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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Neurol.</journal-id>
<journal-title>Frontiers in Neurology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Neurol.</abbrev-journal-title>
<issn pub-type="epub">1664-2295</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fneur.2021.691430</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Neurology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Cortical Venous Changes on Susceptibility-Weighted Imaging Predict the Cerebral Collateral Circulation as Confirmed by Digital Subtraction Angiography</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Zhan</surname> <given-names>Yun-Hao</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1267437/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Chen</surname> <given-names>Yang-Kun</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x0002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/598609/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Li</surname> <given-names>Run-Xiong</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1443144/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Luo</surname> <given-names>Gen-Pei</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1443170/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Wu</surname> <given-names>Zhi-Qiang</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Liu</surname> <given-names>Yong-Lin</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/705354/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Xiao</surname> <given-names>Wei-Min</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1350644/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Hu</surname> <given-names>Wei-Dong</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1443128/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Xie</surname> <given-names>Cai-Qin</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1443168/overview"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Department of Neurology, Affiliated Dongguan Hospital, Southern Medical University (Dongguan People&#x00027;s Hospital)</institution>, <addr-line>Dongguan</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>Department of Radiology, Affiliated Dongguan Hospital, Southern Medical University (Dongguan People&#x00027;s Hospital)</institution>, <addr-line>Dongguan</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: QinJian Sun, Shandong University, China</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Ian Winship, University of Alberta, Canada; Jiachun Feng, First Affiliated Hospital of Jilin University, China; Takashi Shimoyama, Nippon Medical School, Japan</p></fn>
<corresp id="c001">&#x0002A;Correspondence: Yang-Kun Chen <email>cykun78&#x00040;163.com</email></corresp>
<fn fn-type="other" id="fn001"><p>This article was submitted to Endovascular and Interventional Neurology, a section of the journal Frontiers in Neurology</p></fn></author-notes>
<pub-date pub-type="epub">
<day>27</day>
<month>08</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>12</volume>
<elocation-id>691430</elocation-id>
<history>
<date date-type="received">
<day>06</day>
<month>04</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>16</day>
<month>07</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2021 Zhan, Chen, Li, Luo, Wu, Liu, Xiao, Hu and Xie.</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Zhan, Chen, Li, Luo, Wu, Liu, Xiao, Hu and Xie</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p></license></permissions>
<abstract><p><bold>Objective:</bold> Asymmetrical cortical vein sign (ACVS) shown on susceptibility-weighted imaging (SWI) can reflect regional hypoperfusion. We investigated if ACVS could predict the cerebral collateral circulation (CC) as assessed by digital subtraction angiography (DSA) in acute ischemic stroke patients with ipsilateral severe stenosis/occlusion of the anterior circulation.</p>
<p><bold>Methods:</bold> Clinical data and imaging data of 62 acute ischemic stroke patients with ipsilateral severe stenosis or occlusion of the anterior circulation confirmed by DSA were collected retrospectively. Participants underwent magnetic resonance imaging, including an SWI sequence. ACVS was defined as more and/or larger venous signals in the cerebral cortex of one side of SWI than that in the contralateral side. ACVS was measured using the Alberta Stroke Program Early Computed Tomography score based on SWI. The grading of the cerebral CC was judged using DSA.</p>
<p><bold>Results:</bold> Of the 62 patients, 30 patients (48.4%) had moderate-to-severe ACVS. According to DSA assessment, 19 patients (30.6%) had a good CC (grade 3&#x02013;4), and 43 (69.4%) patients had a poor-to-moderate CC (grade 0&#x02013;2). Among the 30 patients with moderate-to-severe ACVS, only three (10%) patients had a good CC, and 27 (90%) patients had a poor-to-moderate CC; among the 32 patients with none or mild ACVS, 16 (50%) of them had a good CC, and the other 50% had a moderate-to-severe CC. We constructed two logistic regression models with ACVS grading and none or mild ACVS entered into the models, respectively, together with age and large-artery occlusion. In model 1, no ACVS (compared with severe ACVS; OR = 40.329, 95%CI = 2.817&#x02013;577.422, <italic>P</italic> = 0.006), mild ACVS (compared with severe ACVS; OR = 17.186, 1.735&#x02013;170.224, 0.015) and large-artery occlusion (OR = 45.645, 4.603&#x02013;452.592, 0.001) correlated with a good CC. In model 2, none or mild ACVS (OR = 36.848, 95%CI = 5.516&#x02013;246.171, <italic>P</italic> &#x0003C; 0.001) was significantly associated with a good CC as judged by DSA, adjusted by age and large-artery occlusion.</p>
