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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Oncol.</journal-id>
<journal-title>Frontiers in Oncology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Oncol.</abbrev-journal-title>
<issn pub-type="epub">2234-943X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fonc.2023.1202505</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Oncology</subject>
<subj-group>
<subject>Systematic Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Head-to-head comparison of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT in the evaluation of primary digestive system cancer: a systematic review and meta-analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Ouyang</surname>
<given-names>Jiqi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2348658"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ding</surname>
<given-names>Peiwen</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2348680"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Zhang</surname>
<given-names>Runshun</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2274864"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lu</surname>
<given-names>Yuexia</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2348618"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Gastroenterology, Guang&#x2019;anmen Hospital, China Academy of Chinese Medical Sciences</institution>, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Graduate School of China Academy of Traditional Chinese Medicine</institution>, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Clinical School, Chengdu University of Traditional Chinese Medicine</institution>, <addr-line>Chengdu, Sichuan</addr-line>, <country>China</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Department of Oncology, Hospital of Chengdu University of Traditional Chinese Medicine</institution>, <addr-line>Chengdu, Sichuan</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Pankaj Gupta, Post Graduate Institute of Medical Education and Research (PGIMER), India</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Amir Hossein Aalami, Islamic Azad University of Mashhad, Iran; Salvatore Annunziata, Fondazione Policlinico Universitario A. Gemelli IRCCS, Italy</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Runshun Zhang, <email xlink:href="mailto:runshunzhang@139.com">runshunzhang@139.com</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>26</day>
<month>06</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>13</volume>
<elocation-id>1202505</elocation-id>
<history>
<date date-type="received">
<day>08</day>
<month>04</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>08</day>
<month>06</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Ouyang, Ding, Zhang and Lu</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Ouyang, Ding, Zhang and Lu</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>
<sec>
<title>Introduction</title>
<p>Althoug <sup>18</sup>F-FDG positron emission tomography/computed tomography (PET/CT) is widely accepted as a diagnostic tool for detecting digestive cancers, <sup>68</sup>Ga-FAPI-04 PET/CT may perform better in detecting gastrointestinal malignancies at an earlier stage. This study aimed to systematically review the diagnostic performance of <sup>68</sup>Ga-FAPI-04 PET/CT compared with that of <sup>18</sup>F-FDG PET/CT in primary digestive system cancers.</p>
</sec>
<sec>
<title>Methods</title>
<p>In this study, a comprehensive search using the PubMed, EMBASE, and Web of Science databases was performed to identify studies that met the eligibility criteria from the beginning of the databases to March 2023. The quality of the relevant studies with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) method was assessed using the RevMan 5.3 software. Sensitivity and specificity were calculated using bivariate random-effects models, and heterogeneity was assessed with the I<sup>2</sup> statistic and meta-regression analysis using the R 4.22 software.</p>
</sec>
<sec>
<title>Results</title>
<p>A total of 800 publications were identified in the initial search. Finally, 15 studies comprising 383 patients were included in the analysis. The pooled sensitivity and specificity of <sup>68</sup>Ga-FAPI-04 PET/CT were 0.98 (95% CI, 0.94&#x2013;1.00) and 0.81 (95% CI, 0.23&#x2013;1.00), whereas those of <sup>18</sup>F-FDG PET/CT were 0.73 (95% CI, 0.60&#x2013;0.84) and 0.77 (95% CI, 0.52&#x2013;0.95), respectively. <sup>68</sup>Ga-FAPI-04 PET/CT performed better for specific tumours, particularly in gastric, liver, biliary tract, and pancreatic cancers. Both imaging modalities had essentially the same diagnostic efficacy in colorectal cancer.</p>
</sec>
<sec>
<title>Conclusions</title>
<p>
<sup>68</sup>Ga-FAPI-04 PET/CT showed a higher diagnostic ability than <sup>18</sup>F-FDG PET/CT in terms of diagnosing primary digestive tract cancers, especially gastric, liver, biliary tract, and pancreatic cancers. The certainty of the evidence was high due to the moderately low risk of bias and low concern regarding applicability. However, the sample size of the included studies was small and heterogeneous. More high-quality prospective studies are needed to obtain higher-quality evidence in the future.</p>
</sec>
<sec>
<title>Systematic Review Registration</title>
<p>The systematic review was registered in PROSPERO [CRD42023402892].</p>
</sec>
</abstract>
<kwd-group>
<kwd>68 Ga-FAPI-04</kwd>
<kwd>18 F-FDG</kwd>
<kwd>PET/CT</kwd>
<kwd>primary cancer</kwd>
<kwd>digestive system</kwd>
<kwd>meta-analysis</kwd>
</kwd-group>
<counts>
<fig-count count="6"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="46"/>
<page-count count="10"/>
