Denoising of diffusion MRI improves peripheral nerve conspicuity and reproducibility

Background Quantitative diffusion MRI is a promising technique for evaluating peripheral nerve integrity but low signal‐to‐noise ratio (SNR) can impede measurement accuracy. Purpose To evaluate principal component analysis (PCA) and generalized spherical deconvolution (genSD) denoising techniques to...

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Veröffentlicht in:Journal of magnetic resonance imaging 2020-04, Vol.51 (4), p.1128-1137
Hauptverfasser: Sneag, Darryl B., Zochowski, Kelly C., Tan, Ek T., Queler, Sophie C., Burge, Alissa, Endo, Yoshimi, Lin, Bin, Fung, Maggie, Shin, Jaemin
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container_end_page 1137
container_issue 4
container_start_page 1128
container_title Journal of magnetic resonance imaging
container_volume 51
creator Sneag, Darryl B.
Zochowski, Kelly C.
Tan, Ek T.
Queler, Sophie C.
Burge, Alissa
Endo, Yoshimi
Lin, Bin
Fung, Maggie
Shin, Jaemin
description Background Quantitative diffusion MRI is a promising technique for evaluating peripheral nerve integrity but low signal‐to‐noise ratio (SNR) can impede measurement accuracy. Purpose To evaluate principal component analysis (PCA) and generalized spherical deconvolution (genSD) denoising techniques to improve within‐subject reproducibility and peripheral nerve conspicuity. Study Type Prospective. Subjects Seven healthy volunteers and three peripheral neuropathy patients. Field Strength/Sequence 3T/multiband single‐shot echo planar diffusion sequence using multishell 55‐direction scheme. Assessment Images were processed using four methods: "original" (no denoising), "average" (10 repetitions), "PCA‐only," and "PCA + genSD." Tibial and common peroneal nerve segmentations and masks were generated from volunteer diffusion data. Quantitative (SNR and contrast‐to‐noise ratio [CNR]) values were calculated. Three radiologists qualitatively evaluated nerve conspicuity for each method. The two denoising methods were also performed in three patients with peripheral neuropathies. Statistical Tests For healthy volunteers, calculations included SNR and CNRFA (computed using FA values). Coefficient of variation (CV%) of CNRFA quantified within‐subject reproducibility. Groups were compared with two‐sample t‐tests (significance P < 0.05; two‐tailed, Bonferroni‐corrected). Odds ratios (ORs) quantified the relative rates of each of three radiologists confidently identifying a nerve, per slice, for the four methods. Results "PCA + genSD" yielded the highest SNR (meanoverall = 14.83 ± 1.99) and tibial and common peroneal nerve CNRFA (meantibial = 3.45, meanperoneal = 2.34) compared to "original" (P SNR < 0.001; P CNR = 0.011) and "PCA‐only" (P SNR < 0.001, P CNR < 0.001). "PCA + genSD" had higher within‐subject reproducibility (low CV%) for tibial (6.04 ± 1.98) and common peroneal nerves (8.27 ± 2.75) compared to "original" and "PCA‐only." The mean FA was higher for "original" than "average" (P < 0.001), but did not differ significantly between "average" and "PCA + genSD" (P = 0.14). "PCA + genSD" had higher tibial and common peroneal nerve conspicuity than "PCA‐only" (ORtibial = 2.50, P < 0.001; ORperoneal = 1.86, P < 0.001) and "original" (ORtibial = 2.73, P < 0.001; ORperoneal = 2.43, P < 0.001). Data Conclusion PCA + genSD denoising method improved SNR, CNRFA, and within‐subject reproducibility (CV%) without biasing FA and nerve conspicuity. This technique holds promise for
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Purpose To evaluate principal component analysis (PCA) and generalized spherical deconvolution (genSD) denoising techniques to improve within‐subject reproducibility and peripheral nerve conspicuity. Study Type Prospective. Subjects Seven healthy volunteers and three peripheral neuropathy patients. Field Strength/Sequence 3T/multiband single‐shot echo planar diffusion sequence using multishell 55‐direction scheme. Assessment Images were processed using four methods: "original" (no denoising), "average" (10 repetitions), "PCA‐only," and "PCA + genSD." Tibial and common peroneal nerve segmentations and masks were generated from volunteer diffusion data. Quantitative (SNR