Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation
Purpose To evaluate the diagnostic accuracy of intravoxel incoherent motion (IVIM) model parameters for the diagnosis and staging of liver fibrosis and inflammation in patients with chronic hepatitis B. Methods Fifty-four patients with chronic hepatitis B and 42 healthy volunteers were included in t...
Ausführliche Beschreibung
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Tosun, Mesude [verfasserIn] |
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E-Artikel |
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Englisch |
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2019 |
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© Springer Science+Business Media, LLC, part of Springer Nature 2019 |
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| Übergeordnetes Werk: |
Enthalten in: Abdominal radiology - [Boston, MA] : Springer US, 2016, 45(2019), 1 vom: 08. Nov., Seite 15-23 |
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| Übergeordnetes Werk: |
volume:45 ; year:2019 ; number:1 ; day:08 ; month:11 ; pages:15-23 |
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| DOI / URN: |
10.1007/s00261-019-02300-z |
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SPR003213544 |
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| 245 | 1 | 0 | |a Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation |
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| 520 | |a Purpose To evaluate the diagnostic accuracy of intravoxel incoherent motion (IVIM) model parameters for the diagnosis and staging of liver fibrosis and inflammation in patients with chronic hepatitis B. Methods Fifty-four patients with chronic hepatitis B and 42 healthy volunteers were included in the study. All subjects were examined by 3 T magnetic resonance imaging. Diffusion-weighted imaging was undertaken with sixteen b values. IVIM parameters [D (true diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction)] were calculated. Histological evaluation of biopsy samples was considered the reference standard for the staging of liver fibrosis and inflammation. Differences in IVIM parameters between patient and control groups were analyzed. In the patient group, fibrosis stage and inflammation grade groups were analyzed with respect to IVIM parameters. The correlation was assessed between IVIM parameters and Ishak-modified scale of fibrosis stages and inflammation grades. Results The D was significantly lower in the patient group than the control group, p = 0.038 with Cohen’s d effect size of 0.452. D was significantly different between fibrosis stage levels. D values decreased in fibrosis stages from the minimal to moderate to marked fibrosis. Fibrosis grades significantly negatively correlated with D and D* values, p = 0.001, and 0.021, respectively. In addition, inflammation grades negatively correlated with f values, p = 0.047. Conclusion D values measured with IVIM imaging may help to diagnose liver fibrosis. IVIM imaging could be an alternative to liver biopsy for the staging of liver fibrosis. | ||
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| 650 | 4 | |a Intravoxel incoherent motion |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Fibrosis stage |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Inflammation grade |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Alparslan, Burcu |0 (orcid)0000-0002-5518-341X |4 aut | |
| 700 | 1 | |a Çetin Akhan, Sıla |4 aut | |
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10.1007/s00261-019-02300-z doi (DE-627)SPR003213544 (SPR)s00261-019-02300-z-e DE-627 ger DE-627 rakwb eng Tosun, Mesude verfasserin (orcid)0000-0001-8278-108X aut Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Purpose To evaluate the diagnostic accuracy of intravoxel incoherent motion (IVIM) model parameters for the diagnosis and staging of liver fibrosis and inflammation in patients with chronic hepatitis B. Methods Fifty-four patients with chronic hepatitis B and 42 healthy volunteers were included in the study. All subjects were examined by 3 T magnetic resonance imaging. Diffusion-weighted imaging was undertaken with sixteen b values. IVIM parameters [D (true diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction)] were calculated. Histological evaluation of biopsy samples was considered the reference standard for the staging of liver fibrosis and inflammation. Differences in IVIM parameters between patient and control groups were analyzed. In the patient group, fibrosis stage and inflammation grade groups were analyzed with respect to IVIM parameters. The correlation was assessed between IVIM parameters and Ishak-modified scale of fibrosis stages and inflammation grades. Results The D was significantly lower in the patient group than the control group, p = 0.038 with Cohen’s d effect size of 0.452. D was significantly different between fibrosis stage levels. D