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Whole‐Liver Apparent Diffusion Coefficient Histogram Analysis for the Diagnosis and Staging of Liver Fibrosis
Background Conventional diffusion‐weighted imaging is limited in the quantitative evaluation of liver fibrosis, and whole‐liver apparent diffusion coefficient (ADC) histogram analysis might contribute to the diagnosis and staging of liver fibrosis. Purpose To explore the value of whole‐liver ADC his...
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| Published in: | Journal of magnetic resonance imaging 2020-06, Vol.51 (6), p.1745-1754 |
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| container_title | Journal of magnetic resonance imaging |
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| creator | Zheng, You Xu, Yong‐Sheng Liu, Zhao Liu, Hai‐Feng Zhai, Ya‐Nan Mao, Xiao‐Rong Lei, Jun‐Qiang |
| description | Background
Conventional diffusion‐weighted imaging is limited in the quantitative evaluation of liver fibrosis, and whole‐liver apparent diffusion coefficient (ADC) histogram analysis might contribute to the diagnosis and staging of liver fibrosis.
Purpose
To explore the value of whole‐liver ADC histogram parameters in the diagnosis and staging of liver fibrosis.
Study Type
Retrospective.
Population
Twenty individuals with no liver disease and 86 patients with liver fibrosis, including 30 with chronic viral hepatitis, 29 with autoimmune hepatitis, and 27 with unexplained liver fibrosis patients.
Field Strength/Sequence
3.0T/T1‐weighted, T2‐weighted, and diffusion‐weighted images.
Assessment
A region of interest (ROI) was drawn in each slice of the diffusion‐weighted images. Whole‐liver histogram parameters were obtained with dedicated software by accumulating all ROIs. The effectiveness of the parameters in differentiating stage 1 or greater (≥F1), stage 2 or greater (≥F2), and stage 3 or greater (≥F3) liver fibrosis was assessed.
Statistical Tests
Mann–Whitney U‐test and receiver operating characteristic curve analysis.
Results
Kurtosis, entropy, skewness, mode, and 90th and 75th percentiles exhibited significant differences among the pathological fibrosis stages (P |
| doi_str_mv | 10.1002/jmri.26987 |
| format | article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2315088806</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2401718458</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3577-fd81a055fc9153e30c19535544ff3b358f06a9ef9922b29acb4ff089fc3fc5123</originalsourceid><addsrcrecordid>eNp9kctKxDAUhoMo3jc-gATciFDNpZkmy2F0vDAieMFlSTPJmKFtxqRVZucj-Iw-ialVFy5cnXDOdz44-QHYw-gYI0RO5pW3x2QgeLYCNjEjJCGMD1bjGzGaYI6yDbAVwhwhJETK1sEGxRkRHONN4B6fXKk_3t4n9kV7OFwspNd1A0-tMW2wroYjp42xynbdCxsaN_OygsNalstgAzTOw-ZJxwU5q13XkfUU3jVyZusZdAb24rEtfDfdAWtGlkHvftdt8DA-ux9dJJOb88vRcJIoyrIsMVOOJWLMKIEZ1RQpLBhlLE2NoQVl3KCBFNoIQUhBhFRFHCAujKJGMUzoNjjsvQvvnlsdmryyQemylLV2bcgJxQxxztEgogd_0LlrfbwvUinCGeYp45E66ikV7whem3zhbSX9Msco72LIuxjyrxgivP-tbItKT3_Rn3-PAO6BV1vq5T-q_Or69rKXfgJa6pOo</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2401718458</pqid></control><display><type>article</type><title>Whole‐Liver Apparent Diffusion Coefficient Histogram Analysis for the Diagnosis and Staging of Liver Fibrosis</title><source>Wiley-Blackwell Read & Publish Collection</source><creator>Zheng, You ; Xu, Yong‐Sheng ; Liu, Zhao ; Liu, Hai‐Feng ; Zhai, Ya‐Nan ; Mao, Xiao‐Rong ; Lei, Jun‐Qiang</creator><creatorcontrib>Zheng, You ; Xu, Yong‐Sheng ; Liu, Zhao ; Liu, Hai‐Feng ; Zhai, Ya‐Nan ; Mao, Xiao‐Rong ; Lei, Jun‐Qiang</creatorcontrib><description>Background
Conventional diffusion‐weighted imaging is limited in the quantitative evaluation of liver fibrosis, and whole‐liver apparent diffusion coefficient (ADC) histogram analysis might contribute to the diagnosis and staging of liver fibrosis.
