Comparison of Perfusion- and Diffusion-weighted Imaging Parameters in Brain Tumor Studies Processed Using Different Software Platforms

Rationale and Objectives To compare quantitative imaging parameter measures from diffusion- and perfusion-weighted imaging magnetic resonance imaging (MRI) sequences in subjects with brain tumors that have been processed with different software platforms. Materials and Methods Scans from 20 subjects...

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Veröffentlicht in:Academic radiology 2014-10, Vol.21 (10), p.1294-1303
Hauptverfasser: Milchenko, Mikhail V., PhD, Rajderkar, Dhanashree, MD, LaMontagne, Pamela, PhD, Massoumzadeh, Parinaz, PhD, Bogdasarian, Ronald, BA, Schweitzer, Gordon, BME, Benzinger, Tammie, MD, PhD, Marcus, Dan, PhD, Shimony, Joshua S., MD, PhD, Fouke, Sarah Jost, MD
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container_end_page 1303
container_issue 10
container_start_page 1294
container_title Academic radiology
container_volume 21
creator Milchenko, Mikhail V., PhD
Rajderkar, Dhanashree, MD
LaMontagne, Pamela, PhD
Massoumzadeh, Parinaz, PhD
Bogdasarian, Ronald, BA
Schweitzer, Gordon, BME
Benzinger, Tammie, MD, PhD
Marcus, Dan, PhD
Shimony, Joshua S., MD, PhD
Fouke, Sarah Jost, MD
description Rationale and Objectives To compare quantitative imaging parameter measures from diffusion- and perfusion-weighted imaging magnetic resonance imaging (MRI) sequences in subjects with brain tumors that have been processed with different software platforms. Materials and Methods Scans from 20 subjects with primary brain tumors were selected from the Comprehensive Neuro-oncology Data Repository at Washington University School of Medicine (WUSM) and the Swedish Neuroscience Institute. MR images were coregistered, and each subject's data set was processed by three software packages: 1) vendor-specific scanner software, 2) research software developed at WUSM, and 3) a commercially available, Food and Drug Administration–approved, processing platform (Nordic Ice). Regions of interest (ROIs) were chosen within the brain tumor and normal nontumor tissue. The results obtained using these methods were compared. Results For diffusion parameters, including mean diffusivity and fractional anisotropy, concordance was high when comparing different processing methods. For perfusion-imaging parameters, a significant variance in cerebral blood volume, cerebral blood flow, and mean transit time (MTT) values was seen when comparing the same raw data processed using different software platforms. Correlation was better with larger ROIs (radii ≥ 5 mm). Greatest variance was observed in MTT. Conclusions Diffusion parameter values were consistent across different software processing platforms. Perfusion parameter values were more variable and were influenced by the software used. Variation in the MTT was especially large suggesting that MTT estimation may be unreliable in tumor tissues using current MRI perfusion methods.
doi_str_mv 10.1016/j.acra.2014.05.016
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Materials and Methods Scans from 20 subjects with primary brain tumors were selected from the Comprehensive Neuro-oncology Data Repository at Washington University School of Medicine (WUSM) and the Swedish Neuroscience Institute. MR images were coregistered, and each subject's data set was processed by three software packages: 1) vendor-specific scanner software, 2) research software developed at WUSM, and 3) a commercially available, Food and Drug Administration–approved, processing platform (Nordic Ice). Regions of interest (ROIs) were chosen within the brain tumor and normal nontumor tissue. The results obtained using these methods were compared. Results For diffusion parameters, including mean diffusivity and fractional anisotropy, concordance was high when comparing different processing methods. For perfusion-imaging parameters, a significant variance in cerebral blood volume, cerebral blood flow, and mean transit time (MTT) values was seen when comparing the same raw data processed using different software platforms. Correlation was better with larger ROIs (radii ≥ 5 mm). Greatest variance was observed in MTT. Conclusions Diffusion parameter values were consistent across different software processing platforms. Perfusion parameter values were more variable and were influenced by the software used. Variation in the MTT was especially large suggesting that MTT estimation may be unreliable in tumor tissues using current MRI perfusion methods.