values decreased in fibrosis stages from the minimal to moderate to marked fibrosis. Fibrosis grades significantly negatively correlated with D and D* values, p = 0.001, and 0.021, respectively. In addition, inflammation grades negatively correlated with f values, p = 0.047. Conclusion D values measured with IVIM imaging may help to diagnose liver fibrosis. IVIM imaging could be an alternative to liver biopsy for the staging of liver fibrosis. Chronic hepatitis (dpeaa)DE-He213 Intravoxel incoherent motion (dpeaa)DE-He213 Fibrosis stage (dpeaa)DE-He213 Inflammation grade (dpeaa)DE-He213 Onal, Tugay (orcid)0000-0003-0705-5090 aut Uslu, Hande (orcid)0000-0003-1530-2573 aut Alparslan, Burcu (orcid)0000-0002-5518-341X aut Çetin Akhan, Sıla aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 45(2019), 1 vom: 08. Nov., Seite 15-23 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:45 year:2019 number:1 day:08 month:11 pages:15-23 https://dx.doi.org/10.1007/s00261-019-02300-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 45 2019 1 08 11 15-23 |
| spelling |
10.1007/s00261-019-02300-z doi (DE-627)SPR003213544 (SPR)s00261-019-02300-z-e DE-627 ger DE-627 rakwb eng Tosun, Mesude verfasserin (orcid)0000-0001-8278-108X aut Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Purpose To evaluate the diagnostic accuracy of intravoxel incoherent motion (IVIM) model parameters for the diagnosis and staging of liver fibrosis and inflammation in patients with chronic hepatitis B. Methods Fifty-four patients with chronic hepatitis B and 42 healthy volunteers were included in the study. All subjects were examined by 3 T magnetic resonance imaging. Diffusion-weighted imaging was undertaken with sixteen b values. IVIM parameters [D (true diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction)] were calculated. Histological evaluation of biopsy samples was considered the reference standard for the staging of liver fibrosis and inflammation. Differences in IVIM parameters between patient and control groups were analyzed. In the patient group, fibrosis stage and inflammation grade groups were analyzed with respect to IVIM parameters. The correlation was assessed between IVIM parameters and Ishak-modified scale of fibrosis stages and inflammation grades. Results The D was significantly lower in the patient group than the control group, p = 0.038 with Cohen’s d effect size of 0.452. D was significantly different between fibrosis stage levels. D values decreased in fibrosis stages from the minimal to moderate to marked fibrosis. Fibrosis grades significantly negatively correlated with D and D* values, p = 0.001, and 0.021, respectively. In addition, inflammation grades negatively correlated with f values, p = 0.047. Conclusion D values measured with IVIM imaging may help to diagnose liver fibrosis. IVIM imaging could be an alternative to liver biopsy for the staging of liver fibrosis. Chronic hepatitis (dpeaa)DE-He213 Intravoxel incoherent motion (dpeaa)DE-He213 Fibrosis stage (dpeaa)DE-He213 Inflammation grade (dpeaa)DE-He213 Onal, Tugay (orcid)0000-0003-0705-5090 aut Uslu, Hande (orcid)0000-0003-1530-2573 aut Alparslan, Burcu (orcid)0000-0002-5518-341X aut Çetin Akhan, Sıla aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 45(2019), 1 vom: 08. Nov., Seite 15-23 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:45 year:2019 number:1 day:08 month:11 pages:15-23 https://dx.doi.org/10.1007/s00261-019-02300-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 45 2019 1 08 11 15-23 |
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10.1007/s00261-019-02300-z doi (DE-627)SPR003213544 (SPR)s00261-019-02300-z-e DE-627 ger DE-627 rakwb eng Tosun, Mesude verfasserin (orcid)0000-0001-8278-108X aut Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Purpose To evaluate the diagnostic accuracy of intravoxel incoherent motion (IVIM) model parameters for the diagnosis and staging of liver fibrosis and inflammation in patients with chronic hepatitis B. Methods Fifty-four patients with chronic hepatitis B and 42 healthy volunteers were included in the study. All subjects were examined by 3 T magnetic resonance imaging. Diffusion-weighted imaging was undertaken with sixteen b values. IVIM parameters [D (true diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction)] were calculated. Histological evaluation of biopsy samples was considered the reference standard for the staging of liver fibrosis and inflammation. Differences in IVIM parameters between patient and control groups were analyzed. In the patient group, fibrosis stage and inflammation grade groups were analyzed with respect to IVIM parameters. The correlation was assessed between IVIM parameters and Ishak-modified scale of fibrosis stages and inflammation grades. Results The D was significantly lower in the patient group than the control group, p = 0.038 with Cohen’s d effect size of 0.452. D was significantly different between