<word-count count="4860"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Cancer Imaging and Image-directed Interventions</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Digestive system cancer affects the largest number of organs and is widely distributed (<xref ref-type="bibr" rid="B1">1</xref>). According to the GLOBOCAN 2020 report (<xref ref-type="bibr" rid="B2">2</xref>), cancers of the digestive system are a significant global health burden, with colon cancer ranking third (10.1%) and gastric cancer (GC) ranking fifth (5.6%) among the most prevalent cancers. In China (<xref ref-type="bibr" rid="B3">3</xref>), four of the top five cancers associated with death are digestive tract tumours, namely, cancers of the liver (12.85%), stomach (12.48%), oesophagus (10.09%), and colorectum (9.63%). Despite this, early detection of digestive tract cancers remains an unmet clinical need (<xref ref-type="bibr" rid="B4">4</xref>). Therefore, it is critical to investigate personalized ways of identifying primary digestive tract cancers early, thereby establishing the best treatment approach for minimizing mortality (<xref ref-type="bibr" rid="B5">5</xref>).</p>
<p>The current imaging-based diagnostic modalities for tumours combined with pathology as the gold standard include ultrasound for thyroid cancer (<xref ref-type="bibr" rid="B6">6</xref>), mammography for breast cancer (<xref ref-type="bibr" rid="B7">7</xref>), and intraoperative ultrasound for colorectal cancer (<xref ref-type="bibr" rid="B8">8</xref>), whereas magnetic resonance imaging (MRI) is becoming the gold standard for liver (<xref ref-type="bibr" rid="B9">9</xref>) and prostate cancer (<xref ref-type="bibr" rid="B10">10</xref>) metastases. Traditional imaging methods, including endoscopic, ultrasound, computed tomography (CT), and MRI (<xref ref-type="bibr" rid="B11">11</xref>), are commonly recommended for the detection of primary digestive tract malignancies. However, these methods have certain limitations. For example, enhanced CT or MRI can fail to accurately distinguish small nodules from atypical lesions in patients with hepatocellular carcinoma (HCC) (<xref ref-type="bibr" rid="B12">12</xref>). Similarly, GC may not be detected during endoscopy (<xref ref-type="bibr" rid="B13">13</xref>), and colonoscopy may not always reach the caecum (<xref ref-type="bibr" rid="B14">14</xref>). Therefore, there is a need for a diagnostic tool that can identify every malignant tumour while minimizing false-positive findings (<xref ref-type="bibr" rid="B15">15</xref>).</p>
<p>Although histopathology remains the diagnostic gold standard, recent developments in imaging methods for evaluating cancers have made the non-invasive diagnosis of cancer possible (<xref ref-type="bibr" rid="B16">16</xref>). Positron emission tomography (PET) has played a significant role in the field of molecular imaging over the past decade (<xref ref-type="bibr" rid="B17">17</xref>) and is commonly utilized for cancer detection (<xref ref-type="bibr" rid="B18">18</xref>). The combined use of PET and CT can avoid the limitations of using each modality alone (<xref ref-type="bibr" rid="B19">19</xref>). A major advantage of PET/CT is that it can detect active lesions throughout the body and has a higher physical sensitivity than other commonly used imaging techniques (<xref ref-type="bibr" rid="B20">20</xref>). In the past 30 years, <sup>18</sup>F-FDG tracers, which take advantage of the tumours&#x2019; aberrant glucose metabolism, have become increasingly available and are now the most widely used PET imaging tool. <sup>18</sup>F-FDG-PET is frequently used to diagnose malignancies, evaluate the effectiveness of tumour treatment, and predict prognosis (<xref ref-type="bibr" rid="B21">21</xref>). However, recent research (<xref ref-type="bibr" rid="B22">22</xref>) has revealed that FDG tracers have limitations in the diagnosis of various gastrointestinal cancers and are unable to differentiate between inflammation and malignancy. Recent studies have also uncovered a correlation between increased fibroblast activation protein (FAP) levels in cancer-associated fibroblasts and tumour growth, metastasis, and prognosis. Fibroblast activation protein inhibitor (FAPI) has therefore emerged as a new cancer imaging molecule (<xref ref-type="bibr" rid="B23">23</xref>). Researchers are seeking radionuclides like <sup>68</sup>Ga, <sup>18</sup>F, <sup>99m</sup>Tc, and <sup>111</sup>In and FAPI derivatives with a better affinity for FAPI (<xref ref-type="bibr" rid="B24">24</xref>). Numerous findings for FAPI-04 in preclinical and clinical settings indicate the potential of FAP tracers for future theranostic applications, as their tumour uptake is quicker than that previously discovered for FAPI-02. However, fewer clinical trials have used the recently discovered FAPI-46, 34, 74, DOTA-2P(FAPI)2, and DOTA.SA (<xref ref-type="bibr" rid="B25">25</xref>). In this systematic review, we found plenty of research on the use of <sup>68</sup>Ga-FAPI-04 PET/CT in gastrointestinal cancers. For instance, Pang et&#xa0;al. (<xref ref-type="bibr" rid="B26">26</xref>) reported that <sup>68</sup>Ga-FAPI-04 PET/CT had higher sensitivity but lower specificity for primary digestive tract cancers than <sup>18</sup>F-FDG PET/CT, whereas Lin et&#xa0;al. (<xref ref-type="bibr" rid="B27">27</xref>) found no difference in sensitivity between the two tracers.</p>
<p>Given these conflicting observations, there is currently a debate about whether <sup>68</sup>Ga-FAPI-04 PET/CT is more sensitive than <sup>18</sup>F-FDG PET/CT for the diagnosis of primary digestive tract tumours. To draw a more definitive conclusion, this systematic review with meta-analysis was conducted by collecting and analysing all the published studies that met the relevant eligibility criteria.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Search strategy</title>
<p>Three English electronic databases (PubMed, EMBASE, and Web of Science) were comprehensively and systematically searched from their inception to March 2023 using the following terms: 1) PET OR positron emission tomography, 2) <sup>68</sup>Ga-FAPI OR FAPI-04 OR FAPI OR fibroblast activation protein OR FAP, and 3) Digestive OR Gastric OR Gastrointestinal OR Pancreatic OR Pancreas OR Pancreatic OR Colorectal OR Hepatic OR Hepatocellular OR Liver. The detailed search terms used are reported in <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S1</bold>
