Comparative Analysis of Lesion Detection and Uptake Characteristics of 68Ga-FAPI PET/CT versus 18F-FDG PET/CT in Gastric Cancer: A Preliminary Translational Study

Comparative Analysis of Lesion Detection and Uptake Characteristics of 68Ga-FAPI PET/CT versus 18F-FDG PET/CT in Gastric Cancer: A Preliminary Translational Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative Analysis of Lesion Detection and Uptake Characteristics of 68 Ga-FAPI PET/CT versus 18 F-FDG PET/CT in Gastric Cancer: A Preliminary Translational Study Ebuzer KALENDER, Edanur EKİNCİ YILDIRIM, Enes YERDEŞ, Buket EREN SARIBAŞ, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9357738/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose This study aimed to compare lesion detection and uptake characteristics of 68 Ga-FAPI PET/CT and 18 F-FDG PET/CT in patients undergoing imaging for gastric cancer (GC) staging. Methods A total of 24 patients with histopathologically confirmed GC were retrospectively evaluated. All patients underwent 18 F-FDG PET/CT followed by 68 Ga-FAPI PET/CT within a short interval as part of their clinical staging workup. Lesion detection rates and semi-quantitative parameters, including SUVmax and tumor-to-background ratio (TBR), were compared between the two modalities. Results 68 Ga-FAPI PET/CT demonstrated significantly higher SUVmax values than 18 F-FDG PET/CT across primary tumors and metastatic lesions (p < 0.05). TBRs were also markedly higher for FAPI due to lower physiological background activity. In lesion-based analysis, 68 Ga-FAPI PET/CT identified a higher number of nodal and distant metastases compared to 18 F-FDG PET/CT; however, these differences did not reach statistical significance (p = 0.25). Notably, discordant findings were observed in a subset of patients, in which lesions—particularly peritoneal metastases—were detected by FAPI but not by FDG. ROC analysis demonstrated higher AUC values for FAPI (0.87) compared to FDG (0.79), suggesting improved discriminative performance. Conclusion 68 Ga-FAPI PET/CT provides higher tracer uptake and improved TBR compared to 18 F-FDG PET/CT in GC. Although lesion detection rates were numerically higher with FAPI, statistical significance was not reached in this cohort. These findings suggest a potential complementary role of FAPI PET/CT, particularly in detecting peritoneal disease and in cases with low FDG avidity. Larger prospective studies are warranted to clarify its clinical impact. 68Ga-FAPI PET/CT 18F-FDG PET/CT gastric cancer molecular imaging CAFs TBR Figures Figure 1 Figure 2 Figure 3 Introduction Gastric cancer (GC) remains one of the leading causes of cancer-related morbidity and mortality worldwide, ranking fifth in incidence and fourth in cancer-related deaths globally [ 1 ]. Accurate staging at diagnosis is critical for determining appropriate therapeutic strategies and predicting prognosis. In this context, imaging modalities play a central role in the assessment of primary tumors, regional lymph node involvement, and distant metastases. Fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) has been widely utilized in oncologic imaging and is included in the clinical staging of various malignancies, including GC. However, ¹⁸F-FDG PET/CT has well-known limitations in GC, particularly in detecting diffuse-type and mucinous histological subtypes, which often demonstrate low or absent FDG uptake [ 2 , 3 ]. Recent advances in molecular imaging have introduced novel radiotracers that may overcome some of these limitations. One such promising agent is ⁶⁸Ga-labeled fibroblast activation protein inhibitor (⁶⁸Ga-FAPI), which targets cancer-associated fibroblasts (CAFs) in the tumor stroma—a feature abundant in desmoplastic tumors such as GC [ 4 ]. Early clinical studies have demonstrated that ⁶⁸Ga-FAPI PET/CT may provide superior lesion contrast, higher tumor uptake, and improved detection rates compared to ¹⁸F-FDG PET/CT, particularly in tumors with low FDG avidity [ 5 , 6 ]. In this study, we aimed to compare lesion detection and uptake characteristics of 18 F-FDG PET/CT and 68 Ga-FAPI PET/CT in patients with gastric cancer undergoing imaging for clinical staging. Given the known limitations of FDG in certain histological subtypes, we further explored whether FAPI PET/CT may provide additional diagnostic information, particularly in cases with low FDG avidity. Materials and Methods This retrospective study included patients with histopathologically confirmed gastric cancer who underwent both 18 F-FDG PET/CT and 68 Ga-FAPI PET/CT as part of their clinical staging workup. All imaging studies were originally performed for staging purposes, and retrospective analysis was conducted focusing on lesion detection and semi-quantitative imaging parameters. A total of 24 patients with pathologically verified GC (16 males, 8 females; mean age, 62.2 years; age range, 21–79 years) were evaluated. All patients initially underwent 18 F-FDG PET/CT for staging purposes, followed—after an interval of three days—by 68 Ga-FAPI PET/CT. Informed consent was obtained from every participant prior to both imaging. Two experienced nuclear medicine physicians reviewed the examinations independently, and inter-modality comparisons were performed to assess diagnostic accuracy. Patient Preparation and Imaging Prior to 18 F-FDG