MRS quality assessment in a multicentre study on MRS-based classification of brain tumours
This paper reports on quality assessment of MRS in the European Union‐funded multicentre project INTERPRET (International Network for Pattern Recognition of Tumours Using Magnetic Resonance; http://azizu.uab.es/INTERPRET), which has developed brain tumour classification software using in vivo proton...
Gespeichert in:
| Veröffentlicht in: | NMR in biomedicine 2008-02, Vol.21 (2), p.148-158 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 158 |
|---|---|
| container_issue | 2 |
| container_start_page | 148 |
| container_title | NMR in biomedicine |
| container_volume | 21 |
| creator | van der Graaf, Marinette Julià-Sapé, Margarida Howe, Franklyn A. Ziegler, Anne Majós, Carles Moreno-Torres, Angel Rijpkema, Mark Acosta, Dionisio Opstad, Kirstie S. van der Meulen, Yvonne M. Arús, Carles Heerschap, Arend |
| description | This paper reports on quality assessment of MRS in the European Union‐funded multicentre project INTERPRET (International Network for Pattern Recognition of Tumours Using Magnetic Resonance; http://azizu.uab.es/INTERPRET), which has developed brain tumour classification software using in vivo proton MR spectra. The quality assessment consisted of both MR system quality assurance (SQA) and quality control (QC) of spectral data acquired from patients and healthy volunteers. The system performance of the MR spectrometers at all participating centres was checked bimonthly by a short measurement protocol using a specially designed INTERPRET phantom. In addition, a more extended SQA protocol was performed yearly and after each hardware or software upgrade. To compare the system performance for in vivo measurements, each centre acquired MR spectra from the brain of five healthy volunteers. All MR systems fulfilled generally accepted minimal system performance for brain MRS during the entire data acquisition period. The QC procedure of the MR spectra in the database comprised automatic determination of the signal‐to‐noise ratio (SNR) in a water‐suppressed spectrum and of the line width of the water resonance (water band width, WBW) in the corresponding non‐suppressed spectrum. Values of SNR > 10 and WBW |
| doi_str_mv | 10.1002/nbm.1172 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_inserm_00381415v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>70290076</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4592-8327a4d2a7218502ec43510623bec6a22a5f699dcf4a808fc00e525c0fd007b03</originalsourceid><addsrcrecordid>eNqFkU1rFTEUhoNY7LUK_gLJSlw47cmZZJIsa9FWvL2CVpS7CZlMBqPz0SYz6v33ptyhrkpX4ZDnfXjhJeQFg2MGgCdD3R8zJvERWTHQumBc42OyAi2wKLmCQ_I0pZ8AoHiJT8ghk1wozdSKbC8_f6E3s-3CtKM2JZ9S74eJhoFa2s_dFFw-o6dpmpsdHQeaA0Vtk2-o63IgtMHZKeSPsaV1tDk4zf04x_SMHLS2S_758h6Rr-_fXZ1dFOtP5x_OTteF40JjoUqUljdoJTIlAL3jpWBQYVl7V1lEK9pK68a13CpQrQPwAoWDtgGQNZRH5M3e-8N25jqG3sadGW0wF6drE4bkY28ASsU4E79Zxl_t8es43sw-TaYPyfmus4Mf52QkoM7i6kEQc0mJlczg6z3o4phS9O1dCwbmdh-T9zG3-2T05eKc6943_8FlkAwUe-BP6PzuXpHZvL1chAsf0uT_3vE2_jK5mRTm2-bcbLffP2624spA-Q8POKdl</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>21067267</pqid></control><display><type>article</type><title>MRS quality assessment in a multicentre study on MRS-based classification of brain tumours</title><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><creator>van der Graaf, Marinette ; Julià-Sapé, Margarida ; Howe, Franklyn A. ; Ziegler, Anne ; Majós, Carles ; Moreno-Torres, Angel ; Rijpkema, Mark ; Acosta, Dionisio ; Opstad, Kirstie S. ; van der Meulen, Yvonne M. ; Arús, Carles ; Heerschap, Arend</creator><creatorcontrib>van der Graaf, Marinette ; Julià-Sapé, Margarida ; Howe, Franklyn A. ; Ziegler, Anne ; Majós, Carles ; Moreno-Torres, Angel ; Rijpkema, Mark ; Acosta, Dionisio ; Opstad, Kirstie S. ; van der Meulen, Yvonne M. ; Arús, Carles ; Heerschap, Arend</creatorcontrib><description>This paper reports on quality assessment of MRS in the European Union‐funded multicentre project INTERPRET (International Network for Pattern Recognition of Tumours Using Magnetic Resonance; http://azizu.uab.es/INTERPRET), which has developed brain tumour classification software using in vivo