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<meta name="HW.identifier" content="/ajnr/early/2021/08/19/ajnr.A7230.atom" />
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<meta name="DC.Title" content="Automating Quantitative Measures of an Established Conventional MRI Scoring System for Preterm-Born Infants Scanned between 29 and 47 Weeks’ Postmenstrual Age" />
<meta name="DC.Identifier" content="10.3174/ajnr.A7230" />
<meta name="DC.Date" content="2021-08-19" />
<meta name="DC.Publisher" content="American Journal of Neuroradiology" />
<meta name="DC.Rights" content="© 2021 by American Journal of Neuroradiology. Indicates open access to non-subscribers at www.ajnr.org" />
<meta name="DC.AccessRights" content="open-access" />
<meta name="DC.Description" content="BACKGROUND AND PURPOSE: Conventional MR imaging scoring is a valuable tool for risk stratification and prognostication of outcomes, but manual scoring is time-consuming, operator-dependent, and requires high-level expertise. This study aimed to automate the regional measurements of an established brain MR imaging scoring system for preterm neonates scanned between 29 and 47 weeks’ postmenstrual age.

MATERIALS AND METHODS: This study used T2WI from the longitudinal Prediction of PREterm Motor Outcomes cohort study and the developing Human Connectome Project. Measures of biparietal width, interhemispheric distance, callosal thickness, transcerebellar diameter, lateral ventricular diameter, and deep gray matter area were extracted manually (Prediction of PREterm Motor Outcomes study only) and automatically. Scans with poor quality, failure of automated analysis, or severe pathology were excluded. Agreement, reliability, and associations between manual and automated measures were assessed and compared against statistics for manual measures. Associations between measures with postmenstrual age, gestational age at birth, and birth weight were examined (Pearson correlation) in both cohorts.

RESULTS: A total of 652 MRIs (86%) were suitable for analysis. Automated measures showed good-to-excellent agreement and good reliability with manual measures, except for interhemispheric distance at early MR imaging (scanned between 29 and 35 weeks, postmenstrual age; in line with poor manual reliability) and callosal thickness measures. All measures were positively associated with postmenstrual age ( r  =   0.11–0.94; R2 = 0.01–0.89). Negative and positive associations were found with gestational age at birth ( r = –0.26–0.71; R2 = 0.05–0.52) and birth weight ( r = –0.25–0.75; R2 = 0.06–0.56). Automated measures were successfully extracted for 80%–99% of suitable scans.

CONCLUSIONS: Measures of brain injury and impaired brain growth can be automatically extracted from neonatal MR imaging, which could assist with clinical reporting.

