Diagnostic performance of multiparametric MRI in the evaluation of treatment response in glioma patients at 3T
Background MRI is one of the most important techniques to assess the treatment response of gliomas. However, differentiating tumor recurrence (TuR) from treatment effects (TrE) remains challenging. Purpose To compare the diagnostic performance of MR diffusion‐weighted imaging (DWI), arterial spin la...
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| Veröffentlicht in: | Journal of magnetic resonance imaging 2020-04, Vol.51 (4), p.1154-1161 |
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| creator | Liu, Jie Li, Cong Chen, Yinsheng Lv, Xiaofei Lv, Yanchun Zhou, Jian Xi, Shaoyan Dou, Weiqiang Qian, Long Zheng, Hairong Wu, Yin Chen, Zhongping |
| description | Background
MRI is one of the most important techniques to assess the treatment response of gliomas. However, differentiating tumor recurrence (TuR) from treatment effects (TrE) remains challenging.
Purpose
To compare the diagnostic performance of MR diffusion‐weighted imaging (DWI), arterial spin labeling (ASL), proton MR spectroscopy (MRS), and amide proton transfer (APT) imaging in differentiating between TuR and TrE in posttreatment glioma patients.
Study Type
Prospective.
Population
Thirty patients with suspected tumor progression.
Field Strength/Sequence
DWI, ASL, proton MRS, and APT imaging were performed at 3T MR.
Assessment
MR indices, including ADC, relative cerebral blood flow (rCBF), ratios of Cho/Cr, Cho/NAA, and NAA/Cr and APT‐weighted (APTw) effect were obtained from DWI, ASL, proton MRS, and APT imaging, respectively. Indices were measured in the contralateral normal‐appearing white matter and lesions defined on the Gd‐enhanced T1w image. TuR or TrE was either determined histologically or clinically from longitudinal MRI follow‐up for at least 6 months.
Statistical Tests
The diagnostic performance of the indices was evaluated using Student's t‐test, receiver operating characteristic (ROC) curve, and multivariate logistic regression analyses.
Results
Among the 30 patients, 16 were diagnosed as having TuR and the rest having TrE. The recurrent tumors showed a significantly higher APTw effect (1.56 ± 1.14%) and rCBF (1.44 ± 0.61) compared with lesions representing treatment effects (–0.44 ± 1.34% and 0.72 ± 0.25, respectively, with P |
| doi_str_mv | 10.1002/jmri.26900 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2335171225</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2375713111</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4230-f474a1bd01ca5c76abf43d25b20107e75b10dd04be1c1e14b2280871068b8b593</originalsourceid><addsrcrecordid>eNp90cFqFTEUBuAgiq3VjQ8gATciTD0nmdzMXUpttaUiSF0PycyZmsskGZOM0rc311tduOgqCefjJ5yfsZcIpwgg3u18cqdiswV4xI5RCdEI1W0e1zso2WAH-og9y3kHANttq56yI4mtrK_umIUPztyGmIsb-EJpismbMBCPE_frXNxikvFUUh1__nrJXeDlO3H6aebVFBfDHpZEpngKhSfKSwyZ9u52dtEbvlRWR5mbwuXNc_ZkMnOmF_fnCft2cX5z9qm5_vLx8uz9dTO0QkIztbo1aEfAwahBb4ydWjkKZQUgaNLKIowjtJZwQMLWCtFBpxE2ne2s2soT9uaQu6T4Y6Vceu_yQPNsAsU190JKhRqFUJW-_o_u4ppC_V1VWmmUiFjV24MaUsw50dQvyXmT7nqEft9Cv2-h_9NCxa_uI1frafxH_669AjyAX26muwei-qu69UPobwqkkcY</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2375713111</pqid></control><display><type>article</type><title>Diagnostic performance of multiparametric MRI in the evaluation of treatment response in glioma patients at 3T</title><source>MEDLINE</source><source>Wiley Journals</source><creator>Liu, Jie ; Li, Cong ; Chen, Yinsheng ; Lv, Xiaofei ; Lv, Yanchun ; Zhou, Jian ; Xi, Shaoyan ; Dou, Weiqiang ; Qian, Long ; Zheng, Hairong ; Wu, Yin ; Chen, Zhongping</creator><creatorcontrib>Liu, Jie ; Li, Cong ; Chen, Yinsheng ; Lv, Xiaofei ; Lv, Yanchun ; Zhou, Jian ; Xi, Shaoyan ; Dou, Weiqiang ; Qian, Long ; Zheng, Hairong ; Wu, Yin ; Chen, Zhongping</creatorcontrib><description>Background
MRI is one of the most important techniques to assess the treatment response of gliomas. However, differentiating tumor recurrence (TuR) from treatment effects (TrE) remains challenging.