<p><bold>Conclusions:</bold> Cortical venous changes in SWI may be a useful indicator for the cerebral CC as confirmed by DSA.</p></abstract>
<kwd-group>
<kwd>acute ischemic stroke</kwd>
<kwd>susceptibility weighted imaging</kwd>
<kwd>asymmetrical cortical vessel sign</kwd>
<kwd>digital subtraction angiography</kwd>
<kwd>collateral circulation</kwd>
</kwd-group>
<counts>
<fig-count count="4"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="25"/>
<page-count count="8"/>
<word-count count="5172"/>
</counts>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<title>Introduction</title>
<p>For patients who have suffered acute ischemic stroke (AIS) in the anterior circulation, the key to saving ischemic penumbra is to open the occluded vessels responsible as soon as possible (<xref ref-type="bibr" rid="B1">1</xref>). The cerebral collateral circulation (CC) is an essential factor for the early existence of ischemic penumbra (<xref ref-type="bibr" rid="B2">2</xref>).</p>
<p>The CC can be divided into three levels. The first level is the circle of Willis. The second level is ophthalmic collateral arteries, pia-mater anastomosis, and other relatively small collateral anastomoses. The third level is neovascularization, which is time-consuming and cannot be evaluated appropriately by digital subtraction angiography (DSA) (<xref ref-type="bibr" rid="B3">3</xref>, <xref ref-type="bibr" rid="B4">4</xref>). Commonly used methods for detecting cerebral CC include DSA, multimodal computed tomography angiography (CTA), magnetic resonance perfusion (MRP), and arterial spin labeling (ASL). DSA is the &#x0201C;gold standard&#x0201D; for evaluating a grade-I and -II CC (<xref ref-type="bibr" rid="B5">5</xref>). However, it is a traumatic and expensive procedure that necessitates the support of a professional neurointerventional team. Multimodal CTA (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B7">7</xref>) may be less sensitive for assessment of the leptomeningeal CC compared with that using DSA. DSA and CTA require injection of a contrast agent and carry the risk of contrast-related injuries. MRP (<xref ref-type="bibr" rid="B8">8</xref>) or ASL (<xref ref-type="bibr" rid="B9">9</xref>) can be used for perfusion assessment rather than direct evaluation for CC. Presence of good CC may enhance the success rate of reperfusion and recanalization in endovascular treatment for AIS (<xref ref-type="bibr" rid="B10">10</xref>). CC is a predictor of maintaining brain tissue and good clinical prognosis after AIS, and poorer CC may result in poorer perfusion.</p>
<p>Susceptibility-weighted imaging (SWI) is a magnetic resonance imaging (MRI) sequence. It has high spatial resolution and sensitivity to identify differences in magnetic susceptibility between tissues. Besides its capacity to detect cerebral microbleeds, SWI is considered to reflect oxygen saturation in brain tissues and cerebral vessels. Asymmetrical cortical vein sign (ACVS) denotes more and/or larger venous signals in the cerebral cortex of one side of SWI than that in the contralateral side (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B12">12</xref>). Several studies show that ACVS is more common in patients with large-vessel occlusion or severe stenosis and reflects cerebral hypoperfusion. Park <italic>et al</italic>. (<xref ref-type="bibr" rid="B13">13</xref>) found that total mismatch of diffusion-weighted imaging (DWI)&#x02013;SWI may be a predictor of good response to treatment in patients with AIS and is associated with cerebral perfusion. In patients with moyamoya disease, ACVS on SWI might be considered as a neuroimaging marker for the evaluation of hemodynamics (<xref ref-type="bibr" rid="B14">14</xref>). Moreover, ACVS was observed to be significantly lessened after revascularization (<xref ref-type="bibr" rid="B15">15</xref>). ACVS has also been studied in the outcome of AIS. Our recent study (<xref ref-type="bibr" rid="B16">16</xref>) found that ACVS might be a useful predictor of early neurological deficits in AIS patients with symptomatic large artery stenosis or occlusion after r-tPA treatment. As perfusion status was significantly affected by CC, it will be interesting to know the relationship between ACVS and CC. To date, very few studies have investigated the relationship between ACVS and CC. Xu <italic>et al</italic>. (<xref ref-type="bibr" rid="B17">17</xref>) found that ACVS was associated with good leptomeningeal collateral flow assessed by hyperintense vessel sign (HVS) on T2-FLAIR images rather than DSA. We wished to assess if ACVS could predict the cerebral CC assessed by DSA in AIS patients with ipsilateral severe stenosis/occlusion of the anterior circulation (ISSACS).</p>
</sec>
<sec sec-type="materials and methods" id="s2">
<title>Materials and Methods</title>
<sec>
<title>Ethical Approval of the Study Protocol</title>
<p>The requirement for written informed consent was waived by the Ethics Committee of the Affiliated Dongguan Hospital, Southern Medical University (Dongguan, China) because this was a retrospective study.</p>
</sec>
<sec>
<title>Inclusion Criteria</title>