Purpose
To explore the value of whole‐liver ADC histogram parameters in the diagnosis and staging of liver fibrosis.
Study Type
Retrospective.
Population
Twenty individuals with no liver disease and 86 patients with liver fibrosis, including 30 with chronic viral hepatitis, 29 with autoimmune hepatitis, and 27 with unexplained liver fibrosis patients.
Field Strength/Sequence
3.0T/T1‐weighted, T2‐weighted, and diffusion‐weighted images.
Assessment
A region of interest (ROI) was drawn in each slice of the diffusion‐weighted images. Whole‐liver histogram parameters were obtained with dedicated software by accumulating all ROIs. The effectiveness of the parameters in differentiating stage 1 or greater (≥F1), stage 2 or greater (≥F2), and stage 3 or greater (≥F3) liver fibrosis was assessed.
Statistical Tests
Mann–Whitney U‐test and receiver operating characteristic curve analysis.
Results
Kurtosis, entropy, skewness, mode, and 90th and 75th percentiles exhibited significant differences among the pathological fibrosis stages (P < 0.05). Kurtosis was found to be the most meaningful parameter in differentiating fibrosis stages of the viral hepatitis, autoimmune hepatitis, and unexplained liver fibrosis group (area under the curve) (AUC = 0.793, 0.771, 0.798, respectively). In the combined liver fibrosis group, kurtosis achieved the highest AUC (0.801; 95% confidence interval [CI]: 0.702–0.900; sensitivity: 0.750; specificity: 0.850; positive likelihood ratio: 4.953; negative likelihood ratio: 0.302; positive predictive value: 0.946; negative predictive value: 0.486), with a cutoff value of 1.817, in differentiating fibrosis stage ≥F1.
Data Conclusion
Kurtosis, entropy, skewness, mode, and 90th and 75th percentiles may contribute to the diagnosis and staging of liver fibrosis, especially kurtosis.
Level of Evidence: 4
Technical Efficacy: Stage 2
J. Magn. Reson. Imaging 2020;51:1745–1754.</description><identifier>ISSN: 1053-1807</identifier><identifier>EISSN: 1522-2586</identifier><identifier>DOI: 10.1002/jmri.26987</identifier><identifier>PMID: 31729811</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>apparent diffusion coefficient ; Bile ; Confidence intervals ; Diagnosis ; Diffusion ; Diffusion coefficient ; Diffusion Magnetic Resonance Imaging ; Entropy ; Fibrosis ; Field strength ; Hepatitis ; histogram ; Histograms ; Humans ; Image Interpretation, Computer-Assisted ; Image processing ; Kurtosis ; Likelihood ratio ; Liver ; Liver Cirrhosis - diagnostic imaging ; Liver diseases ; liver fibrosis ; Magnetic resonance imaging ; Medical imaging ; Parameters ; Population studies ; Retrospective Studies ; ROC Curve ; Sensitivity and Specificity ; Skewness ; Statistical analysis ; Statistical tests</subject><ispartof>Journal of magnetic resonance imaging, 2020-06, Vol.51 (6), p.1745-1754</ispartof><rights>2019 International Society for Magnetic Resonance in Medicine</rights><rights>2019 International Society for Magnetic Resonance in Medicine.</rights><rights>2020 International Society for Magnetic Resonance in Medicine</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3577-fd81a055fc9153e30c19535544ff3b358f06a9ef9922b29acb4ff089fc3fc5123</citedby><cites>FETCH-LOGICAL-c3577-fd81a055fc9153e30c19535544ff3b358f06a9ef9922b29acb4ff089fc3fc5123</cites><orcidid>0000-0002-3259-2253 ; 0000-0002-5348-6943</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31729811$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zheng, You</creatorcontrib><creatorcontrib>Xu, Yong‐Sheng</creatorcontrib><creatorcontrib>Liu, Zhao</creatorcontrib><creatorcontrib>Liu, Hai‐Feng</creatorcontrib><creatorcontrib>Zhai, Ya‐Nan</creatorcontrib><creatorcontrib>Mao, Xiao‐Rong</creatorcontrib><creatorcontrib>Lei, Jun‐Qiang</creatorcontrib><title>Whole‐Liver Apparent Diffusion Coefficient Histogram Analysis for the Diagnosis and Staging of Liver Fibrosis</title><title>Journal of magnetic resonance imaging</title><addtitle>J Magn Reson Imaging</addtitle><description>Background
Conventional diffusion‐weighted imaging is limited in the quantitative evaluation of liver fibrosis, and whole‐liver apparent diffusion coefficient (ADC) histogram analysis might contribute to the diagnosis and staging of liver fibrosis.