PET/CT, patients fasted for a minimum of six hours and discontinued intravenous glucose intake. Capillary blood glucose levels were required to be ≤150 mg/dL. Intravenous tracer administration consisted of 3.5–5.5 MBq/kg for 18 F-FDG and 2 MBq/kg for 68 Ga-FAPI-04. All imaging was carried out on a Discovery IQ PET/CT system (GE Healthcare, Milwaukee, WI, USA) equipped with five detector rings and a 20-cm axial field of view. Whole-body acquisitions were obtained one hour post-injection, extending from the cranial vertex to the mid-thigh. CT scans were performed at 120 kV and 80 mAs per slice, with a 700-mm field of view, 64 × 0.625 mm collimation, and reconstructed to a 3.3-mm slice thickness. PET data were acquired in 3D mode under identical positioning, with an acquisition time of 2.5 minutes per bed position, and reconstructed using dedicated software. Image Evaluation and Statistical Methods All PET/CT datasets were interpreted in axial, coronal, and sagittal orientations. Semi-quantitative measurements were performed using AW VolumeShare software (GE Healthcare), with tracer uptake expressed as maximum standardized uptake value (SUVmax). Volumes of interests (VOIs) were manually delineated in three orthogonal planes for both primary tumors and metastatic lesions. Statistical analyses were carried out using SPSS software (version 27, IBM Corp., Armonk, NY, USA). Continuous variables were reported as mean, median, minimum, and maximum, while categorical variables were expressed as counts and percentages. The Wilcoxon signed-rank test was used to compare paired non-parametric SUVmax values between FDG and FAPI PET/CT scans. Spearman’s rank correlation coefficient (ρ) was used to evaluate the strength and direction of associations between SUVmax values and clinical parameters such as age, primary tumor localization, and lymph node involvement. A p-value of < 0.05 was considered statistically significant. Results A total of 24 patients with histopathologically confirmed GC were included in the study. The mean age was 62.2 ± 11.9 years (range 21–79), and the majority were male (66.7%). Regarding histopathological subtypes, adenocarcinoma was the most common (54.2%), followed by signet-ring cell adenocarcinoma (29.2%), mucinous adenocarcinoma (12.5%), and poorly differentiated adenocarcinoma (4.1%). Tumors were most frequently located in the antrum (50%), with lower frequencies in the corpus (25.0%), cardia (8.3%), pylorus (8.3%), and corpus–antrum region (8.3%). The median tumor size was 5.0 cm (range 3–10 cm) (Table 1). Table 1. Patient Demographic and Clinical Characteristics. Variable Value, Mean±SD (Range) or n (%) Age, years 62.2 ± 11.9 (21–79) Gender, Male/Female 16 (66.7%) / 8 (33.3%) Histopathology Adenocarcinoma 13 (54.2%) Signet-ring cell adenocarcinoma 7 (29.2%) Mucinous adenocarcinoma 3 (12.5%) Poorly differentiated adenocarcinoma 1 (4.1%) Tumor location Antrum 12 (50%) Corpus 6 (25.0%) Cardia 2 (8.3%) Pylorus 2 (8.3%) Corpus–Antrum 2 (8.3%) Tumor size (cm) 5.0 (3–10) Analysis of SUVmax values demonstrated that FAPI uptake was significantly higher than FDG uptake across primary tumors and metastatic sites. For primary gastric tumors, mean FAPI SUVmax was 14.49 ± 4.14 compared to FDG SUVmax of 6.18 ± 6.24 (p = 0.006). In histological subgroups, FAPI uptake remained consistently higher, with significant differences in adenocarcinoma (14.01 ± 4.77 vs. 7.38 ± 7.73; p < 0.05) and signet-ring cell carcinoma (16.33 ± 2.23 vs. 4.97 ± 2.57; p < 0.01). It was also higher in mucinous adenocarcinoma (20.6 ± 6.8 vs. 3.25 ± 1.77; p < 0.01); however, it was not statistically significant due to the low number of patients. In terms of background uptake, hepatic SUVmean was markedly lower for FAPI (0.5 ± 0.2) compared to FDG (2.0 ± 0.7; p < 0.001), indicating superior tumor-to-liver contrast. For nodal metastases, FAPI showed significantly higher uptake (9.6 ± 3.8 vs. 5.2 ± 2.1; p = 0.040), with consistent findings in both N1 and N2 subgroups. Similarly, distant metastases demonstrated greater FAPI activity (13.5 ± 4.2 vs. 7.4 ± 2.8; p = 0.030), with significant differences across liver (p = 0.040), bone (p = 0.030), and peritoneal (p = 0.020) lesions (Table 2., Figure 1.). Table 2. Comparison of FDG and FAPI SUVmax values for primary tumors. Parameter FDG SUVmax FAPI SUVmax p-value (Mean ± SD, Range) or n (%) Primary tumor (cm) 6.18 ± 6.24 (2.0–26.4) 14.49 ± 4.14 (6.6–19.0) 0.006 Adenocarcinoma (AdenoCA) 7.38 ± 7.73 14.01 ± 4.77 < 0.05 Signet-ring cell AdenoCA 4.97 ± 2.57 16.33 ± 2.23 < 0.01 Mucinous adenocarcinoma 3.25 ± 1.77 20.6 ± 6.8 0.06 Poorly differentiated a AdenoCA 4.3 19.2 – Liver SUVmean 2.0 ± 0.7 0.5 ± 0.0 < 0.001 Lymph node (any) 5.2 ± 2.1 9.6 ± 3.8 0.040 – N1 4.8 ± 1.7 8.9 ± 3.5 0.050 – N2 6.1 ± 2.2 10.3 ± 4.1 0.040 Distant metastases (any) 7.4 ± 2.8 13.5 ± 4.2 0.030 – Liver 6.9 ± 2.6 12.8 ± 4.1 0.040 – Bone 7.2 ± 3.1 14.2 ± 3.8 0.030 – Peritoneum 6.5 ± 2.9 13.0 ± 4.4 0.020 When evaluating metastatic involvement, FAPI PET/CT identified a higher number of positive cases compared to FDG PET/CT. For lymph nodes, FAPI detected 11/24 patients (45.8%), whereas FDG detected 8/24 (33.3%). Similarly, for distant metastases, FAPI was positive in 11/24 (45.8%), while FDG was positive in 8/24 (33.3%). Of these three patients with positive FAPI and negative FDG, two had peritoneal