DGMA
:   deep gray matter area
dHCP
:   developing Human Connectome Project
GA
:   gestational age at birth
ICC
:   intraclass correlation coefficient
LoA
:   95% limits of agreement
LVD
:   lateral ventricular diameter
PMA
:   postmenstrual age
PPREMO
:   Prediction of PREterm Motor Outcomes study
SEM
:   standard error of measurement
TEA
:   term-equivalent age" />
<meta name="DC.Contributor" content="L. van Eijk" />
<meta name="DC.Contributor" content="M. Seidel" />
<meta name="DC.Contributor" content="K. Pannek" />
<meta name="DC.Contributor" content="J.M. George" />
<meta name="DC.Contributor" content="S. Fiori" />
<meta name="DC.Contributor" content="A. Guzzetta" />
<meta name="DC.Contributor" content="A. Coulthard" />
<meta name="DC.Contributor" content="J. Bursle" />
<meta name="DC.Contributor" content="R.S. Ware" />
<meta name="DC.Contributor" content="D. Bradford" />
<meta name="DC.Contributor" content="S. Rose" />
<meta name="DC.Contributor" content="P.B. Colditz" />
<meta name="DC.Contributor" content="R.N. Boyd" />
<meta name="DC.Contributor" content="J. Fripp" />
<meta name="article:published_time" content="2021-08-19" />
<meta name="article:section" content="PEDIATRICS" />
<meta name="citation_title" content="Automating Quantitative Measures of an Established Conventional MRI Scoring System for Preterm-Born Infants Scanned between 29 and 47 Weeks’ Postmenstrual Age" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;Conventional MR imaging scoring is a valuable tool for risk stratification and prognostication of outcomes, but manual scoring is time-consuming, operator-dependent, and requires high-level expertise. This study aimed to automate the regional measurements of an established brain MR imaging scoring system for preterm neonates scanned between 29 and 47 weeks’ postmenstrual age.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;This study used T2WI from the longitudinal Prediction of PREterm Motor Outcomes cohort study and the developing Human Connectome Project. Measures of biparietal width, interhemispheric distance, callosal thickness, transcerebellar diameter, lateral ventricular diameter, and deep gray matter area were extracted manually (Prediction of PREterm Motor Outcomes study only) and automatically. Scans with poor quality, failure of automated analysis, or severe pathology were excluded. Agreement, reliability, and associations between manual and automated measures were assessed and compared against statistics for manual measures. Associations between measures with postmenstrual age, gestational age at birth, and birth weight were examined (Pearson correlation) in both cohorts.&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;A total of 652 MRIs (86%) were suitable for analysis. Automated measures showed good-to-excellent agreement and good reliability with manual measures, except for interhemispheric distance at early MR imaging (scanned between 29 and 35 weeks, postmenstrual age; in line with poor manual reliability) and callosal thickness measures. All measures were positively associated with postmenstrual age (&lt;i&gt;r &lt;/i&gt;=&lt;i&gt; &lt;/i&gt;0.11–0.94; &lt;i&gt;R&lt;sup&gt;2&lt;/sup&gt;&lt;/i&gt; = 0.01–0.89). Negative and positive associations were found with gestational age at birth (&lt;i&gt;r&lt;/i&gt; = –0.26–0.71; &lt;i&gt;R&lt;sup&gt;2&lt;/sup&gt; =&lt;/i&gt; 0.05–0.52) and birth weight (&lt;i&gt;r&lt;/i&gt; = –0.25–0.75; &lt;i&gt;R&lt;sup&gt;2&lt;/sup&gt; =&lt;/i&gt; 0.06–0.56). Automated measures were successfully extracted for 80%–99% of suitable scans.&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;Measures of brain injury and impaired brain growth can be automatically extracted from neonatal MR imaging, which could assist with clinical reporting.&lt;/p&gt;" />
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<meta name="twitter:title" content="Automating Quantitative Measures of an Established Conventional MRI Scoring System for Preterm-Born Infants Scanned between 29 and 47 Weeks’ Postmenstrual Age" />
<meta name="twitter:card" content="summary" />
<meta name="twitter:description" content="BACKGROUND AND PURPOSE: Conventional MR imaging scoring is a valuable tool for risk stratification and prognostication of outcomes, but manual scoring is time-consuming, operator-dependent, and requires high-level expertise. This study aimed to automate the regional measurements of an established brain MR imaging scoring system for preterm neonates scanned between 29 and 47 weeks’ postmenstrual age.

MATERIALS AND METHODS: This study used T2WI from the longitudinal Prediction of PREterm Motor Outcomes cohort study and the developing Human Connectome Project. Measures of biparietal width, interhemispheric distance, callosal thickness, transcerebellar diameter, lateral ventricular diameter, and deep gray matter area were extracted manually (Prediction of PREterm Motor Outcomes study only) and automatically. Scans with poor quality, failure of automated analysis, or severe pathology were excluded. Agreement, reliability, and associations between manual and automated measures were assessed and compared against statistics for manual measures. Associations between measures with postmenstrual age, gestational age at birth, and birth weight were examined (Pearson correlation) in both cohorts.