</xref> in the Supplementary Material.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Eligibility criteria</title>
<p>Selection criteria were developed based on the principles of PICOS (Participants, Interventions, Comparisons, Outcomes, and Study design). Studies that matched all of the following criteria were considered: 1) participants: patients with digestive system tumours; 2) intervention: a head-to-head comparison of <sup>68</sup>Ga-FAPI-04 PET/CT; 3) comparisons: <sup>18</sup>F-FDG PET/CT; 4) gold standard: histological pathology or follow-up imaging (<xref ref-type="bibr" rid="B5">5</xref>); type of study: prospective or retrospective diagnostic studies; 6) language: studies published in English.</p>
<p>We excluded studies that were 1) duplicated papers; 2) abstracts, editorial comments, letters, case reports, reviews, or meta-analyses; 3) irrelevant studies; 4) studies in languages other than English; 5) studies in which the true-positive (TP), false-positive (FP), true-negative (TN), and false-negative (FN) data could not be extracted.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Data screening and extraction process</title>
<p>Two authors (J.O. and P.D.) performed the initial screening by reviewing the titles and abstracts of the records in Endnote X20. They were then assigned to conduct a secondary screening by independently reading the identified full text based on predetermined inclusion criteria. They also independently extracted data from the included studies using a Microsoft Excel spreadsheet. The extracted data included 1) author names and year of publication; 2) study characteristics, including country, design, analysis, and criteria for final diagnosis; 3) patient characteristics, including sample size, mean/median age, gender (M:F), and tumour type, size, and stage; 4) technical characteristics, including mean injected activity per kg or total for FAPI or FDG, time interval FAPI or FDG tracer injection and image acquisition, the median period between FAPI and FDG tracer, scanner modality, and TP, FP, FN, and TN. Disagreements that emerged during the screening process were left to the third author (S.Z.) to make the final decision based on the conditions included in the meta-analysis.</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Risk of bias and quality assessment</title>
<p>Two qualified researchers (J.O. and Y.L.) used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) technique to analyze each study&#x2019;s bias risk and applicability. The four main sections of this instrument cover &#x201c;Patient Selection, Index Test, Reference Standard, and Flow and Timing&#x201d;. Each domain is evaluated separately for risk of bias and includes three components: information used to support the judgment of risk of bias, signaling questions, and judgment of risk of bias. The questions are judged by &#x201c;yes&#x201d;, &#x201c;no&#x201d;, or &#x201c;unclear&#x201d;, where &#x201c;yes&#x201d; represents a low risk of bias. The domains other than &#x201c;Timing&#x201d; results were used to evaluate the applicability concerns, and each question was given a &#x201c;low&#x201d;, &#x201c;high&#x201d;, or &#x201c;unclear&#x201d; rating (<xref ref-type="bibr" rid="B28">28</xref>). The RevMan (version 5.3) software was used for the evaluation. An additional reviewer was engaged to resolve any potential disagreements.</p>
</sec>
<sec id="s2_5">
<label>2.5</label>
<title>Publication bias</title>
<p>To assess publication bias, an Egger&#x2019;s test and a funnel plot were used. Statistical analyses were run with the R 4.2.2 statistical computing and graphics package. P-Values &lt;0.05 were considered statistically significant.</p>
</sec>
<sec id="s2_6">
<label>2.6</label>
<title>Data synthesis</title>
<p>Using the DerSimonian and Laird method, the Freeman&#x2013;Tukey double inverse sine transformation was used to evaluate and transform sensitivities and specificities. Jackson&#x2019;s method was used to calculate confidence intervals. Our analysis of heterogeneity within and between groups was based on the Cochrane Q and I<sup>2</sup> statistics. We decided to perform a sensitivity analysis if there was a substantial difference in study heterogeneity (p &lt; 0.10 or I<sup>2</sup> &gt; 50%) by reassessing the sensitivities and specificities after excluding each publication individually. Furthermore, a meta-regression analysis was performed if the sensitivity analysis could not identify any sources of heterogeneity. These analyses were conducted to determine the robustness of the overall sensitivities and specificities and to identify single studies that may contribute to heterogeneity.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Literature search</title>
<p>The initial search yielded 800 publications, of which 414 remained after eliminating 386 duplicates. Of these, 387 studies were excluded based on their title or abstract, with 64 being case reports, abstracts, letters, reviews, or meta-analyses, and 323 having irrelevant titles and abstracts. Of the remaining 27 studies, five lacked data, five were abstracts, and two used different radiotracers; these were therefore excluded. Finally, 15 studies were included, which evaluated head-to-head the diagnostic performance of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT for primary digestive system cancer. <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref> shows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram for selecting the included studies.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>The PRISMA flow chart of the study selection process. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-13-1202505-g001.tif"/>
</fig>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Characteristics of the included studies</title>
<p>