metastasis and one had bone metastasis. In both sites (lymph nodes and distant metastases), there were three additional patients who were positive only on FAPI, and importantly, there were no cases positive on FDG but negative on FAPI. The majority of patients were concordant (n = 8) across both tracers. However, despite the higher detection rate of FAPI, the differences did not reach statistical significance (p = 0.25 for both lymph nodes and distant metastases) (Table 3.). Table 3. Comparison of metastasis detection rates between FDG and FAPI PET/CT. Site FDG positive n (%) FAPI positive n (%) Concordant (+/+) Discordant (FDG+/FAPI–) Discordant (FDG–/FAPI+) p-value Lymph nodes 8 (33.3%) 11 (45.8%) 8 0 3 0.25 Distant metastasis 8 (33.3%) 11 (45.8%) 8 0 3 0.25 In the assessment of metastatic detection, FAPI PET/CT demonstrated numerically higher detection rates; however, these differences did not reach statistical significance. ROC curve analysis demonstrated higher AUC values for FAPI PET/CT (0.87) compared to FDG PET/CT (0.79), suggesting improved discriminative performance. However, this finding should be interpreted with caution given the limited sample size and lack of statistical comparison between AUC values (Figure 2). Correlation analysis revealed no significant association between tumor size and SUVmax values. For tumor size, the correlation with FDG SUVmax was weak (r = 0.04, p = 0.897), and similarly, with FAPI SUVmax was low (r = 0.27, p = 0.402), indicating no meaningful relationship. In addition, the direct comparison between FDG and FAPI SUVmax values also demonstrated a negligible correlation (r = 0.07, p = 0.829) (Table 4.). Table 4. Correlation between SUVmax values (FDG vs FAPI) and tumor size. Parameter FDG SUVmax r (p) FAPI SUVmax r (p) Tumor size (cm) 0.04 (p = 0.897) 0.27 (p = 0.402) FAPI SUVmax r = 0.07 (p = 0.829) - Discussion GC remains one of the most common malignancies worldwide, particularly in East Asia, Eastern Europe, and parts of South America. Adenocarcinoma accounts for more than 95% of cases, and synchronous peritoneal metastases are observed in approximately 15–30% of patients at diagnosis [7]. Other frequent metastatic sites include the liver and lungs [8]. These metastatic patterns, particularly peritoneal dissemination, have a substantial impact on staging accuracy and therapeutic decision-making. Accurate staging of GC is critical for determining prognosis and guiding treatment strategies. Conventional imaging modalities such as contrast-enhanced computed tomography (CT), magnetic resonance imaging (MRI), and endoscopic ultrasound (EUS) are widely used. However, CT has limited sensitivity in detecting peritoneal metastases and small nodal disease [9]. MRI has shown promise in evaluating peritoneal and hepatic lesions [10], while EUS is effective for local staging but operator-dependent [11]. Laparoscopic staging remains the gold standard for peritoneal dissemination but is invasive and not routinely performed. In this context, molecular imaging techniques have emerged as valuable complementary tools. ¹⁸F-FDG PET/CT provides functional imaging based on glucose metabolism and plays a role in GC staging. However, its diagnostic performance is influenced by tumor biology, including histological subtype, tumor size, and physiological gastric uptake [12–14]. In particular, diffuse-type and mucinous tumors often demonstrate low FDG avidity. Moreover, ¹⁸F-FDG PET/CT has limited sensitivity for peritoneal metastases, which represents a major limitation in surgical planning [15]. Therefore, 18 FDG PET/CT cannot be considered a stand-alone modality for staging GC. The introduction of ⁶⁸Ga-FAPI PET/CT represents a novel stromal-targeted imaging approach. By binding to fibroblast activation protein expressed in cancer-associated fibroblasts (CAFs), which may constitute a substantial portion of tumor mass in GC [16–18], FAPI imaging provides high TBR. Previous studies have demonstrated increased uptake and improved lesion conspicuity with FAPI, particularly in FDG-negative tumors [19, 20]. In the present study, 68 Ga-FAPI PET/CT demonstrated significantly higher tracer uptake and TBR compared to 18 F-FDG PET/CT across primary tumors and metastatic lesions. These findings are consistent with prior reports by Chen et al. [21] and Kuten et al. [22], who also observed higher SUVmax values and improved detection, particularly in peritoneal disease. In lesion-based analysis, 68 Ga-FAPI PET/CT identified a higher number of nodal and distant metastatic lesions compared to 18 F-FDG PET/CT. However, these differences did not reach statistical significance (p = 0.25), likely due to the limited sample size. Therefore, our findings should be interpreted as hypothesis-generating rather than definitive evidence of superiority. Importantly, discordant findings were observed in a subset of patients, in which metastatic lesions—particularly peritoneal and bone involvement—were detected by FAPI but not by FDG. Notably, no FDG-positive/FAPI-negative cases were observed. These discordant cases may be clinically relevant, as peritoneal metastases represent a key determinant in treatment planning, and even small differences in detection may significantly influence therapeutic decisions. ROC analysis demonstrated higher AUC values for FAPI PET/CT compared to FDG