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<article xml:lang="en" article-type="review-article" dtd-version="1.4"><processing-meta base-tagset="archiving" mathml-version="3.0" table-model="xhtml" tagset-family="jats"><restricted-by>pmc</restricted-by></processing-meta><front><journal-meta><journal-id journal-id-type="nlm-ta">Eur Clin Respir J</journal-id><journal-id journal-id-type="iso-abbrev">Eur Clin Respir J</journal-id><journal-id journal-id-type="pmc-domain-id">2829</journal-id><journal-id journal-id-type="pmc-domain">ecrj</journal-id><journal-id journal-id-type="nlm-id">101662134</journal-id><journal-title-group><journal-title>European Clinical Respiratory Journal</journal-title></journal-title-group><issn pub-type="epub">2001-8525</issn><?publisher_abbrev taylorfran?><publisher><publisher-name>Taylor &amp; Francis</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmcid">PMC11288198</article-id><article-id pub-id-type="pmcid-ver">PMC11288198.1</article-id><article-id pub-id-type="pmcaid">11288198</article-id><article-id pub-id-type="pmcaiid">11288198</article-id><article-id pub-id-type="pmid">39081799</article-id><article-id pub-id-type="doi">10.1080/20018525.2024.2381898</article-id><article-id pub-id-type="publisher-id">2381898</article-id><article-version-alternatives><article-version article-version-type="pmc-version">1</article-version><article-version vocab="JAV" vocab-identifier="http://www.niso.org/publications/rp/RP-8-2008.pdf" vocab-term="Version of Record" article-version-type="VoR">Version of Record</article-version></article-version-alternatives><article-categories><subj-group subj-group-type="article-type"><subject>Review Article</subject></subj-group><subj-group subj-group-type="heading"><subject>Review Article</subject></subj-group></article-categories><title-group><article-title>Comparison of lung volumes measured with computed tomography and whole-body plethysmography – a systematic review</article-title><alt-title alt-title-type="left-running-head">H. J. B. OLSEN AND J. MORTENSEN</alt-title><alt-title alt-title-type="right-running-head">EUROPEAN CLINICAL RESPIRATORY JOURNAL</alt-title></title-group><contrib-group><contrib contrib-type="author"><name name-style="western"><surname>Olsen</surname><given-names initials="HJB">Høgni Janus Bjarnason</given-names></name><xref rid="aff0001" ref-type="aff">
<sup>a</sup>
</xref></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="false">https://orcid.org/0000-0002-1399-8995</contrib-id><name name-style="western"><surname>Mortensen</surname><given-names initials="J">Jann</given-names></name><xref rid="aff0001" ref-type="aff">
<sup>a</sup>
</xref><xref rid="aff0002" ref-type="aff">
<sup>b</sup>
</xref><xref rid="aff0003" ref-type="aff">
<sup>c</sup>
</xref><xref rid="an0001" ref-type="corresp"/></contrib><aff id="aff0001"><label>a</label>Department of Clinical Physiology and Nuclear Medicine, <institution-wrap><institution>Copenhagen University Hospital - Rigshospitalet</institution></institution-wrap>, <city>Copenhagen</city>, <country>Denmark</country></aff><aff id="aff0002"><label>b</label>Department of Clinical Medicine, <institution-wrap><institution>University of Copenhagen</institution></institution-wrap>, <city>Copenhagen</city>, <country>Denmark</country></aff><aff id="aff0003"><label>c</label>Department of Medicine, <institution-wrap><institution>The National Hospital</institution></institution-wrap>, <city>Torshavn</city>, <country>Faroe Islands</country></aff></contrib-group><author-notes><corresp id="an0001">CONTACT Jann Mortensen <email xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="mailto:jann.mortensen@regionh.dk">jann.mortensen@regionh.dk</email> Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet, <addr-line>Blegdamsvej 9</addr-line>, <city>Copenhagen</city>
<postal-code>2100</postal-code>, <country>Denmark</country></corresp></author-notes><pub-date date-type="pub" publication-format="electronic"><day>29</day><month>7</month><year>2024</year></pub-date><pub-date date-type="collection" publication-format="electronic"><year>2024</year></pub-date><volume>11</volume><issue>1</issue><issue-id pub-id-type="pmc-issue-id">452373</issue-id><elocation-id seq="19">2381898</elocation-id><pub-history><event event-type="pmc-release"><date><day>29</day><month>07</month><year>2024</year></date></event><event event-type="pmc-live"><date><day>30</day><month>07</month><year>2024</year></date></event><event event-type="pmc-last-change"><date iso-8601-date="2024-07-31 17:25:14.420"><day>31</day><month>07</month><year>2024</year></date></event><event event-type="tagger"><event-desc>Integra</event-desc><date><day>23</day><month>7</month><year>2024</year></date></event><event event-type="final"><event-desc>Integra</event-desc><date><day>23</day><month>7</month><year>2024</year></date></event><event event-type="received"><date><day>01</day><month>4</month><year>2024</year></date></event><event event-type="accepted"><date><day>15</day><month>7</month><year>2024</year></date></event></pub-history><permissions><copyright-statement>© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor &amp; Francis Group.</copyright-statement><copyright-year>2024</copyright-year><copyright-holder>The Author(s)</copyright-holder><license><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/" specific-use="textmining" content-type="ccbynclicense">https://creativecommons.org/licenses/by-nc/4.0/</ali:license_ref><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (<ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by-nc/4.0/">http://creativecommons.org/licenses/by-nc/4.0/</ext-link>), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.</license-p></license></permissions><self-uri xmlns:xlink="http://www.w3.org/1999/xlink" content-type="pmc-pdf" xlink:href="ZECR_11_2381898.pdf"><?pdf-name ZECR_11_2381898.pdf?><?pdf-size 3917996?><?pdf-md5 2d3767a96d84596f44791f7c3b8aae14?><?pdf-image-server-status NEVER_LOAD?><?pdf-cloudpmc-urn urn:app:bf4d/11288198/2d3767a96d84/ZECR_11_2381898.pdf?></self-uri><self-uri xmlns:xlink="http://www.w3.org/1999/xlink" content-type="pdf" xlink:href="ZECR_11_2381898.pdf"/><abstract><title>ABSTRACT</title><sec sec-type="intro"><title>Introduction</title><p>Whole-body plethysmography is the preferred method for measuring the static lung volumes: total lung capacity (TLC), functional residual capacity (FRC) and residual volume (RV), as it also incorporates trapped gas – a common finding in chronic obstructive pulmonary disease (COPD). Quantitative computed tomography (CT) is a promising alternative to plethysmography, which can be challenging to perform for patients with severely impaired lung function. The present systematic review explores the agreement between lung volumes measured by plethysmography and CT, as well as the attempts being made to optimize alignment between these two methods.</p></sec><sec><title>Methods</title><p>A literature search was performed on the PubMed database using the block search strategy. Articles were included if they provided both CT based and plethysmography based TLC. Risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) checklist.</p></sec><sec><title>Results</title><p>22 articles were included. On average, CT-derived TLC (CT-TLC) was 709 mL lower compared to plethysmography TLC (p-TLC) with a 12.1% deviation from the reference standard, p-TLC. This discrepancy (ΔTLC) appeared slightly larger in obstructive patients (obstructive: 781 mL, non-obstructive: 609 mL), whereas percent deviation was slightly smaller (obstructive: 11.4%, non-obstructive: 13.5%). CT-based RV analyses primarily based on COPD patients measured 603 mL higher than plethysmography (p-RV) with 17.8% deviation from p-RV. Studies utilizing spirometry-gating for CT acquisition reported good agreement between modalities (ΔTLC: 70–280 mL), and one study demonstrated noticeable improvements compared to conventional breath-hold instructions in an otherwise identical study setting.</p></sec><sec><title>Conclusion</title><p>CT quantifications routinely underestimate TLC and overestimate RV in comparison to plethysmography. Spirometry gating reduces the level of disagreement and can be of assistance when patients are already undergoing CT. However, further studies are needed to confirm these results.