proton MR spectra. The quality assessment consisted of both MR system quality assurance (SQA) and quality control (QC) of spectral data acquired from patients and healthy volunteers. The system performance of the MR spectrometers at all participating centres was checked bimonthly by a short measurement protocol using a specially designed INTERPRET phantom. In addition, a more extended SQA protocol was performed yearly and after each hardware or software upgrade. To compare the system performance for in vivo measurements, each centre acquired MR spectra from the brain of five healthy volunteers. All MR systems fulfilled generally accepted minimal system performance for brain MRS during the entire data acquisition period. The QC procedure of the MR spectra in the database comprised automatic determination of the signal‐to‐noise ratio (SNR) in a water‐suppressed spectrum and of the line width of the water resonance (water band width, WBW) in the corresponding non‐suppressed spectrum. Values of SNR > 10 and WBW < 8 Hz at 1.5 T were determined empirically as conservative threshold levels required for spectra to be of acceptable quality. These thresholds only hold for SNR and WBW values using the definitions and data processing described in this article. A final QC check consisted of visual inspection of each clinically validated water‐suppressed metabolite spectrum by two, or, in the case of disagreement, three, experienced MR spectroscopists, to detect artefacts such as large baseline distortions, exceptionally broadened metabolite peaks, insufficient removal of the water line, large phase errors, and signals originating from outside the voxel. In the end, 10% of 889 spectra with completed spectroscopic judgement were discarded. Copyright © 2007 John Wiley & Sons, Ltd.</description><identifier>ISSN: 0952-3480</identifier><identifier>EISSN: 1099-1492</identifier><identifier>DOI: 10.1002/nbm.1172</identifier><identifier>PMID: 17458918</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>1H MRS ; Bioengineering ; Brain Neoplasms ; Brain Neoplasms - classification ; Brain Neoplasms - diagnosis ; Cancer ; Clinical Protocols ; Clinical Protocols - standards ; Databases, Factual ; Databases, Factual - standards ; Equipment Failure Analysis ; European Union ; Expert Systems ; Humans ; Imaging ; Life Sciences ; Magnetic Resonance Spectroscopy ; Magnetic Resonance Spectroscopy - instrumentation ; Magnetic Resonance Spectroscopy - standards ; MR spectra ; Multicenter Studies as Topic ; Multicenter Studies as Topic - standards ; multicentre study ; Pattern Recognition, Automated ; Pattern Recognition, Automated - standards ; phantom ; Phantoms, Imaging ; Program Evaluation ; Protons ; quality assessment ; Quality Control ; Reference Standards ; Reproducibility of Results ; Software ; system quality assurance ; Water ; Water - analysis</subject><ispartof>NMR in biomedicine, 2008-02, Vol.21 (2), p.148-158</ispartof><rights>Copyright © 2007 John Wiley & Sons, Ltd.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4592-8327a4d2a7218502ec43510623bec6a22a5f699dcf4a808fc00e525c0fd007b03</citedby><cites>FETCH-LOGICAL-c4592-8327a4d2a7218502ec43510623bec6a22a5f699dcf4a808fc00e525c0fd007b03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fnbm.1172$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fnbm.1172$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,780,784,885,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/17458918$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://inserm.hal.science/inserm-00381415$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>van der Graaf, Marinette</creatorcontrib><creatorcontrib>Julià-Sapé, Margarida</creatorcontrib><creatorcontrib>Howe, Franklyn A.</creatorcontrib><creatorcontrib>Ziegler, Anne</creatorcontrib><creatorcontrib>Majós, Carles</creatorcontrib><creatorcontrib>Moreno-Torres, Angel</creatorcontrib><creatorcontrib>Rijpkema, Mark</creatorcontrib><creatorcontrib>Acosta, Dionisio</creatorcontrib><creatorcontrib>Opstad, Kirstie S.</creatorcontrib><creatorcontrib>van der Meulen, Yvonne M.