PET/CT, suggesting improved discriminative performance. However, this finding should be interpreted cautiously given the limited cohort size and absence of statistical comparison between AUC values. Rather than replacing FDG PET/CT, our findings suggest that FAPI imaging may provide complementary diagnostic information, particularly in biologically heterogeneous tumors and in cases with low FDG avidity. Several meta-analyses have reported higher sensitivity of FAPI PET/CT compared to FDG in gastric cancer [23-27]. However, our study contributes to the literature by providing real-world data and highlighting clinically relevant discordant cases, particularly in peritoneal metastases. This may be particularly relevant in clinical scenarios where treatment decisions rely heavily on accurate detection of peritoneal disease. Gao et al. [23] pooled 141 patients and demonstrated significantly higher sensitivity for FAPI compared to FDG (0.95 vs. 0.84). This meta-analysis concluded that 68 Ga-FAPI PET/CT was significantly more sensitive than 18 F-FDG PET/CT in assessing primary gastric tumors, lymph nodes, and distant metastases, but the difference in the specificity of lymph node metastasis was not significant. Ruan et al. [24] confirmed FAPI’s superiority across T, N, and M staging, while Pang et al. [25] and Lin et al. [26] both showed enhanced detection of primary and metastatic disease. Watabe et al. [27] demonstrated FAPI’s markedly higher sensitivity for peritoneal metastases compared to FDG. 68 Ga-FAPI PET/CT shows higher accumulation in primary sites and metastatic lesions compared with 18 F-FDG PET/CT, especially for the detection of peritoneal carcinomatosis. In our cohort, FAPI showed significantly higher tracer uptake in both primary tumors and metastases (Figure 3). Selçuk et al. [28] demonstrated that FAPI PET/CT led to stage modification in a significant proportion of FDG-negative or equivocal cases. Although a formal staging change analysis was beyond the scope of our study, the detection of additional lesions by FAPI in our cohort suggests a potential impact on clinical decision-making. Translational Perspective Beyond diagnostic performance, our findings suggest a potential translational impact of 68 Ga-FAPI PET/CT in gastric cancer. Improved detection of peritoneal metastases may contribute to more accurate preoperative staging, potentially preventing unnecessary surgical interventions. In this context, FAPI PET/CT may enhance patient selection and support individualized treatment strategies. Clinical Implications and Future Directions The clinical implications of these findings are noteworthy. Incorporating FAPI PET/CT into the diagnostic workflow may improve detection of otherwise occult disease. In addition, its high TBR may facilitate radiotherapy planning and opens the door for theranostic applications using FAP-targeted radioligands. However, larger prospective studies are required to validate these findings. Study Limitations Despite these promising findings, our study has several limitations. It is a retrospective, single-center study with a relatively small sample size, which may limit the generalizability of the results. Histopathological confirmation of all metastatic lesions was not feasible, introducing a potential risk of verification bias. In addition, although FAPI uptake is strongly tumor-associated, it is not entirely specific, as inflammatory and fibrotic processes may also demonstrate tracer uptake [31]. Furthermore, this study focused primarily on diagnostic performance and did not evaluate the relationship between imaging findings and treatment response or survival outcomes. Finally, the absence of long-term follow-up data precludes assessment of prognostic implications. Conclusion 68 Ga-FAPI PET/CT demonstrates higher tracer uptake and improved TBR contrast compared to 18 F-FDG PET/CT in GC. Although lesion detection rates were numerically higher with FAPI, statistical significance was not reached in this cohort. These findings support a potential complementary role of FAPI PET/CT, particularly in detecting peritoneal disease and in cases with low FDG avidity. Further large-scale prospective studies are needed to define its clinical utility. Declarations Ethics Approval and Consent to Participate This study did not receive any specific funding from public, commercial, or not-for-profit organizations. The present retrospective study was conducted with the approval of the Clinical Research Ethics Committee of Gaziantep University (Approval No: 2025/171) and adhered to the ethical standards set forth in the Declaration of Helsinki. Author Contribution E.K. and E.E.Y. contributed to study conception and design. E.K., E.Y., and B.E.S. were involved in data collection and image analysis. E.K. performed the statistical analysis and drafted the manuscript. U.E. and E.Ş. supervised the study and contributed to critical revision of the manuscript. V.M.Ç. contributed to data interpretation and manuscript editing. All authors reviewed and approved the final version of the manuscript. Data Availability Data Availability StatementThe data that support the findings of this study are available from the corresponding author upon reasonable request. The data are not publicly available due to privacy and ethical restrictions. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49. Smyth EC, Nilsson M, Grabsch HI, van Grieken NCT, Lordick F. 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Impact of 68 Ga-FAPi PET/CT on staging or restaging digestive system tumors in patients with negative or equivocal 18 F-FDG PET/CT findings. Mol Imaging Radionucl Ther . 2025; 34(1):31–37. Röhrich M, Syed M, Liew DP, Giesel FL, Liermann J, Choyke PL, et al. 68 Ga-FAPI-PET/CT improves diagnostic staging and radiotherapy planning of adenoid cystic carcinomas - Imaging analysis and histological validation. Radiother Oncol. 2021;192-201. Privé BM, Boussihmad MA, Timmermans B, van Gemert WA, Peters SMB, Derks YHW. Fibroblast activation protein-targeted radionuclide therapy: background, opportunities, and challenges of first (pre)clinical studies. Eur J Nucl Med Mol Imaging. 2023;50(7):1906-1918. Kessler L, Ferdinandus J, Hirmas N, Zarrad F, Nader M, Kersting D, et al. Pitfalls and Common Findings in 68 Ga-FAPI PET: A Pictorial Analysis. J Nucl Med. 2022;63(6):890-896. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9357738","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":624810123,"identity":"8d9e4a93-4d4e-41bf-b8e6-81ad672af161","order_by":0,"name":"Ebuzer KALENDER","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYDCCAwwMzEBKzgDMM7AgXouxAZgykCBeS+IGMMVAhBa+2wcYHxe21aVvZ+8/uuFHgQQDf3t3Al4tkucSmI1ntrHl7uw5zHazB+gwiTNnN+DVYnCGgU2at40nd8ONZLYbPEAtBhK5BLWw/+Ztk0g3AGq5+YdILWzMvG0GCSAtt4myRfIMY7P0jHMJhhvOHDa7LWMgwUPQL3xnmA9+Liirkzc43vjs5ps/NnL87b34tTAwMDagcHkIKB8Fo2AUjIJRQAwAAJq9QpUDnO4uAAAAAElFTkSuQmCC","orcid":"","institution":"Gaziantep University","correspondingAuthor":true,"prefix":"","firstName":"Ebuzer","middleName":"","lastName":"KALENDER","suffix":""},{"id":624810124,"identity":"e7b263c4-a004-4cb1-97ce-436d4d5237a3","order_by":1,"name":"Edanur EKİNCİ YILDIRIM","email":"","orcid":"","institution":"Gaziantep University","correspondingAuthor":false,"prefix":"","firstName":"Edanur","middleName":"EKİNCİ","lastName":"YILDIRIM","suffix":""},{"id":624810125,"identity":"6019f063-dbdd-4780-9c80-2d5fc4a2e8a4","order_by":2,"name":"Enes YERDEŞ","email":"","orcid":"","institution":"Gaziantep University","correspondingAuthor":false,"prefix":"","firstName":"Enes","middleName":"","lastName":"YERDEŞ","suffix":""},{"id":624810126,"identity":"49e0f49f-f01c-4246-8409-e6a45bc4e22b","order_by":3,"name":"Buket EREN SARIBAŞ","email":"","orcid":"","institution":"Gaziantep University","correspondingAuthor":false,"prefix":"","firstName":"Buket","middleName":"EREN","lastName":"SARIBAŞ","suffix":""},{"id":624810127,"identity":"6c5c29e1-77fd-4084-924c-7488cef158b2","order_by":4,"name":"Umut ELBOĞA","email":"","orcid":"","institution":"Gaziantep University","correspondingAuthor":false,"prefix":"","firstName":"Umut","middleName":"","lastName":"ELBOĞA","suffix":""},{"id":624810128,"identity":"f62ee4e8-fb94-48c9-817c-0f1c1833cc84","order_by":5,"name":"Ertan ŞAHİN","email":"","orcid":"","institution":"Gaziantep University","correspondingAuthor":false,"prefix":"","firstName":"Ertan","middleName":"","lastName":"ŞAHİN","suffix":""},{"id":624810129,"identity":"1c5a1b25-6e74-4c47-aa5f-38169f3cd1f5","order_by":6,"name":"Vuslat MUMCU ÇİMEN","email":"","orcid":"","institution":"Gaziantep City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Vuslat","middleName":"MUMCU","lastName":"ÇİMEN","suffix":""}],"badges":[],"createdAt":"2026-04-08 13:39:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9357738/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9357738/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107675530,"identity":"b92d2448-47ab-478f-98c6-da982e112d78","added_by":"auto","created_at":"2026-04-24 00:44:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":24098,"visible":true,"origin":"","legend":"\u003cp\u003eSUVmax distribution of lesions for FDG and FAPI.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9357738/v1/80e3dc67d5a8b66571f45802.png"},{"id":107707839,"identity":"88de8155-0661-4adb-9f90-173fa49effe0","added_by":"auto","created_at":"2026-04-24 09:21:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":111459,"visible":true,"origin":"","legend":"\u003cp\u003eROC Curves Comparing FDG and FAPI PET/CT for Metastasis Detection\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9357738/v1/d0b4dd10452aabf871f62572.png"},{"id":107675532,"identity":"c3ca0672-60c2-48e1-820d-c9bd1f953134","added_by":"auto","created_at":"2026-04-24 00:44:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":237121,"visible":true,"origin":"","legend":"\u003cp\u003eA 56-year-old male patient with gastric adenocarcinoma. \u003csup\u003e68\u003c/sup\u003eGa-FAPI-04 PET/CT images (A, axial; B, maximum intensity projection) demonstrate markedly increased radiotracer uptake in the primary gastric tumor as well as in hepatic and peritoneal metastases (arrows). In comparison, \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT images (C, axial; D, maximum intensity projection) show considerably lower tracer accumulation in the same sites.