and contrast‐to‐noise ratio [CNR]) values were calculated. Three radiologists qualitatively evaluated nerve conspicuity for each method. The two denoising methods were also performed in three patients with peripheral neuropathies. Statistical Tests For healthy volunteers, calculations included SNR and CNRFA (computed using FA values). Coefficient of variation (CV%) of CNRFA quantified within‐subject reproducibility. Groups were compared with two‐sample t‐tests (significance P < 0.05; two‐tailed, Bonferroni‐corrected). Odds ratios (ORs) quantified the relative rates of each of three radiologists confidently identifying a nerve, per slice, for the four methods. Results "PCA + genSD" yielded the highest SNR (meanoverall = 14.83 ± 1.99) and tibial and common peroneal nerve CNRFA (meantibial = 3.45, meanperoneal = 2.34) compared to "original" (P SNR < 0.001; P CNR = 0.011) and "PCA‐only" (P SNR < 0.001, P CNR < 0.001). "PCA + genSD" had higher within‐subject reproducibility (low CV%) for tibial (6.04 ± 1.98) and common peroneal nerves (8.27 ± 2.75) compared to "original" and "PCA‐only." The mean FA was higher for "original" than "average" (P < 0.001), but did not differ significantly between "average" and "PCA + genSD" (P = 0.14). "PCA + genSD" had higher tibial and common peroneal nerve conspicuity than "PCA‐only" (ORtibial = 2.50, P < 0.001; ORperoneal = 1.86, P < 0.001) and "original" (ORtibial = 2.73, P < 0.001; ORperoneal = 2.43, P < 0.001). Data Conclusion PCA + genSD denoising method improved SNR, CNRFA, and within‐subject reproducibility (CV%) without biasing FA and nerve conspicuity. This technique holds promise for facilitating more reliable, unbiased diffusion measurements of peripheral nerves. Level of Evidence: 2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:1128–1137.]]></description><identifier>ISSN: 1053-1807</identifier><identifier>EISSN: 1522-2586</identifier><identifier>DOI: 10.1002/jmri.26965</identifier><identifier>PMID: 31654542</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley &amp; Sons, Inc</publisher><subject>Coefficient of variation ; Conspicuity ; denoising ; Diffusion ; Diffusion Magnetic Resonance Imaging ; diffusion tensor imaging ; Evaluation ; Field strength ; Humans ; Identification methods ; Magnetic resonance imaging ; Masks ; Mathematical analysis ; MRI ; Noise ; Noise reduction ; peripheral nerve ; Peripheral nerves ; Peripheral Nervous System Diseases - diagnostic imaging ; Peripheral neuropathy ; Peroneal nerve ; Principal components analysis ; Prospective Studies ; Reproducibility ; Reproducibility of Results ; Signal-To-Noise Ratio ; Statistical analysis ; Statistical tests</subject><ispartof>Journal of magnetic resonance imaging, 2020-04, Vol.51 (4), p.1128-1137</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-c3575-2eb0f578477927c4379f151edda8a6627af7cb96a8a258e3b4d62f11689facc33</citedby><cites>FETCH-LOGICAL-c3575-2eb0f578477927c4379f151edda8a6627af7cb96a8a258e3b4d62f11689facc33</cites><orcidid>0000-0002-1457-4318</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.26965$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjmri.26965$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27903,27904,45553,45554</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31654542$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sneag, Darryl B.</creatorcontrib><creatorcontrib>Zochowski, Kelly C.</creatorcontrib><creatorcontrib>Tan, Ek T.</creatorcontrib><creatorcontrib>Queler, Sophie C.</creatorcontrib><creatorcontrib>Burge, Alissa</creatorcontrib><creatorcontrib>Endo, Yoshimi</creatorcontrib><creatorcontrib>Lin, Bin</creatorcontrib><creatorcontrib>Fung, Maggie</creatorcontrib><creatorcontrib>Shin, Jaemin</creatorcontrib><title>Denoising of diffusion MRI improves peripheral nerve conspicuity and reproducibility</title><title>Journal of magnetic resonance imaging</title><addtitle>J Magn Reson Imaging</addtitle><description><![CDATA[Background Quantitative diffusion MRI is a promising technique for evaluating peripheral nerve integrity but low signal‐to‐noise ratio (SNR) can impede measurement accuracy. Purpose To evaluate principal component analysis (PCA) and generalized spherical deconvolution (genSD) denoising techniques to