</creatorcontrib><creatorcontrib>Arús, Carles</creatorcontrib><creatorcontrib>Heerschap, Arend</creatorcontrib><title>MRS quality assessment in a multicentre study on MRS-based classification of brain tumours</title><title>NMR in biomedicine</title><addtitle>NMR Biomed</addtitle><description>This paper reports on quality assessment of MRS in the European Union‐funded multicentre project INTERPRET (International Network for Pattern Recognition of Tumours Using Magnetic Resonance; http://azizu.uab.es/INTERPRET), which has developed brain tumour classification software using in vivo proton MR spectra. The quality assessment consisted of both MR system quality assurance (SQA) and quality control (QC) of spectral data acquired from patients and healthy volunteers. The system performance of the MR spectrometers at all participating centres was checked bimonthly by a short measurement protocol using a specially designed INTERPRET phantom. In addition, a more extended SQA protocol was performed yearly and after each hardware or software upgrade. To compare the system performance for in vivo measurements, each centre acquired MR spectra from the brain of five healthy volunteers. All MR systems fulfilled generally accepted minimal system performance for brain MRS during the entire data acquisition period. The QC procedure of the MR spectra in the database comprised automatic determination of the signal‐to‐noise ratio (SNR) in a water‐suppressed spectrum and of the line width of the water resonance (water band width, WBW) in the corresponding non‐suppressed spectrum. Values of SNR > 10 and WBW < 8 Hz at 1.5 T were determined empirically as conservative threshold levels required for spectra to be of acceptable quality. These thresholds only hold for SNR and WBW values using the definitions and data processing described in this article. A final QC check consisted of visual inspection of each clinically validated water‐suppressed metabolite spectrum by two, or, in the case of disagreement, three, experienced MR spectroscopists, to detect artefacts such as large baseline distortions, exceptionally broadened metabolite peaks, insufficient removal of the water line, large phase errors, and signals originating from outside the voxel. In the end, 10% of 889 spectra with completed spectroscopic judgement were discarded. Copyright © 2007 John Wiley & Sons, Ltd.</description><subject>1H MRS</subject><subject>Bioengineering</subject><subject>Brain Neoplasms</subject><subject>Brain Neoplasms - classification</subject><subject>Brain Neoplasms - diagnosis</subject><subject>Cancer</subject><subject>Clinical Protocols</subject><subject>Clinical Protocols - standards</subject><subject>Databases, Factual</subject><subject>Databases, Factual - standards</subject><subject>Equipment Failure Analysis</subject><subject>European Union</subject><subject>Expert Systems</subject><subject>Humans</subject><subject>Imaging</subject><subject>Life Sciences</subject><subject>Magnetic Resonance Spectroscopy</subject><subject>Magnetic Resonance Spectroscopy - instrumentation</subject><subject>Magnetic Resonance Spectroscopy - standards</subject><subject>MR spectra</subject><subject>Multicenter Studies as Topic</subject><subject>Multicenter Studies as Topic - standards</subject><subject>multicentre study</subject><subject>Pattern Recognition, Automated</subject><subject>Pattern Recognition, Automated - standards</subject><subject>phantom</subject><subject>Phantoms, Imaging</subject><subject>Program Evaluation</subject><subject>Protons</subject><subject>quality assessment</subject><subject>Quality Control</subject><subject>Reference Standards</subject><subject>Reproducibility of Results</subject><subject>Software</subject><subject>system quality assurance</subject><subject>Water</subject><subject>Water - analysis</subject><issn>0952-3480</issn><issn>1099-1492</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkU1rFTEUhoNY7LUK_gLJSlw47cmZZJIsa9FWvL2CVpS7CZlMBqPz0SYz6v33ptyhrkpX4ZDnfXjhJeQFg2MGgCdD3R8zJvERWTHQumBc42OyAi2wKLmCQ_I0pZ8AoHiJT8ghk1wozdSKbC8_f6E3s-3CtKM2JZ9S74eJhoFa2s_dFFw-o6dpmpsdHQeaA0Vtk2-o63IgtMHZKeSPsaV1tDk4zf04x_SMHLS2S_758h6Rr-_fXZ1dFOtP5x_OTteF40JjoUqUljdoJTIlAL3jpWBQYVl7V1lEK9pK68a13CpQrQPwAoWDtgGQNZRH5M3e-8N25jqG3sadGW0wF6drE4bkY28ASsU4E79Zxl_t8es43sw-TaYPyfmus4Mf52QkoM7i6kEQc0mJlczg6z3o4phS9O1dCwbmdh-T9zG3-2T05eKc6943_8FlkAwUe-BP6PzuXpHZvL1chAsf0uT_3vE2_jK5mRTm2-bcbLffP2624spA-Q8POKdl</recordid><startdate>200802</startdate><enddate>200802</enddate><creator>van der Graaf, Marinette</creator><creator>Julià-Sapé, Margarida</creator><creator>Howe, Franklyn A.