RESULTS: A total of 652 MRIs (86%) were suitable for analysis. Automated measures showed good-to-excellent agreement and good reliability with manual measures, except for interhemispheric distance at early MR imaging (scanned between 29 and 35 weeks, postmenstrual age; in line with poor manual reliability) and callosal thickness measures. All measures were positively associated with postmenstrual age ( r  =   0.11–0.94; R2 = 0.01–0.89). Negative and positive associations were found with gestational age at birth ( r = –0.26–0.71; R2 = 0.05–0.52) and birth weight ( r = –0.25–0.75; R2 = 0.06–0.56). Automated measures were successfully extracted for 80%–99% of suitable scans.

CONCLUSIONS: Measures of brain injury and impaired brain growth can be automatically extracted from neonatal MR imaging, which could assist with clinical reporting.

DGMA
:   deep gray matter area
dHCP
:   developing Human Connectome Project
GA
:   gestational age at birth
ICC
:   intraclass correlation coefficient
LoA
:   95% limits of agreement
LVD
:   lateral ventricular diameter
PMA
:   postmenstrual age
PPREMO
:   Prediction of PREterm Motor Outcomes study
SEM
:   standard error of measurement
TEA
:   term-equivalent age" />
<meta name="og-title" property="og:title" content="Automating Quantitative Measures of an Established Conventional MRI Scoring System for Preterm-Born Infants Scanned between 29 and 47 Weeks’ Postmenstrual Age" />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/early/2021/08/19/ajnr.A7230" />
<meta name="og-site-name" property="og:site_name" content="American Journal of Neuroradiology" />
<meta name="og-description" property="og:description" content="BACKGROUND AND PURPOSE: Conventional MR imaging scoring is a valuable tool for risk stratification and prognostication of outcomes, but manual scoring is time-consuming, operator-dependent, and requires high-level expertise. This study aimed to automate the regional measurements of an established brain MR imaging scoring system for preterm neonates scanned between 29 and 47 weeks’ postmenstrual age.

MATERIALS AND METHODS: This study used T2WI from the longitudinal Prediction of PREterm Motor Outcomes cohort study and the developing Human Connectome Project. Measures of biparietal width, interhemispheric distance, callosal thickness, transcerebellar diameter, lateral ventricular diameter, and deep gray matter area were extracted manually (Prediction of PREterm Motor Outcomes study only) and automatically. Scans with poor quality, failure of automated analysis, or severe pathology were excluded. Agreement, reliability, and associations between manual and automated measures were assessed and compared against statistics for manual measures. Associations between measures with postmenstrual age, gestational age at birth, and birth weight were examined (Pearson correlation) in both cohorts.

RESULTS: A total of 652 MRIs (86%) were suitable for analysis. Automated measures showed good-to-excellent agreement and good reliability with manual measures, except for interhemispheric distance at early MR imaging (scanned between 29 and 35 weeks, postmenstrual age; in line with poor manual reliability) and callosal thickness measures. All measures were positively associated with postmenstrual age ( r  =   0.11–0.94; R2 = 0.01–0.89). Negative and positive associations were found with gestational age at birth ( r = –0.26–0.71; R2 = 0.05–0.52) and birth weight ( r = –0.25–0.75; R2 = 0.06–0.56). Automated measures were successfully extracted for 80%–99% of suitable scans.

CONCLUSIONS: Measures of brain injury and impaired brain growth can be automatically extracted from neonatal MR imaging, which could assist with clinical reporting.