fibrosis stage levels. D values decreased in fibrosis stages from the minimal to moderate to marked fibrosis. Fibrosis grades significantly negatively correlated with D and D* values, p = 0.001, and 0.021, respectively. In addition, inflammation grades negatively correlated with f values, p = 0.047. Conclusion D values measured with IVIM imaging may help to diagnose liver fibrosis. IVIM imaging could be an alternative to liver biopsy for the staging of liver fibrosis. Chronic hepatitis (dpeaa)DE-He213 Intravoxel incoherent motion (dpeaa)DE-He213 Fibrosis stage (dpeaa)DE-He213 Inflammation grade (dpeaa)DE-He213 Onal, Tugay (orcid)0000-0003-0705-5090 aut Uslu, Hande (orcid)0000-0003-1530-2573 aut Alparslan, Burcu (orcid)0000-0002-5518-341X aut Çetin Akhan, Sıla aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 45(2019), 1 vom: 08. Nov., Seite 15-23 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:45 year:2019 number:1 day:08 month:11 pages:15-23 https://dx.doi.org/10.1007/s00261-019-02300-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 45 2019 1 08 11 15-23 |
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10.1007/s00261-019-02300-z doi (DE-627)SPR003213544 (SPR)s00261-019-02300-z-e DE-627 ger DE-627 rakwb eng Tosun, Mesude verfasserin (orcid)0000-0001-8278-108X aut Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Purpose To evaluate the diagnostic accuracy of intravoxel incoherent motion (IVIM) model parameters for the diagnosis and staging of liver fibrosis and inflammation in patients with chronic hepatitis B. Methods Fifty-four patients with chronic hepatitis B and 42 healthy volunteers were included in the study. All subjects were examined by 3 T magnetic resonance imaging. Diffusion-weighted imaging was undertaken with sixteen b values. IVIM parameters [D (true diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction)] were calculated. Histological evaluation of biopsy samples was considered the reference standard for the staging of liver fibrosis and inflammation. Differences in IVIM parameters between patient and control groups were analyzed. In the patient group, fibrosis stage and inflammation grade groups were analyzed with respect to IVIM parameters. The correlation was assessed between IVIM parameters and Ishak-modified scale of fibrosis stages and inflammation grades. Results The D was significantly lower in the patient group than the control group, p = 0.038 with Cohen’s d effect size of 0.452. D was significantly different between fibrosis stage levels. D values decreased in fibrosis stages from the minimal to moderate to marked fibrosis. Fibrosis grades significantly negatively correlated with D and D* values, p = 0.001, and 0.021, respectively. In addition, inflammation grades negatively correlated with f values, p = 0.047. Conclusion D values measured with IVIM imaging may help to diagnose liver fibrosis. IVIM imaging could be an alternative to liver biopsy for the staging of liver fibrosis. Chronic hepatitis (dpeaa)DE-He213 Intravoxel incoherent motion (dpeaa)DE-He213 Fibrosis stage (dpeaa)DE-He213 Inflammation grade (dpeaa)DE-He213 Onal, Tugay (orcid)0000-0003-0705-5090 aut Uslu, Hande (orcid)0000-0003-1530-2573 aut Alparslan, Burcu (orcid)0000-0002-5518-341X aut Çetin Akhan, Sıla aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 45(2019), 1 vom: 08. Nov., Seite 15-23 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:45 year:2019 number:1 day:08 month:11 pages:15-23 https://dx.doi.org/10.1007/s00261-019-02300-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 45 2019 1 08 11 15-23 |
| allfieldsSound |
10.1007/s00261-019-02300-z doi (DE-627)SPR003213544 (SPR)s00261-019-02300-z-e DE-627 ger DE-627 rakwb eng Tosun, Mesude verfasserin (orcid)0000-0001-8278-108X aut Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Purpose To evaluate the diagnostic accuracy of intravoxel incoherent motion (IVIM) model parameters for the diagnosis and staging of liver fibrosis and inflammation in patients with chronic hepatitis B. Methods Fifty-four patients with chronic hepatitis B and 42 healthy volunteers were included in the study. All subjects were examined by 3 T magnetic resonance imaging. Diffusion-weighted imaging was undertaken with sixteen b values. IVIM parameters [D (true diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction)] were calculated. Histological evaluation of biopsy samples was considered the reference standard for the staging of liver fibrosis and inflammation. Differences in IVIM parameters between patient and control groups were analyzed. In the patient group, fibrosis stage and inflammation grade groups were analyzed with respect to IVIM parameters. The correlation was assessed between IVIM parameters and Ishak-modified scale of fibrosis stages and inflammation grades. Results The D was significantly lower in the patient group than the control group, p = 0.038 with Cohen’s d effect size of 0.452. D