<p>The inclusion criteria were (i) age &#x02265;18 years; (ii) AIS patients with acute infarction of the anterior circulation within 7 days; (iii) complete clinical and imaging data, including, as a minimum, a DWI sequence, SWI sequence, and DSA image: (iv) prestroke modified Rankin scale score &#x02264; 2.</p>
</sec>
<sec>
<title>Exclusion Criteria</title>
<p>The exclusion criteria were (i) a parenchymatous hemorrhage (PH) evident on CT, (ii) MRI-confirmed AIS of the posterior circulation, (iii) absence of complete clinical and imaging data, (iv) emergency or elective endovascular therapy before MRI completion.</p>
</sec>
<sec>
<title>Participants</title>
<p>We retrospectively recruited 62 patients with AIS in the Affiliated Dongguan Hospital between January 1, 2019, and December 31, 2020. During the study period, 534 patients received DSA, and 188 were diagnosed with AIS by DWI. Of these 188 patients, 126 were excluded because of lack of complete clinical and imaging data (<italic>n</italic> = 65); AIS of the posterior circulation (<italic>n</italic> = 55); diagnosed with Moyamoya disease (<italic>n</italic> = 4); or PH detection by CT (<italic>n</italic> = 2). Eventually, 62 patients formed the study cohort.</p>
</sec>
<sec>
<title>Collection of Clinical Data</title>
<p>We acquired demographic (age, sex) and clinical (National Institutes of Health Stroke Scale score, history of hypertension, previous stroke, diabetes mellitus, tobacco smoking, atrial fibrillation, homocysteine level, hyperlipidemia) data from each patient.</p>
</sec>
<sec>
<title>MRI Assessment</title>
<p>MRI (T1-weighted imaging, T2-weighted imaging, fluid-attenuated inversion recovery, DWI, and SWI) of the brain was undertaken for each participant using a 3.0-T system (Skyra; Siemens Medical, Hamburg, Germany) within 7 days of hospital admission.</p>
<p>The MRI parameters for T1-weighted imaging were time of repetition [TR]/time of echo [TE]/excitation = 1,500/11/1, field of view [FOV] = 220 mm, slice thickness/gap = 4 mm/1.2 mm, matrix = 320 &#x000D7; 320, and time of acquisition = 1 min 26 s. The MRI parameters for T1-weighted imaging were TR/TE/excitation = 4,720/96/2, turbo factor = 15, FOV = 220 mm, slice thickness/gap = 4 mm/1.2 mm, matrix of 512 &#x000D7; 512, and time of acquisition = 1 min 50 s. The MRI parameters for DWI (echo planar imaging (EPI) were TR/TE/excitation = 4,640/67/1, matrix = 192 &#x000D7; 192, FOV = 230 mm, slice thickness/gap = 4 mm/1.2 mm, EPI factor = 91, and acquisition time = 1 min 44 s; three orthogonally applied gradients were applied with b values of 0 and 1000. The MRI parameters for SWI were TR/TE/excitation = 27/20/1, FOV = 220 mm, slice thickness/ gap = 3 mm/0.6 mm, matrix 256 &#x000D7; 256, and time of acquisition = 2 min 28s.</p>
<p>One experienced neuroradiologist (C.Q.X.) and one trained neurologist (Y.L.L.), blinded to patients&#x00027; clinical data, assessed the ACVS grade on SWI independently based on the Alberta Stroke Program Early Computed Tomography (ASPECT) score (&#x0201C;Ins,&#x0201D; &#x0201C;Deep,&#x0201D; and &#x0201C;M1-6&#x0201D;) (<xref ref-type="bibr" rid="B18">18</xref>). The SWI-ASPECT score ranged from 0 (&#x0201C;no ACVS&#x0201D;) to 8 [&#x0201C;ACVS abutting all middle cerebral artery (MCA) cortical areas&#x0201D;]. The ACVS grade was classified as (1) &#x0201C;none&#x0201D; (no ACVS in any MCA cortical area), (2) &#x0201C;mild&#x0201D; (ACVS in 1&#x02013;3 defined MCA cortical areas), (3) &#x0201C;moderate&#x0201D; (ACVS in 4&#x02013;6 defined MCA cortical areas), or (4) &#x0201C;severe&#x0201D; (ACVS in 7&#x02013;8 defined MCA cortical areas) (<xref ref-type="bibr" rid="B19">19</xref>) (<xref ref-type="fig" rid="F1">Figure 1</xref>). Testing of inter-rater and intra-rater reliability of ACVS grade was done in 10 randomized cases. The intra-rater agreement of SWI measurements was good-to-excellent; kappa was 0.83; the kappa for inter-rater agreement was 0.76.</p>
<fig id="F1" position="float">
<label>Figure 1</label>
<caption><p>Three typical cases of ACVS, graded as &#x0201C;mild,&#x0201D; &#x0201C;moderate,&#x0201D; and &#x0201C;severe&#x0201D; <bold>(A,B)</bold> In the left hemisphere, ACVS in M2 was evident on SWI and defined as &#x0201C;mild ACVS.&#x0201D; <bold>(C,D)</bold> In the right hemisphere, ACVS in M1 and M2 and M4, M5, and Deep were evident on SWI, and defined as &#x0201C;moderate ACVS.&#x0201D; <bold>(E,F)</bold> In the left hemisphere, ACVS in M1, M2, M3, and Ins and M4, M5, M6, and Deep were evident on SWI and defined as &#x0201C;severe ACVS&#x0201D;. AIS, acute ischemic stroke; ACVS, asymmetric cortical vein sign; M1, anterior MCA cortex; M2, MCA cortex lateral to the insular cortex; M3, posterior MCA cortex; M4, M5, M6, the anterior, lateral and posterior MCA territories immediately superior to M1, M2 and M3, respectively; Deep, deep white matter; Ins, insula; MCA, middle cerebral artery; SWI, susceptibility-weighted imaging.</p></caption>
<graphic xlink:href="fneur-12-691430-g0001.tif"/>
</fig>
</sec>
<sec>
<title>Evaluation of the Cerebral CC</title>
<p>The decision to undertake DSA was made according to the attending physician. DSA was done using an angiography unit (Allura; Philips Medical Systems, Amsterdam, the Netherlands) after MRI. Carotid and vertebrobasilar angiography were obtained by orthographic projection and lateral projection, and these two projections had a similar angiographic volume and injection rate. Arterial, capillary, and venous phases were imaged to evaluate slow-moving collateral vessels. All patients underwent DSA and MRI during hospitalization.</p>