improve within‐subject reproducibility and peripheral nerve conspicuity. Study Type Prospective. Subjects Seven healthy volunteers and three peripheral neuropathy patients. Field Strength/Sequence 3T/multiband single‐shot echo planar diffusion sequence using multishell 55‐direction scheme. Assessment Images were processed using four methods: "original" (no denoising), "average" (10 repetitions), "PCA‐only," and "PCA + genSD." Tibial and common peroneal nerve segmentations and masks were generated from volunteer diffusion data. Quantitative (SNR and contrast‐to‐noise ratio [CNR]) values were calculated. Three radiologists qualitatively evaluated nerve conspicuity for each method. The two denoising methods were also performed in three patients with peripheral neuropathies. Statistical Tests For healthy volunteers, calculations included SNR and CNRFA (computed using FA values). Coefficient of variation (CV%) of CNRFA quantified within‐subject reproducibility. Groups were compared with two‐sample t‐tests (significance P < 0.05; two‐tailed, Bonferroni‐corrected). Odds ratios (ORs) quantified the relative rates of each of three radiologists confidently identifying a nerve, per slice, for the four methods. Results "PCA + genSD" yielded the highest SNR (meanoverall = 14.83 ± 1.99) and tibial and common peroneal nerve CNRFA (meantibial = 3.45, meanperoneal = 2.34) compared to "original" (P SNR < 0.001; P CNR = 0.011) and "PCA‐only" (P SNR < 0.001, P CNR < 0.001). "PCA + genSD" had higher within‐subject reproducibility (low CV%) for tibial (6.04 ± 1.98) and common peroneal nerves (8.27 ± 2.75) compared to "original" and "PCA‐only." The mean FA was higher for "original" than "average" (P < 0.001), but did not differ significantly between "average" and "PCA + genSD" (P = 0.14). "PCA + genSD" had higher tibial and common peroneal nerve conspicuity than "PCA‐only" (ORtibial = 2.50, P < 0.001; ORperoneal = 1.86, P < 0.001) and "original" (ORtibial = 2.73, P < 0.001; ORperoneal = 2.43, P < 0.001). Data Conclusion PCA + genSD denoising method improved SNR, CNRFA, and within‐subject reproducibility (CV%) without biasing FA and nerve conspicuity. This technique holds promise for facilitating more reliable, unbiased diffusion measurements of peripheral nerves. Level of Evidence: 2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:1128–1137.]]></description><subject>Coefficient of variation</subject><subject>Conspicuity</subject><subject>denoising</subject><subject>Diffusion</subject><subject>Diffusion Magnetic Resonance Imaging</subject><subject>diffusion tensor imaging</subject><subject>Evaluation</subject><subject>Field strength</subject><subject>Humans</subject><subject>Identification methods</subject><subject>Magnetic resonance imaging</subject><subject>Masks</subject><subject>Mathematical analysis</subject><subject>MRI</subject><subject>Noise</subject><subject>Noise reduction</subject><subject>peripheral nerve</subject><subject>Peripheral nerves</subject><subject>Peripheral Nervous System Diseases - diagnostic imaging</subject><subject>Peripheral neuropathy</subject><subject>Peroneal nerve</subject><subject>Principal components analysis</subject><subject>Prospective Studies</subject><subject>Reproducibility</subject><subject>Reproducibility of Results</subject><subject>Signal-To-Noise Ratio</subject><subject>Statistical analysis</subject><subject>Statistical tests</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>eNp9kMtKAzEUQIMotlY3foAE3IgwNclMkslS6puKILoeMpkbTZmXiVPp35tadeHCVR4cTm4OQoeUTCkh7GzReDdlQgm-hcaUM5YwnovtuCc8TWhO5AjthbAghCiV8V00SqngGc_YGD1dQNu54NoX3FlcOWuH4LoW3z_eYtf0vltCwD1417-C1zVuwS8Bm64NvTODe19h3VbYQySrwbjS1fFuH-1YXQc4-F4n6Pnq8ml2k8wfrm9n5_PEpFzyhEFJLJd5JqVi0mSpVJZyClWlcy0Ek9pKUyoRT_FDkJZZJZilVOTKamPSdIJONt74-tsA4b1oXDBQ17qFbggFS4nK1Nof0eM_6KIbfBuni5TkklIl8kidbijjuxA82KL3rtF-VVBSrFsX69bFV-sIH30rh7KB6hf9iRsBugE-XA2rf1TFXcy9kX4CtBGJ3g</recordid><startdate>202004</startdate><enddate>202004</enddate><creator>Sneag, Darryl B.</creator><creator>Zochowski, Kelly C.</creator><creator>Tan, Ek T.</creator><creator>Queler, Sophie C.</creator><creator>Burge, Alissa</creator><creator>Endo, Yoshimi</creator><creator>Lin, Bin</creator><creator>Fung, Maggie</creator><creator>Shin, Jaemin</creator><general>John Wiley &amp; 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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>Sneag, Darryl B.