was significantly different between fibrosis stage levels. D values decreased in fibrosis stages from the minimal to moderate to marked fibrosis. Fibrosis grades significantly negatively correlated with D and D* values, p = 0.001, and 0.021, respectively. In addition, inflammation grades negatively correlated with f values, p = 0.047. Conclusion D values measured with IVIM imaging may help to diagnose liver fibrosis. IVIM imaging could be an alternative to liver biopsy for the staging of liver fibrosis. Chronic hepatitis (dpeaa)DE-He213 Intravoxel incoherent motion (dpeaa)DE-He213 Fibrosis stage (dpeaa)DE-He213 Inflammation grade (dpeaa)DE-He213 Onal, Tugay (orcid)0000-0003-0705-5090 aut Uslu, Hande (orcid)0000-0003-1530-2573 aut Alparslan, Burcu (orcid)0000-0002-5518-341X aut Çetin Akhan, Sıla aut Enthalten in Abdominal radiology [Boston, MA] : Springer US, 2016 45(2019), 1 vom: 08. Nov., Seite 15-23 (DE-627)847023133 (DE-600)2845742-0 2366-0058 nnns volume:45 year:2019 number:1 day:08 month:11 pages:15-23 https://dx.doi.org/10.1007/s00261-019-02300-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 45 2019 1 08 11 15-23 |
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Enthalten in Abdominal radiology 45(2019), 1 vom: 08. Nov., Seite 15-23 volume:45 year:2019 number:1 day:08 month:11 pages:15-23 |
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Enthalten in Abdominal radiology 45(2019), 1 vom: 08. Nov., Seite 15-23 volume:45 year:2019 number:1 day:08 month:11 pages:15-23 |
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Chronic hepatitis Intravoxel incoherent motion Fibrosis stage Inflammation grade |
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Abdominal radiology |
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Tosun, Mesude @@aut@@ Onal, Tugay @@aut@@ Uslu, Hande @@aut@@ Alparslan, Burcu @@aut@@ Çetin Akhan, Sıla @@aut@@ |
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Methods Fifty-four patients with chronic hepatitis B and 42 healthy volunteers were included in the study. All subjects were examined by 3 T magnetic resonance imaging. Diffusion-weighted imaging was undertaken with sixteen b values. IVIM parameters [D (true diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction)] were calculated. Histological evaluation of biopsy samples was considered the reference standard for the staging of liver fibrosis and inflammation. Differences in IVIM parameters between patient and control groups were analyzed. In the patient group, fibrosis stage and inflammation grade groups were analyzed with respect to IVIM parameters. The correlation was assessed between IVIM parameters and Ishak-modified scale of fibrosis stages and inflammation grades. Results The D was significantly lower in the patient group than the control group, p = 0.038 with Cohen’s d effect size of 0.452. D was significantly different between fibrosis stage levels. D values decreased in fibrosis stages from the minimal to moderate to marked fibrosis. Fibrosis grades significantly negatively correlated with D and D* values, p = 0.001, and 0.021, respectively. In addition, inflammation grades negatively correlated with f values, p = 0.047. Conclusion D values measured with IVIM imaging may help to diagnose liver fibrosis. 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Tosun, Mesude |
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Tosun, Mesude misc Chronic hepatitis misc Intravoxel incoherent motion misc Fibrosis stage misc Inflammation grade Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation |
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Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation Chronic hepatitis (dpeaa)DE-He213 Intravoxel incoherent motion (dpeaa)DE-He213 Fibrosis stage (dpeaa)DE-He213 Inflammation grade (dpeaa)DE-He213 |
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Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation |
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Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation |
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intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation |
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Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation |
| abstract |