<p>The parameters of DSA images were measured using the measurement tool of Neuosoft Picture Archive and Communication System (PACS)/Radiography Information System (RIS). The criteria for collateral flow map&#x02013;based collateral grade were chosen based on the American Society of Interventional and Therapeutic Neuroradiology (ASITN) scale (<xref ref-type="bibr" rid="B20">20</xref>). ASITN score is the most commonly used to evaluate collateral circulation, which is widely used in the evaluation of collateral circulation on DSA. The latter can be divided into five grades: 0 (no visible CC in the ischemic site), 1 (slow CC around the ischemic site and persistent partial defect), 2 (rapid CC around the ischemic site), 3 (slow CC but complete blood flow to the ischemic bed in late vein), 4 (collateral blood flow can reach the ischemic bed completely and rapidly through retrograde perfusion). Grade 3&#x02013;4 was designated a &#x0201C;good&#x0201D; CC. Grade 0&#x02013;2 was designated as a &#x0201C;poor-to-moderate&#x0201D; CC. We chose three cases to describe this grading system (<xref ref-type="fig" rid="F2">Figure 2</xref>). Y.H.Z. and G.P.L. assessed the DSA results independently and were blinded to the SWI results. Twenty cases were selected to test the intra-rater agreement and inter-rater agreement. The intra-rater agreement of DSA measurements was good (kappa = 0.82). The inter-rater agreement of the DSA measurements was good (kappa = 0.74). If the raters disagreed, then a discussion was initiated until consensus was reached.</p>
<fig id="F2" position="float">
<label>Figure 2</label>
<caption><p>Examples for case selection. <bold>(A,B)</bold> SWI images, ACVS in M1, M2, M3, and Ins and M4, M5, M6, and Deep were evident, ACVS grade was &#x0201C;severe.&#x0201D; <bold>(C,D)</bold> DSA images showed the right MCA was occluded in horizontal segment (red arrow), no visible CC in the ischemic site (red circle), ASITN grade = 0. <bold>(E,F)</bold> SWI images, ACVS in M5 was evident, ACVS grade is &#x0201C;mild.&#x0201D; <bold>(G,H)</bold> DSA images showed the slow CC but complete blood flow to the ischemic bed, ASITN grade = 3. <bold>(I,J)</bold> SWI images, no ACVS in any MCA cortical area, ACVS grade is &#x0201C;none.&#x0201D; <bold>(K,L)</bold> DSA images showed the left ICA was occluded in start section (red arrow), the CC is rapidly and completely perfused to the whole ischemic vascular bed (red circle), ASITN grade = 4. SWI, susceptibility-weighted imaging; ACVS, asymmetric cortical vein sign; Ins, insula; Deep, deep white matter; MCA, middle cerebral artery; DSA, digital subtraction angiography; CC, collateral circulation; ASITN, American Society of Interventional and Therapeutic Neuroradiology; ICA, internal carotid artery; red arrow: responsible vessel; red circle: collateral circulation.</p></caption>
<graphic xlink:href="fneur-12-691430-g0002.tif"/>
</fig>
</sec>
<sec>
<title>Statistical Analyses</title>
<p>Statistical analyses were conducted using SPSS 23.0 (IBM, Armonk, NY, USA). Participants were classified into two groups in terms of a good CC or a not good CC. Continuous variables with a normal distribution are reported as the mean &#x000B1; SD. Variables with a non-normal distribution are reported as the median and interquartile range. Clinical variables and MRI variables were compared between the two groups using the &#x003C7;<sup>2</sup> test, independent-samples <italic>t</italic>-test, Fisher&#x00027;s exact test, or Mann&#x02013;Whitney <italic>U</italic>-test, as appropriate. Logistic regression analysis was conducted for a good CC confirmed by DSA. The power of ACVS prediction for a good CC was calculated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. <italic>P</italic> &#x0003C; 0.05 (two-sided) was considered significant.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<p>Sixty-two patients (mean age, 59.2 &#x000B1; 10.6 years; 69.4% male) were evaluated. Thirty-one patients (50%) had occlusion of the internal carotid artery or M1 segment of the MCA. According to the ASITN scale score, 19 patients (30.65%) had a good CC (grade 3&#x02013;4), and 43 (69.35%) patients had a poor-to-moderate CC (grade 0&#x02013;2). Among the 30 patients with moderate-to-severe ACVS, only three (10%) patients had a good CC, and 27 (90%) patients had a poor-to-moderate CC; among the 32 patients with none or mild ACVS, 16 (50%) of them had a good CC and the other 50% had a moderate-to-severe CC. Patients with a good CC did not differ significantly from those with a poor-to-moderate CC in terms of age, sex, vascular risk factors, or previous stroke (<italic>P</italic> &#x0003E; 0.05 for all). Patients with a good CC were more likely to have large-artery occlusion (73.7 vs. 39.5%, <italic>P</italic> = 0.013) (<xref ref-type="table" rid="T1">Table 1</xref>).</p>
<table-wrap position="float" id="T1">
<label>Table 1</label>
<caption><p>Comparisons of clinical variables and neuroimaging variables between patients with a DSA-confirmed good collateral circulation or not.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="center"><bold>Whole sample</bold></th>
<th valign="top" align="center"><bold>Good collateral circulation</bold></th>
<th valign="top" align="center"><bold>Poor-to-moderate collateral circulation</bold></th>
<th valign="top" align="center"><italic><bold>P</bold></italic></th>
</tr>
<tr>
<th/>
<th valign="top" align="center"><italic><bold>N</bold></italic> <bold>&#x0003D; 62</bold></th>
<th valign="top" align="center"><italic><bold>N</bold></italic> <bold>&#x0003D; 19</bold></th>
