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Comparison of the values of MRI diffusion kurtosis imaging and diffusion tensor imaging in cerebral astrocytoma grading and their association with aquaporin-4
Objective: To compare the value of MRI diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) in grading cerebral astrocytomas and to analyze the correlation of respective parameters with aquaporin-4 (AQP4) expression. Methods: Sixty patients with cerebral astrocytoma, including low-gra...
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Published in: | Neurology India 2016-03, Vol.64 (2), p.265-272 |
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description | Objective: To compare the value of MRI diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) in grading cerebral astrocytomas and to analyze the correlation of respective parameters with aquaporin-4 (AQP4) expression.
Methods: Sixty patients with cerebral astrocytoma, including low-grade astrocytomas (LGA, n = 25) and high-grade astrocytomas (HGA, n = 35), were studied. The values of DKI parameters (mean kurtosis [MK], radial kurtosis [Kr], and axial kurtosis [Ka]) and DTI parameters (fractional anisotropy, mean diffusivity [MD]) corrected by contralateral normal-appearing white matter in the solid parts of the tumors and peritumoral edema were compared. Receiver operating characteristic curves were used to identify the best parameters. Spearman correlation analysis was conducted to assess the correlation of AQP4 expression with each parameter value.
Results: MK, Ka, and Krvalues were significantly higher whereas MD values were significantly lower in the solid parts of HGA, as compared to those of LGA. MK value in peritumoral edematous tissue was significantly higher in HGA as compared to that in LGA. Ka (0.889) had the largest area under the curve (AUC), followed by MK (0.840), Kr (0.750), and MD (0.764). The AUC of Kaand MK was significantly higher than that of MD. Optimal thresholds for MK, Ka, Kr, and MD for differentiating the two groups were 0.490, 0.525, 0.432, and 1.493, respectively. The AQP4 expression in the solid parts of the tumors was significantly higher in HGAs. MK, Kr, Kavalues positively correlated with the AQP4 expression, whereas MD showed a slight negative correlation with AQP4.
Conclusion: Use of DKI improved grading of cerebral astrocytomas when compared with DTI. DKI parameters appeared to reflect the level of AQP4 expression in astrocytomas. |
doi_str_mv | 10.4103/0028-3886.177621 |
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Methods: Sixty patients with cerebral astrocytoma, including low-grade astrocytomas (LGA, n = 25) and high-grade astrocytomas (HGA, n = 35), were studied. The values of DKI parameters (mean kurtosis [MK], radial kurtosis [Kr], and axial kurtosis [Ka]) and DTI parameters (fractional anisotropy, mean diffusivity [MD]) corrected by contralateral normal-appearing white matter in the solid parts of the tumors and peritumoral edema were compared. Receiver operating characteristic curves were used to identify the best parameters. Spearman correlation analysis was conducted to assess the correlation of AQP4 expression with each parameter value.
Results: MK, Ka, and Krvalues were significantly higher whereas MD values were significantly lower in the solid parts of HGA, as compared to those of LGA. MK value in peritumoral edematous tissue was significantly higher in HGA as compared to that in LGA. Ka (0.889) had the largest area under the curve (AUC), followed by MK (0.840), Kr (0.750), and MD (0.764). The AUC of Kaand MK was significantly higher than that of MD. Optimal thresholds for MK, Ka, Kr, and MD for differentiating the two groups were 0.490, 0.525, 0.432, and 1.493, respectively. The AQP4 expression in the solid parts of the tumors was significantly higher in HGAs. MK, Kr, Kavalues positively correlated with the AQP4 expression, whereas MD showed a slight negative correlation with AQP4.
Conclusion: Use of DKI improved grading of cerebral astrocytomas when compared with DTI. DKI parameters appeared to reflect the level of AQP4 expression in astrocytomas.</description><identifier>ISSN: 0028-3886</identifier><identifier>EISSN: 1998-4022</identifier><identifier>DOI: 10.4103/0028-3886.177621</identifier><identifier>PMID: 26954804</identifier><language>eng</language><publisher>India: Wolters Kluwer - Medknow Publications</publisher><subject>Analysis ; Aquaporin 4 - metabolism ; Aquaporins ; Astrocytoma - diagnosis ; Astrocytoma - metabolism ; Brain Neoplasms - diagnosis ; Brain Neoplasms - metabolism ; Care and treatment ; Comparative analysis ; Diffusion Tensor Imaging ; Dosage and administration ; Gliomas ; Humans ; Magnetic Resonance Imaging</subject><ispartof>Neurology India, 2016-03, Vol.64 (2), p.265-272</ispartof><rights>COPYRIGHT 2016 Medknow Publications and Media Pvt. Ltd.</rights><rights>Copyright Medknow Publications & Media Pvt Ltd Mar-Apr 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c491s-d5899a74f55f201a5f79b91d5330a16102543d428b378541c813efbda8ffc7733</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/1795936877?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,37013,44590</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26954804$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Tan, Yan</creatorcontrib><creatorcontrib>Zhang, Hui</creatorcontrib><creatorcontrib>Zhao, Rui-Feng</creatorcontrib><creatorcontrib>Wang, Xiao-Chun</creatorcontrib><creatorcontrib>Qin, Jiang-Bo</creatorcontrib><creatorcontrib>Wu, Xiao-Feng</creatorcontrib><title>Comparison of the values of MRI diffusion kurtosis imaging and diffusion tensor imaging in cerebral astrocytoma grading and their association with aquaporin-4</title><title>Neurology India</title><addtitle>Neurol India</addtitle><description>Objective: To compare the value of MRI diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) in grading cerebral astrocytomas and to analyze the correlation of respective parameters with aquaporin-4 (AQP4) expression.