</au><au>Zochowski, Kelly C.</au><au>Tan, Ek T.</au><au>Queler, Sophie C.</au><au>Burge, Alissa</au><au>Endo, Yoshimi</au><au>Lin, Bin</au><au>Fung, Maggie</au><au>Shin, Jaemin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Denoising of diffusion MRI improves peripheral nerve conspicuity and reproducibility</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>1128</spage><epage>1137</epage><pages>1128-1137</pages><issn>1053-1807</issn><eissn>1522-2586</eissn><abstract><![CDATA[Background Quantitative diffusion MRI is a promising technique for evaluating peripheral nerve integrity but low signal‐to‐noise ratio (SNR) can impede measurement accuracy. Purpose To evaluate principal component analysis (PCA) and generalized spherical deconvolution (genSD) denoising techniques to improve within‐subject reproducibility and peripheral nerve conspicuity. Study Type Prospective. Subjects Seven healthy volunteers and three peripheral neuropathy patients. Field Strength/Sequence 3T/multiband single‐shot echo planar diffusion sequence using multishell 55‐direction scheme. Assessment Images were processed using four methods: "original" (no denoising), "average" (10 repetitions), "PCA‐only," and "PCA + genSD." Tibial and common peroneal nerve segmentations and masks were generated from volunteer diffusion data. Quantitative (SNR and contrast‐to‐noise ratio [CNR]) values were calculated. Three radiologists qualitatively evaluated nerve conspicuity for each method. The two denoising methods were also performed in three patients with peripheral neuropathies. Statistical Tests For healthy volunteers, calculations included SNR and CNRFA (computed using FA values). Coefficient of variation (CV%) of CNRFA quantified within‐subject reproducibility. Groups were compared with two‐sample t‐tests (significance P < 0.05; two‐tailed, Bonferroni‐corrected). Odds ratios (ORs) quantified the relative rates of each of three radiologists confidently identifying a nerve, per slice, for the four methods. Results "PCA + genSD" yielded the highest SNR (meanoverall = 14.83 ± 1.99) and tibial and common peroneal nerve CNRFA (meantibial = 3.45, meanperoneal = 2.34) compared to "original" (P SNR < 0.001; P CNR = 0.011) and "PCA‐only" (P SNR < 0.001, P CNR < 0.001). "PCA + genSD" had higher within‐subject reproducibility (low CV%) for tibial (6.04 ± 1.98) and common peroneal nerves (8.27 ± 2.75) compared to "original" and "PCA‐only." The mean FA was higher for "original" than "average" (P < 0.001), but did not differ significantly between "average" and "PCA + genSD" (P = 0.14). "PCA + genSD" had higher tibial and common peroneal nerve conspicuity than "PCA‐only" (ORtibial = 2.50, P < 0.001; ORperoneal = 1.86, P < 0.001) and "original" (ORtibial = 2.73, P < 0.001; ORperoneal = 2.43, P < 0.001). Data Conclusion PCA + genSD denoising method improved SNR, CNRFA, and within‐subject reproducibility (CV%) without biasing FA and nerve conspicuity. This technique holds promise for facilitating more reliable, unbiased diffusion measurements of peripheral nerves. Level of Evidence: 2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:1128–1137.]]></abstract><cop>Hoboken, USA</cop><pub>John Wiley &amp; Sons, Inc</pub><pmid>31654542</pmid><doi>10.1002/jmri.26965</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-1457-4318</orcidid></addata></record>
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subjects Coefficient of variation
Conspicuity
denoising
Diffusion
Diffusion Magnetic Resonance Imaging
diffusion tensor imaging
Evaluation
Field strength
Humans
Identification methods
Magnetic resonance imaging
Masks
Mathematical analysis
MRI
Noise
Noise reduction
peripheral nerve
Peripheral nerves
Peripheral Nervous System Diseases - diagnostic imaging
Peripheral neuropathy
Peroneal nerve
Principal components analysis
Prospective Studies
Reproducibility
Reproducibility of Results
Signal-To-Noise Ratio
Statistical analysis
Statistical tests
title Denoising of diffusion MRI improves peripheral nerve conspicuity and reproducibility
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