<th valign="top" align="center"><italic><bold>N</bold></italic> <bold>&#x0003D; 43</bold></th>
<th/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Age<xref ref-type="table-fn" rid="TN1">&#x0002A;</xref> (years)</td>
<td valign="top" align="center">59.2 &#x000B1; 10.6</td>
<td valign="top" align="center">61.58 &#x000B1; 7.42</td>
<td valign="top" align="center">58.12 &#x000B1; 11.60</td>
<td valign="top" align="center">0.059</td>
</tr>
<tr>
<td valign="top" align="left">Sex<sup><xref ref-type="table-fn" rid="TN2">&#x02020;</xref></sup></td>
<td valign="top" align="center">43(69.4%)</td>
<td valign="top" align="center">16(84.2%)</td>
<td valign="top" align="center">37(86.0%)</td>
<td valign="top" align="center">0.850</td>
</tr>
<tr>
<td valign="top" align="left">Hypertension<sup><xref ref-type="table-fn" rid="TN2">&#x02020;</xref></sup></td>
<td valign="top" align="center">53(85.5%)</td>
<td valign="top" align="center">18(94.7%)</td>
<td valign="top" align="center">35(81.4%)</td>
<td valign="top" align="center">0.169</td>
</tr>
<tr>
<td valign="top" align="left">Diabetes mellitus<sup><xref ref-type="table-fn" rid="TN2">&#x02020;</xref></sup></td>
<td valign="top" align="center">20(32.3%)</td>
<td valign="top" align="center">5(26.3%)</td>
<td valign="top" align="center">15(34.9%)</td>
<td valign="top" align="center">0.506</td>
</tr>
<tr>
<td valign="top" align="left">Smoker<sup><xref ref-type="table-fn" rid="TN2">&#x02020;</xref></sup></td>
<td valign="top" align="center">31(50.0%)</td>
<td valign="top" align="center">11(57.9%)</td>
<td valign="top" align="center">20(46.5%)</td>
<td valign="top" align="center">0.409</td>
</tr>
<tr>
<td valign="top" align="left">Atrial fibrillation<sup><xref ref-type="table-fn" rid="TN2">&#x02020;</xref></sup></td>
<td valign="top" align="center">3(4.8%)</td>
<td valign="top" align="center">1(5.3%)</td>
<td valign="top" align="center">2(4.7%)</td>
<td valign="top" align="center">0.918</td>
</tr>
<tr>
<td valign="top" align="left">Previous stroke history<sup><xref ref-type="table-fn" rid="TN2">&#x02020;</xref></sup></td>
<td valign="top" align="center">12(19.4%)</td>
<td valign="top" align="center">4(21.1%)</td>
<td valign="top" align="center">8(18.6%)</td>
<td valign="top" align="center">0.822</td>
</tr>
<tr>
<td valign="top" align="left">Hyperlipidemia<sup><xref ref-type="table-fn" rid="TN2">&#x02020;</xref></sup></td>
<td valign="top" align="center">31(50.0%)</td>
<td valign="top" align="center">11(57.9%)</td>
<td valign="top" align="center">20(46.5%)</td>
<td valign="top" align="center">0.409</td>
</tr>
<tr>
<td valign="top" align="left">NIHSS score on admission<sup><xref ref-type="table-fn" rid="TN4">&#x000A7;</xref></sup></td>
<td valign="top" align="center">2(0&#x02013;15)</td>
<td valign="top" align="center">3(0&#x02013;13)</td>
<td valign="top" align="center">2(1&#x02013;15)</td>
<td valign="top" align="center">0.423</td>
</tr>
<tr>
<td valign="top" align="left"><bold>SWI&#x02013;MRI measures</bold></td>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">DWI-infarct volume (mm<sup>3</sup>) <sup><xref ref-type="table-fn" rid="TN4">&#x000A7;</xref></sup></td>
<td valign="top" align="center">6.5(0.3&#x02013;115.6)</td>
<td valign="top" align="center">6.7(1&#x02013;95.4)</td>
<td valign="top" align="center">5.8(0.3&#x02013;115.6)</td>
<td valign="top" align="center">0.987</td>
</tr>
<tr>
<td valign="top" align="left">MRI timing(days) <sup><xref ref-type="table-fn" rid="TN4">&#x000A7;</xref></sup></td>
<td valign="top" align="center">2(0.5&#x02013;6)</td>
<td valign="top" align="center">2(0.5&#x02013;6)</td>
<td valign="top" align="center">1(0.5&#x02013;5)</td>
<td valign="top" align="center">0.024</td>
</tr>
<tr>
<td valign="top" align="left">ACVS grade<sup><xref ref-type="table-fn" rid="TN2">&#x02020;</xref></sup></td>
<td/>
<td/>
<td/>
<td valign="top" align="center">0.006</td>
</tr>
<tr>
<td valign="top" align="left">None</td>
<td valign="top" align="center">20(32.3%)</td>
<td valign="top" align="center">9(47.4%)</td>
<td valign="top" align="center">11(25.6%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Mild</td>
<td valign="top" align="center">12(19.4%)</td>
<td valign="top" align="center">7(36.8%)</td>
<td valign="top" align="center">5(11.6%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Moderate</td>
<td valign="top" align="center">15(24.2%)</td>
<td valign="top" align="center">1(5.3%)</td>
<td valign="top" align="center">14(32.6%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Severe</td>
<td valign="top" align="center">15(24.2%)</td>
<td valign="top" align="center">2(10.5%)</td>
<td valign="top" align="center">13(30.2%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">None or mild ACVS<sup><xref ref-type="table-fn" rid="TN2">&#x02020;</xref></sup></td>
<td valign="top" align="center">32(51.6%)</td>
<td valign="top" align="center">16(84.2%)</td>
<td valign="top" align="center">16(37.2%)</td>
<td valign="top" align="center">0.001</td>
</tr>
<tr>
<td valign="top" align="left">DSA timing(days) <sup><xref ref-type="table-fn" rid="TN4">&#x000A7;</xref></sup></td>
<td valign="top" align="center">5(0.5&#x02013;7)</td>
<td valign="top" align="center">5(0.5&#x02013;7)</td>
<td valign="top" align="center">5(0.5&#x02013;7)</td>
<td valign="top" align="center">0.691</td>
</tr>
<tr>
<td valign="top" align="left"><bold>DSA measures</bold></td>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Occlusion<sup><xref ref-type="table-fn" rid="TN2">&#x02020;</xref></sup></td>