</creator><creator>Ziegler, Anne</creator><creator>Majós, Carles</creator><creator>Moreno-Torres, Angel</creator><creator>Rijpkema, Mark</creator><creator>Acosta, Dionisio</creator><creator>Opstad, Kirstie S.</creator><creator>van der Meulen, Yvonne M.</creator><creator>Arús, Carles</creator><creator>Heerschap, Arend</creator><general>John Wiley & Sons, Ltd</general><general>Wiley</general><scope>BSCLL</scope><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>P64</scope><scope>7X8</scope><scope>1XC</scope><scope>VOOES</scope></search><sort><creationdate>200802</creationdate><title>MRS quality assessment in a multicentre study on MRS-based classification of brain tumours</title><author>van der Graaf, Marinette ; Julià-Sapé, Margarida ; Howe, Franklyn A. ; Ziegler, Anne ; Majós, Carles ; Moreno-Torres, Angel ; Rijpkema, Mark ; Acosta, Dionisio ; Opstad, Kirstie S. ; van der Meulen, Yvonne M. ; Arús, Carles ; Heerschap, Arend</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4592-8327a4d2a7218502ec43510623bec6a22a5f699dcf4a808fc00e525c0fd007b03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>1H MRS</topic><topic>Bioengineering</topic><topic>Brain Neoplasms</topic><topic>Brain Neoplasms - classification</topic><topic>Brain Neoplasms - diagnosis</topic><topic>Cancer</topic><topic>Clinical Protocols</topic><topic>Clinical Protocols - standards</topic><topic>Databases, Factual</topic><topic>Databases, Factual - standards</topic><topic>Equipment Failure Analysis</topic><topic>European Union</topic><topic>Expert Systems</topic><topic>Humans</topic><topic>Imaging</topic><topic>Life Sciences</topic><topic>Magnetic Resonance Spectroscopy</topic><topic>Magnetic Resonance Spectroscopy - instrumentation</topic><topic>Magnetic Resonance Spectroscopy - standards</topic><topic>MR spectra</topic><topic>Multicenter Studies as Topic</topic><topic>Multicenter Studies as Topic - standards</topic><topic>multicentre study</topic><topic>Pattern Recognition, Automated</topic><topic>Pattern Recognition, Automated - standards</topic><topic>phantom</topic><topic>Phantoms, Imaging</topic><topic>Program Evaluation</topic><topic>Protons</topic><topic>quality assessment</topic><topic>Quality Control</topic><topic>Reference Standards</topic><topic>Reproducibility of Results</topic><topic>Software</topic><topic>system quality assurance</topic><topic>Water</topic><topic>Water - analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>van der Graaf, Marinette</creatorcontrib><creatorcontrib>Julià-Sapé, Margarida</creatorcontrib><creatorcontrib>Howe, Franklyn A.</creatorcontrib><creatorcontrib>Ziegler, Anne</creatorcontrib><creatorcontrib>Majós, Carles</creatorcontrib><creatorcontrib>Moreno-Torres, Angel</creatorcontrib><creatorcontrib>Rijpkema, Mark</creatorcontrib><creatorcontrib>Acosta, Dionisio</creatorcontrib><creatorcontrib>Opstad, Kirstie S.</creatorcontrib><creatorcontrib>van der Meulen, Yvonne M.</creatorcontrib><creatorcontrib>Arús, Carles</creatorcontrib><creatorcontrib>Heerschap, Arend</creatorcontrib><collection>Istex</collection><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>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>NMR in biomedicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>van der Graaf, Marinette</au><au>Julià-Sapé, Margarida</au><au>Howe, Franklyn A.</au><au>Ziegler, Anne</au><au>Majós, Carles</au><au>Moreno-Torres, Angel</au><au>Rijpkema, Mark</au><au>Acosta, Dionisio</au><au>Opstad, Kirstie S.</au><au>van der Meulen, Yvonne M.