</p></sec></abstract><kwd-group kwd-group-type="author"><title>KEYWORDS</title><kwd>Systematic review</kwd><kwd>total lung capacity</kwd><kwd>functional residual capacity</kwd><kwd>residual volume</kwd><kwd>static lung volumes</kwd><kwd>computed tomography</kwd><kwd>body box</kwd><kwd>whole-body plethysmography</kwd></kwd-group><support-group><funding-group><funding-statement>There has been no funding for this work.</funding-statement></funding-group></support-group><counts><fig-count count="4"/><table-count count="6"/><ref-count count="29"/><page-count count="1"/><word-count count="4708"/></counts><custom-meta-group><custom-meta><meta-name>pmc-status-qastatus</meta-name><meta-value>0</meta-value></custom-meta><custom-meta><meta-name>pmc-status-live</meta-name><meta-value>yes</meta-value></custom-meta><custom-meta><meta-name>pmc-status-embargo</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-status-released</meta-name><meta-value>yes</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-open-access</meta-name><meta-value>yes</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-olf</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-manuscript</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-legally-suppressed</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-has-pdf</meta-name><meta-value>yes</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-has-supplement</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-pdf-only</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-suppress-copyright</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-is-real-version</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-is-scanned-article</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-preprint</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-in-epmc</meta-name><meta-value>yes</meta-value></custom-meta><custom-meta><meta-name>pmc-license-ref</meta-name><meta-value>CC BY-NC</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec sec-type="intro" disp-level="1" id="s0001"><title>Introduction</title><p>After its introduction in 1956 [<xref rid="cit0001" ref-type="bibr">1</xref>], whole-body plethysmography has been regarded as gold standard for measuring static lung volumes including residual volume (RV), functional residual capacity (FRC) and total lung capacity (TLC). Methods based upon multiple-breath gas dilution or washout techniques depend on communicating gas and thus only measure a subject’s ventilated lung volumes. In contrast, plethysmography includes also trapped air so it is applicable for patients with lung diseases characterized by air trapping such as chronic obstructive pulmonary disease (COPD) [<xref rid="cit0002" ref-type="bibr">2</xref>]. Performing the necessary respiratory maneuvers correctly requires meticulous coaching and multiple attempts [<xref rid="cit0003" ref-type="bibr">3</xref>]. This can be especially demanding for patients with severely impaired lung function and might not be suitable for patients (e.g. children) who find it challenging to follow instruction. In addition, the intermittent closure of air flow and compact dimensions of the body box can induce panic attacks in patients suffering from claustrophobia.</p><p>CT lung volumetrics is promising as an alternative tool for assessing pulmonary function and volumes. Furthermore, software can both quantify degree of emphysema and segment the lung into pulmonary lobes, which is helpful when selecting lobes as target for lung volume reduction therapy.</p><p>A technician or voice recording usually instructs the patient to fully inhale or exhale and hold still as the CT scan is performed. Patient cooperation and scan timing is among the challenges faced and can be managed by spirometry-gating and other solutions.</p><p>The aim of this systematic review is to assess the agreement between static lung volumes measured by quantitative CT volumetrics and body plethysmography and explore the attempts being made to optimize alignment. It is hypothesized that inspiratory CT-based volumes underestimate TLC and expiratory CT-based volumes overestimate RV whereas spirometry gating reduces the level of disagreement.</p></sec><sec disp-level="1" id="s0002"><title>Methods</title><sec disp-level="2" id="s0002-s2001"><title>Search and study selection</title><p>The research question was <italic toggle="yes">‘What is the agreement between lung volumes measured with CT and body box?’</italic> A systematic search strategy was applied on PubMed using block-searching strategy with the entries: (TLC OR RV) AND CT AND plethysmography. The first broad search identified 1405 results (<xref rid="t0004" ref-type="table">Table A1</xref>. <italic toggle="yes">Search Protocol #1</italic>) and a second, narrower search yielded 111 results (<xref rid="t0005" ref-type="table">Table A2</xref>. <italic toggle="yes">Search Protocol #2</italic>). Titles and abstracts were screened, and articles were assessed for eligibility by screening the full-text version. Reference lists were searched for additional relevant articles. Articles had to include human subjects and TLC derived from CT acquired at maximum inspiration as well as plethysmography TLC as comparator. Results had to be original studies in English or a Scandinavian language and include an abstract and a full-text version.</p><p>The selection process is visualized using a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram (<xref rid="f0001" ref-type="fig">Figure 1</xref>) [<xref rid="cit0004" ref-type="bibr">4</xref>].<fig position="float" id="f0001" fig-type="figure" orientation="portrait"><label>Figure 1.</label><caption><p>PRISMA flow diagram.</p></caption><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" content-type="color" specific-use="web-only" position="float" orientation="portrait" xlink:href="ZECR_A_2381898_F0001_OC.jpg"><?image-name ZECR_A_2381898_F0001_OC.jpg?><?image-size 122441?><?image-md5 dd65d7d5c9f68d070f8d92caed8642de?><?image-image-server-status LOAD_COMPLETED?><?image-original-height 1138?><?image-original-width 1200?><?image-scaled-height 759?><?image-scaled-width 800?><?image-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/dd65d7d5c9f6/ZECR_A_2381898_F0001_OC.jpg?><?thumb-name ZECR_A_2381898_F0001_OC.gif?><?thumb-size 2800?><?thumb-md5 f872ff5dac2725bfcac98dcacce52cb4?><?thumb-image-server-status NEVER_LOAD?><?thumb-scaled-height 95?><?thumb-scaled-width 100?><?thumb-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/f872ff5dac27/ZECR_A_2381898_F0001_OC.gif?></graphic><graphic xmlns:xlink="http://www.w3.org/1999/xlink" content-type="black-white" specific-use="print-only" position="float" orientation="portrait" xlink:href="ZECR_A_2381898_F0001_PB.jpg"><?image-name ZECR_A_2381898_F0001_PB.jpg?><?image-size 68387?><?image-md5 dd121be84c2b9721645c3e54047d3110?><?image-image-server-status LOAD_COMPLETED?><?image-original-height 1138?><?image-original-width 1200?><?image-scaled-height 759?><?image-scaled-width 800?><?image-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/dd121be84c2b/ZECR_A_2381898_F0001_PB.jpg?><?thumb-name ZECR_A_2381898_F0001_PB.gif?><?thumb-size 3974?><?thumb-md5 50d697e1f9cca7d59a93e4c21bb59dfd?><?thumb-image-server-status NEVER_LOAD?><?thumb-scaled-height 95?><?thumb-scaled-width 100?><?thumb-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/50d697e1f9cc/ZECR_A_2381898_F0001_PB.gif?></graphic></alternatives></fig></p><p>Since whole-body plethysmography is the gold standard for measuring static lung volumes, articles based on multiple-breath gas dilution or washout methods were excluded. If studies provided data from before and after thoracic surgery, only pre-surgery data was included to avoid patients contributing to the result multiple times.</p></sec><sec disp-level="2" id="s0002-s2002"><title>Risk of bias</title><p>The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool was used for evaluating the risk of bias and method quality (<xref rid="f0002" ref-type="fig">Figure 2</xref>) [<xref rid="cit0005" ref-type="bibr">5</xref>]. For each article, the following domains were evaluated: patient selection, index test, reference standard, and flow and timing.