</description><identifier>ISSN: 1076-6332</identifier><identifier>EISSN: 1878-4046</identifier><identifier>DOI: 10.1016/j.acra.2014.05.016</identifier><identifier>PMID: 25088833</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Algorithms ; Blood Flow Velocity ; Brain Neoplasms - diagnosis ; Brain Neoplasms - physiopathology ; cerebral diffusion ; cerebral perfusion ; Cerebrovascular Circulation ; Diffusion Magnetic Resonance Imaging - methods ; Humans ; Image Interpretation, Computer-Assisted - methods ; Magnetic Resonance Angiography - methods ; MRI ; Radiology ; Reproducibility of Results ; Sensitivity and Specificity ; Software ; Software Validation ; Tumor imaging</subject><ispartof>Academic radiology, 2014-10, Vol.21 (10), p.1294-1303</ispartof><rights>AUR</rights><rights>2014 AUR</rights><rights>Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c580t-8ceb869e026ef4be879554ebf67a7dc092ea624fbde2098932903ffd8824e71f3</citedby><cites>FETCH-LOGICAL-c580t-8ceb869e026ef4be879554ebf67a7dc092ea624fbde2098932903ffd8824e71f3</cites><orcidid>0000-0002-8114-0552</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1076633214002219$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25088833$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Milchenko, Mikhail V., PhD</creatorcontrib><creatorcontrib>Rajderkar, Dhanashree, MD</creatorcontrib><creatorcontrib>LaMontagne, Pamela, PhD</creatorcontrib><creatorcontrib>Massoumzadeh, Parinaz, PhD</creatorcontrib><creatorcontrib>Bogdasarian, Ronald, BA</creatorcontrib><creatorcontrib>Schweitzer, Gordon, BME</creatorcontrib><creatorcontrib>Benzinger, Tammie, MD, PhD</creatorcontrib><creatorcontrib>Marcus, Dan, PhD</creatorcontrib><creatorcontrib>Shimony, Joshua S., MD, PhD</creatorcontrib><creatorcontrib>Fouke, Sarah Jost, MD</creatorcontrib><title>Comparison of Perfusion- and Diffusion-weighted Imaging Parameters in Brain Tumor Studies Processed Using Different Software Platforms</title><title>Academic radiology</title><addtitle>Acad Radiol</addtitle><description>Rationale and Objectives To compare quantitative imaging parameter measures from diffusion- and perfusion-weighted imaging magnetic resonance imaging (MRI) sequences in subjects with brain tumors that have been processed with different software platforms. Materials and Methods Scans from 20 subjects with primary brain tumors were selected from the Comprehensive Neuro-oncology Data Repository at Washington University School of Medicine (WUSM) and the Swedish Neuroscience Institute. MR images were coregistered, and each subject's data set was processed by three software packages: 1) vendor-specific scanner software, 2) research software developed at WUSM, and 3) a commercially available, Food and Drug Administration–approved, processing platform (Nordic Ice). Regions of interest (ROIs) were chosen within the brain tumor and normal nontumor tissue. The results obtained using these methods were compared. Results For diffusion parameters, including mean diffusivity and fractional anisotropy, concordance was high when comparing different processing methods. For perfusion-imaging parameters, a significant variance in cerebral blood volume, cerebral blood flow, and mean transit time (MTT) values was seen when comparing the same raw data processed using different software platforms. Correlation was better with larger ROIs (radii ≥ 5 mm). Greatest variance was observed in MTT. Conclusions Diffusion parameter values were consistent across different software processing platforms. Perfusion parameter values were more variable and were influenced by the software used. 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Rajderkar, Dhanashree, MD ; LaMontagne, Pamela, PhD ; Massoumzadeh, Parinaz, PhD ; Bogdasarian, Ronald, BA ; Schweitzer, Gordon, BME ; Benzinger, Tammie, MD, PhD ; Marcus, Dan, PhD ; Shimony, Joshua S., MD, PhD ; Fouke, Sarah Jost, MD</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c580t-8ceb869e026ef4be879554ebf67a7dc092ea624fbde2098932903ffd8824e71f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Algorithms</topic><topic>Blood Flow Velocity</topic><topic>Brain Neoplasms - diagnosis</topic><topic>Brain Neoplasms - physiopathology</topic><topic>cerebral diffusion</topic><topic>cerebral perfusion</topic><topic>Cerebrovascular Circulation</topic><topic>Diffusion