Cerebral OEF quantification: A comparison study between quantitative susceptibility mapping and dual‐gas calibrated BOLD imaging
Purpose To compare regional oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO2) quantified from the microvascular quantitative susceptibility mapping (QSM) using a hypercapnic gas challenge with those measured by the dual‐gas calibrated BOLD imaging (DGC‐BOLD)...
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Veröffentlicht in: | Magnetic resonance in medicine 2020-01, Vol.83 (1), p.68-82 |
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creator | Ma, Yuhan Sun, Hongfu Cho, Junghun Mazerolle, Erin L. Wang, Yi Pike, G. Bruce |
description | Purpose
To compare regional oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO2) quantified from the microvascular quantitative susceptibility mapping (QSM) using a hypercapnic gas challenge with those measured by the dual‐gas calibrated BOLD imaging (DGC‐BOLD) in healthy subjects.
Methods
Ten healthy subjects were scanned using a 3T MR system. The QSM data were acquired with a multi‐echo gradient‐echo sequence at baseline and hypercapnia. Cerebral blood flow data were acquired using the pseudo‐continuous arterial spin labeling technique. Baseline OEF and CMRO2 were calculated using QSM and cerebral blood flow measurements. The DGC‐BOLD data were also collected under a hypercapnic and a hyperoxic condition to yield baseline OEF and CMRO2. The QSM‐OEF and CMRO2 maps were compared with DGC‐BOLD OEF and CMRO2 maps using region of interest (vascular territories) analysis and Bland‐Altman plots.
Results
Hypercapnia is a robust stimulus for mapping OEF in combination with QSM. Average OEF in 16 vascular territory regions of interest across 10 subjects was 0.40 ± 0.04 by QSM‐OEF and 0.38 ± 0.09 by DGC‐BOLD. The average CMRO2 was 176 ± 35 and 167 ± 53 μmol O2/min/100g by QSM‐OEF and DGC‐BOLD, respectively. A Bland‐Altman plot of regional OEF and CMRO2 in regions of interest revealed a statistically significant but small difference (OEF difference = 0.02, CMRO2 difference = 9 μmol O2/min/100g, p < .05) between the 2 methods for the 10 healthy subjects.
Conclusion
Hypercapnic challenge–assisted QSM‐OEF is a feasible approach to quantify regional brain OEF and CMRO2. Compared with DGC‐BOLD, hypercapnia QSM‐OEF results in smaller intersubject variability and requires only 1 gas challenge. |
doi_str_mv | 10.1002/mrm.27907 |
format | Article |
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To compare regional oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO2) quantified from the microvascular quantitative susceptibility mapping (QSM) using a hypercapnic gas challenge with those measured by the dual‐gas calibrated BOLD imaging (DGC‐BOLD) in healthy subjects.
Methods
Ten healthy subjects were scanned using a 3T MR system. The QSM data were acquired with a multi‐echo gradient‐echo sequence at baseline and hypercapnia. Cerebral blood flow data were acquired using the pseudo‐continuous arterial spin labeling technique. Baseline OEF and CMRO2 were calculated using QSM and cerebral blood flow measurements. The DGC‐BOLD data were also collected under a hypercapnic and a hyperoxic condition to yield baseline OEF and CMRO2. The QSM‐OEF and CMRO2 maps were compared with DGC‐BOLD OEF and CMRO2 maps using region of interest (vascular territories) analysis and Bland‐Altman plots.
Results
Hypercapnia is a robust stimulus for mapping OEF in combination with QSM. Average OEF in 16 vascular territory regions of interest across 10 subjects was 0.40 ± 0.04 by QSM‐OEF and 0.38 ± 0.09 by DGC‐BOLD. The average CMRO2 was 176 ± 35 and 167 ± 53 μmol O2/min/100g by QSM‐OEF and DGC‐BOLD, respectively. A Bland‐Altman plot of regional OEF and CMRO2 in regions of interest revealed a statistically significant but small difference (OEF difference = 0.02, CMRO2 difference = 9 μmol O2/min/100g, p < .05) between the 2 methods for the 10 healthy subjects.