<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref> summarizes the characteristics of the 15 studies that were included in this meta-analysis. The included studies involved a total of 383 participants with primary gastrointestinal cancers. The studies were published between 2020 and 2023 and included patients with five different main types of cancer: six for GC (<xref ref-type="bibr" rid="B26">26</xref>, <xref ref-type="bibr" rid="B29">29</xref>&#x2013;<xref ref-type="bibr" rid="B34">34</xref>), four for liver cancer (<xref ref-type="bibr" rid="B35">35</xref>&#x2013;<xref ref-type="bibr" rid="B38">38</xref>), three for biliary tract carcinoma (BTC) (<xref ref-type="bibr" rid="B37">37</xref>&#x2013;<xref ref-type="bibr" rid="B39">39</xref>), four for colorectal cancer (<xref ref-type="bibr" rid="B26">26</xref>, <xref ref-type="bibr" rid="B27">27</xref>, <xref ref-type="bibr" rid="B34">34</xref>, <xref ref-type="bibr" rid="B40">40</xref>), and one for pancreatic cancer (<xref ref-type="bibr" rid="B41">41</xref>). Of these 15 studies, eight were retrospective and seven were prospective. Four studies used pathological diagnosis alone as the gold standard, and 11 used either pathological diagnosis or imaging follow-up. Ten studies were based on patient analysis, while five were based on lesion analysis. We derived the following: the mean age of the included patients from four studies, with one study reporting a mean age of &lt;60 years and four studies reporting a mean age of &#x2265;60 years; the tumour size from five studies, with two studies reporting a tumour size of &lt;3&#xa0;cm and three with a tumour size &#x2265;3 cm; the patients&#x2019; gender distribution from six studies, with men accounting for &lt;70% in three studies and &#x2265;70% in the other three studies; and the tumour stage from seven papers, with five studies reporting early and advanced stages with a ratio of &lt;1 and two studies with a ratio of &#x2265;1. Other technical aspects are displayed in <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S2</bold>
</xref> in the Supplementary Material.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Study and PB characteristics of the included studies.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Authors, years</th>
<th valign="middle" align="center">Country</th>
<th valign="middle" align="center">Study design</th>
<th valign="middle" align="center">Age (range)</th>
<th valign="middle" align="center">Gender (M%)</th>
<th valign="middle" align="center">No. of patients</th>
<th valign="middle" align="center">Criteria</th>
<th valign="middle" align="center">Analysis</th>
<th valign="middle" align="center">Type</th>
<th valign="middle" align="center">Size (cm)</th>
<th valign="middle" align="center">Stage (early: advanced)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B26">26</xref>) 2021</td>
<td valign="middle" align="center">China</td>
<td valign="middle" align="center">Retro</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">19</td>
<td valign="middle" align="center">PA</td>
<td valign="middle" align="center">PB</td>
<td valign="middle" align="center">GC, CRC</td>
<td valign="middle" align="center">2.2</td>
<td valign="middle" align="center">21:7</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B27">27</xref>) 2023</td>
<td valign="middle" align="center">China</td>
<td valign="middle" align="center">Pro</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">36</td>
<td valign="middle" align="center">PA or FU</td>
<td valign="middle" align="center">LB</td>
<td valign="middle" align="center">CRC</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B29">29</xref>) 2022</td>
<td valign="middle" align="center">China</td>
<td valign="middle" align="center">Retro</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">22</td>
<td valign="middle" align="center">PA or FU</td>
<td valign="middle" align="center">PB</td>
<td valign="middle" align="center">GC</td>
<td valign="middle" align="center">1.6</td>
<td valign="middle" align="center">13:9</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B30">30</xref>) 2021</td>
<td valign="middle" align="center">Turkey</td>
<td valign="middle" align="center">Pro</td>
<td valign="middle" align="center">60.5</td>
<td valign="middle" align="center">60%</td>
<td valign="middle" align="center">15</td>
<td valign="middle" align="center">PA</td>
<td valign="middle" align="center">PB</td>
<td valign="middle" align="center">GC</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B31">31</xref>) 2022</td>
<td valign="middle" align="center">China</td>
<td valign="middle" align="center">Pro</td>
<td valign="middle" align="center">64</td>
<td valign="middle" align="center">71%</td>
<td valign="middle" align="center">62</td>
<td valign="middle" align="center">PA or FU</td>
<td valign="middle" align="center">LB</td>
<td valign="middle" align="center">GC</td>
<td valign="middle" align="center">&gt;3&#xa0;cm 52<break/>&#x2264;3 cm<break/>10</td>
<td valign="middle" align="center">8:54</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B32">32</xref>) 2022</td>
<td valign="middle" align="center">China</td>
<td valign="middle" align="center">Pro</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">45</td>
<td valign="middle" align="center">PA or FU</td>
<td valign="middle" align="center">PB</td>
<td valign="middle" align="center">GC</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">35%:68.75%</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B33">33</xref>) 2022</td>
<td valign="middle" align="center">China</td>
<td valign="middle" align="center">Retro</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">52.6%</td>
<td valign="middle" align="center">19</td>
<td valign="middle" align="center">PA or FU</td>
<td valign="middle" align="center">PB</td>
<td valign="middle" align="center">GC</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">8:11</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B34">34</xref>) 2022</td>
<td valign="middle" align="center">China</td>