</au><au>Arús, Carles</au><au>Heerschap, Arend</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MRS quality assessment in a multicentre study on MRS-based classification of brain tumours</atitle><jtitle>NMR in biomedicine</jtitle><addtitle>NMR Biomed</addtitle><date>2008-02</date><risdate>2008</risdate><volume>21</volume><issue>2</issue><spage>148</spage><epage>158</epage><pages>148-158</pages><issn>0952-3480</issn><eissn>1099-1492</eissn><abstract>This paper reports on quality assessment of MRS in the European Union‐funded multicentre project INTERPRET (International Network for Pattern Recognition of Tumours Using Magnetic Resonance; http://azizu.uab.es/INTERPRET), which has developed brain tumour classification software using in vivo proton MR spectra. The quality assessment consisted of both MR system quality assurance (SQA) and quality control (QC) of spectral data acquired from patients and healthy volunteers. The system performance of the MR spectrometers at all participating centres was checked bimonthly by a short measurement protocol using a specially designed INTERPRET phantom. In addition, a more extended SQA protocol was performed yearly and after each hardware or software upgrade. To compare the system performance for in vivo measurements, each centre acquired MR spectra from the brain of five healthy volunteers. All MR systems fulfilled generally accepted minimal system performance for brain MRS during the entire data acquisition period. The QC procedure of the MR spectra in the database comprised automatic determination of the signal‐to‐noise ratio (SNR) in a water‐suppressed spectrum and of the line width of the water resonance (water band width, WBW) in the corresponding non‐suppressed spectrum. Values of SNR > 10 and WBW < 8 Hz at 1.5 T were determined empirically as conservative threshold levels required for spectra to be of acceptable quality. These thresholds only hold for SNR and WBW values using the definitions and data processing described in this article. A final QC check consisted of visual inspection of each clinically validated water‐suppressed metabolite spectrum by two, or, in the case of disagreement, three, experienced MR spectroscopists, to detect artefacts such as large baseline distortions, exceptionally broadened metabolite peaks, insufficient removal of the water line, large phase errors, and signals originating from outside the voxel. In the end, 10% of 889 spectra with completed spectroscopic judgement were discarded. Copyright © 2007 John Wiley & Sons, Ltd.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><pmid>17458918</pmid><doi>10.1002/nbm.1172</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0952-3480 |
| ispartof | NMR in biomedicine, 2008-02, Vol.21 (2), p.148-158 |
| issn | 0952-3480 1099-1492 |
| language | eng |
| recordid | cdi_hal_primary_oai_HAL_inserm_00381415v1 |
| source | MEDLINE; Wiley Online Library Journals Frontfile Complete |
| subjects | 1H MRS Bioengineering Brain Neoplasms Brain Neoplasms - classification Brain Neoplasms - diagnosis Cancer Clinical Protocols Clinical Protocols - standards Databases, Factual Databases, Factual - standards Equipment Failure Analysis European Union Expert Systems Humans Imaging Life Sciences Magnetic Resonance Spectroscopy Magnetic Resonance Spectroscopy - instrumentation Magnetic Resonance Spectroscopy - standards MR spectra Multicenter Studies as Topic Multicenter Studies as Topic - standards multicentre study Pattern Recognition, Automated Pattern Recognition, Automated - standards phantom Phantoms, Imaging Program Evaluation Protons quality assessment Quality Control Reference Standards Reproducibility of Results Software system quality assurance Water Water - analysis |
| title | MRS quality assessment in a multicentre study on MRS-based classification of brain tumours |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-20T18%3A31%3A29IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_hal_p&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=MRS%20quality%20assessment%20in%20a%20multicentre%20study%20on%20MRS-based%20classification%20of%20brain%20tumours&rft.jtitle=NMR%20in%20biomedicine&rft.au=van%20der%20Graaf,%20Marinette&rft.date=2008-02&rft.volume=21&rft.issue=2&rft.spage=148&rft.epage=158&rft.pages=148-158&rft.issn=0952-3480&rft.eissn=1099-1492&rft_id=info:doi/10.1002/nbm.1172&rft_dat=%3Cproquest_hal_p%3E70290076%3C/proquest_hal_p%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=21067267&rft_id=info:pmid/17458918&rfr_iscdi=true |