Conclusion
Hypercapnic challenge–assisted QSM‐OEF is a feasible approach to quantify regional brain OEF and CMRO2. Compared with DGC‐BOLD, hypercapnia QSM‐OEF results in smaller intersubject variability and requires only 1 gas challenge.</description><identifier>ISSN: 0740-3194</identifier><identifier>EISSN: 1522-2594</identifier><identifier>DOI: 10.1002/mrm.27907</identifier><identifier>PMID: 31373088</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Adult ; Algorithms ; Blood flow ; Brain - diagnostic imaging ; Brain Mapping ; calibrated BOLD ; Calibration ; Cerebral blood flow ; Cerebrovascular Circulation ; Computer Simulation ; Data acquisition ; Echo-Planar Imaging ; Female ; Functional magnetic resonance imaging ; Gray Matter - diagnostic imaging ; Healthy Volunteers ; Humans ; Hypercapnia ; Hypercapnia - metabolism ; Hyperoxia - metabolism ; Image processing ; Image Processing, Computer-Assisted - methods ; Magnetic Resonance Imaging ; Male ; Mapping ; Metabolic rate ; Microvasculature ; Neuroimaging ; Oxygen - blood ; Oxygen Consumption ; oxygen extraction fraction ; quantitative susceptibility mapping ; Reproducibility of Results ; Spin labeling ; Spin Labels ; Statistical analysis ; Territory</subject><ispartof>Magnetic resonance in medicine, 2020-01, Vol.83 (1), p.68-82</ispartof><rights>2019 International Society for Magnetic Resonance in Medicine</rights><rights>2019 International Society for Magnetic Resonance in Medicine.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3887-5f2235125938cfd9e4fde1336bb17f359b95b17a2f1a829c0df4a8acac7660753</citedby><cites>FETCH-LOGICAL-c3887-5f2235125938cfd9e4fde1336bb17f359b95b17a2f1a829c0df4a8acac7660753</cites><orcidid>0000-0002-0826-5463 ; 0000-0003-1404-8526 ; 0000-0001-7025-7539 ; 0000-0003-3436-7831</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%2Fmrm.27907$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fmrm.27907$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1416,1432,27923,27924,45573,45574,46408,46832</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31373088$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ma, Yuhan</creatorcontrib><creatorcontrib>Sun, Hongfu</creatorcontrib><creatorcontrib>Cho, Junghun</creatorcontrib><creatorcontrib>Mazerolle, Erin L.</creatorcontrib><creatorcontrib>Wang, Yi</creatorcontrib><creatorcontrib>Pike, G. Bruce</creatorcontrib><title>Cerebral OEF quantification: A comparison study between quantitative susceptibility mapping and dual‐gas calibrated BOLD imaging</title><title>Magnetic resonance in medicine</title><addtitle>Magn Reson Med</addtitle><description>Purpose
To compare regional oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO2) quantified from the microvascular quantitative susceptibility mapping (QSM) using a hypercapnic gas challenge with those measured by the dual‐gas calibrated BOLD imaging (DGC‐BOLD) in healthy subjects.
Methods
Ten healthy subjects were scanned using a 3T MR system. The QSM data were acquired with a multi‐echo gradient‐echo sequence at baseline and hypercapnia. Cerebral blood flow data were acquired using the pseudo‐continuous arterial spin labeling technique. Baseline OEF and CMRO2 were calculated using QSM and cerebral blood flow measurements. The DGC‐BOLD data were also collected under a hypercapnic and a hyperoxic condition to yield baseline OEF and CMRO2. The QSM‐OEF and CMRO2 maps were compared with DGC‐BOLD OEF and CMRO2 maps using region of interest (vascular territories) analysis and Bland‐Altman plots.
Results
Hypercapnia is a robust stimulus for mapping OEF in combination with QSM. Average OEF in 16 vascular territory regions of interest across 10 subjects was 0.40 ± 0.04 by QSM‐OEF and 0.38 ± 0.09 by DGC‐BOLD. The average CMRO2 was 176 ± 35 and 167 ± 53 μmol O2/min/100g by QSM‐OEF and DGC‐BOLD, respectively. A Bland‐Altman plot of regional OEF and CMRO2 in regions of interest revealed a statistically significant but small difference (OEF difference = 0.02, CMRO2 difference = 9 μmol O2/min/100g, p < .05) between the 2 methods for the 10 healthy subjects.