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9357738/v1/ec7564b0cf9c7bf8b55a7ea6.png"},{"id":108406451,"identity":"f50e178f-6c88-452b-8ac8-c95d41aa3704","added_by":"auto","created_at":"2026-05-04 09:42:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":549440,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9357738/v1/dccc8c01-a3bf-42b7-894c-fca2dcbad2d9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eComparative Analysis of Lesion Detection and Uptake Characteristics of \u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e68\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eGa-FAPI PET/CT versus \u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e18\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eF-FDG PET/CT in Gastric Cancer: A Preliminary Translational Study\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGastric cancer (GC) remains one of the leading causes of cancer-related morbidity and mortality worldwide, ranking fifth in incidence and fourth in cancer-related deaths globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Accurate staging at diagnosis is critical for determining appropriate therapeutic strategies and predicting prognosis. In this context, imaging modalities play a central role in the assessment of primary tumors, regional lymph node involvement, and distant metastases.\u003c/p\u003e \u003cp\u003eFluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (\u0026sup1;⁸F-FDG PET/CT) has been widely utilized in oncologic imaging and is included in the clinical staging of various malignancies, including GC. However, \u0026sup1;⁸F-FDG PET/CT has well-known limitations in GC, particularly in detecting diffuse-type and mucinous histological subtypes, which often demonstrate low or absent FDG uptake [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent advances in molecular imaging have introduced novel radiotracers that may overcome some of these limitations. One such promising agent is ⁶⁸Ga-labeled fibroblast activation protein inhibitor (⁶⁸Ga-FAPI), which targets cancer-associated fibroblasts (CAFs) in the tumor stroma\u0026mdash;a feature abundant in desmoplastic tumors such as GC [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Early clinical studies have demonstrated that ⁶⁸Ga-FAPI PET/CT may provide superior lesion contrast, higher tumor uptake, and improved detection rates compared to \u0026sup1;⁸F-FDG PET/CT, particularly in tumors with low FDG avidity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we aimed to compare lesion detection and uptake characteristics of \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT and \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT in patients with gastric cancer undergoing imaging for clinical staging. Given the known limitations of FDG in certain histological subtypes, we further explored whether FAPI PET/CT may provide additional diagnostic information, particularly in cases with low FDG avidity.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThis retrospective study included patients with histopathologically confirmed gastric cancer who underwent both \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT and \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT as part of their clinical staging workup. All imaging studies were originally performed for staging purposes, and retrospective analysis was conducted focusing on lesion detection and semi-quantitative imaging parameters.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA total of 24 patients with pathologically verified GC (16 males, 8 females; mean age, 62.2 years; age range, 21\u0026ndash;79 years) were evaluated. All patients initially underwent \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT for staging purposes, followed\u0026mdash;after an interval of three days\u0026mdash;by \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT. Informed consent was obtained from every participant prior to both imaging. Two experienced nuclear medicine physicians reviewed the examinations independently, and inter-modality comparisons were performed to assess diagnostic accuracy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient Preparation and Imaging\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Prior to \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT, patients fasted for a minimum of six hours and discontinued intravenous glucose intake. Capillary blood glucose levels were required to be\u0026nbsp;\u0026le;150 mg/dL. Intravenous tracer administration consisted of 3.5\u0026ndash;5.5 MBq/kg for \u003csup\u003e18\u003c/sup\u003eF-FDG and 2 MBq/kg for \u003csup\u003e68\u003c/sup\u003eGa-FAPI-04.\u003c/p\u003e\n\u003cp\u003eAll imaging was carried out on a Discovery IQ PET/CT system (GE Healthcare, Milwaukee, WI, USA) equipped with five detector rings and a 20-cm axial field of view. Whole-body acquisitions were obtained one hour post-injection, extending from the cranial vertex to the mid-thigh.\u003c/p\u003e\n\u003cp\u003eCT scans were performed at 120 kV and 80 mAs per slice, with a 700-mm field of view, 64 \u0026times; 0.625 mm collimation, and reconstructed to a 3.3-mm slice thickness. PET data were acquired in 3D mode under identical positioning, with an acquisition time of 2.5 minutes per bed position, and reconstructed using dedicated software.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImage Evaluation and Statistical Methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;All PET/CT datasets were interpreted in axial, coronal, and sagittal orientations. Semi-quantitative measurements were performed using AW VolumeShare software (GE Healthcare), with tracer uptake expressed as maximum standardized uptake value (SUVmax). Volumes of interests (VOIs) were manually delineated in three orthogonal planes for both primary tumors and metastatic lesions.