<fig position="float" id="f0002" fig-type="figure" orientation="portrait"><label>Figure 2.</label><caption><p>Risk of bias and applicability assessment using the QUADAS-2 tool.</p></caption><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" content-type="color" specific-use="web-only" position="float" orientation="portrait" xlink:href="ZECR_A_2381898_F0002_OC.jpg"><?image-name ZECR_A_2381898_F0002_OC.jpg?><?image-size 471751?><?image-md5 a21246f3148d377930cbb2dce78fbc88?><?image-image-server-status LOAD_COMPLETED?><?image-original-height 1991?><?image-original-width 1200?><?image-scaled-height 1327?><?image-scaled-width 800?><?image-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/a21246f3148d/ZECR_A_2381898_F0002_OC.jpg?><?thumb-name ZECR_A_2381898_F0002_OC.gif?><?thumb-size 6296?><?thumb-md5 d6c6b9076c5cec80d8c8ee2ea5a392ed?><?thumb-image-server-status NEVER_LOAD?><?thumb-scaled-height 166?><?thumb-scaled-width 100?><?thumb-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/d6c6b9076c5c/ZECR_A_2381898_F0002_OC.gif?></graphic><graphic xmlns:xlink="http://www.w3.org/1999/xlink" content-type="black-white" specific-use="print-only" position="float" orientation="portrait" xlink:href="ZECR_A_2381898_F0002_PB.jpg"><?image-name ZECR_A_2381898_F0002_PB.jpg?><?image-size 150564?><?image-md5 855626d225472a7b06399d97bb10aaeb?><?image-image-server-status LOAD_COMPLETED?><?image-original-height 1991?><?image-original-width 1200?><?image-scaled-height 1327?><?image-scaled-width 800?><?image-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/855626d22547/ZECR_A_2381898_F0002_PB.jpg?><?thumb-name ZECR_A_2381898_F0002_PB.gif?><?thumb-size 6847?><?thumb-md5 3e767c8859456d894ba3202067f6fdfa?><?thumb-image-server-status NEVER_LOAD?><?thumb-scaled-height 166?><?thumb-scaled-width 100?><?thumb-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/3e767c885945/ZECR_A_2381898_F0002_PB.gif?></graphic></alternatives></fig></p><p>It was considered appropriate if plethysmography was performed according to guidelines, such as from the American Thoracic Society and European Respiratory Society [<xref rid="cit0003" ref-type="bibr">3</xref>], or if the described method of static spirometry followed the same standards. A maximum time interval of 30 days between pulmonary function testing and CT acquisition was considered appropriate. However, the acceptable interval was shortened if patients had fluctuating lung function impairment such as in asthma.</p></sec></sec><sec disp-level="1" id="s0003"><title>Results</title><sec disp-level="2" id="s0003-s2001"><title>Search</title><p>We identified 115 articles via the database search (<xref rid="f0001" ref-type="fig">Figure 1</xref>) comprising 111 from the final search and additionally four from the original search (<xref rid="t0004" ref-type="table">Tables A1</xref> and <xref rid="t0002" ref-type="table">2</xref>). Nineteen articles met the inclusion criteria described in <italic toggle="yes">Search and Study Selection</italic>. An additional three eligible articles were uncovered by screening the reference list of these articles. In total, 22 articles were included for revision; eight studies were prospective and 14 retrospective (<xref rid="t0001" ref-type="table">Table 1</xref>).<table-wrap position="float" id="t0001" orientation="portrait"><label>Table 1.</label><caption><p>Study characteristics.</p></caption><table frame="hsides" rules="groups"><colgroup span="1"><col width="1*" align="left" span="1"/><col width="1*" align="left" span="1"/><col width="1*" align="char" char="." span="1"/><col width="1*" align="char" char="." span="1"/><col width="1*" align="center" span="1"/><col width="1*" align="left" span="1"/></colgroup><thead><tr><th align="left" colspan="1" rowspan="1">Study</th><th align="center" colspan="1" rowspan="1">Study Type</th><th align="center" char="." colspan="1" rowspan="1">Publishing Year</th><th align="center" char="." colspan="1" rowspan="1">No. of Participants</th><th align="center" colspan="1" rowspan="1">Age, years<break/>(Mean±SD)</th><th align="center" colspan="1" rowspan="1">Indication, type of subjects</th></tr></thead><tbody><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Bakker JT</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">2022</td><td align="char" char="." colspan="1" rowspan="1">200</td><td align="center" colspan="1" rowspan="1">62 ± 8</td><td align="left" colspan="1" rowspan="1">COPD</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Barjaktarevic I</italic> et al.</td><td align="left" colspan="1" rowspan="1">Prospective, multi-center</td><td align="char" char="." colspan="1" rowspan="1">2015</td><td align="char" char="." colspan="1" rowspan="1">460</td><td align="center" colspan="1" rowspan="1">64 ± 7</td><td align="left" colspan="1" rowspan="1">COPD</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Becker MD</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">1997</td><td align="char" char="." colspan="1" rowspan="1">28</td><td align="center" colspan="1" rowspan="1">65 ± 7</td><td align="left" colspan="1" rowspan="1">COPD</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Brown MS</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">1999</td><td align="char" char="." colspan="1" rowspan="1">43</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">21 normal<break/>9 asthma<break/>9 scleroderma<break/>4 COPD</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Brown MS</italic> et al.</td><td align="left" colspan="1" rowspan="1">Prospective, multi-center</td><td align="char" char="." colspan="1" rowspan="1">2010</td><td align="char" char="." colspan="1" rowspan="1">486</td><td align="center" colspan="1" rowspan="1">63 ± 7</td><td align="left" colspan="1" rowspan="1">COPD</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Chen F</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">2011</td><td align="char" char="." colspan="1" rowspan="1">21</td><td align="center" colspan="1" rowspan="1">42 ± 11</td><td align="left" colspan="1" rowspan="1">Healthy lung donation candidates</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Coxson HO</italic> et al.</td><td align="left" colspan="1" rowspan="1">Prospective, multi-center</td><td align="char" char="." colspan="1" rowspan="1">2008</td><td align="char" char="." colspan="1" rowspan="1">57</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">COPD</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Daghighi A</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, Multi-center</td><td align="char" char="." colspan="1" rowspan="1">2018</td><td align="char" char="." colspan="1" rowspan="1">61</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Thoracic scoliosis</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Garfield JL</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">2012</td><td align="char" char="." colspan="1" rowspan="1">59</td><td align="center" colspan="1" rowspan="1">63 ± 9</td><td align="left" colspan="1" rowspan="1">COPD</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Gawlitza J</italic> et al.</td><td align="left" colspan="1" rowspan="1">Prospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">2017</td><td align="char" char="." colspan="1" rowspan="1">46</td><td align="center" colspan="1" rowspan="1">66 ± 10</td><td align="left" colspan="1" rowspan="1">COPD</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Jung WS</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">2016</td><td align="char" char="." colspan="1" rowspan="1">264</td><td align="center" colspan="1" rowspan="1">61 ± 14</td><td align="left" colspan="1" rowspan="1">LTx candidates grouped according to PFT results: Normal Obstructive Restrictive</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Kauczor HU</italic> et al.