Purpose
To explore the value of whole‐liver ADC histogram parameters in the diagnosis and staging of liver fibrosis.
Study Type
Retrospective.
Population
Twenty individuals with no liver disease and 86 patients with liver fibrosis, including 30 with chronic viral hepatitis, 29 with autoimmune hepatitis, and 27 with unexplained liver fibrosis patients.
Field Strength/Sequence
3.0T/T1‐weighted, T2‐weighted, and diffusion‐weighted images.
Assessment
A region of interest (ROI) was drawn in each slice of the diffusion‐weighted images. Whole‐liver histogram parameters were obtained with dedicated software by accumulating all ROIs. The effectiveness of the parameters in differentiating stage 1 or greater (≥F1), stage 2 or greater (≥F2), and stage 3 or greater (≥F3) liver fibrosis was assessed.
Statistical Tests
Mann–Whitney U‐test and receiver operating characteristic curve analysis.
Results
Kurtosis, entropy, skewness, mode, and 90th and 75th percentiles exhibited significant differences among the pathological fibrosis stages (P < 0.05). Kurtosis was found to be the most meaningful parameter in differentiating fibrosis stages of the viral hepatitis, autoimmune hepatitis, and unexplained liver fibrosis group (area under the curve) (AUC = 0.793, 0.771, 0.798, respectively). In the combined liver fibrosis group, kurtosis achieved the highest AUC (0.801; 95% confidence interval [CI]: 0.702–0.900; sensitivity: 0.750; specificity: 0.850; positive likelihood ratio: 4.953; negative likelihood ratio: 0.302; positive predictive value: 0.946; negative predictive value: 0.486), with a cutoff value of 1.817, in differentiating fibrosis stage ≥F1.
Data Conclusion
Kurtosis, entropy, skewness, mode, and 90th and 75th percentiles may contribute to the diagnosis and staging of liver fibrosis, especially kurtosis.