<td valign="top" align="center">31(50.0%)</td>
<td valign="top" align="center">14(73.7%)</td>
<td valign="top" align="center">17(39.5%)</td>
<td valign="top" align="center">0.013</td>
</tr>
<tr>
<td valign="top" align="left">ASITN grade<sup><xref ref-type="table-fn" rid="TN3">&#x000B6;</xref></sup></td>
<td valign="top" align="center">3(0&#x02013;6.25)</td>
<td valign="top" align="center">4(3&#x02013;4)</td>
<td valign="top" align="center">0(0&#x02013;2)</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>ASITN, American Society of Interventional and Therapeutic Neuroradiology; NIHSS, National Institutes of Health Stroke Scale; SWI, susceptibility weighted imaging; ACVS, asymmetric cortical vein sign; DSA, digital subtraction angiography</italic>.</p>
<fn id="TN1"><label>&#x0002A;</label><p><italic>mean (SD), t-test</italic>;</p></fn>
<fn id="TN2"><label>&#x02020;</label><p><italic>n(%), &#x003C7;<sup>2</sup> test</italic>;</p></fn>
<fn id="TN3"><label>&#x000B6;</label><p><italic>n(%), Fisher&#x00027;s exact test</italic>;</p></fn>
<fn id="TN4"><label>&#x000A7;</label><p><italic>median (25Q&#x02212;75Q), Mann&#x02013;Whitney U-test</italic>.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>We constructed two logistic regression models with ACVS grading and none or mild ACVS entered into the models, respectively, together with age and large-artery occlusion. In model 1, no ACVS (compared with severe ACVS, odds ratio (OR) = 40.329, 95% confidence interval (CI) = 2.817&#x02013;577.422, <italic>P</italic> = 0.006), mild ACVS (compared with severe ACVS, OR = 17.186, 95%CI = 1.735&#x02013;170.224, <italic>P</italic> = 0.015), and large-artery occlusion (OR = 45.645, 95%CI = 4.603&#x02013;452.592, <italic>P</italic> = 0.001) correlated with a good CC. In model 2, none or mild ACVS (OR = 36.848, 95%CI = 5.516&#x02013;246.171, <italic>P</italic> &#x0003C; 0.001) was significantly associated with a good CC judged by DSA, adjusted by age and large-artery occlusion (<xref ref-type="table" rid="T2">Table 2</xref>). We also conducted a logistic regression model with poor CC serving as a dependent variable. Moderate-to-severe ACVS did not significantly correlate with poor CC (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 1</xref>).</p>
<table-wrap position="float" id="T2">
<label>Table 2</label>
<caption><p>Logistic regression analysis of a good collateral circulation confirmed by DSA.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="center" colspan="3" style="border-bottom: thin solid #000000;"><bold>Univariate logistic regression</bold></th>
<th valign="top" align="center" colspan="3" style="border-bottom: thin solid #000000;"><bold>Multivariate logistic regression</bold></th>
</tr>
<tr>
<th valign="top" align="left"><bold>Variables</bold></th>
<th valign="top" align="center"><bold>OR</bold></th>
<th valign="top" align="center"><bold>95%CI</bold></th>
<th valign="top" align="center"><italic><bold>P</bold></italic></th>
<th valign="top" align="center"><bold>OR</bold></th>
<th valign="top" align="center"><bold>95%CI</bold></th>
<th valign="top" align="center"><italic><bold>P</bold></italic></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left"><bold>Model 1</bold></td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Age</td>
<td valign="top" align="center">1.035</td>
<td valign="top" align="center">0.978&#x02013;1.095</td>
<td valign="top" align="center">0.236</td>
<td valign="top" align="center">1.048</td>
<td valign="top" align="center">0.966&#x02013;1.136</td>
<td valign="top" align="center">0.257</td>
</tr>
<tr>
<td valign="top" align="left">DWI-infarct volume</td>
<td valign="top" align="center">1.000</td>
<td valign="top" align="center">0.978&#x02013;1.023</td>
<td valign="top" align="center">0.987</td>
<td valign="top" align="center">0.962</td>
<td valign="top" align="center">0.912&#x02013;1.016</td>
<td valign="top" align="center">0.162</td>
</tr>
<tr>
<td valign="top" align="left">MRI timing</td>
<td valign="top" align="center">1.706</td>
<td valign="top" align="center">1.043&#x02013;2.788</td>
<td valign="top" align="center">0.033</td>
<td valign="top" align="center">1.536</td>
<td valign="top" align="center">0.767-3.073</td>
<td valign="top" align="center">0.225</td>
</tr>
<tr>
<td valign="top" align="left">DSA timing</td>
<td valign="top" align="center">0.954</td>
<td valign="top" align="center">0.758&#x02013;1.201</td>
<td valign="top" align="center">0.689</td>
<td valign="top" align="center">0.825</td>
<td valign="top" align="center">0.534&#x02013;1.275</td>
<td valign="top" align="center">0.825</td>
</tr>
<tr>
<td valign="top" align="left">Occlusion</td>
<td valign="top" align="center">7.407</td>
<td valign="top" align="center">1.875&#x02013;29.265</td>
<td valign="top" align="center">0.004</td>
<td valign="top" align="center">45.645</td>
<td valign="top" align="center">4.603&#x02013;452.592</td>
<td valign="top" align="center">0.001</td>
</tr>
<tr>
<td valign="top" align="left">ACVS grade</td>
<td/>
<td/>
<td valign="top" align="center">0.019</td>
<td/>
<td/>
<td valign="top" align="center">0.006</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;&#x000A0;&#x000A0;&#x000A0;Severe</td>
<td valign="top" align="center">ref</td>
<td/>
<td/>
<td valign="top" align="center">ref</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;&#x000A0;&#x000A0;&#x000A0;None</td>
<td valign="top" align="center">5.318</td>
<td valign="top" align="center">0.943&#x02013;29.993</td>
<td valign="top" align="center">0.058</td>