</td><td align="left" colspan="1" rowspan="1">Prospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">1998</td><td align="char" char="." colspan="1" rowspan="1">72</td><td align="center" colspan="1" rowspan="1">59</td><td align="left" colspan="1" rowspan="1">Suspected lung disease</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Lacerda LS</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">2018</td><td align="char" char="." colspan="1" rowspan="1">43</td><td align="center" colspan="1" rowspan="1">Cystic fibrosis: 31<break/>Controls: 24<break/>Mean: 27</td><td align="left" colspan="1" rowspan="1">21 Cystic fibrosis<break/>22 Controls</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Matsumoto AJ</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">2017</td><td align="char" char="." colspan="1" rowspan="1">118</td><td align="center" colspan="1" rowspan="1">54 ± 11</td><td align="left" colspan="1" rowspan="1">LTx recipients before transplantation</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">O’Donnell CR</italic> et al.</td><td align="left" colspan="1" rowspan="1">Prospective, multi-center</td><td align="char" char="." colspan="1" rowspan="1">2010</td><td align="char" char="." colspan="1" rowspan="1">132</td><td align="center" colspan="1" rowspan="1">60 ± 11</td><td align="left" colspan="1" rowspan="1">Various indications for CT</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Schlesinger AE</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">1994</td><td align="char" char="." colspan="1" rowspan="1">21</td><td align="center" colspan="1" rowspan="1">11</td><td align="left" colspan="1" rowspan="1">Follow-up of LTx children</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Shen M</italic> et al.</td><td align="left" colspan="1" rowspan="1">Prospective, multi-center</td><td align="char" char="." colspan="1" rowspan="1">2019</td><td align="char" char="." colspan="1" rowspan="1">29</td><td align="center" colspan="1" rowspan="1">62</td><td align="left" colspan="1" rowspan="1">COPD</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Song L</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">2020</td><td align="char" char="." colspan="1" rowspan="1">172</td><td align="center" colspan="1" rowspan="1">66 ± 7</td><td align="left" colspan="1" rowspan="1">COPD</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Tantucci C</italic> et al.</td><td align="left" colspan="1" rowspan="1">Prospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">2016</td><td align="char" char="." colspan="1" rowspan="1">37</td><td align="center" colspan="1" rowspan="1">Control:57 ± 11<break/>Obstructive: 70 ± 9<break/>Restrictive: 66 ± 13</td><td align="left" colspan="1" rowspan="1">Subjects grouped according to PFT results: Controls Obstructive Restrictive</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Wielpütz MO</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, multi-center</td><td align="char" char="." colspan="1" rowspan="1">2014</td><td align="char" char="." colspan="1" rowspan="1">49</td><td align="center" colspan="1" rowspan="1">64 ± 9</td><td align="left" colspan="1" rowspan="1">COPD</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Wu F</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, single-center</td><td align="char" char="." colspan="1" rowspan="1">2021</td><td align="char" char="." colspan="1" rowspan="1">65</td><td align="center" colspan="1" rowspan="1">56</td><td align="left" colspan="1" rowspan="1">Healthy</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Zaporozhan J</italic> et al.</td><td align="left" colspan="1" rowspan="1">Retrospective, multi-center</td><td align="char" char="." colspan="1" rowspan="1">2005</td><td align="char" char="." colspan="1" rowspan="1">31</td><td align="center" colspan="1" rowspan="1">60 ± 8</td><td align="left" colspan="1" rowspan="1">COPD</td></tr></tbody></table><table-wrap-foot><fn id="tfn0001"><p>Note: Study characteristics of all included studies [<xref rid="cit0001" ref-type="bibr">1</xref>,<xref rid="cit0006" ref-type="bibr">6–26</xref>]. COPD: Chronic Obstructive Pulmonary Disease, LTx: Lung transplantation, PFT: Pulmonary function test.</p></fn></table-wrap-foot></table-wrap></p></sec><sec disp-level="2" id="s0003-s2002"><title>Differences in lung volumes measured by CT and Plethysmography</title><p>In the 17 articles that provided absolute TLC volumes derived from plethysmography (p-TLC) and CT (CT-TLC), plethysmography measured a larger volume than quantified in a corresponding inspiratory CT image (<xref rid="t0002" ref-type="table">Table 2</xref> and <xref rid="f0003" ref-type="fig">Figure 3</xref>). On average, p-TLC was 709 mL larger than CT-TLC (maximum: 1380 mL, minimum: 70 mL) and the mean percent deviation was 12.1% (maximum: 23.7%, minimum: 3.7%) with p-TLC as reference.
<fig position="float" id="f0003" fig-type="figure" orientation="portrait"><label>Figure 3.</label><caption><p>Total lung capacity (TLC) plot. <italic toggle="yes">plotted values of differences between TLC (in ml) measured with plethysmography and</italic> CT (ΔTLC) <italic toggle="yes">and given as percent deviation (100% * (plethysmography - CT)/Plethysmography). Black line represents standard deviation when available. Each colour represents a patient group. Blue: mixed. Red: restrictive. Green: healthy. Black: obstructive</italic>. [<xref rid="cit0001" ref-type="bibr">1</xref>,<xref rid="cit0007" ref-type="bibr">7–17</xref>,<xref rid="cit0020" ref-type="bibr">20–24</xref>].</p></caption><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" content-type="color" specific-use="web-only" position="float" orientation="portrait" xlink:href="ZECR_A_2381898_F0003_OC.jpg"><?image-name ZECR_A_2381898_F0003_OC.jpg?><?image-size 102872?><?image-md5 4d40fced1354d646429713bc085082bd?><?image-image-server-status LOAD_COMPLETED?><?image-original-height 721?><?image-original-width 1200?><?image-scaled-height 481?><?image-scaled-width 800?><?image-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/4d40fced1354/ZECR_A_2381898_F0003_OC.jpg?><?thumb-name ZECR_A_2381898_F0003_OC.gif?><?thumb-size 3039?><?thumb-md5 1651c57790f6b412dbff2bb9599471bf?><?thumb-image-server-status NEVER_LOAD?><?thumb-scaled-height 80?><?thumb-scaled-width 133?><?thumb-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/1651c57790f6/ZECR_A_2381898_F0003_OC.gif?></graphic><graphic xmlns:xlink="http://www.w3.org/1999/xlink" content-type="black-white" specific-use="print-only" position="float" orientation="portrait" xlink:href="ZECR_A_2381898_F0003_PB.jpg"><?image-name ZECR_A_2381898_F0003_PB.jpg?><?image-size 59002?><?image-md5 37255ba5a060831938c3eae80a3e4a41?><?image-image-server-status LOAD_COMPLETED?><?image-original-height 721?><?image-original-width 1200?><?image-scaled-height 481?><?image-scaled-width 800?><?image-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/37255ba5a060/ZECR_A_2381898_F0003_PB.jpg?><?thumb-name ZECR_A_2381898_F0003_PB.gif?><?thumb-size 3910?><?thumb-md5 7f869993ba995c28de413207567a5f88?><?thumb-image-server-status NEVER_LOAD?><?thumb-scaled-height 80?><?thumb-scaled-width 133?><?thumb-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/7f869993ba99/ZECR_A_2381898_F0003_PB.gif?></graphic></alternatives></fig><table-wrap position="float" id="t0002" orientation="portrait"><label>Table 2.</label><caption><p>Total lung capacity data.</p></caption><table frame="hsides" rules="groups"><col width="1*" align="center" span="1"/><tbody><tr><td align="center" colspan="1" rowspan="1"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" id="ilg0001" xlink:href="ZECR_A_2381898_ILG0001.jpg"><?image-name ZECR_A_2381898_ILG0001.jpg?><?image-size 71201?><?image-md5 5cb0ea7a761ba62cf6929f51b126f704?><?image-image-server-status NEVER_LOAD?><?image-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/5cb0ea7a761b/ZECR_A_2381898_ILG0001.jpg?></inline-graphic></td></tr></tbody></table><table-wrap-foot><fn id="tfn0002"><p>Note: Total lung capacity (TLC). ΔTLC: difference between Plethysmograpic-TLC and CT-TLC. In cases where difference was not provided, the authors calculated it as: ΔTLC = P-TLC – CT-TLC. Percent Deviation = (ΔTLC/P-TLC)*100. YACTA, LowATT and Pulmo3D are different CT software packages. Each colour represents a patient group. Blue: mixed. Red: restrictive. Green: healthy. Black: obstructive [<xref rid="cit0001" ref-type="bibr">1</xref>,<xref rid="cit0006" ref-type="bibr">6–26</xref>].