Level of Evidence: 4
Technical Efficacy: Stage 2
J. Magn. Reson. Imaging 2020;51:1745–1754.</description><subject>apparent diffusion coefficient</subject><subject>Bile</subject><subject>Confidence intervals</subject><subject>Diagnosis</subject><subject>Diffusion</subject><subject>Diffusion coefficient</subject><subject>Diffusion Magnetic Resonance Imaging</subject><subject>Entropy</subject><subject>Fibrosis</subject><subject>Field strength</subject><subject>Hepatitis</subject><subject>histogram</subject><subject>Histograms</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted</subject><subject>Image processing</subject><subject>Kurtosis</subject><subject>Likelihood ratio</subject><subject>Liver</subject><subject>Liver Cirrhosis - diagnostic imaging</subject><subject>Liver diseases</subject><subject>liver fibrosis</subject><subject>Magnetic resonance imaging</subject><subject>Medical imaging</subject><subject>Parameters</subject><subject>Population studies</subject><subject>Retrospective Studies</subject><subject>ROC Curve</subject><subject>Sensitivity and Specificity</subject><subject>Skewness</subject><subject>Statistical analysis</subject><subject>Statistical tests</subject><issn>1053-1807</issn><issn>1522-2586</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kctKxDAUhoMo3jc-gATciFDNpZkmy2F0vDAieMFlSTPJmKFtxqRVZucj-Iw-ialVFy5cnXDOdz44-QHYw-gYI0RO5pW3x2QgeLYCNjEjJCGMD1bjGzGaYI6yDbAVwhwhJETK1sEGxRkRHONN4B6fXKk_3t4n9kV7OFwspNd1A0-tMW2wroYjp42xynbdCxsaN_OygsNalstgAzTOw-ZJxwU5q13XkfUU3jVyZusZdAb24rEtfDfdAWtGlkHvftdt8DA-ux9dJJOb88vRcJIoyrIsMVOOJWLMKIEZ1RQpLBhlLE2NoQVl3KCBFNoIQUhBhFRFHCAujKJGMUzoNjjsvQvvnlsdmryyQemylLV2bcgJxQxxztEgogd_0LlrfbwvUinCGeYp45E66ikV7whem3zhbSX9Msco72LIuxjyrxgivP-tbItKT3_Rn3-PAO6BV1vq5T-q_Or69rKXfgJa6pOo</recordid><startdate>202006</startdate><enddate>202006</enddate><creator>Zheng, You</creator><creator>Xu, Yong‐Sheng</creator><creator>Liu, Zhao</creator><creator>Liu, Hai‐Feng</creator><creator>Zhai, Ya‐Nan</creator><creator>Mao, Xiao‐Rong</creator><creator>Lei, Jun‐Qiang</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-3259-2253</orcidid><orcidid>https://orcid.org/0000-0002-5348-6943</orcidid></search><sort><creationdate>202006</creationdate><title>Whole‐Liver Apparent Diffusion Coefficient Histogram Analysis for the Diagnosis and Staging of Liver Fibrosis</title><author>Zheng, You ; Xu, Yong‐Sheng ; Liu, Zhao ; Liu, Hai‐Feng ; Zhai, Ya‐Nan ; Mao, Xiao‐Rong ; Lei, Jun‐Qiang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3577-fd81a055fc9153e30c19535544ff3b358f06a9ef9922b29acb4ff089fc3fc5123</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>apparent diffusion coefficient</topic><topic>Bile</topic><topic>Confidence intervals</topic><topic>Diagnosis</topic><topic>Diffusion</topic><topic>Diffusion coefficient</topic><topic>Diffusion Magnetic Resonance Imaging</topic><topic>Entropy</topic><topic>Fibrosis</topic><topic>Field strength</topic><topic>Hepatitis</topic><topic>histogram</topic><topic>Histograms</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted</topic><topic>Image processing</topic><topic>Kurtosis</topic><topic>Likelihood ratio</topic><topic>Liver</topic><topic>Liver Cirrhosis - diagnostic imaging</topic><topic>Liver diseases</topic><topic>liver fibrosis</topic><topic>Magnetic resonance imaging</topic><topic>Medical imaging</topic><topic>Parameters</topic><topic>Population studies</topic><topic>Retrospective Studies</topic><topic>ROC Curve</topic><topic>Sensitivity and Specificity</topic><topic>Skewness</topic><topic>Statistical analysis</topic><topic>Statistical tests</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zheng, You</creatorcontrib><creatorcontrib>Xu, Yong‐Sheng</creatorcontrib><creatorcontrib>Liu, Zhao</creatorcontrib><creatorcontrib>Liu, Hai‐Feng</creatorcontrib><creatorcontrib>Zhai, Ya‐Nan</creatorcontrib><creatorcontrib>Mao, Xiao‐Rong</creatorcontrib><creatorcontrib>Lei, Jun‐Qiang</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of magnetic resonance imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zheng, You</au><au>Xu, Yong‐Sheng</au><au>Liu, Zhao</au><au>Liu, Hai‐Feng</au><au>Zhai, Ya‐Nan</au><au>Mao, Xiao‐Rong</au><au>Lei, Jun‐Qiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Whole‐Liver Apparent Diffusion Coefficient Histogram Analysis for the Diagnosis and Staging of Liver Fibrosis</atitle><jtitle>Journal of magnetic resonance imaging</jtitle><addtitle>J Magn Reson Imaging</addtitle><date>2020-06</date><risdate>2020</risdate><volume>51</volume><issue>6</issue><spage>1745</spage><epage>1754</epage><pages>1745-1754</pages><issn>1053-1807</issn><eissn>1522-2586</eissn><abstract>Background
Conventional diffusion‐weighted imaging is limited in the quantitative evaluation of liver fibrosis, and whole‐liver apparent diffusion coefficient (ADC) histogram analysis might contribute to the diagnosis and staging of liver fibrosis.