Purpose
To compare the diagnostic performance of MR diffusion‐weighted imaging (DWI), arterial spin labeling (ASL), proton MR spectroscopy (MRS), and amide proton transfer (APT) imaging in differentiating between TuR and TrE in posttreatment glioma patients.
Study Type
Prospective.
Population
Thirty patients with suspected tumor progression.
Field Strength/Sequence
DWI, ASL, proton MRS, and APT imaging were performed at 3T MR.
Assessment
MR indices, including ADC, relative cerebral blood flow (rCBF), ratios of Cho/Cr, Cho/NAA, and NAA/Cr and APT‐weighted (APTw) effect were obtained from DWI, ASL, proton MRS, and APT imaging, respectively. Indices were measured in the contralateral normal‐appearing white matter and lesions defined on the Gd‐enhanced T1w image. TuR or TrE was either determined histologically or clinically from longitudinal MRI follow‐up for at least 6 months.
Statistical Tests
The diagnostic performance of the indices was evaluated using Student's t‐test, receiver operating characteristic (ROC) curve, and multivariate logistic regression analyses.
Results
Among the 30 patients, 16 were diagnosed as having TuR and the rest having TrE. The recurrent tumors showed a significantly higher APTw effect (1.56 ± 1.14%) and rCBF (1.44 ± 0.61) compared with lesions representing treatment effects (–0.44 ± 1.34% and 0.72 ± 0.25, respectively, with P < 0.001). The areas under the curve (AUCs) were 0.87 and 0.90 for APTw and rCBF, respectively, in differentiating between TuR and TrE. Combining APTw and rCBF achieved a higher AUC of 0.93. MRS index ratios of Cho/Cr (P = 0.25), Cho/NAA (P = 0.16), and NAA/Cr (P = 0.86) and ADC (P = 0.37) showed no significant differences between TuR and TrE lesions, with AUCs lower than 0.70.
Data Conclusion
Compared with DWI and MRS, ASL and APT imaging techniques showed better diagnostic capability in distinguishing TuR from TrE.
Level of Evidence: 1
Technical Efficacy: Stage 4
J. Magn. Reson. Imaging 2020;51:1154–1161.</description><identifier>ISSN: 1053-1807</identifier><identifier>EISSN: 1522-2586</identifier><identifier>DOI: 10.1002/jmri.26900</identifier><identifier>PMID: 31430008</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>amide proton transfer imaging ; Blood flow ; Brain Neoplasms - diagnostic imaging ; Brain Neoplasms - therapy ; Brain tumors ; Cerebral blood flow ; diagnostic performance ; Diagnostic systems ; Diffusion Magnetic Resonance Imaging ; Field strength ; Gadolinium ; Glioma ; Glioma - diagnostic imaging ; Glioma - therapy ; Humans ; Image enhancement ; Imaging techniques ; Lesions ; Magnetic Resonance Imaging ; Magnetic resonance spectroscopy ; Medical imaging ; Multiparametric Magnetic Resonance Imaging ; Neoplasm Recurrence, Local ; Population studies ; Prospective Studies ; Protons ; Regression analysis ; Spin labeling ; Statistical analysis ; Statistical tests ; Substantia alba ; treatment effects ; tumor recurrence ; Tumors</subject><ispartof>Journal of magnetic resonance imaging, 2020-04, Vol.51 (4), p.1154-1161</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-c4230-f474a1bd01ca5c76abf43d25b20107e75b10dd04be1c1e14b2280871068b8b593</citedby><cites>FETCH-LOGICAL-c4230-f474a1bd01ca5c76abf43d25b20107e75b10dd04be1c1e14b2280871068b8b593</cites><orcidid>0000-0002-4323-5083 ; 0000-0002-1712-630X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjmri.26900$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjmri.26900$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31430008$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liu, Jie</creatorcontrib><creatorcontrib>Li, Cong</creatorcontrib><creatorcontrib>Chen, Yinsheng</creatorcontrib><creatorcontrib>Lv, Xiaofei</creatorcontrib><creatorcontrib>Lv, Yanchun</creatorcontrib><creatorcontrib>Zhou, Jian</creatorcontrib><creatorcontrib>Xi, Shaoyan</creatorcontrib><creatorcontrib>Dou, Weiqiang</creatorcontrib><creatorcontrib>Qian, Long</creatorcontrib><creatorcontrib>Zheng, Hairong</creatorcontrib><creatorcontrib>Wu, Yin</creatorcontrib><creatorcontrib>Chen, Zhongping</creatorcontrib><title>Diagnostic performance of multiparametric MRI in the evaluation of treatment response in glioma patients at 3T</title><title>Journal of magnetic resonance imaging</title><addtitle>J Magn Reson Imaging</addtitle><description>Background
MRI is one of the most important techniques to assess the treatment response of gliomas. However, differentiating tumor recurrence (TuR) from treatment effects (TrE) remains challenging.