<td valign="top" align="center">40.329</td>
<td valign="top" align="center">2.817&#x02013;577.422</td>
<td valign="top" align="center">0.006</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;&#x000A0;&#x000A0;&#x000A0;Mild</td>
<td valign="top" align="center">9.100</td>
<td valign="top" align="center">1.318&#x02013;59.619</td>
<td valign="top" align="center">0.021</td>
<td valign="top" align="center">17.186</td>
<td valign="top" align="center">1.735&#x02013;170.224</td>
<td valign="top" align="center">0.015</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;&#x000A0;&#x000A0;&#x000A0;Moderate</td>
<td valign="top" align="center">0.464</td>
<td valign="top" align="center">0.037&#x02013;5.749</td>
<td valign="top" align="center">0.550</td>
<td valign="top" align="center">0.393</td>
<td valign="top" align="center">0.030&#x02013;5.231</td>
<td valign="top" align="center">0.479</td>
</tr>
<tr>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left"><bold>Model 2</bold></td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Age</td>
<td valign="top" align="center">1.035</td>
<td valign="top" align="center">0.978&#x02013;1.095</td>
<td valign="top" align="center">0.236</td>
<td valign="top" align="center">1.056</td>
<td valign="top" align="center">0.975&#x02013;1.144</td>
<td valign="top" align="center">0.178</td>
</tr>
<tr>
<td valign="top" align="left">Occlusion</td>
<td valign="top" align="center">7.407</td>
<td valign="top" align="center">1.875&#x02013;29.265</td>
<td valign="top" align="center">0.004</td>
<td valign="top" align="center">32.260</td>
<td valign="top" align="center">4.791&#x02013;217.233</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">None or mild ACVS</td>
<td valign="top" align="center">9.000</td>
<td valign="top" align="center">2.265&#x02013;35.755</td>
<td valign="top" align="center">0.002</td>
<td valign="top" align="center">36.848</td>
<td valign="top" align="center">5.516&#x02013;246.171</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>ACVS, Asymmetric cortical vein sign</italic>.</p>
</table-wrap-foot>
</table-wrap>
<p>The ROC curve showed the predictive ability of ACVS grading and none or mild ACVS for CC. The AUC for predicting a good CC for none or mild ACVS and ACVS grading was 0.735 and 0.706, respectively (<xref ref-type="fig" rid="F3">Figure 3</xref>).</p>
<fig id="F3" position="float">
<label>Figure 3</label>
<caption><p>ROC curve of ACVS to predict a good collateral circulation as confirmed by DSA. ROC curve showing the predictive ability of ACVS grading (dotted line) and none or mild ACVS (solid line) for a collateral circulation. ROC, receiver operating characteristic; ACVS, asymmetric cortical vein sign.</p></caption>
<graphic xlink:href="fneur-12-691430-g0003.tif"/>
</fig>
<p>A box plot shows the relationship between ACVS grading (abscissa) and NIHSS stroke score (ordinate) (<xref ref-type="fig" rid="F4">Figure 4</xref>). ACVS grading correlated with the severity of stroke (Spearman r = 0.275, <italic>P</italic> = 0.031).</p>
<fig id="F4" position="float">
<label>Figure 4</label>
<caption><p>Box plot of the relationship between ACVS and NIHSS stroke score. Box plot showing the relationship between ACVS grading (abscissa) and NIHSS stroke score (ordinate). ACVS, asymmetric cortical vein sign.</p></caption>
<graphic xlink:href="fneur-12-691430-g0004.tif"/>
</fig>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>The main finding of our study was that, in AIS patients with ISSACS, ACVS grading (especially none or mild ACVS on SWI) strongly predicted a good CC on DSA. This finding is practical for physicians to acquire, in a prompt and non-traumatic way, CC status using only MRI without the need for contrast-agent injection.</p>
<p>The principle of SWI is dependent mainly on deoxyhemoglobin content in venous blood (<xref ref-type="bibr" rid="B21">21</xref>). In patients with AIS, the vasodilation caused by ischemia in the cerebral cortex on the affected side (as well as an imbalance in the supply and demand of oxygen in hypoperfused tissue after cerebral-artery occlusion) leads to a relative increase in the deoxyhemoglobin level in the corresponding draining veins and a relative decrease in the oxyhemoglobin level. This action leads to ACVS, which, as a new imaging marker of CC status, is discussed in a few studies (<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B13">13</xref>). A study on the mismatch between DWI and SWI indicates that the increased oxygen demand of hypoperfused brain tissue leads to an increase in the deoxyhemoglobin:oxyhemoglobin ratio. If the insufficiency of cerebral perfusion can be improved and blood vessels can be recanalized, the risk of irreversible ischemic injury can be reduced (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B22">22</xref>).</p>