Conclusion
Hypercapnic challenge–assisted QSM‐OEF is a feasible approach to quantify regional brain OEF and CMRO2. Compared with DGC‐BOLD, hypercapnia QSM‐OEF results in smaller intersubject variability and requires only 1 gas challenge.</description><subject>Adult</subject><subject>Algorithms</subject><subject>Blood flow</subject><subject>Brain - diagnostic imaging</subject><subject>Brain Mapping</subject><subject>calibrated BOLD</subject><subject>Calibration</subject><subject>Cerebral blood flow</subject><subject>Cerebrovascular Circulation</subject><subject>Computer Simulation</subject><subject>Data acquisition</subject><subject>Echo-Planar Imaging</subject><subject>Female</subject><subject>Functional magnetic resonance imaging</subject><subject>Gray Matter - diagnostic imaging</subject><subject>Healthy Volunteers</subject><subject>Humans</subject><subject>Hypercapnia</subject><subject>Hypercapnia - metabolism</subject><subject>Hyperoxia - metabolism</subject><subject>Image processing</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Magnetic Resonance Imaging</subject><subject>Male</subject><subject>Mapping</subject><subject>Metabolic rate</subject><subject>Microvasculature</subject><subject>Neuroimaging</subject><subject>Oxygen - blood</subject><subject>Oxygen Consumption</subject><subject>oxygen extraction fraction</subject><subject>quantitative susceptibility mapping</subject><subject>Reproducibility of Results</subject><subject>Spin labeling</subject><subject>Spin Labels</subject><subject>Statistical analysis</subject><subject>Territory</subject><issn>0740-3194</issn><issn>1522-2594</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp10btuFDEUBmALgcgSKHgBZIkGikl8GY9turAkgLTRSghq64zHXjmaW2xPou0QT8Az8iQYdqFAorKLT_85Rz9Czyk5o4Sw8yEOZ0xqIh-gFRWMVUzo-iFaEVmTilNdn6AnKd0QQrSW9WN0wimXnCi1Qt_WLro2Qo-3l1f4doExBx8s5DCNb_AFttMwQwxpGnHKS7fHrcv3zo1Hmgu8czgtybo5hzb0Ie_xAPMcxh2GscPdAv2Pr993kLCFPpRR2XX47XbzDocBdoU9RY889Mk9O76n6MvV5ef1h2qzff9xfbGpLFdKVsIzxgUtp3Flfadd7TtHOW_alkrPhW61KD9gnoJi2pLO16DAgpVNQ6Tgp-jVIXeO0-3iUjZDKGv3PYxuWpJhrFGckkaqQl_-Q2-mJY5lO8M4oUTUjZBFvT4oG6eUovNmjuWmuDeUmF_FmFKM-V1MsS-OiUs7uO6v_NNEAecHcB96t_9_krn-dH2I_AklAJmi</recordid><startdate>202001</startdate><enddate>202001</enddate><creator>Ma, Yuhan</creator><creator>Sun, Hongfu</creator><creator>Cho, Junghun</creator><creator>Mazerolle, Erin L.</creator><creator>Wang, Yi</creator><creator>Pike, G. Bruce</creator><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>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7Z</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-0826-5463</orcidid><orcidid>https://orcid.org/0000-0003-1404-8526</orcidid><orcidid>https://orcid.org/0000-0001-7025-7539</orcidid><orcidid>https://orcid.org/0000-0003-3436-7831</orcidid></search><sort><creationdate>202001</creationdate><title>Cerebral OEF quantification: A comparison study between quantitative susceptibility mapping and dual‐gas calibrated BOLD imaging</title><author>Ma, Yuhan ; Sun, Hongfu ; Cho, Junghun ; Mazerolle, Erin L. ; Wang, Yi ; Pike, G. Bruce</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3887-5f2235125938cfd9e4fde1336bb17f359b95b17a2f1a829c0df4a8acac7660753</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adult</topic><topic>Algorithms</topic><topic>Blood flow</topic><topic>Brain - diagnostic imaging</topic><topic>Brain Mapping</topic><topic>calibrated BOLD</topic><topic>Calibration</topic><topic>Cerebral blood flow</topic><topic>Cerebrovascular Circulation</topic><topic>Computer Simulation</topic><topic>Data acquisition</topic><topic>Echo-Planar Imaging</topic><topic>Female</topic><topic>Functional magnetic resonance imaging</topic><topic>Gray Matter - diagnostic imaging</topic><topic>Healthy Volunteers</topic><topic>Humans</topic><topic>Hypercapnia</topic><topic>Hypercapnia - metabolism</topic><topic>Hyperoxia - metabolism</topic><topic>Image processing</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>Magnetic Resonance Imaging</topic><topic>Male</topic><topic>Mapping</topic><topic>Metabolic rate</topic><topic>Microvasculature</topic><topic>Neuroimaging</topic><topic>Oxygen - blood</topic><topic>Oxygen Consumption</topic><topic>oxygen extraction fraction</topic><topic>quantitative susceptibility mapping</topic><topic>Reproducibility of Results</topic><topic>Spin labeling</topic><topic>Spin Labels</topic><topic>Statistical analysis</topic><topic>Territory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ma, Yuhan</creatorcontrib><creatorcontrib>Sun, Hongfu</creatorcontrib><creatorcontrib>Cho, Junghun</creatorcontrib><creatorcontrib>Mazerolle, Erin L.