Purpose
To compare the diagnostic performance of MR diffusion‐weighted imaging (DWI), arterial spin labeling (ASL), proton MR spectroscopy (MRS), and amide proton transfer (APT) imaging in differentiating between TuR and TrE in posttreatment glioma patients.
Study Type
Prospective.
Population
Thirty patients with suspected tumor progression.
Field Strength/Sequence
DWI, ASL, proton MRS, and APT imaging were performed at 3T MR.
Assessment
MR indices, including ADC, relative cerebral blood flow (rCBF), ratios of Cho/Cr, Cho/NAA, and NAA/Cr and APT‐weighted (APTw) effect were obtained from DWI, ASL, proton MRS, and APT imaging, respectively. Indices were measured in the contralateral normal‐appearing white matter and lesions defined on the Gd‐enhanced T1w image. TuR or TrE was either determined histologically or clinically from longitudinal MRI follow‐up for at least 6 months.
Statistical Tests
The diagnostic performance of the indices was evaluated using Student's t‐test, receiver operating characteristic (ROC) curve, and multivariate logistic regression analyses.
Results
Among the 30 patients, 16 were diagnosed as having TuR and the rest having TrE. The recurrent tumors showed a significantly higher APTw effect (1.56 ± 1.14%) and rCBF (1.44 ± 0.61) compared with lesions representing treatment effects (–0.44 ± 1.34% and 0.72 ± 0.25, respectively, with P < 0.001). The areas under the curve (AUCs) were 0.87 and 0.90 for APTw and rCBF, respectively, in differentiating between TuR and TrE. Combining APTw and rCBF achieved a higher AUC of 0.93. MRS index ratios of Cho/Cr (P = 0.25), Cho/NAA (P = 0.16), and NAA/Cr (P = 0.86) and ADC (P = 0.37) showed no significant differences between TuR and TrE lesions, with AUCs lower than 0.70.
Data Conclusion
Compared with DWI and MRS, ASL and APT imaging techniques showed better diagnostic capability in distinguishing TuR from TrE.
Level of Evidence: 1
Technical Efficacy: Stage 4
J. Magn. Reson. Imaging 2020;51:1154–1161.</description><subject>amide proton transfer imaging</subject><subject>Blood flow</subject><subject>Brain Neoplasms - diagnostic imaging</subject><subject>Brain Neoplasms - therapy</subject><subject>Brain tumors</subject><subject>Cerebral blood flow</subject><subject>diagnostic performance</subject><subject>Diagnostic systems</subject><subject>Diffusion Magnetic Resonance Imaging</subject><subject>Field strength</subject><subject>Gadolinium</subject><subject>Glioma</subject><subject>Glioma - diagnostic imaging</subject><subject>Glioma - therapy</subject><subject>Humans</subject><subject>Image enhancement</subject><subject>Imaging techniques</subject><subject>Lesions</subject><subject>Magnetic Resonance Imaging</subject><subject>Magnetic resonance spectroscopy</subject><subject>Medical imaging</subject><subject>Multiparametric Magnetic Resonance Imaging</subject><subject>Neoplasm Recurrence, Local</subject><subject>Population studies</subject><subject>Prospective Studies</subject><subject>Protons</subject><subject>Regression analysis</subject><subject>Spin labeling</subject><subject>Statistical analysis</subject><subject>Statistical tests</subject><subject>Substantia alba</subject><subject>treatment effects</subject><subject>tumor