Purpose To evaluate the diagnostic accuracy of intravoxel incoherent motion (IVIM) model parameters for the diagnosis and staging of liver fibrosis and inflammation in patients with chronic hepatitis B. Methods Fifty-four patients with chronic hepatitis B and 42 healthy volunteers were included in the study. All subjects were examined by 3 T magnetic resonance imaging. Diffusion-weighted imaging was undertaken with sixteen b values. IVIM parameters [D (true diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction)] were calculated. Histological evaluation of biopsy samples was considered the reference standard for the staging of liver fibrosis and inflammation. Differences in IVIM parameters between patient and control groups were analyzed. In the patient group, fibrosis stage and inflammation grade groups were analyzed with respect to IVIM parameters. The correlation was assessed between IVIM parameters and Ishak-modified scale of fibrosis stages and inflammation grades. Results The D was significantly lower in the patient group than the control group, p = 0.038 with Cohen’s d effect size of 0.452. D was significantly different between fibrosis stage levels. D values decreased in fibrosis stages from the minimal to moderate to marked fibrosis. Fibrosis grades significantly negatively correlated with D and D* values, p = 0.001, and 0.021, respectively. In addition, inflammation grades negatively correlated with f values, p = 0.047. Conclusion D values measured with IVIM imaging may help to diagnose liver fibrosis. IVIM imaging could be an alternative to liver biopsy for the staging of liver fibrosis. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
| abstractGer |
Purpose To evaluate the diagnostic accuracy of intravoxel incoherent motion (IVIM) model parameters for the diagnosis and staging of liver fibrosis and inflammation in patients with chronic hepatitis B. Methods Fifty-four patients with chronic hepatitis B and 42 healthy volunteers were included in the study. All subjects were examined by 3 T magnetic resonance imaging. Diffusion-weighted imaging was undertaken with sixteen b values. IVIM parameters [D (true diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction)] were calculated. Histological evaluation of biopsy samples was considered the reference standard for the staging of liver fibrosis and inflammation. Differences in IVIM parameters between patient and control groups were analyzed. In the patient group, fibrosis stage and inflammation grade groups were analyzed with respect to IVIM parameters. The correlation was assessed between IVIM parameters and Ishak-modified scale of fibrosis stages and inflammation grades. Results The D was significantly lower in the patient group than the control group, p = 0.038 with Cohen’s d effect size of 0.452. D was significantly different between fibrosis stage levels. D values decreased in fibrosis stages from the minimal to moderate to marked fibrosis. Fibrosis grades significantly negatively correlated with D and D* values, p = 0.001, and 0.021, respectively. In addition, inflammation grades negatively correlated with f values, p = 0.047. Conclusion D values measured with IVIM imaging may help to diagnose liver fibrosis. IVIM imaging could be an alternative to liver biopsy for the staging of liver fibrosis. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
| abstract_unstemmed |
Purpose To evaluate the diagnostic accuracy of intravoxel incoherent motion (IVIM) model parameters for the diagnosis and staging of liver fibrosis and inflammation in patients with chronic hepatitis B. Methods Fifty-four patients with chronic hepatitis B and 42 healthy volunteers were included in the study. All subjects were examined by 3 T magnetic resonance imaging. Diffusion-weighted imaging was undertaken with sixteen b values. IVIM parameters [D (true diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction)] were calculated. Histological evaluation of biopsy samples was considered the reference standard for the staging of liver fibrosis and inflammation. Differences in IVIM parameters between patient and control groups were analyzed. In the patient group, fibrosis stage and inflammation grade groups were analyzed with respect to IVIM parameters. The correlation was assessed between IVIM parameters and Ishak-modified scale of fibrosis stages and inflammation grades. Results The D was significantly lower in the patient group than the control group, p = 0.038 with Cohen’s d effect size of 0.452. D was significantly different between fibrosis stage levels. D values decreased in fibrosis stages from the minimal to moderate to marked fibrosis. Fibrosis grades significantly negatively correlated with D and D* values, p = 0.001, and 0.021, respectively. In addition, inflammation grades negatively correlated with f values, p = 0.047. Conclusion D values measured with IVIM imaging may help to diagnose liver fibrosis. IVIM imaging could be an alternative to liver biopsy for the staging of liver fibrosis. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
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Intravoxel incoherent motion imaging for diagnosing and staging the liver fibrosis and inflammation |
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https://dx.doi.org/10.1007/s00261-019-02300-z |
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Onal, Tugay Uslu, Hande Alparslan, Burcu Çetin Akhan, Sıla |
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2024-08-28T05:54:10.874Z |
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| score |
7.1688757 |