DGMA
:   deep gray matter area
dHCP
:   developing Human Connectome Project
GA
:   gestational age at birth
ICC
:   intraclass correlation coefficient
LoA
:   95% limits of agreement
LVD
:   lateral ventricular diameter
PMA
:   postmenstrual age
PPREMO
:   Prediction of PREterm Motor Outcomes study
SEM
:   standard error of measurement
TEA
:   term-equivalent age" />
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    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">L. van Eijk</span>, <span class="highwire-citation-author" data-delta="1">M. Seidel</span>, <span class="highwire-citation-author" data-delta="2">K. Pannek</span>, <span class="highwire-citation-author" data-delta="3">J.M. George</span>, <span class="highwire-citation-author" data-delta="4">S. Fiori</span>, <span class="highwire-citation-author" data-delta="5">A. Guzzetta</span>, <span class="highwire-citation-author" data-delta="6">A. Coulthard</span>, <span class="highwire-citation-author" data-delta="7">J. Bursle</span>, <span class="highwire-citation-author" data-delta="8">R.S. Ware</span>, <span class="highwire-citation-author" data-delta="9">D. Bradford</span>, <span class="highwire-citation-author" data-delta="10">S. Rose</span>, <span class="highwire-citation-author" data-delta="11">P.B. Colditz</span>, <span class="highwire-citation-author" data-delta="12">R.N. Boyd</span> and <span class="highwire-citation-author" data-delta="13">J. Fripp</span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">August 2021,  </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A7230 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-92705--61077551247" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">L. van Eijk </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From The Australian e-Health Research Centre (L.v.E., M.S., K.P., D.B., S.R., J.F.), Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia</div><div class='author-affiliation'><span class='nlm-sup'>b</span>Faculty of Medicine (L.v.E., M.S.)</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=L.%2Bvan%2BEijk%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=van%20Eijk%20L&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AL.%2Bvan%2BEijk%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0001-8254-1019" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for L. van Eijk</a></li></ul></div><div class="author-tooltip-1"><div class="author-tooltip-name">M. Seidel </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From The Australian e-Health Research Centre (L.v.E., M.S., K.P., D.B., S.R., J.F.), Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia</div><div class='author-affiliation'><span class='nlm-sup'>b</span>Faculty of Medicine (L.v.E., M.S.)</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=M.%2BSeidel%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Seidel%20M&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AM.%2BSeidel%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-6416-1861" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for M. Seidel</a></li></ul></div><div class="author-tooltip-2"><div class="author-tooltip-name">K. Pannek </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From The Australian e-Health Research Centre (L.v.E., M.S., K.P., D.B., S.R., J.F.), Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=K.%2BPannek%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Pannek%20K&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AK.%2BPannek%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-6512-7630" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for K. Pannek</a></li></ul></div><div class="author-tooltip-3"><div class="author-tooltip-name">J.M. George </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>c</span>Queensland Cerebral Palsy and Rehabilitation Research Centre (J.M.G., R.N.B.)</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=J.M.%2BGeorge%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=George%20J&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AJ.M.%2BGeorge%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0003-4893-6564" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for J.M. George</a></li></ul></div><div class="author-tooltip-4"><div class="author-tooltip-name">S. Fiori </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>f</span>Department of Developmental Neuroscience (S.F., A.G.), Istituto di Ricovero e Cura a Carattere Scientifico Stella Maris, Pisa, Italy</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=S.%2BFiori%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Fiori%20S&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AS.%2BFiori%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-0933-6120" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for S. Fiori</a></li></ul></div><div class="author-tooltip-5"><div class="author-tooltip-name">A. Guzzetta </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>f</span>Department of Developmental Neuroscience (S.F., A.G.), Istituto di Ricovero e Cura a Carattere Scientifico Stella Maris, Pisa, Italy</div><div class='author-affiliation'><span class='nlm-sup'>g</span>Department of Clinical and Experimental Medicine (A.G.), University of Pisa, Pisa, Italy</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=A.