Non-Invasive Assessment of Hepatic Fibrosis by Elastic Measurement of Liver Using Magnetic Resonance Tagging Images
To date, the measurement of the stiffness of liver requires a special vibrational tool that limits its application in many hospitals. In this study, we developed a novel method for automatically assessing the elasticity of the liver without any use of contrast agents or mechanical devices. By calcul...
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| Format: | Article |
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MDPI AG
2018-03-01
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| Series: | Applied Sciences |
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| Online Access: | http://www.mdpi.com/2076-3417/8/3/437 |
| _version_ | 1828850628914315264 |
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| author | Xuejun Zhang Xiangrong Zhou Takeshi Hara Hiroshi Fujita |
| author_facet | Xuejun Zhang Xiangrong Zhou Takeshi Hara Hiroshi Fujita |
| author_sort | Xuejun Zhang |
| collection | DOAJ |
| description | To date, the measurement of the stiffness of liver requires a special vibrational tool that limits its application in many hospitals. In this study, we developed a novel method for automatically assessing the elasticity of the liver without any use of contrast agents or mechanical devices. By calculating the non-rigid deformation of the liver from magnetic resonance (MR) tagging images, the stiffness was quantified as the displacement of grids on the liver image during a forced exhalation cycle. Our methods include two major processes: (1) quantification of the non-rigid deformation as the bending energy (BE) based on the thin-plate spline method in the spatial domain and (2) calculation of the difference in the power spectrum from the tagging images, by using fast Fourier transform in the frequency domain. By considering 34 cases (17 normal and 17 abnormal liver cases), a remarkable difference between the two groups was found by both methods. The elasticity of the liver was finally analyzed by combining the bending energy and power spectral features obtained through MR tagging images. The result showed that only one abnormal case was misclassified in our dataset, which implied our method for non-invasive assessment of liver fibrosis has the potential to reduce the traditional liver biopsy. |
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| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-12-12T23:15:52Z |
| publishDate | 2018-03-01 |
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| spelling | doaj.art-4f1a43b349524983850ba1c63f6d94972022-12-22T00:08:27ZengMDPI AGApplied Sciences2076-34172018-03-018343710.3390/app8030437app8030437Non-Invasive Assessment of Hepatic Fibrosis by Elastic Measurement of Liver Using Magnetic Resonance Tagging ImagesXuejun Zhang0Xiangrong Zhou1Takeshi Hara2Hiroshi Fujita3School of Computer and Electronic Information, Guangxi University, Nanning 530004, Guangxi, ChinaDepartment of Electrical, Electronic and Computer Engineering, Gifu University, Gifu 501-1193, JapanDepartment of Electrical, Electronic and Computer Engineering, Gifu University, Gifu 501-1193, JapanDepartment of Electrical, Electronic and Computer Engineering, Gifu University, Gifu 501-1193, JapanTo date, the measurement of the stiffness of liver requires a special vibrational tool that limits its application in many hospitals. In this study, we developed a novel method for automatically assessing the elasticity of the liver without any use of contrast agents or mechanical devices. By calculating the non-rigid deformation of the liver from magnetic resonance (MR) tagging images, the stiffness was quantified as the displacement of grids on the liver image during a forced exhalation cycle. Our methods include two major processes: (1) quantification of the non-rigid deformation as the bending energy (BE) based on the thin-plate spline method in the spatial domain and (2) calculation of the difference in the power spectrum from the tagging images, by using fast Fourier transform in the frequency domain. By considering 34 cases (17 normal and 17 abnormal liver cases), a remarkable difference between the two groups was found by both methods. The elasticity of the liver was finally analyzed by combining the bending energy and power spectral features obtained through MR tagging images. The result showed that only one abnormal case was misclassified in our dataset, which implied our method for non-invasive assessment of liver fibrosis has the potential to reduce the traditional liver biopsy.http://www.mdpi.com/2076-3417/8/3/437computer-aided diagnosis (CAD)magnetic resonance imagingcine-taggingliver fibrosiselastographybending energypower spectrum |
| spellingShingle | Xuejun Zhang Xiangrong Zhou Takeshi Hara Hiroshi Fujita Non-Invasive Assessment of Hepatic Fibrosis by Elastic Measurement of Liver Using Magnetic Resonance Tagging Images Applied Sciences computer-aided diagnosis (CAD) magnetic resonance imaging cine-tagging liver fibrosis elastography bending energy power spectrum |
| title | Non-Invasive Assessment of Hepatic Fibrosis by Elastic Measurement of Liver Using Magnetic Resonance Tagging Images |
| title_full | Non-Invasive Assessment of Hepatic Fibrosis by Elastic Measurement of Liver Using Magnetic Resonance Tagging Images |
| title_fullStr | Non-Invasive Assessment of Hepatic Fibrosis by Elastic Measurement of Liver Using Magnetic Resonance Tagging Images |
| title_full_unstemmed | Non-Invasive Assessment of Hepatic Fibrosis by Elastic Measurement of Liver Using Magnetic Resonance Tagging Images |
| title_short | Non-Invasive Assessment of Hepatic Fibrosis by Elastic Measurement of Liver Using Magnetic Resonance Tagging Images |
| title_sort | non invasive assessment of hepatic fibrosis by elastic measurement of liver using magnetic resonance tagging images |
| topic | computer-aided diagnosis (CAD) magnetic resonance imaging cine-tagging liver fibrosis elastography bending energy power spectrum |
| url | http://www.mdpi.com/2076-3417/8/3/437 |
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