</creatorcontrib><creatorcontrib>Wang, Yi</creatorcontrib><creatorcontrib>Pike, G. Bruce</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biochemistry Abstracts 1</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Magnetic resonance in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ma, Yuhan</au><au>Sun, Hongfu</au><au>Cho, Junghun</au><au>Mazerolle, Erin L.</au><au>Wang, Yi</au><au>Pike, G. Bruce</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cerebral OEF quantification: A comparison study between quantitative susceptibility mapping and dual‐gas calibrated BOLD imaging</atitle><jtitle>Magnetic resonance in medicine</jtitle><addtitle>Magn Reson Med</addtitle><date>2020-01</date><risdate>2020</risdate><volume>83</volume><issue>1</issue><spage>68</spage><epage>82</epage><pages>68-82</pages><issn>0740-3194</issn><eissn>1522-2594</eissn><abstract>Purpose
To compare regional oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO2) quantified from the microvascular quantitative susceptibility mapping (QSM) using a hypercapnic gas challenge with those measured by the dual‐gas calibrated BOLD imaging (DGC‐BOLD) in healthy subjects.
Methods
Ten healthy subjects were scanned using a 3T MR system. The QSM data were acquired with a multi‐echo gradient‐echo sequence at baseline and hypercapnia. Cerebral blood flow data were acquired using the pseudo‐continuous arterial spin labeling technique. Baseline OEF and CMRO2 were calculated using QSM and cerebral blood flow measurements. The DGC‐BOLD data were also collected under a hypercapnic and a hyperoxic condition to yield baseline OEF and CMRO2. The QSM‐OEF and CMRO2 maps were compared with DGC‐BOLD OEF and CMRO2 maps using region of interest (vascular territories) analysis and Bland‐Altman plots.
Results
Hypercapnia is a robust stimulus for mapping OEF in combination with QSM. Average OEF in 16 vascular territory regions of interest across 10 subjects was 0.40 ± 0.04 by QSM‐OEF and 0.38 ± 0.09 by DGC‐BOLD. The average CMRO2 was 176 ± 35 and 167 ± 53 μmol O2/min/100g by QSM‐OEF and DGC‐BOLD, respectively. A Bland‐Altman plot of regional OEF and CMRO2 in regions of interest revealed a statistically significant but small difference (OEF difference = 0.02, CMRO2 difference = 9 μmol O2/min/100g, p < .05) between the 2 methods for the 10 healthy subjects.
Conclusion
Hypercapnic challenge–assisted QSM‐OEF is a feasible approach to quantify regional brain OEF and CMRO2. Compared with DGC‐BOLD, hypercapnia QSM‐OEF results in smaller intersubject variability and requires only 1 gas challenge.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>31373088</pmid><doi>10.1002/mrm.27907</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-0826-5463</orcidid><orcidid>https://orcid.org/0000-0003-1404-8526</orcidid><orcidid>https://orcid.org/0000-0001-7025-7539</orcidid><orcidid>https://orcid.org/0000-0003-3436-7831</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adult Algorithms Blood flow Brain - diagnostic imaging Brain Mapping calibrated BOLD Calibration Cerebral blood flow Cerebrovascular Circulation Computer Simulation Data acquisition Echo-Planar Imaging Female Functional magnetic resonance imaging Gray Matter - diagnostic imaging Healthy Volunteers Humans Hypercapnia Hypercapnia - metabolism Hyperoxia - metabolism Image processing Image Processing, Computer-Assisted - methods Magnetic Resonance Imaging Male Mapping Metabolic rate Microvasculature Neuroimaging Oxygen - blood Oxygen Consumption oxygen extraction fraction quantitative susceptibility mapping Reproducibility of Results Spin labeling Spin Labels Statistical analysis Territory |
title | Cerebral OEF quantification: A comparison study between quantitative susceptibility mapping and dual‐gas calibrated BOLD imaging |
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