%2BGuzzetta%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Guzzetta%20A&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AA.%2BGuzzetta%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0003-3868-0059" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for A. Guzzetta</a></li></ul></div><div class="author-tooltip-6"><div class="author-tooltip-name">A. Coulthard </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>d</span>Centre for Children’s Health Research, Discipline of Medical Imaging (A.C.)</div><div class='author-affiliation'><span class='nlm-sup'>h</span>Departments of Medical Imaging (A.C., J.B.)</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=A.%2BCoulthard%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Coulthard%20A&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AA.%2BCoulthard%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0003-1110-9207" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for A. Coulthard</a></li></ul></div><div class="author-tooltip-7"><div class="author-tooltip-name">J. Bursle </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>h</span>Departments of Medical Imaging (A.C., J.B.)</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=J.%2BBursle%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Bursle%20J&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AJ.%2BBursle%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-7233-104X" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for J. Bursle</a></li></ul></div><div class="author-tooltip-8"><div class="author-tooltip-name">R.S. Ware </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>j</span>Menzies Health Institute Queensland (R.S.W.), Griffith University, Brisbane, Australia.</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=R.S.%2BWare%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Ware%20R&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AR.S.%2BWare%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-6129-6736" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for R.S. Ware</a></li></ul></div><div class="author-tooltip-9"><div class="author-tooltip-name">D. Bradford </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From The Australian e-Health Research Centre (L.v.E., M.S., K.P., D.B., S.R., J.F.), Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=D.%2BBradford%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Bradford%20D&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AD.%2BBradford%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-2939-3018" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for D. Bradford</a></li></ul></div><div class="author-tooltip-10"><div class="author-tooltip-name">S. Rose </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From The Australian e-Health Research Centre (L.v.E., M.S., K.P., D.B., S.R., J.F.), Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=S.%2BRose%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Rose%20S&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AS.%2BRose%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0003-1558-6297" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for S. Rose</a></li></ul></div><div class="author-tooltip-11"><div class="author-tooltip-name">P.B. Colditz </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>e</span>Perinatal Research Centre (P.B.C.), Faculty of Medicine, University of Queensland Centre for Clinical Research, The University of Queensland, Brisbane, Australia</div><div class='author-affiliation'><span class='nlm-sup'>i</span>Perinatal Research Centre (P.B.C.), Royal Brisbane and Women’s Hospital, Brisbane, Australia</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=P.B.%2BColditz%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Colditz%20P&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AP.B.%2BColditz%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-6408-8238" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for P.B. 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Fripp </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From The Australian e-Health Research Centre (L.v.E., M.S., K.P., D.B., S.R., J.F.), Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=J.%2BFripp%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Fripp%20J&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AJ.%2BFripp%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0001-9705-0079" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for J. 