Magnetic Resonance Imaging - methods</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Magnetic Resonance Angiography - methods</topic><topic>MRI</topic><topic>Radiology</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Software</topic><topic>Software Validation</topic><topic>Tumor imaging</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Milchenko, Mikhail V., PhD</creatorcontrib><creatorcontrib>Rajderkar, Dhanashree, MD</creatorcontrib><creatorcontrib>LaMontagne, Pamela, PhD</creatorcontrib><creatorcontrib>Massoumzadeh, Parinaz, PhD</creatorcontrib><creatorcontrib>Bogdasarian, Ronald, BA</creatorcontrib><creatorcontrib>Schweitzer, Gordon, BME</creatorcontrib><creatorcontrib>Benzinger, Tammie, MD, PhD</creatorcontrib><creatorcontrib>Marcus, Dan, PhD</creatorcontrib><creatorcontrib>Shimony, Joshua S., MD, PhD</creatorcontrib><creatorcontrib>Fouke, Sarah Jost, MD</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Academic radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Milchenko, Mikhail V., PhD</au><au>Rajderkar, Dhanashree, MD</au><au>LaMontagne, Pamela, PhD</au><au>Massoumzadeh, Parinaz, PhD</au><au>Bogdasarian, Ronald, BA</au><au>Schweitzer, Gordon, BME</au><au>Benzinger, Tammie, MD, PhD</au><au>Marcus, Dan, PhD</au><au>Shimony, Joshua S., MD, PhD</au><au>Fouke, Sarah Jost, MD</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison of Perfusion- and Diffusion-weighted Imaging Parameters in Brain Tumor Studies Processed Using Different Software Platforms</atitle><jtitle>Academic radiology</jtitle><addtitle>Acad Radiol</addtitle><date>2014-10-01</date><risdate>2014</risdate><volume>21</volume><issue>10</issue><spage>1294</spage><epage>1303</epage><pages>1294-1303</pages><issn>1076-6332</issn><eissn>1878-4046</eissn><abstract>Rationale and Objectives To compare quantitative imaging parameter measures from diffusion- and perfusion-weighted imaging magnetic resonance imaging (MRI) sequences in subjects with brain tumors that have been processed with different software platforms. Materials and Methods Scans from 20 subjects with primary brain tumors were selected from the Comprehensive Neuro-oncology Data Repository at Washington University School of Medicine (WUSM) and the Swedish Neuroscience Institute. MR images were coregistered, and each subject's data set was processed by three software packages: 1) vendor-specific scanner software, 2) research software developed at WUSM, and 3) a commercially available, Food and Drug Administration–approved, processing platform (Nordic Ice). Regions of interest (ROIs) were chosen within the brain tumor and normal nontumor tissue. The results obtained using these methods were compared. Results For diffusion parameters, including mean diffusivity and fractional anisotropy, concordance was high when comparing different processing methods. For perfusion-imaging parameters, a significant variance in cerebral blood volume, cerebral blood flow, and mean transit time (MTT) values was seen when comparing the same raw data processed using different software platforms. Correlation was better with larger ROIs (radii ≥ 5 mm). Greatest variance was observed in MTT. Conclusions Diffusion parameter values were consistent across different software processing platforms. Perfusion parameter values were more variable and were influenced by the software used. Variation in the MTT was especially large suggesting that MTT estimation may be unreliable in tumor tissues using current MRI perfusion methods.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>25088833</pmid><doi>10.1016/j.acra.2014.05.016</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-8114-0552</orcidid><oa>free_for_read</oa></addata></record>
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source MEDLINE; Elsevier ScienceDirect Journals
subjects Algorithms
Blood Flow Velocity
Brain Neoplasms - diagnosis
Brain Neoplasms - physiopathology
cerebral diffusion
cerebral perfusion
Cerebrovascular Circulation
Diffusion Magnetic Resonance Imaging - methods
Humans
Image Interpretation, Computer-Assisted - methods
Magnetic Resonance Angiography - methods
MRI
Radiology
Reproducibility of Results
Sensitivity and Specificity
Software
Software Validation
Tumor imaging
title Comparison of Perfusion- and Diffusion-weighted Imaging Parameters in Brain Tumor Studies Processed Using Different Software Platforms
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