Methods: Sixty patients with cerebral astrocytoma, including low-grade astrocytomas (LGA, n = 25) and high-grade astrocytomas (HGA, n = 35), were studied. The values of DKI parameters (mean kurtosis [MK], radial kurtosis [Kr], and axial kurtosis [Ka]) and DTI parameters (fractional anisotropy, mean diffusivity [MD]) corrected by contralateral normal-appearing white matter in the solid parts of the tumors and peritumoral edema were compared. Receiver operating characteristic curves were used to identify the best parameters. Spearman correlation analysis was conducted to assess the correlation of AQP4 expression with each parameter value.
Results: MK, Ka, and Krvalues were significantly higher whereas MD values were significantly lower in the solid parts of HGA, as compared to those of LGA. MK value in peritumoral edematous tissue was significantly higher in HGA as compared to that in LGA. Ka (0.889) had the largest area under the curve (AUC), followed by MK (0.840), Kr (0.750), and MD (0.764). The AUC of Kaand MK was significantly higher than that of MD. Optimal thresholds for MK, Ka, Kr, and MD for differentiating the two groups were 0.490, 0.525, 0.432, and 1.493, respectively. The AQP4 expression in the solid parts of the tumors was significantly higher in HGAs. MK, Kr, Kavalues positively correlated with the AQP4 expression, whereas MD showed a slight negative correlation with AQP4.
Conclusion: Use of DKI improved grading of cerebral astrocytomas when compared with DTI. DKI parameters appeared to reflect the level of AQP4 expression in astrocytomas.</description><subject>Analysis</subject><subject>Aquaporin 4 - metabolism</subject><subject>Aquaporins</subject><subject>Astrocytoma - diagnosis</subject><subject>Astrocytoma - metabolism</subject><subject>Brain Neoplasms - diagnosis</subject><subject>Brain Neoplasms - metabolism</subject><subject>Care and treatment</subject><subject>Comparative analysis</subject><subject>Diffusion Tensor Imaging</subject><subject>Dosage and administration</subject><subject>Gliomas</subject><subject>Humans</subject><subject>Magnetic Resonance Imaging</subject><issn>0028-3886</issn><issn>1998-4022</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNptks9v0zAcxSMEYt3gzglZ4sIlxT8T-zgqGJOGkBCcLcexO6-J3dkO1f4Z_lYcda02VOUQ2e_znvN1XlW9Q3BJESSfIMS8Jpw3S9S2DUYvqgUSgtcUYvyyWhzls-o8pbuyJATh19UZbgSjHNJF9XcVxq2KLgUPggX51oA_aphMmlfff16D3lk7JVfkzRRzSC4BN6q182ugfP9EzsanEI-i80CbaLqoBqBSjkE_5DAqsI6qP5jLaS4WNQXtVJ5Ddi7fAnU_qW2Iztf0TfXKqiGZt4_vi-r31y-_Vt_qmx9X16vLm1pTgVLdMy6EaqllzGKIFLOt6ATqGSFQoQZBzCjpKeYdaTmjSHNEjO16xa3VbUvIRfVxn7uN4b5Mn-XokjbDoLwJU5LlejGijLVNQT_8h96FKfrydYUSTJCGl8QjtVaDkc7bkKPSc6i8pLQhAmEqClWfoNbGm3JtwRvryvYzfnmCL09vRqdPGuDeoGNIKRort7H8ofggEZRzheTcETl3RO4rVCzvH-ebutH0R8OhMwX4vAd2Ycgmps0w7UyUhd34sHsWXD8JLgFMHtpG_gEc8NYI</recordid><startdate>20160301</startdate><enddate>20160301</enddate><creator>Tan, Yan</creator><creator>Zhang, Hui</creator><creator>Zhao, Rui-Feng</creator><creator>Wang, Xiao-Chun</creator><creator>Qin, Jiang-Bo</creator><creator>Wu, Xiao-Feng</creator><general>Wolters Kluwer - Medknow Publications</general><general>Medknow Publications and Media Pvt. 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Wang, Xiao-Chun ; Qin, Jiang-Bo ; Wu, Xiao-Feng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c491s-d5899a74f55f201a5f79b91d5330a16102543d428b378541c813efbda8ffc7733</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Analysis</topic><topic>Aquaporin 4 - metabolism</topic><topic>Aquaporins</topic><topic>Astrocytoma - diagnosis</topic><topic>Astrocytoma - metabolism</topic><topic>Brain Neoplasms - diagnosis</topic><topic>Brain Neoplasms - metabolism</topic><topic>Care and treatment</topic><topic>Comparative analysis</topic><topic>Diffusion Tensor Imaging</topic><topic>Dosage