\u003c/p\u003e\n\u003cp\u003eStatistical analyses were carried out using SPSS software (version 27, IBM Corp., Armonk, NY, USA). Continuous variables were reported as mean, median, minimum, and maximum, while categorical variables were expressed as counts and percentages. The Wilcoxon signed-rank test was used to compare paired non-parametric SUVmax values between FDG and FAPI PET/CT scans. Spearman\u0026rsquo;s rank correlation coefficient (\u0026rho;) was used to evaluate the strength and direction of associations between SUVmax values and clinical parameters such as age, primary tumor localization, and lymph node involvement. A p-value of \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 24 patients with histopathologically confirmed GC were included in the study. The mean age was 62.2 \u0026plusmn; 11.9 years (range 21\u0026ndash;79), and the majority were male (66.7%). Regarding histopathological subtypes, adenocarcinoma was the most common (54.2%), followed by signet-ring cell adenocarcinoma (29.2%), mucinous adenocarcinoma (12.5%), and poorly differentiated adenocarcinoma (4.1%). Tumors were most frequently located in the antrum (50%), with lower frequencies in the corpus (25.0%), cardia (8.3%), pylorus (8.3%), and corpus\u0026ndash;antrum region (8.3%). The median tumor size was 5.0 cm (range 3\u0026ndash;10 cm) (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Patient Demographic and Clinical Characteristics.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"465\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eValue,\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u0026plusmn;SD (Range) or n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e62.2 \u0026plusmn; 11.9 (21\u0026ndash;79)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eGender, Male/Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e16 (66.7%) / 8 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eHistopathology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eAdenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e13 (54.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eSignet-ring cell adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e7 (29.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eMucinous adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e3 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003ePoorly differentiated adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e1 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eTumor location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eAntrum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e12 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eCorpus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e6 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eCardia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e2 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003ePylorus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e2 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eCorpus\u0026ndash;Antrum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e2 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eTumor size (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e5.0 (3\u0026ndash;10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAnalysis of SUVmax values demonstrated that FAPI uptake was significantly higher than FDG uptake across primary tumors and metastatic sites. For primary gastric tumors, mean FAPI SUVmax was 14.49 \u0026plusmn; 4.14 compared to FDG SUVmax of 6.18 \u0026plusmn; 6.24 (p = 0.006). In histological subgroups, FAPI uptake remained consistently higher, with significant differences in adenocarcinoma (14.01 \u0026plusmn; 4.77 vs. 7.38 \u0026plusmn; 7.73; p \u0026lt; 0.05) and signet-ring cell carcinoma (16.33 \u0026plusmn; 2.23 vs. 4.97 \u0026plusmn; 2.57; p \u0026lt; 0.01). It was also higher in mucinous adenocarcinoma (20.6 \u0026plusmn; 6.8 vs. 3.25 \u0026plusmn; 1.77; p \u0026lt; 0.01); however, it was not statistically significant due to the low number of patients. In terms of background uptake, hepatic SUVmean was markedly lower for FAPI (0.5 \u0026plusmn; 0.2) compared to FDG (2.0 \u0026plusmn; 0.7; p \u0026lt; 0.001), indicating superior tumor-to-liver contrast. For nodal metastases, FAPI showed significantly higher uptake (9.6 \u0026plusmn; 3.8 vs. 5.2 \u0026plusmn; 2.1; p = 0.040), with consistent findings in both N1 and N2 subgroups. Similarly, distant metastases demonstrated greater FAPI activity (13.5 \u0026plusmn; 4.2 vs. 7.4 \u0026plusmn; 2.8; p = 0.030), with significant differences across liver (p = 0.040), bone (p = 0.030), and peritoneal (p = 0.020) lesions (Table 2., Figure 1.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Comparison of FDG and FAPI SUVmax values for primary tumors.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"555\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFDG SUVmax\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFAPI SUVmax\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean \u0026plusmn; SD, Range) or n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003ePrimary tumor (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e6.18 \u0026plusmn; 6.24\u003c/p\u003e\n \u003cp\u003e(2.0\u0026ndash;26.