<td valign="middle" align="center">Retro</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">18</td>
<td valign="middle" align="center">PA or FU</td>
<td valign="middle" align="center">PB</td>
<td valign="middle" align="center">GC, CRC</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B35">35</xref>) 2021</td>
<td valign="middle" align="center">China</td>
<td valign="middle" align="center">Retro</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">96%</td>
<td valign="middle" align="center">25</td>
<td valign="middle" align="center">PA</td>
<td valign="middle" align="center">LB</td>
<td valign="middle" align="center">HCC</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">21:7</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B36">36</xref>) 2020</td>
<td valign="middle" align="center">China</td>
<td valign="middle" align="center">Pro</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">17</td>
<td valign="middle" align="center">PA or FU</td>
<td valign="middle" align="center">PB</td>
<td valign="middle" align="center">HCC</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B37">37</xref>) 2020</td>
<td valign="middle" align="center">China</td>
<td valign="middle" align="center">Retro</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">23</td>
<td valign="middle" align="center">PA or FU</td>
<td valign="middle" align="center">PB</td>
<td valign="middle" align="center">HCC, BTC</td>
<td valign="middle" align="center">4.57</td>
<td valign="middle" align="center">NA</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B38">38</xref>) 2023</td>
<td valign="middle" align="center">Thailand</td>
<td valign="middle" align="center">Retro</td>
<td valign="middle" align="center">68</td>
<td valign="middle" align="center">71%</td>
<td valign="middle" align="center">27</td>
<td valign="middle" align="center">PA or FU</td>
<td valign="middle" align="center">PB</td>
<td valign="middle" align="center">HCC, BTC</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B39">39</xref>) 2022</td>
<td valign="middle" align="center">China</td>
<td valign="middle" align="center">Pro</td>
<td valign="middle" align="center">61.8</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">13</td>
<td valign="middle" align="center">PA or FU</td>
<td valign="middle" align="center">LB</td>
<td valign="middle" align="center">BTC</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">2:14</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B40">40</xref>) 2023</td>
<td valign="middle" align="center">India</td>
<td valign="middle" align="center">Retro</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">16</td>
<td valign="middle" align="center">PA</td>
<td valign="middle" align="center">LB</td>
<td valign="middle" align="center">CRC</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">NA</td>
</tr>
<tr>
<td valign="middle" align="left">(<xref ref-type="bibr" rid="B41">41</xref>) 2021</td>
<td valign="middle" align="center">China</td>
<td valign="middle" align="center">Pro</td>
<td valign="middle" align="center">NA</td>
<td valign="middle" align="center">61.5%</td>
<td valign="middle" align="center">26</td>
<td valign="middle" align="center">PA or FU</td>
<td valign="middle" align="center">PB</td>
<td valign="middle" align="center">PCAN</td>
<td valign="middle" align="center">3.9</td>
<td valign="middle" align="center">NA</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Type, tumour type; Size, tumour size; Stage, tumour stage; Pro, prospective; Retro, retrospective; PB, patient-based; LB, lesion-based; PA, pathology; FU, follow-up; GC, gastric cancer; CRC, colorectal cancer; HCC, hepatic cell carcinoma; BTC, biliary tract carcinoma; PCAN, pancreatic cancer; NA, not available.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Risk of bias and quality assessment</title>
<p>Quality assessment was performed using QUADAS-2. Based on the quality assessment graph, high-risk bias concerns were primarily discovered in flow and timing. <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref> summarizes the quality of the included studies. In terms of risk of bias, four (26.7%) studies were not detailed in terms of patient selection; six (40%) studies had an unclear risk of bias for reference standards; and the flow and timing of four (26.7%) studies were judged to be vague. Two (13.3%) studies were considered to be high-risk due to extended intervals. In terms of applicability, 15 (100%) studies were judged to have low applicability. The included studies were overall considered to have a moderately low risk of bias and low concern regarding the applicability, indicating a high standard of evidence.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Graph of risk of bias and applicability of all eligible studies based on the QUADAS-2 tool. QUADAS-2, Quality Assessment of Diagnostic Accuracy Studies.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-13-1202505-g002.tif"/>
</fig>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Sensitivity</title>
<p>The pooled sensitivity of <sup>68</sup>Ga-FAPI-04 PET/CT for primary digestive system cancer was 0.98 (95% CI, 0.94&#x2013;1.00), with an I<sup>2</sup> value of 56% (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). Meta-regression showed that the tumour stage (p = 0.009) was a possible cause of heterogeneity. Excluding the data from Chen et&#xa0;al., sensitivity analysis revealed a combined sensitivity of 0.98 (95% CI, 0.96&#x2013;1.00), with minimal heterogeneity (I<sup>2</sup> = 36.0%).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Forest plots of the combined sensitivity of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT for digestive system cancer. FAPI, fibroblast activation protein inhibitor; PET/CT, positron emission tomography/computed tomography.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-13-1202505-g003.tif"/>
</fig>