</p></fn></table-wrap-foot></table-wrap></p><p>All except one study (<italic toggle="yes">O’Donnell CR</italic> et al. [<xref rid="cit0001" ref-type="bibr">1</xref>]) calculated a correlation coefficient between results from both modalities [<xref rid="cit0001" ref-type="bibr">1</xref>]. In general, CT-TLC correlated well with p-TLC averaging 0.83 (maximum: 0.98, minimum: 0.38). <italic toggle="yes">Gawlitza J</italic> et al. [<xref rid="cit0006" ref-type="bibr">6</xref>] were the only ones observing a weak association (0.38) between plethysmography- and CT-derived lung volumes.</p><p>Seven articles provided absolute measurements of RV [<xref rid="cit0007" ref-type="bibr">7–13</xref>] (<xref rid="t0003" ref-type="table">Table 3</xref>). The mean difference between p-RV and CT-RV was −603 mL (maximum: −1060 mL, minimum: −290 mL), and the average percent deviation was −17.8% (maximum: −39.1%, minimum: −6.0%). Correlations for the RV assessments were somewhat weaker but still good as indicated by an average correlation coefficient of 0.76 (maximum: 0.84, minimum: 0.65).<table-wrap position="float" id="t0003" orientation="portrait"><label>Table 3.</label><caption><p>Residual volume data.</p></caption><table frame="hsides" rules="groups"><col width="1*" align="center" span="1"/><tbody><tr><td align="center" colspan="1" rowspan="1"><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" id="ilg0002" xlink:href="ZECR_A_2381898_ILG0002.jpg"><?image-name ZECR_A_2381898_ILG0002.jpg?><?image-size 33516?><?image-md5 9314d104d23ca216a0e3e90725b93cd0?><?image-image-server-status NEVER_LOAD?><?image-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/9314d104d23c/ZECR_A_2381898_ILG0002.jpg?></inline-graphic></td></tr></tbody></table><table-wrap-foot><fn id="tfn0003"><p>Residual volume (RV). ΔRV: difference between Plethysmographic-RV (p-RV) and CT-RV. In cases where difference was not provided, the author calculated it as: ΔRV = P-RV – CT-RV. Percent Deviation = (ΔRV/P-RV)*100. Each colour represents a patient group. Blue: mixed. Green: healthy. Black: obstructive [<xref rid="cit0006" ref-type="bibr">6–13</xref>,<xref rid="cit0025" ref-type="bibr">25</xref>].</p></fn></table-wrap-foot></table-wrap></p><p>Five out of the seven articles on RV studied patients with COPD exclusively [<xref rid="cit0007" ref-type="bibr">7</xref>,<xref rid="cit0008" ref-type="bibr">8</xref>,<xref rid="cit0010" ref-type="bibr">10</xref>,<xref rid="cit0011" ref-type="bibr">11</xref>,<xref rid="cit0013" ref-type="bibr">13</xref>] (<xref rid="t0003" ref-type="table">Table 3</xref>). When comparing pooled volumes in subjects with COPD and non-COPD subjects (these included healthy subjects and patients with suspected lung disease, respectively), it is evident that a moderate disagreement in mean absolute difference between the groups (COPD: −561 mL, non-COPD: −730 mL) contributes to a significant discrepancy in percent deviation from the reference standard, p-RV (COPD: 12.2%, non-COPD: 31.8%) (<xref rid="f0004" ref-type="fig">Figure 4</xref>).
<fig position="float" id="f0004" fig-type="figure" orientation="portrait"><label>Figure 4.</label><caption><p>Residual volume (RV) plot. <italic toggle="yes">plotted values of differences between RV (in ml) measured with plethysmography and</italic> CT (ΔRV) <italic toggle="yes">and given as percent deviation (100% * (plethysmography - CT)/Plethysmography). Black line represents standard deviation when available. Each colour represents a patient group. Blue: mixed. Green: healthy. Black: obstructive</italic>. [<xref rid="cit0007" ref-type="bibr">7–13</xref>].</p></caption><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" content-type="color" specific-use="web-only" position="float" orientation="portrait" xlink:href="ZECR_A_2381898_F0004_OC.jpg"><?image-name ZECR_A_2381898_F0004_OC.jpg?><?image-size 50120?><?image-md5 4c369ff5e02ad0913d8dbfea83c84abb?><?image-image-server-status LOAD_COMPLETED?><?image-original-height 341?><?image-original-width 1200?><?image-scaled-height 227?><?image-scaled-width 800?><?image-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/4c369ff5e02a/ZECR_A_2381898_F0004_OC.jpg?><?thumb-name ZECR_A_2381898_F0004_OC.gif?><?thumb-size 3094?><?thumb-md5 5d0e46fe0bbc419a6637d65a693dfc7b?><?thumb-image-server-status NEVER_LOAD?><?thumb-scaled-height 57?><?thumb-scaled-width 200?><?thumb-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/5d0e46fe0bbc/ZECR_A_2381898_F0004_OC.gif?></graphic><graphic xmlns:xlink="http://www.w3.org/1999/xlink" content-type="black-white" specific-use="print-only" position="float" orientation="portrait" xlink:href="ZECR_A_2381898_F0004_PB.jpg"><?image-name ZECR_A_2381898_F0004_PB.jpg?><?image-size 27013?><?image-md5 95caca56bdedc4ed4cf2c415a8171729?><?image-image-server-status LOAD_COMPLETED?><?image-original-height 341?><?image-original-width 1200?><?image-scaled-height 227?><?image-scaled-width 800?><?image-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/95caca56bded/ZECR_A_2381898_F0004_PB.jpg?><?thumb-name ZECR_A_2381898_F0004_PB.gif?><?thumb-size 4177?><?thumb-md5 f0805ce290484a188bcdf73c72c193ce?><?thumb-image-server-status NEVER_LOAD?><?thumb-scaled-height 57?><?thumb-scaled-width 200?><?thumb-cloudpmc-urn urn:cdn:blobs/bf4d/11288198/f0805ce29048/ZECR_A_2381898_F0004_PB.gif?></graphic></alternatives></fig></p><p>When TLC data is divided into an obstructive and a non-obstructive group, ΔTLC appears slightly larger in obstructive patients (obstructive: 781 mL, non-obstructive: 609 mL), whereas percent deviation is slightly smaller (obstructive: 11.4%, non-obstructive: 13.5%) (<xref rid="f0003" ref-type="fig">Figure 3</xref>).</p><p>Three studies stated that a bronchodilator was administered before performing body plethysmography and CT [<xref rid="cit0007" ref-type="bibr">7</xref>,<xref rid="cit0011" ref-type="bibr">11</xref>,<xref rid="cit0014" ref-type="bibr">14</xref>]. In contrast, <italic toggle="yes">Tantucci C</italic> et al. stated that when relevant, inhalations were withdrawn 24–48 h beforehand [<xref rid="cit0015" ref-type="bibr">15</xref>]. However, results from these articles did not seem to differ noticeably from other articles on obstructive patients.</p><p><italic toggle="yes">Jung WS</italic> et al. and <italic toggle="yes">Tantucci C</italic> et al. categorized subjects into restrictive, obstructive and control groups according to dynamic spirometry results. In the study conducted by <italic toggle="yes">Jung WS</italic> et al. patients with a restrictive pattern had the smallest ΔTLC, percent deviation and correlation coefficient [<xref rid="cit0016" ref-type="bibr">16</xref>]. In contrast, <italic toggle="yes">Tantucci C</italic> et al. reported an excellent correlation (0.98, 0.97 and 0.98) and minimal ΔTLC (110 mL, 70 mL and 80 mL) in all patient groups showing no noteworthy variation in the groups [<xref rid="cit0015" ref-type="bibr">15</xref>].</p><p>This was also one of only two studies utilizing a spirometer to gate CT acquisition – all other studies gave conventional breath-hold instructions. <italic toggle="yes">Bakker JT</italic> et al. aimed to investigate the effects of spirometric gating on patients with COPD by comparing it to instructing patients to hold their breath [<xref rid="cit0007" ref-type="bibr">7</xref>]. This technique rendered noticeable improvements in all parameters in an otherwise identical study setting (<xref rid="t0002" ref-type="table">Tables 2</xref> and <xref rid="t0003" ref-type="table">3</xref>).</p></sec></sec><sec disp-level="1" id="s0004"><title>Discussion</title><p>The findings of the present review suggest that discrepancy between plethysmography- and CT-derived lung volumes is a universal phenomenon. Specifically, quantitative CT routinely underestimates TLC and overestimates RV in comparison to body plethysmography. Utilizing a spirometer to gate CT acquisition reduces disagreement noticeably though it does not eliminate it entirely.