<p>The CC is the basis of ischemic penumbra. A good CC can provide sufficient perfusion for the affected hemisphere (<xref ref-type="bibr" rid="B23">23</xref>) and reduce the need of ischemic tissue for a metabolic reserve. Early and rapid identification of ischemic penumbra can help to decide whether intravenous thrombolysis or mechanical thrombectomy is indicated. We found that, in comparison with people with severe ACVS, those without or with only mild ACVS were more likely to have a good CC even if they had symptomatic ISSACS. In addition, none or mild ACVS seems to be a strong indicator for a good CC. These results are in accordance with data from a study by Verma <italic>et al</italic>. (<xref ref-type="bibr" rid="B8">8</xref>), which also found that the better the state of the CC, the smaller was the range of ACVS. However, that study had only 33 cases and conducted univariate comparisons only. Determination of ACVS is difficult if bilateral large arteries have severe stenosis/occlusion. Thus, we recruited only AIS patients with ISSACS. Furthermore, we also adjusted these results by age and large-artery occlusion and confirmed this strong association. However, we did not find that severity of ACVS could predict a poor CC. Moderate-to-severe ACVS commonly implicates hypoperfusion, which does not always mean the presence of poor CC. ACVS on MRI-SWI is a non-invasive technique without radiation and contrast allergy risk. Not every AIS patient with large arterial stenosis or occlusion needs a DSA evaluation. It can partially replace DSA assessment of CC in patients with contraindications or unwilling to have DSA for collateral circulation evaluation. However, ACVS is not suitable for patients with bilateral severe large arterial stenosis or occlusion.</p>
<p>In a study of dynamic changes of SWI signals in AIS, Baik et al. (<xref ref-type="bibr" rid="B15">15</xref>) found that ACVS was significantly lessened after revascularization. Also, the prognosis of these patients was, in general, not poor but, for patients with hypoperfusion who did not have brain improvement in a timely and complete manner, ACVS on SWI indicated that these patients would be more prone to early neurological deterioration. Previously, we also found that ACVS can predict early neurological deterioration effectively in AIS patients with symptomatic large-artery stenosis/occlusion after treatment with recombinant tissue plasminogen activator (<xref ref-type="bibr" rid="B24">24</xref>).</p>
<p>ACVS was difficult to quantify accurately. We used the ASPECT scoring to evaluate the range of ACVS. ASPECT scoring was initially used for the measures of the early CT ischemic changes range in predicting benefit with intravenous thrombolysis. A lower ASPECT score implicates a larger range of involvement. ACVS reflects the change of vein shape and number and is difficult to quantify. SWI-ASPECT scoring can be used to evaluate the range of ACVS as recommended by some studies. Only one study (<xref ref-type="bibr" rid="B25">25</xref>) attempted to define ACVS quantitatively using susceptibility percentage change. However, to the best of our knowledge, no studies have successfully quantified the extent of ACVS using objective methods.</p>
<p>The strengths of our study were that the CC was confirmed using DSA (the gold standard) and that we adjusted for confounders in our analyses. However, our study had four main limitations. First, the sample size of our study was small, and the regression model might have been not very stable. Second, we recruited only AIS patients with ipsilateral arterial lesions. Thus, this finding may be valuable only for unilateral severe stenosis/occlusion in the anterior circulation and not applicable for bilateral lesions. Third, as mentioned before, ACVS is difficult to quantify, and we assessed it <italic>via</italic> a semi-quantitative method. Last, we did not have dynamic evaluation of ACVS as no patients in our stroke center would have SWI examination before thrombolysis or thrombectomy according to the guideline of our stroke center.</p>
</sec>
<sec sec-type="conclusions" id="s5">
<title>Conclusions</title>
<p>Our study provides evidence for the reliability of ACVS in judging the CC in treatment of AIS in the anterior circulation. Further longitudinal studies using larger patient cohorts and more objective ACVS quantification, e.g., using machine-learning methods, are warranted to justify this finding.</p>
</sec>
<sec sec-type="data-availability-statement" id="s6">
<title>Data Availability Statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec id="s7">
<title>Ethics Statement</title>
<p>The studies involving human participants were reviewed and approved by Ethics Committee of Affiliated Dongguan Hospital, Southern Medical University. The ethics committee waived the requirement of written informed consent for participation.</p>
</sec>
<sec id="s8">
<title>Author Contributions</title>
<p>Y-HZ and Y-KC conceptualized and designed the study, acquired and analyzed data, and drafted the manuscript for intellectual content. Y-HZ and G-PL took measurements. Y-LL and C-QX measured SWI data. R-XL, Z-QW, W-MX, and W-DH selected and recruited the patients. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec sec-type="COI-statement" id="conf1">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="s9">
<title>Publisher&#x00027;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
</body>
<back>
<sec sec-type="supplementary-material" id="s10">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fneur.2021.691430/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fneur.2021.691430/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Table_1.DOCX" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/></sec>
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<title>References</title>
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<fn-group>
<fn fn-type="financial-disclosure"><p><bold>Funding.</bold> This work was supported by the Guangdong Province Science and Technology Plan Project Public Welfare Fund and Ability Construction Project, China (2017A020215002).</p>
</fn>
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