<p>The combined <sup>18</sup>F-FDG PET/CT sensitivity for primary gastrointestinal system cancer was 0.73 (95% CI, 0.60&#x2013;0.84), with an I<sup>2</sup> value of 87%. Meta-regression showed that the number of patients included (p = 0.04), the study design (p = 0.01), and the average size (p = 0.003) and stage (p = 0.009) of the tumours were possible causes of heterogeneity. No source of heterogeneity was identified by the sensitivity analysis for <sup>18</sup>F-FDG PET/CT. The meta-regression analysis of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT for primary digestive tract cancer is summarized in <xref ref-type="supplementary-material" rid="SM1">
<bold>Tables S3</bold></xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>S4</bold>
</xref> in the Supplementary Material. The sensitivity analysis of the overall detection rate for <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT is summarized in <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S5</bold>
</xref> in the Supplementary Material.</p>
<p>
<sup>68</sup>Ga-FAPI-04 PET/CT showed a significantly higher sensitivity (p &lt; 0.01) than <sup>18</sup>F-FDG PET/CT in diagnosing primary digestive system cancer.</p>
<p>The pooled sensitivity of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT for GC was 0.90 (95% CI, 0.76&#x2013;0.99) and 0.68 (95% CI, 0.39&#x2013;0.91), respectively; for liver cancer, 0.81 (95% CI, 0.53&#x2013;0.99) and 0.62 (95% CI, 0.51&#x2013;0.73), respectively; for BTC, 1.00 (95% CI, 0.95&#x2013;1.00) and 0.65 (95% CI, 0.48&#x2013;0.81), respectively; for colorectal cancer, 1.00 (95% CI, 0.98&#x2013;1.00) and 0.94 (95% CI, 0.72&#x2013;1.00), respectively; and for pancreatic cancer, 1.00 (95% CI, 0.87&#x2013;1.00) and 0.73 (95% CI, 0.52&#x2013;0.88), respectively. There was a significant difference between the sensitivity of FAPI and FDG tracers in detecting different types of tumours (p &lt; 0.01) (<xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4</bold>
</xref>, <xref ref-type="fig" rid="f5">
<bold>5</bold>
</xref>). The pooled sensitivity of both <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT was the highest for colorectal cancer. The <sup>68</sup>Ga-FAPI-04 PET/CT pooled sensitivity was significantly higher than that of <sup>18</sup>F-FDG PET/CT for the rest of the four tumour types.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Forest plots of the combined sensitivity of <sup>68</sup>Ga-FAPI-04 PET/CT with subgroups of tumour types for digestive system cancer. FAPI, fibroblast activation protein inhibitor; PET/CT, positron emission tomography/computed tomography.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-13-1202505-g004.tif"/>
</fig>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Forest plots of the combined sensitivity of <sup>18</sup>F-FDG PET/CT with subgroups of tumour types for digestive system cancer. FAPI, fibroblast activation protein inhibitor; PET/CT, positron emission tomography/computed tomography.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-13-1202505-g005.tif"/>
</fig>
</sec>
<sec id="s3_5">
<label>3.4</label>
<title>Specificity</title>
<p>The pooled specificity of <sup>68</sup>Ga-FAPI-04 PET/CT for primary digestive system cancer was 0.81 (95% CI, 0.23&#x2013;1.00), with an I<sup>2</sup> value of 81%. Sensitivity analysis by excluding data from Pang et&#xa0;al. demonstrated a combined specificity of 1.00 (0.77&#x2013;1.00), with no heterogeneity (I<sup>2</sup> = 0%). The sensitivity analysis of overall specificity for <sup>68</sup>Ga-FAPI-04 PET/CT is summarized in <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S5</bold>
</xref> in the Supplementary Material. Due to the small number of included studies, we did not perform subgroup or meta-regression analyses.</p>
<p>The pooled specificity of <sup>18</sup>F-FDG PET/CT for primary digestive system cancer was 0.77 (95% CI, 0.52&#x2013;0.95), with an I<sup>2</sup> value of 8%, which showed low heterogeneity (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>). No significant difference was observed in the specificities of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT (p = 0.09).</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Forest plots of the combined specificity of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT for digestive system cancer. FAPI, fibroblast activation protein inhibitor; PET/CT, positron emission tomography/computed tomography.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-13-1202505-g006.tif"/>
</fig>
</sec>
<sec id="s3_6">
<label>3.5</label>
<title>Publication bias</title>
<p>Deek&#x2019;s funnel plot asymmetry test and Egger&#x2019;s test revealed no significant publication bias for <sup>68</sup>Ga-FAPI-04 PET/CT (p = 0.63) and <sup>18</sup>F-FDG PET/CT (p = 0.19). Deek&#x2019;s funnel plot for the two contrast agents is shown in <xref ref-type="supplementary-material" rid="SM1">
<bold>Figures S1</bold>
</xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>S2</bold>
</xref> in the Supplementary Material.</p>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>Early diagnosis of primary gastrointestinal tumours is crucial for determining a patient&#x2019;s survival and recurrence risk and for developing an appropriate treatment plan. Two previous meta-analyses (<xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B43">43</xref>) have evaluated the use of <sup>68</sup>Ga-FAPI-04 PET/CT in diagnosing gastrointestinal tumours. However, neither of these studies conducted a head-to-head comparison of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT in primary digestive tract tumours, which can provide strong evidence for choosing the most suitable contrast agent for early diagnosis. Wang et&#xa0;al. (<xref ref-type="bibr" rid="B42">42</xref>) conducted a meta-analysis comparing <sup>68</sup>Ga-FAPI-04 and <sup>18</sup>F-FDG PET/MRI and PET/CT studies for GC only. They reported that <sup>68</sup>Ga-FAPI-04 PET/MRI or PET/CT was more effective than <sup>18</sup>F-FDG PET/MRI or PET/CT in detecting primary GC. However, the statistical significance of this finding needs to be clarified. Another meta-analysis by Huang et&#xa0;al. (<xref ref-type="bibr" rid="B43">43</xref>) included fewer studies on primary digestive system cancers than our study. They reported that the sensitivity of <sup>68</sup>Ga-FAPI PET for the diagnostic assessment of primary tumour lesions in the digestive system was 0.97, which is similar to our findings. However, their study did not conduct a head-to-head comparison of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT in primary digestive tract tumours. By conducting a head-to-head comparison of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT, our study provides strong evidence for a more suitable contrast agent for the early diagnosis of primary digestive tract tumours.</p>