</p><p>TLC can be defined as the total gas volume in the lung after a full inspiratory maneuver [<xref rid="cit0003" ref-type="bibr">3</xref>]. It has been challenging to determine whether gas in the conductive airways is included in this definition. Even though it might seem trivial, this appears to be an import factor to consider. Body plethysmography incorporates volumes in the oropharynx, trachea, and anatomic dead space in the main conducting airways [<xref rid="cit0010" ref-type="bibr">10</xref>]. Some types of CT segmentation software include gas volumes in the tracheobronchial tree, others do not. For instance, the post-processing software used in <italic toggle="yes">Shen M</italic> et al.’s study excluded these volumes [<xref rid="cit0010" ref-type="bibr">10</xref>]. In contrast, <italic toggle="yes">Tantucci C</italic> et al. included anatomic dead space of 150 mL in their CT-TLC calculations [<xref rid="cit0015" ref-type="bibr">15</xref>]. Compressed gas in the upper gastrointestinal tract might also further increase FRC, which forms the basis for TLC and RV calculations [<xref rid="cit0003" ref-type="bibr">3</xref>].</p><p>Another important factor to note is the difference in posture (supine in CT vs. upright position in body plethysmography). By comparing conventional supine CT with upright CT in a specialized CT scanner, a study demonstrated that CT-based inspiratory and expiratory volumes were significantly smaller in the supine position than in the standing and sitting position in healthy subjects [<xref rid="cit0027" ref-type="bibr">27</xref>]. This is largely due to abdominal content pressing up against the diaphragm in the supine position, which has been shown by other studies to reduce vital capacity by less than 10% in normal subjects [<xref rid="cit0017" ref-type="bibr">17</xref>]. This is consistent with the results from the present review showing that CT-TLC is smaller than p-TLC.</p><p>However, the above studies contradict the present findings of a generally negative ΔRV (<xref rid="t0003" ref-type="table">Table 3</xref>). This may be due to various CT software packages include lung tissue and blood vessels in their TLC volumetrics, which proportionally makes up more of the total lung volume at full expiration. ΔRV was largely based on data from COPD patients, a disease characterized by hyperinflation and an impaired ability to fully expire. Perhaps, the supine position exacerbates an already present muscle weakness, such as in the accessory expiratory muscles.</p><p><italic toggle="yes">Tantucci C</italic> et al. calibrated CT and plethysmography TLC results by adding or subtracting the difference between vital capacity obtained in the seated and supine position, respectively, and presented excellent correlations [<xref rid="cit0015" ref-type="bibr">15</xref>] (<xref rid="t0002" ref-type="table">Table 2</xref>).</p><p>Body plethysmography measures pressure changes at the mouth opening based on the assumption that these reflect pressure changes in the alveoli during shutter valve occlusion. In the presence of airway obstruction, however, this assumption might fail. <italic toggle="yes">O’Donnell CR</italic> et al. find that a worsening in airway obstruction leads to increasing overestimation of TLC, which might be due to an incomplete transmission of alveolar pressure changes to the mouth [<xref rid="cit0028" ref-type="bibr">28</xref>]. This may be part of the reason for ΔTLC being slightly larger in studies with data from obstructive patients.</p><p>Plethysmography is a very standardized method of determining lung volumes with universally applied guidelines by the American Thoracic Society and the European Respiratory Society [<xref rid="cit0003" ref-type="bibr">3</xref>]. A skilled technician instructs the patient to perform a sequence of respiratory maneuvers, and multiple attempts are made to obtain repeatability of the volume results to correct for variability in patient effort and cooperation, which can be monitored simultaneously.</p><p>Due to radiation concerns, CT acquisition is rarely repeated, and thus such unpredictable errors cannot be rectified. This becomes increasingly relevant in patients having difficulty maintaining inspiratory and expiratory breath-hold during the scan due to dyspnea. It is not possible to confirm with certainty the amount of effort patients put into following instructions. As CT accuracy depends on subject performance, being able to monitor patient effort becomes crucial in determining reliability of volume quantifications as well as certain qualitative radiological descriptions.</p><p><italic toggle="yes">Bakker JT</italic> et al. showed that utilizing a spirometer can help bring CT-based volumes to a closer alignment with plethysmography measurements in patients with severe emphysema [<xref rid="cit0007" ref-type="bibr">7</xref>].</p><p>Spirometry gating is an easily applicable tool and largely tolerant to subject’s cooperation. Although studies on this are limited, the technique shows great promise in minimizing disagreements ascribable to patient effort or cooperation between patient and instructor. This would be relevant for patients already undergoing inspiratory and expiratory CT evaluation, such as candidates for lung volume reduction surgery or lung transplantation. For patients without a CT appointment, these improvements do not justify body plethysmography being replaced by spirometry-gated CT as radiation is still a concern.</p><p>Spirometers with a shutter valve are also available ensuring total control of airflow. However, <italic toggle="yes">Kauczor HU</italic> et al. had to discontinue spirometry gating with shutter occlusion as four out of five subjects took the device out of their mouth for both inspiratory and expiratory CT acquisition [<xref rid="cit0009" ref-type="bibr">9</xref>]. Sudden blockage of airflow may not be tolerated by all patients, in particular children, patients suffering from claustrophobia, and patients prone to anxiety, which many people with COPD experience [<xref rid="cit0029" ref-type="bibr">29</xref>].</p><p>CT machines differ in scan time ranging from one to several seconds. Many patients with severe lung disease are not capable of holding their breath for the required amount of time – regardless of spirometry gating. The studies using a spirometer scanned their patients within 6 seconds. Thus, their results may not be applicable in hospital departments with slow scanners. Other CT specifications, such as a difference in slice thickness, do not seem to have a significant impact on the results (<xref rid="t0006" ref-type="table">Table A3</xref>).</p><p>The limitations of the present review need to be addressed. It was decided to narrow down the literature search, which entails a risk of missing eligible articles. In addition, this review is based on results from one single database, PubMed. It is possible that the results would be different if the search had included more databases e.g. Embase. The good congruence between both modalities may be attributed to the fact that publishers tend to exclude studies if their findings contradict current research in the area.</p><p>Another limitation may stem from individual variations in age distribution. Most studies predominantly involved middle-aged patients in their 50s and 60s. However, three studies by <italic toggle="yes">Chen F</italic> et al. <italic toggle="yes">Lacerda LS</italic> et al. and <italic toggle="yes">Schlesinger AE</italic> et al. included younger groups with mean ages of 42, 27 and 11 years, respectively [<xref rid="cit0018" ref-type="bibr">18–20</xref>]. As expected, the first two studies aligned well with overall findings, as they included adult participants whose body composition and size are comparable to those of middle-aged patients.</p><p>It might be anticipated that the smaller lung volume of <italic toggle="yes">Schlesinger AE</italic> et al.’s group, consisting of children with lung transplants aged 3 to 18 years, would result in a smaller absolute difference in total lung capacity, while percentage deviation would likely remain consistent with general outcomes of this study [<xref rid="cit0018" ref-type="bibr">18</xref>]. However, only a correlation coefficient for TLC was provided, which stood at 0.92, indicating a strong correlation as expected.