recurrence</subject><subject>Tumors</subject><issn>1053-1807</issn><issn>1522-2586</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp90cFqFTEUBuAgiq3VjQ8gATciTD0nmdzMXUpttaUiSF0PycyZmsskGZOM0rc311tduOgqCefjJ5yfsZcIpwgg3u18cqdiswV4xI5RCdEI1W0e1zso2WAH-og9y3kHANttq56yI4mtrK_umIUPztyGmIsb-EJpismbMBCPE_frXNxikvFUUh1__nrJXeDlO3H6aebVFBfDHpZEpngKhSfKSwyZ9u52dtEbvlRWR5mbwuXNc_ZkMnOmF_fnCft2cX5z9qm5_vLx8uz9dTO0QkIztbo1aEfAwahBb4ydWjkKZQUgaNLKIowjtJZwQMLWCtFBpxE2ne2s2soT9uaQu6T4Y6Vceu_yQPNsAsU190JKhRqFUJW-_o_u4ppC_V1VWmmUiFjV24MaUsw50dQvyXmT7nqEft9Cv2-h_9NCxa_uI1frafxH_669AjyAX26muwei-qu69UPobwqkkcY</recordid><startdate>202004</startdate><enddate>202004</enddate><creator>Liu, Jie</creator><creator>Li, Cong</creator><creator>Chen, Yinsheng</creator><creator>Lv, Xiaofei</creator><creator>Lv, Yanchun</creator><creator>Zhou, Jian</creator><creator>Xi, Shaoyan</creator><creator>Dou, Weiqiang</creator><creator>Qian, Long</creator><creator>Zheng, Hairong</creator><creator>Wu, Yin</creator><creator>Chen, Zhongping</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/0000-0002-4323-5083</orcidid><orcidid>https://orcid.org/0000-0002-1712-630X</orcidid></search><sort><creationdate>202004</creationdate><title>Diagnostic performance of multiparametric MRI in the evaluation of treatment response in glioma patients at 3T</title><author>Liu, Jie ; Li, Cong ; Chen, Yinsheng ; Lv, Xiaofei ; Lv, Yanchun ; Zhou, Jian ; Xi, Shaoyan ; Dou, Weiqiang ; Qian, Long ; Zheng, Hairong ; Wu, Yin ; Chen, Zhongping</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4230-f474a1bd01ca5c76abf43d25b20107e75b10dd04be1c1e14b2280871068b8b593</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>amide proton transfer imaging</topic><topic>Blood flow</topic><topic>Brain Neoplasms - diagnostic imaging</topic><topic>Brain Neoplasms - therapy</topic><topic>Brain tumors</topic><topic>Cerebral blood flow</topic><topic>diagnostic performance</topic><topic>Diagnostic systems</topic><topic>Diffusion Magnetic Resonance Imaging</topic><topic>Field strength</topic><topic>Gadolinium</topic><topic>Glioma</topic><topic>Glioma - diagnostic imaging</topic><topic>Glioma - therapy</topic><topic>Humans</topic><topic>Image enhancement</topic><topic>Imaging techniques</topic><topic>Lesions</topic><topic>Magnetic Resonance Imaging</topic><topic>Magnetic resonance spectroscopy</topic><topic>Medical imaging</topic><topic>Multiparametric Magnetic Resonance Imaging</topic><topic>Neoplasm Recurrence, Local</topic><topic>Population studies</topic><topic>Prospective Studies</topic><topic>Protons</topic><topic>Regression analysis</topic><topic>Spin labeling</topic><topic>Statistical analysis</topic><topic>Statistical tests</topic><topic>Substantia alba</topic><topic>treatment effects</topic><topic>tumor recurrence</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Jie</creatorcontrib><creatorcontrib>Li, Cong</creatorcontrib><creatorcontrib>Chen, Yinsheng</creatorcontrib><creatorcontrib>Lv, Xiaofei</creatorcontrib><creatorcontrib>Lv, Yanchun</creatorcontrib><creatorcontrib>Zhou, Jian</creatorcontrib><creatorcontrib>Xi, Shaoyan</creatorcontrib><creatorcontrib>Dou, Weiqiang</creatorcontrib><creatorcontrib>Qian, Long</creatorcontrib><creatorcontrib>Zheng, Hairong</creatorcontrib><creatorcontrib>Wu, Yin</creatorcontrib><creatorcontrib>Chen, Zhongping</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>Liu, Jie</au><au>Li, Cong</au><au>Chen, Yinsheng</au><au>Lv, Xiaofei</au><au>Lv, Yanchun</au><au>Zhou, Jian</au><au>Xi, Shaoyan</au><au>Dou, Weiqiang</au><au>Qian, Long</au><au>Zheng, Hairong</au><au>Wu, Yin</au><au>Chen, Zhongping</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Diagnostic performance of multiparametric MRI in the evaluation of treatment response in glioma patients at 3T</atitle><jtitle>Journal of magnetic resonance imaging</jtitle><addtitle>J Magn Reson Imaging</addtitle><date>2020-04</date><risdate>2020</risdate><volume>51</volume><issue>4</issue><spage>1154</spage><epage>1161</epage><pages>1154-1161</pages><issn>1053-1807</issn><eissn>1522-2586</eissn><abstract>Background
MRI is one of the most important techniques to assess the treatment response of gliomas. However, differentiating tumor recurrence (TuR) from treatment effects (TrE) remains challenging.
