, these techniques are only applicable to images acquired without the use of contrast agent, even though contrast-enhanced CT imaging is more prevalent in clinical practice. In this paper, we introduce a method that allows for direct quantification of liver fat for both contrast-free and contrast- enhanced CT images. Phantom and patient data are used for validation, and we conclude that our algorithm allows for highly accurate and repeatable quantification of liver fat for spectral CT.

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Year:  2013        PMID: 24505682     DOI: 10.1007/978-3-642-40811-3_41

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  7 in total

1.  Accuracy of Liver Fat Quantification With Advanced CT, MRI, and Ultrasound Techniques: Prospective Comparison With MR Spectroscopy.

Authors:  Harald Kramer; Perry J Pickhardt; Mark A Kliewer; Diego Hernando; Guang-Hong Chen; James A Zagzebski; Scott B Reeder
Journal:  AJR Am J Roentgenol       Date:  2016-10-11       Impact factor: 3.959

2.  Noninvasive estimation of local speed of sound by pulse-echo ultrasound in a rat model of nonalcoholic fatty liver.

Authors:  Arsenii V Telichko; Rehman Ali; Thurston Brevett; Huaijun Wang; Jose G Vilches-Moure; Sukumar U Kumar; Ramasamy Paulmurugan; Jeremy J Dahl
Journal:  Phys Med Biol       Date:  2022-01-17       Impact factor: 3.609

3.  S2FLNet: Hepatic steatosis detection network with body shape.

Authors:  Qiyue Wang; Wu Xue; Xiaoke Zhang; Fang Jin; James Hahn
Journal:  Comput Biol Med       Date:  2021-11-30       Impact factor: 6.698

4.  Association of non-alcoholic fatty liver disease with renal stone disease detected on computed tomography.

Authors:  In Chul Nam
Journal:  Eur J Radiol Open       Date:  2016-08-02

Review 5.  Current status of imaging in nonalcoholic fatty liver disease.

Authors:  Qian Li; Manish Dhyani; Joseph R Grajo; Claude Sirlin; Anthony E Samir
Journal:  World J Hepatol       Date:  2018-08-27

6.  Quantification of Fat Concentration and Vascular Response in Brown and White Adipose Tissue of Rats by Spectral CT Imaging.

Authors:  Xin Gui Peng; Zhen Zhao; Di Chang; Yingying Bai; Qiuzhen Xu; Shenghong Ju
Journal:  Korean J Radiol       Date:  2020-02       Impact factor: 3.500

Review 7.  Quantitative ultrasound approaches for diagnosis and monitoring hepatic steatosis in nonalcoholic fatty liver disease.

Authors:  Amir M Pirmoazen; Aman Khurana; Ahmed El Kaffas; Aya Kamaya
Journal:  Theranostics       Date:  2020-03-04       Impact factor: 11.556

  7 in total

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