<p>This study is the first systematic review and meta-analysis evaluating the diagnostic performance of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT for primary digestive system cancer. The included studies were assessed as having a low risk of bias and low concern regarding applicability. The pooled sensitivity and specificity of <sup>68</sup>Ga-FAPI-PET/CT vs. <sup>18</sup>F-FDG PET/CT were 0.98 (95% CI, 0.94&#x2013;1.00) and 0.81 (95% CI, 0.23&#x2013;1.00) vs. 0.73 (95% CI, 0.60&#x2013;0.84) and 0.77 (95% CI, 0.52&#x2013;0.95), respectively. These results indicate that <sup>68</sup>Ga-FAPI-04 PET/CT has a significantly higher sensitivity (p &lt; 0.01) than <sup>18</sup>F-FDG PET/CT in diagnosing primary digestive system cancer. However, there was no significant difference between the two contrast agents in terms of specificity. No significant publication bias was observed for either <sup>68</sup>Ga-FAPI-04 PET/CT or <sup>18</sup>F-FDG PET/CT. In addition, the risk of bias and concern regarding the applicability of the included studies were both low. Therefore, due to the moderately low risk of bias and low concern regarding the applicability, the certainty of the evidence was considered high.</p>
<p>Both the sensitivity and specificity of <sup>68</sup>Ga-FAPI-PET/CT and the specificity of <sup>18</sup>F-FDG PET/CT exhibited high heterogeneity. Therefore, meta-regression and sensitivity analyses were performed to identify the sources of heterogeneity among the studies. For <sup>68</sup>Ga-FAPI-PET/CT, the results of the meta-regression analysis revealed that the tumour stage was a potential source of heterogeneity. Also, we achieved an acceptable level of heterogeneity (I<sup>2</sup> = 36%) by eliminating data from Chen et&#xa0;al., whose criteria could explain the final diagnosis and cutoff values. Nonetheless, there may be additional explanations, such as patient variation, method, and analysis. Notably, the specificity of <sup>68</sup>Ga-FAPI-PET/CT remained the same (1.00) when the study by Pang et&#xa0;al. (<xref ref-type="bibr" rid="B41">41</xref>) was excluded, indicating the robustness of the results. For <sup>18</sup>F-FDG PET/CT, the meta-regression analysis showed that the number of patients, the study design, and the average size and stage of the tumours were possible causes of heterogeneity.</p>
<p>Most of the studies included in this analysis focused on GC. The pooled sensitivity of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT for GC was 0.90 (95% CI, 0.76&#x2013;0.99) and 0.68 (95% CI, 0.39&#x2013;0.91), respectively. Their detection rate was [88.5% (154/174) vs. 72.4% (126/174), respectively]. Several studies (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B32">32</xref>) have found that FAPI PET/CT is more sensitive than FDG PET/CT in diagnosing gastric adenocarcinoma, likely due to FAPI&#x2019;s ability to target fibroblasts in the tumour microenvironment with more precision. However, different pathological tumour types are associated with varying levels of FDG PET/CT uptake in GC, as noted by Jiang et&#xa0;al. (<xref ref-type="bibr" rid="B44">44</xref>) and Chen et&#xa0;al. (<xref ref-type="bibr" rid="B29">29</xref>). Miao et&#xa0;al. (<xref ref-type="bibr" rid="B31">31</xref>) and Chen et&#xa0;al. (<xref ref-type="bibr" rid="B29">29</xref>) found that FAPI was equally effective at detecting early gastric cancer (EGC) as FDG PET/CT, with both modalities having a low detection rate. Endoscopy remains the gold standard for diagnosing EGC. The sub-optimal accuracy of the FAPI tracer is reflected in its superiority to the latest National Comprehensive Cancer Network (NCCN) (<xref ref-type="bibr" rid="B45">45</xref>) recommendation of <sup>18</sup>F-FDG PET/CT for the diagnosis of indolent cell carcinoma. For BTC, the pooled sensitivity of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT was 1.00 (95% CI, 0.95&#x2013;1.00) and 0.65 (95% CI, 0.48&#x2013;0.81), respectively. The detection rate of FAPI PET/CT and FDG PET/CT for BTC was [100.00% (36/36) vs. 63.89% (23/36), respectively]. In the diagnosis and staging of intrahepatic cholangiocarcinoma and cholangiocarcinoma (CCA), FAPI is more accurate than the FDG tracer because the low liver background helps to distinguish periportal CCA from BTC invasion of the adjacent liver parenchyma. <sup>68</sup>Ga-FAPI-04 diagnosis of CCA was comparable to MRI, which is becoming the gold standard in liver detection (<xref ref-type="bibr" rid="B9">9</xref>), with a higher target-background-ratio (TBR) for CCA as reported by Guo et&#xa0;al. (<xref ref-type="bibr" rid="B37">37</xref>). Additionally, they discovered a correlation between the severity of the primary tumor&#x2019;s corresponding pathological grade and the lesion&#x2019;s FAPI uptake activity. In liver cancer, the pooled sensitivity of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT was 0.81 (95% CI, 0.53&#x2013;0.99) and 0.62 (95% CI, 0.51&#x2013;0.73), respectively. The detection rate of FAPI PET/CT and FDG PET/CT for liver cancer was [71.95% (59/82) vs. 62.19% (51/82)]. The FAPI tracer was able to distinguish between various types of liver nodules, unlike the FDG tracer, which is flawed in the diagnosis of