Purpose
To compare the diagnostic performance of MR diffusion‐weighted imaging (DWI), arterial spin labeling (ASL), proton MR spectroscopy (MRS), and amide proton transfer (APT) imaging in differentiating between TuR and TrE in posttreatment glioma patients.
Study Type
Prospective.
Population
Thirty patients with suspected tumor progression.
Field Strength/Sequence
DWI, ASL, proton MRS, and APT imaging were performed at 3T MR.
Assessment
MR indices, including ADC, relative cerebral blood flow (rCBF), ratios of Cho/Cr, Cho/NAA, and NAA/Cr and APT‐weighted (APTw) effect were obtained from DWI, ASL, proton MRS, and APT imaging, respectively. Indices were measured in the contralateral normal‐appearing white matter and lesions defined on the Gd‐enhanced T1w image. TuR or TrE was either determined histologically or clinically from longitudinal MRI follow‐up for at least 6 months.
Statistical Tests
The diagnostic performance of the indices was evaluated using Student's t‐test, receiver operating characteristic (ROC) curve, and multivariate logistic regression analyses.
Results
Among the 30 patients, 16 were diagnosed as having TuR and the rest having TrE. The recurrent tumors showed a significantly higher APTw effect (1.56 ± 1.14%) and rCBF (1.44 ± 0.61) compared with lesions representing treatment effects (–0.44 ± 1.34% and 0.72 ± 0.25, respectively, with P < 0.001). The areas under the curve (AUCs) were 0.87 and 0.90 for APTw and rCBF, respectively, in differentiating between TuR and TrE. Combining APTw and rCBF achieved a higher AUC of 0.93. MRS index ratios of Cho/Cr (P = 0.25), Cho/NAA (P = 0.16), and NAA/Cr (P = 0.86) and ADC (P = 0.37) showed no significant differences between TuR and TrE lesions, with AUCs lower than 0.70.
Data Conclusion
Compared with DWI and MRS, ASL and APT imaging techniques showed better diagnostic capability in distinguishing TuR from TrE.
Level of Evidence: 1
Technical Efficacy: Stage 4
J. Magn. Reson. Imaging 2020;51:1154–1161.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><pmid>31430008</pmid><doi>10.1002/jmri.26900</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-4323-5083</orcidid><orcidid>https://orcid.org/0000-0002-1712-630X</orcidid></addata></record> |
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| subjects | amide proton transfer imaging Blood flow Brain Neoplasms - diagnostic imaging Brain Neoplasms - therapy Brain tumors Cerebral blood flow diagnostic performance Diagnostic systems Diffusion Magnetic Resonance Imaging Field strength Gadolinium Glioma Glioma - diagnostic imaging Glioma - therapy Humans Image enhancement Imaging techniques Lesions Magnetic Resonance Imaging Magnetic resonance spectroscopy Medical imaging Multiparametric Magnetic Resonance Imaging Neoplasm Recurrence, Local Population studies Prospective Studies Protons Regression analysis Spin labeling Statistical analysis Statistical tests Substantia alba treatment effects tumor recurrence Tumors |
| title | Diagnostic performance of multiparametric MRI in the evaluation of treatment response in glioma patients at 3T |
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