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    <div class="highwire-markup"><div xmlns="http://www.w3.org/1999/xhtml" class="content-block-markup" xmlns:xhtml="http://www.w3.org/1999/xhtml"><div xmlns:xhtml="http://www.w3.org/1999/xhtml" class="contributors"><ol class="contributor-list" id="contrib-group-1"><li class="contributor" id="contrib-1"><span class="name">L. van Eijk</span><a id="xref-aff-1-1" class="xref-aff" href="#aff-1">a</a><span class="xref-sep">,</span><a id="xref-aff-2-1" class="xref-aff" href="#aff-2">b</a>, </li><li class="contributor" id="contrib-2"><span class="name">M. Seidel</span><a id="xref-aff-1-2" class="xref-aff" href="#aff-1">a</a><span class="xref-sep">,</span><a id="xref-aff-2-2" class="xref-aff" href="#aff-2">b</a>, </li><li class="contributor" id="contrib-3"><span class="name">K. Pannek</span><a id="xref-aff-1-3" class="xref-aff" href="#aff-1">a</a>, </li><li class="contributor" id="contrib-4"><span class="name">J.M. George</span><a id="xref-aff-3-1" class="xref-aff" href="#aff-3">c</a>, </li><li class="contributor" id="contrib-5"><span class="name">S. Fiori</span><a id="xref-aff-6-1" class="xref-aff" href="#aff-6">f</a>, </li><li class="contributor" id="contrib-6"><span class="name">A. Guzzetta</span><a id="xref-aff-6-2" class="xref-aff" href="#aff-6">f</a><span class="xref-sep">,</span><a id="xref-aff-7-1" class="xref-aff" href="#aff-7">g</a>, </li><li class="contributor" id="contrib-7"><span class="name">A. Coulthard</span><a id="xref-aff-4-1" class="xref-aff" href="#aff-4">d</a><span class="xref-sep">,</span><a id="xref-aff-8-1" class="xref-aff" href="#aff-8">h</a>, </li><li class="contributor" id="contrib-8"><span class="name">J. Bursle</span><a id="xref-aff-8-2" class="xref-aff" href="#aff-8">h</a>, </li><li class="contributor" id="contrib-9"><span class="name">R.S. Ware</span><a id="xref-aff-10-1" class="xref-aff" href="#aff-10">j</a>, </li><li class="contributor" id="contrib-10"><span class="name">D. Bradford</span><a id="xref-aff-1-4" class="xref-aff" href="#aff-1">a</a>, </li><li class="contributor" id="contrib-11"><span class="name">S. Rose</span><a id="xref-aff-1-5" class="xref-aff" href="#aff-1">a</a>, </li><li class="contributor" id="contrib-12"><span class="name">P.B. Colditz</span><a id="xref-aff-5-1" class="xref-aff" href="#aff-5">e</a><span class="xref-sep">,</span><a id="xref-aff-9-1" class="xref-aff" href="#aff-9">i</a>, </li><li class="contributor" id="contrib-13"><span class="name">R.N. Boyd</span><a id="xref-aff-3-2" class="xref-aff" href="#aff-3">c</a> and </li><li class="last" id="contrib-14"><span class="name">J. Fripp</span><a id="xref-aff-1-6" class="xref-aff" href="#aff-1">a</a></li></ol><ol class="affiliation-list"><li class="aff"><a id="aff-1" name="aff-1"></a><address><sup>a</sup>From The Australian e-Health Research Centre (L.v.E., M.S., K.P., D.B., S.R., J.F.), Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia</address></li><li class="aff"><a id="aff-2" name="aff-2"></a><address><sup>b</sup>Faculty of Medicine (L.v.E., M.S.)</address></li><li class="aff"><a id="aff-3" name="aff-3"></a><address><sup>c</sup>Queensland Cerebral Palsy and Rehabilitation Research Centre (J.M.G., R.N.B.)</address></li><li class="aff"><a id="aff-4" name="aff-4"></a><address><sup>d</sup>Centre for Children’s Health Research, Discipline of Medical Imaging (A.C.)</address></li><li class="aff"><a id="aff-5" name="aff-5"></a><address><sup>e</sup>Perinatal Research Centre (P.B.C.), Faculty of Medicine, University of Queensland Centre for Clinical Research, The University of Queensland, Brisbane, Australia</address></li><li class="aff"><a id="aff-6" name="aff-6"></a><address><sup>f</sup>Department of Developmental Neuroscience (S.F., A.G.), Istituto di Ricovero e Cura a Carattere Scientifico Stella Maris, Pisa, Italy</address></li><li class="aff"><a id="aff-7" name="aff-7"></a><address><sup>g</sup>Department of Clinical and Experimental Medicine (A.G.), University of Pisa, Pisa, Italy</address></li><li class="aff"><a id="aff-8" name="aff-8"></a><address><sup>h</sup>Departments of Medical Imaging (A.C., J.B.)</address></li><li class="aff"><a id="aff-9" name="aff-9"></a><address><sup>i</sup>Perinatal Research Centre (P.B.C.), Royal Brisbane and Women’s Hospital, Brisbane, Australia</address></li><li class="aff"><a id="aff-10" name="aff-10"></a><address><sup>j</sup>Menzies Health Institute Queensland (R.S.W.), Griffith University, Brisbane, Australia.</address></li></ol><ol class="corresp-list"><li class="corresp" id="corresp-1">Please address correspondence to K. Pannek, MD, <span class="addr-line">The Australian e-Health Research Centre, CSIRO, Level 5 UQ Health Sciences Building, Royal Brisbane and Women’s Hospital, Herston, Queensland 4029 Australia</span>; e-mail: <span class="em-link"><span class="em-addr">Kerstin.Pannek{at}csiro.au</span></span></li></ol></div></div><a href="http://ajnr-stage2.stage.highwire.org/content/early/2021/08/19/ajnr.A7230.full" class="hw-link hw-link-article-full-text" data-icon-position="" data-hide-link-title="0">View Full Text</a></div>  </div>

  
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      <div class="highwire-cite-title">Automating Quantitative Measures of an Established Conventional MRI Scoring System for Preterm-Born Infants Scanned between 29 and 47 Weeks’ Postmenstrual Age</div>  
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