and administration</topic><topic>Gliomas</topic><topic>Humans</topic><topic>Magnetic Resonance Imaging</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tan, Yan</creatorcontrib><creatorcontrib>Zhang, Hui</creatorcontrib><creatorcontrib>Zhao, Rui-Feng</creatorcontrib><creatorcontrib>Wang, Xiao-Chun</creatorcontrib><creatorcontrib>Qin, Jiang-Bo</creatorcontrib><creatorcontrib>Wu, Xiao-Feng</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Health and Medical</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest research library</collection><collection>Research Library (Corporate)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Neurology India</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tan, Yan</au><au>Zhang, Hui</au><au>Zhao, Rui-Feng</au><au>Wang, Xiao-Chun</au><au>Qin, Jiang-Bo</au><au>Wu, Xiao-Feng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison of the values of MRI diffusion kurtosis imaging and diffusion tensor imaging in cerebral astrocytoma grading and their association with aquaporin-4</atitle><jtitle>Neurology India</jtitle><addtitle>Neurol India</addtitle><date>2016-03-01</date><risdate>2016</risdate><volume>64</volume><issue>2</issue><spage>265</spage><epage>272</epage><pages>265-272</pages><issn>0028-3886</issn><eissn>1998-4022</eissn><abstract>Objective: To compare the value of MRI diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) in grading cerebral astrocytomas and to analyze the correlation of respective parameters with aquaporin-4 (AQP4) expression.
Methods: Sixty patients with cerebral astrocytoma, including low-grade astrocytomas (LGA, n = 25) and high-grade astrocytomas (HGA, n = 35), were studied. The values of DKI parameters (mean kurtosis [MK], radial kurtosis [Kr], and axial kurtosis [Ka]) and DTI parameters (fractional anisotropy, mean diffusivity [MD]) corrected by contralateral normal-appearing white matter in the solid parts of the tumors and peritumoral edema were compared. Receiver operating characteristic curves were used to identify the best parameters. Spearman correlation analysis was conducted to assess the correlation of AQP4 expression with each parameter value.
Results: MK, Ka, and Krvalues were significantly higher whereas MD values were significantly lower in the solid parts of HGA, as compared to those of LGA. MK value in peritumoral edematous tissue was significantly higher in HGA as compared to that in LGA. Ka (0.889) had the largest area under the curve (AUC), followed by MK (0.840), Kr (0.750), and MD (0.764). The AUC of Kaand MK was significantly higher than that of MD. Optimal thresholds for MK, Ka, Kr, and MD for differentiating the two groups were 0.490, 0.525, 0.432, and 1.493, respectively. The AQP4 expression in the solid parts of the tumors was significantly higher in HGAs. MK, Kr, Kavalues positively correlated with the AQP4 expression, whereas MD showed a slight negative correlation with AQP4.
Conclusion: Use of DKI improved grading of cerebral astrocytomas when compared with DTI. DKI parameters appeared to reflect the level of AQP4 expression in astrocytomas.</abstract><cop>India</cop><pub>Wolters Kluwer - Medknow Publications</pub><pmid>26954804</pmid><doi>10.4103/0028-3886.177621</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Aquaporin 4 - metabolism Aquaporins Astrocytoma - diagnosis Astrocytoma - metabolism Brain Neoplasms - diagnosis Brain Neoplasms - metabolism Care and treatment Comparative analysis Diffusion Tensor Imaging Dosage and administration Gliomas Humans Magnetic Resonance Imaging |
title | Comparison of the values of MRI diffusion kurtosis imaging and diffusion tensor imaging in cerebral astrocytoma grading and their association with aquaporin-4 |
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