Purpose
To explore the value of whole‐liver ADC histogram parameters in the diagnosis and staging of liver fibrosis.
Study Type
Retrospective.
Population
Twenty individuals with no liver disease and 86 patients with liver fibrosis, including 30 with chronic viral hepatitis, 29 with autoimmune hepatitis, and 27 with unexplained liver fibrosis patients.
Field Strength/Sequence
3.0T/T1‐weighted, T2‐weighted, and diffusion‐weighted images.
Assessment
A region of interest (ROI) was drawn in each slice of the diffusion‐weighted images. Whole‐liver histogram parameters were obtained with dedicated software by accumulating all ROIs. The effectiveness of the parameters in differentiating stage 1 or greater (≥F1), stage 2 or greater (≥F2), and stage 3 or greater (≥F3) liver fibrosis was assessed.
Statistical Tests
Mann–Whitney U‐test and receiver operating characteristic curve analysis.
Results
Kurtosis, entropy, skewness, mode, and 90th and 75th percentiles exhibited significant differences among the pathological fibrosis stages (P < 0.05). Kurtosis was found to be the most meaningful parameter in differentiating fibrosis stages of the viral hepatitis, autoimmune hepatitis, and unexplained liver fibrosis group (area under the curve) (AUC = 0.793, 0.771, 0.798, respectively). In the combined liver fibrosis group, kurtosis achieved the highest AUC (0.801; 95% confidence interval [CI]: 0.702–0.900; sensitivity: 0.750; specificity: 0.850; positive likelihood ratio: 4.953; negative likelihood ratio: 0.302; positive predictive value: 0.946; negative predictive value: 0.486), with a cutoff value of 1.817, in differentiating fibrosis stage ≥F1.
Data Conclusion
Kurtosis, entropy, skewness, mode, and 90th and 75th percentiles may contribute to the diagnosis and staging of liver fibrosis, especially kurtosis.
Level of Evidence: 4
Technical Efficacy: Stage 2
J. Magn. Reson. Imaging 2020;51:1745–1754.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><pmid>31729811</pmid><doi>10.1002/jmri.26987</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-3259-2253</orcidid><orcidid>https://orcid.org/0000-0002-5348-6943</orcidid></addata></record> |
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| source | Wiley-Blackwell Read & Publish Collection |
| subjects | apparent diffusion coefficient Bile Confidence intervals Diagnosis Diffusion Diffusion coefficient Diffusion Magnetic Resonance Imaging Entropy Fibrosis Field strength Hepatitis histogram Histograms Humans Image Interpretation, Computer-Assisted Image processing Kurtosis Likelihood ratio Liver Liver Cirrhosis - diagnostic imaging Liver diseases liver fibrosis Magnetic resonance imaging Medical imaging Parameters Population studies Retrospective Studies ROC Curve Sensitivity and Specificity Skewness Statistical analysis Statistical tests |
| title | Whole‐Liver Apparent Diffusion Coefficient Histogram Analysis for the Diagnosis and Staging of Liver Fibrosis |
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