</p><p>Based on the QUADAS-2 risk of bias assessment, 16 articles included domains with high risk of bias, whereas two articles demonstrated a low risk of bias. An inappropriately long time interval between plethysmography and CT leads to a high risk rating in the flow and timing domain. Four studies were unclear, as they did not provide sufficient information to assess the domains of interest. The majority of studies were retrospective and they used data originally collected for other purposes. Moreover, there is a risk of extracting patient data out of convenience rather than relevance in this type of study. For instance, <italic toggle="yes">Lacerda LS</italic> et al. scored a high risk of bias in the patient selection domain due to their study being based on a convenience sample of patients [<xref rid="cit0019" ref-type="bibr">19</xref>]. Yet, there seems to be no difference between retrospective and prospective studies regarding their results.</p></sec><sec disp-level="1" id="s0005"><title>Conclusion</title><p>CT-based volume quantifications align well with lung volumes measured in the whole-body plethysmograph, although a clear tendency to underestimate TLC and overestimate RV in comparison to gold standard plethysmography is evident. Spirometry gating continues to be a suitable tool to reduce disagreement and can be of assistance when patients are already undergoing CT. However, research on this instrument is scarce and limitations of the present review should be considered. Standardization of CT software and further research is needed before evaluation of the static volumes of pulmonary function can be fully based on CT.</p></sec></body><back><sec sec-type="data-availability" disp-level="1" id="s0006"><title>Data availability statement</title><p>The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request in anonymized form.</p></sec><sec sec-type="COI-statement" disp-level="1" id="s0007"><title>Disclosure statement</title><p>No potential conflict of interest was reported by the author(s).</p></sec><ref-list><title>References</title><ref id="cit0001"><label>[1]</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><string-name name-style="western"><surname>O’Donnell</surname>
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<table-wrap position="anchor" id="t0004" orientation="portrait"><label>Table A1.</label><caption><p>Search protocol #.</p></caption><table frame="hsides" rules="groups"><colgroup span="1"><col width="1*" align="left" span="1"/><col width="1*" align="left" span="1"/><col width="1*" align="center" span="1"/></colgroup><thead><tr><th align="left" colspan="1" rowspan="1">Database</th><th align="center" colspan="1" rowspan="1">Search Strings</th><th align="center" colspan="1" rowspan="1">Hits</th></tr></thead><tbody><tr><td rowspan="4" align="left" colspan="1">PubMed 1966 -</td><td align="left" colspan="1" rowspan="1"><bold>#1</bold>:(“Lung Volume Measurements”[Mesh]) OR (“Lung volume*” OR “Total lung capacity” OR “TLC” OR “Residual volume” OR “RV” OR “Total lung volume” OR “Functional residual capacity” OR “FRC” OR “Inspiratory lung volume” OR “Expiratory lung volume” OR “Lung-volume quantification” OR “end-inspiratory lung volume” OR “end-expiratory lung volume” OR “Lung volume measurement*” OR “Static lung volumes” OR “Lung Capacity”)</td><td align="center" colspan="1" rowspan="1">91782</td></tr><tr><td align="left" colspan="1" rowspan="1"><bold>#2</bold>:(“Tomography, X-Ray Computed”[Mesh]) OR (“Computer tomography” OR “computer-assisted tomography” OR “Chest computed tomography” OR “CT” OR “Inspiration CT” OR “Expiration CT” OR “CT-derived lung volumes” OR “Multidetector Computed tomography” OR “computed tomography segmentation” OR “computed tomography” OR “Computerized tomography” OR “Volumetric chest CT” OR “CAT scan” OR “low-dose CT” OR “high-resolution CT” OR “tomodensitometry” OR “quantitative CT”)</td><td align="center" colspan="1" rowspan="1">903743</td></tr><tr><td align="left" colspan="1" rowspan="1"><bold>#3</bold>:(“Plethysmography, Whole Body”[Mesh]) OR (“Body plethysmography” OR “plethysmography analysis” OR “plethysmographic” OR “plethysmographic methods” OR “Respiratory function tests” OR “Static spirometry” OR “Body box” OR “Plethysmograph*” OR “Whole Body Plethysmography” OR “Pulmonary function test*”)</td><td align="center" colspan="1" rowspan="1">80527</td></tr><tr><td align="left" colspan="1" rowspan="1"><bold>#1</bold> AND <bold>#2</bold> AND <bold>#3</bold></td><td align="center" colspan="1" rowspan="1">1405</td></tr></tbody></table><table-wrap-foot><fn id="tfn0004"><p>Note: Protocol 1: the original search on PubMed using the block searching strategy.</p></fn></table-wrap-foot></table-wrap>
</p><p>
<table-wrap position="anchor" id="t0005" orientation="portrait"><label>Table A2.</label><caption><p>Search Protocol #2.</p></caption><table frame="hsides" rules="groups"><colgroup span="1"><col width="1*" align="left" span="1"/><col width="1*" align="left" span="1"/><col width="1*" align="center" span="1"/></colgroup><thead><tr><th align="left" colspan="1" rowspan="1">Database</th><th align="center" colspan="1" rowspan="1">Search Strings</th><th align="center" colspan="1" rowspan="1">Hits</th></tr></thead><tbody><tr><td rowspan="4" align="left" colspan="1">PubMed 1966 -</td><td align="left" colspan="1" rowspan="1"><bold>#1</bold>: (“Total Lung Capacity”[Mesh]) OR (“Total Lung Capacity” OR “TLC”)</td><td align="center" colspan="1" rowspan="1">47199</td></tr><tr><td align="left" colspan="1" rowspan="1"><bold>#2</bold>: (“Tomography, X-Ray Computed”[Mesh]) OR (“Computer tomography” OR “computer-assisted tomography” OR “Chest computed tomography” OR “CT” OR “Inspiration CT” OR “Expiration CT” OR “CT-derived lung volumes” OR “Multidetector Computed tomography” OR “computed tomography segmentation” OR “computed tomography” OR “Computerized tomography” OR “Volumetric chest CT” OR “CAT scan” OR “low-dose CT” OR “high-resolution CT” OR “tomodensitometry” OR “quantitative CT”)</td><td align="center" colspan="1" rowspan="1">903743</td></tr><tr><td align="left" colspan="1" rowspan="1"><bold>#3</bold>:(“Plethysmography, Whole Body”[Mesh]) OR (“Body plethysmography” OR “plethysmography analysis” OR “plethysmographic” OR “plethysmographic methods” OR “Static spirometry” OR “Body box” OR “Plethysmograph*” OR “Whole Body Plethysmography”)</td><td align="center" colspan="1" rowspan="1">25428</td></tr><tr><td align="left" colspan="1" rowspan="1"><bold>#1</bold> AND <bold>#2</bold> AND <bold>#3</bold></td><td align="center" colspan="1" rowspan="1">111</td></tr></tbody></table><table-wrap-foot><fn id="tfn0005"><p>Note: Protocol 2: the narrowed search on PubMed using the block searching strategy.</p></fn></table-wrap-foot></table-wrap>
<table-wrap position="anchor" id="t0006" orientation="portrait"><label>Table A3.</label><caption><p>CT Specifications.</p></caption><table frame="hsides" rules="groups"><colgroup span="1"><col width="1*" align="left" span="1"/><col width="1*" align="left" span="1"/><col width="1*" align="left" span="1"/><col width="1*" align="center" span="1"/><col width="1*" align="center" span="1"/><col width="1*" align="left" span="1"/></colgroup><thead><tr><th align="left" colspan="1" rowspan="1">Study</th><th align="center" colspan="1" rowspan="1">Gating</th><th align="center" colspan="1" rowspan="1">CT Scanner</th><th align="center" colspan="1" rowspan="1">Slice Thickness (mm)</th><th align="center" colspan="1" rowspan="1">Scan Time (sec)</th><th align="center" colspan="1" rowspan="1">Volumetric Software</th></tr></thead><tbody><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Bakker JT</italic> et al.</td><td align="left" colspan="1" rowspan="1">Gated group:<break/>Spirometric gating without shutter occlusion.<break/>Non-gated group:<break/>Breath-hold.</td><td align="left" colspan="1" rowspan="1">Second-generation dual source CT scanner (CT Somatom Definition Flash; Siemens, Erlangen, Germany)</td><td align="center" colspan="1" rowspan="1">1</td><td align="center" colspan="1" rowspan="1">1.5</td><td align="left" colspan="1" rowspan="1">LungQ; Thirona, Nijemegen, The Netherlands</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Barjaktarevic I</italic> et al.</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Multislice CT scanning (GE Healthcare or Siemens healthcare scanners)</td><td align="center" colspan="1" rowspan="1">1, 1.25</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Pulmonary Workstation 2.0 software (VIDA Diagnostics Inc)</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Becker MD</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">Conventional scanner (GE 9800 HiLite; GE Medical Systems, Milwaukee, W1)</td><td align="center" colspan="1" rowspan="1">10</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Custom software written in Visual C++ (Microsoft, Redmond, WA)</td></tr><tr><td align="left" colspan="1" rowspan="1">