primary liver cancer because well-differentiated HCC lesions have similar FDG tracer uptake capacity to healthy liver tissue. The FAPI tracer can better detect extrahepatic metastases and improve diagnostic efficiency compared with the current clinical recommendation of liver MRI (<xref ref-type="bibr" rid="B38">38</xref>). For colorectal cancer, we obtained results consistent with previous findings by Lin et&#xa0;al. (<xref ref-type="bibr" rid="B27">27</xref>) and Li et&#xa0;al. (<xref ref-type="bibr" rid="B34">34</xref>), showing no significant difference between the detection rate of <sup>68</sup>Ga-FAPI-04 PET/CT [1.00 (95% CI, 0.98&#x2013;1.00)] and <sup>18</sup>F-FDG PET/CT [0.94 (95% CI, 0.72&#x2013;1.00)]. However, the detection rate of FAPI and FDG for colorectal cancer was [100.00% (64/64) vs. 93.75% (60/64)]. This may be attributed to the potential of the FDG tracer to detect false negatives due to the physiological bowel activity. Based on the studies by Pang et&#xa0;al. (<xref ref-type="bibr" rid="B26">26</xref>) and Lin et&#xa0;al. (<xref ref-type="bibr" rid="B27">27</xref>), <sup>18</sup>F-FDG PET/CT should be used preferentially for hypofractionated bowel cancer. Langer et&#xa0;al. (<xref ref-type="bibr" rid="B46">46</xref>) demonstrated that the clinical application of <sup>68</sup>Ga-FAPI-04 PET/CT or <sup>18</sup>F-FDG PET/CT diagnostics can lower the financial expenditures for patients by reducing unnecessary treatments. In previous studies, we analyzed only pancreatic cancer data from the study of Pang et&#xa0;al. (<xref ref-type="bibr" rid="B41">41</xref>) The pooled sensitivity of <sup>68</sup>Ga-FAPI-04 PET/CT and <sup>18</sup>F-FDG PET/CT for pancreatic cancer was 1.00 (95% CI, 0.87&#x2013;1.00) and 0.73 (95% CI, 0.52&#x2013;0.88), respectively. The detection rate of FAPI and FDG for pancreatic cancer was [100.00% (26/26) vs. 73.07% (19/26)]. It has been found that <sup>68</sup>Ga-FAPI-04 can fill the gap in <sup>18</sup>F-FDG PET/CT&#x2019;s inability to detect small pancreatic tumours (&lt;20&#xa0;mm). However, <sup>68</sup>Ga-FAPI-04 is less specific than <sup>18</sup>F-FDG PET/CT since it has difficulty distinguishing pancreatitis from pancreatic cancer due to its affinity for inflammatory cells. Therefore, we presume that <sup>18</sup>F-FDG PET/CT has a lower rate of misdiagnosis than <sup>68</sup>Ga-FAPI-04 PET/CT for pancreatic cancer.</p>
<p>It is also important to mention the limitations of our meta-analysis. First, we searched only three databases and did not look for grey literature; in addition, we limited ourselves to English literature, thus resulting in a small sample size of included studies. Second, we could extract data on the degree of specificity of the two contrast agents only in three studies. Moreover, we excluded some studies because they only stated specificity and lacked specific TN and FP values. To clarify the difference between the two specificities, follow-up studies of high quality should be conducted to expand the sample size. Third, there was a degree of heterogeneity in the results due to the inclusion of fewer prospective than retrospective studies and the inclusion of fewer studies with large samples. The low number of high-quality studies is due to the inclusion criteria, which required head-to-head comparison studies. Thus, more prospective studies with large samples need to be conducted. Fourth, the reference standards for the diagnosis of digestive tract cancers are pathology and follow-up imaging. However, pathological results were not available for all patients in the included studies. Fifth, one of the included studies (<xref ref-type="bibr" rid="B39">39</xref>) involved multiple tumours, and each tumor&#x2019;s TN, TP, FN, and FP values could not be extracted, leaving incomplete data for sensitivity analyses by tumour type as a subgroup. Therefore, the reported results should be interpreted with caution.</p>
</sec>
<sec id="s5" sec-type="conclusions">
<label>5</label>
<title>Conclusion</title>
<p>This study shows that <sup>68</sup>Ga-FAPI-04 PET/CT has a significantly higher sensitivity (p &lt; 0.01) than <sup>18</sup>F-FDG PET/CT when used to detect primary digestive system cancer. Instead, we did not observe a significant difference in specificity between the two contrast agents. <sup>68</sup>Ga-FAPI-04 PET/CT is more advantageous in diagnosing gastric, liver, biliary tract, and pancreatic cancers, while both contrast agents have the same power in diagnosing colorectal cancer. However, PET/CT results were derived from studies with small sample sizes. Therefore, our observations need to be validated by a more extensive and comprehensive prospective study.</p>
</sec>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Material</bold>
</xref>. Further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>JO: Literature Search and Review, Manuscript Writing, Meta-Analysis, Content planning. PD: Literature Search and Data collection. YL: Manuscript and Literature Search. RZ: Proofreading Manuscript. All authors contributed to the article and approved the submitted version.</p>
</sec>
</body>
<back>
<ack>
<title>Acknowledgments</title>
<p>The first author greatly appreciates Mr. Huo for his help with article ideas and analytical approach. We would like to thank Editage (<ext-link ext-link-type="uri" xlink:href="http://www.editage.cn">www.editage.cn</ext-link>) for English language editing.</p>
</ack>
<sec id="s8" sec-type="COI-statement">
<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 id="s9" sec-type="disclaimer">
<title>Publisher&#x2019;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>
<sec id="s10" sec-type="supplementary-material">
<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/fonc.2023.1202505/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fonc.2023.1202505/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="DataSheet_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/>
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