<italic toggle="yes">Brown MS et al. 1999</italic>
</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">Either helical or electron beam CT. Helical: GE HiSpeed Advantage or CT/I scanners (GE Medical Systems, Milwaukee, WI, U.S.A.). Electron beam: Siemens Evolution scanner (Siemens Medical Systems, Iselin, NJ, U.S.A.)</td><td align="center" colspan="1" rowspan="1">6, 8, 10</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Custom software</td></tr><tr><td align="left" colspan="1" rowspan="1">
<italic toggle="yes">Brown MS et al. 2010</italic>
</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">Multicenter study with different scanners (GE, Siemens, Philips, Toshiba)</td><td align="center" colspan="1" rowspan="1">5–10</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Custom made knowledge-based segmentation software</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Chen F</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">multidetector Aquilion 64 CT scanner (Toshiba Medical Systems, Tochigi, Japan)</td><td align="center" colspan="1" rowspan="1">0.5</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">AZE Virtual Place Lexus workstation (AZE Ca, Ltd, Tokyo, Japan)</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Coxson HO</italic> et al.</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">High-resolution CT, Multislice CT or thick slice protocol</td><td align="center" colspan="1" rowspan="1">1, 1.25, 5</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Custom software (EmphylxJ, Vancouver, BC, Canada)</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Daghighi A</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">SOMATOM Definition Flash, Siemens Medical Solutions, Forchheim, Germany</td><td align="center" colspan="1" rowspan="1">4</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">MIALite</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Garfield JL</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">16 or 64 MDCT scanner (Somatom Sensation; Siemens Medical Systems, Erlangen, Germany)</td><td align="center" colspan="1" rowspan="1">0.75, 5</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Custom software (Pulmonary Workstation Plus, VIDA Diagnostics, Inc, Coralville, IA)</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Gawlitza J</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">3rd generation dual-source CT (Somatom FORCE, Siemens Healthineers, Forchheim, Germany)</td><td align="center" colspan="1" rowspan="1">1.5</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Dedicated semiautomatic software (SyngoViaB10, Pulmo3D, Siemens Healthineers, Forchheim, Germany)</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Jung WS</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">128-slice (Somatom Definition AS+) or 64-slice (Somatom Sensation 64) or 16-slice (Somatom Sensation 16; Siemens Medical Solutions, Erlangen, Germany) multidetector CT</td><td align="center" colspan="1" rowspan="1">3, 5</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Aquarius iNtuition version 4.4.6; TeraRecon, Foster City, CA</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Kauczor HU</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">Unenhanced helical CT using Somatom Plus-S scanner (Siemens, Erlangen, Germany)</td><td align="center" colspan="1" rowspan="1">8</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Pulmo-CT Siemens or Allegro workstation (ISG Technologies, Mississauga, Ontario, Canada)</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Lacerda LS</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">64-channel Multislice Philips system (Brilliance 40, Philips Medical Systems, Cleveland, Ohio)</td><td align="center" colspan="1" rowspan="1">2</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">OsiriX program (OsiriX 64-bits, Pixmeo Sarl, Geneva, Switzerland)</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Matsumoto AJ</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">Multicenter, retrospective with different spiral-CT scanners (Siemens, GE, Imatron, Toshiba)</td><td align="center" colspan="1" rowspan="1">1–5</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">CALIPER</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">O’Donnell CR</italic> et al.</td><td align="left" colspan="1" rowspan="1">Hospital 1: Spirometric gating<break/>Hospital 2: Breath-hold<break/>Hospital 3: Breath-hold</td><td align="left" colspan="1" rowspan="1">Three centers with spiral-CT scanners</td><td align="center" colspan="1" rowspan="1">–</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Custom software</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Schlesinger AE</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">Helical CT in 17 patients and conventional in remaining four (Somatom Plus S, Siemens, Erlangen, Germany)</td><td align="center" colspan="1" rowspan="1">–</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Manual tracing</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Shen M</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">64-slice multiple-detector CT scanner (Somatom Sensation 64; Siemens, Erlangen, Germany)</td><td align="center" colspan="1" rowspan="1">1</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">The LungSeg Toolbox (The Hamlyn Centre, Imperial College London, UK) or Syngo CT Pulmo 3D (Siemens Healthineers GmbH, Erlangen, Germany)</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Song L</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">Noncontrast multislice CT (MSCT) scanning (Light Speed Ultra 8 or Revolution EVO, both General Electric Healthcare, Chicago, IL, USA)</td><td align="center" colspan="1" rowspan="1">0.625, 1.25</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">MeVis PULMO3D software (v 3.7.1, Fraunhofer MEVIS, Bremen, Germany)</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Tantucci C</italic> et al.</td><td align="left" colspan="1" rowspan="1">Spirometric gating with shutter occlusion</td><td align="left" colspan="1" rowspan="1">Multidetector CT scanner (Somatom Definition Flash, Siemens Medical Solutions, Forchheim, Germany)</td><td align="center" colspan="1" rowspan="1">1</td><td align="center" colspan="1" rowspan="1">5.7</td><td align="left" colspan="1" rowspan="1">Aquarius iNtuition version 4.4.6; TeraRecon, Foster City, CA</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Wielpütz MO</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">4-slice Volume Zoom helical computer tomograph (Siemens Medical Solutions AG, Forchheim, Germany)</td><td align="center" colspan="1" rowspan="1">1.25</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">YACTA (in-house software) or LowATT (Aquarius) or Pulmo 3D (Syngo.Via)</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Wu F</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">64-detector scanner (IQon Spectral CT, Philips Healthcare, Best, The Netherlands)</td><td align="center" colspan="1" rowspan="1">1</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Philips IntelliSpace Portal post-processing workstation (version 12.0) using Chronic Obstructive Pulmonary Disease (COPD) analysis software</td></tr><tr><td align="left" colspan="1" rowspan="1"><italic toggle="yes">Zaporozhan J</italic> et al.</td><td align="left" colspan="1" rowspan="1">Breath-hold</td><td align="left" colspan="1" rowspan="1">16-detector CT (Aquilion-16; Toshiba Medical Systems, Tochigi, Japan)</td><td align="center" colspan="1" rowspan="1">1</td><td align="center" colspan="1" rowspan="1">–</td><td align="left" colspan="1" rowspan="1">Self-written software (YACTA; Mainz, Germany)</td></tr></tbody></table><table-wrap-foot><fn id="tfn0006"><p>Note: CT specifications and gating techniques used in all included articles [<xref rid="cit0001" ref-type="bibr">1</xref>,<xref rid="cit0006" ref-type="bibr">6–26</xref>].</p></fn></table-wrap-foot></table-wrap>
</p></app></app-group></back></article>