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e14.49 \u0026plusmn; 4.14\u003c/p\u003e\n \u003cp\u003e(6.6\u0026ndash;19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003eAdenocarcinoma (AdenoCA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e7.38 \u0026plusmn; 7.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e14.01 \u0026plusmn; 4.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003eSignet-ring cell AdenoCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e4.97 \u0026plusmn; 2.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e16.33 \u0026plusmn; 2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003eMucinous\u0026nbsp;adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e3.25 \u0026plusmn; 1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e20.6 \u0026plusmn; 6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003ePoorly differentiated a AdenoCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e19.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003eLiver SUVmean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e2.0 \u0026plusmn; 0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.5 \u0026plusmn; 0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003eLymph node (any)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e5.2 \u0026plusmn; 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e9.6 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003e\u0026ndash; N1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e4.8 \u0026plusmn; 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e8.9 \u0026plusmn; 3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003e\u0026ndash; N2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e6.1 \u0026plusmn; 2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e10.3 \u0026plusmn; 4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003eDistant metastases (any)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e7.4 \u0026plusmn; 2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e13.5 \u0026plusmn; 4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003e\u0026ndash; Liver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e6.9 \u0026plusmn; 2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e12.8 \u0026plusmn; 4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003e\u0026ndash; Bone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e7.2 \u0026plusmn; 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e14.2 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003e\u0026ndash; Peritoneum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e6.5 \u0026plusmn; 2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e13.0 \u0026plusmn; 4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eWhen evaluating metastatic involvement, FAPI PET/CT identified a higher number of positive cases compared to FDG PET/CT. For lymph nodes, FAPI detected 11/24 patients (45.8%), whereas FDG detected 8/24 (33.3%). Similarly, for distant metastases, FAPI was positive in 11/24 (45.8%), while FDG was positive in 8/24 (33.3%). Of these three patients with positive FAPI and negative FDG, two had peritoneal metastasis and one had bone metastasis.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In both sites (lymph nodes and distant metastases), there were three additional patients who were positive only on FAPI, and importantly, there were no cases positive on FDG but negative on FAPI. The majority of patients were concordant (n = 8) across both tracers. However, despite the higher detection rate of FAPI, the differences did not reach statistical significance (p = 0.25 for both lymph nodes and distant metastases) (Table 3.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Comparison of metastasis detection rates between FDG and FAPI PET/CT.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"647\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFDG positive\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFAPI positive\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConcordant\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(+/+)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiscordant\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(FDG+/FAPI\u0026ndash;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiscordant\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(FDG\u0026ndash;/FAPI+)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eLymph nodes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e8 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e11 (45.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eDistant metastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e8 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e11 (45.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn the assessment of metastatic detection, FAPI PET/CT demonstrated numerically higher detection rates; however, these differences did not reach statistical significance. ROC curve analysis demonstrated higher AUC values for FAPI PET/CT (0.87) compared to FDG PET/CT (0.79), suggesting improved discriminative performance. However, this finding should be interpreted with caution given the limited sample size and lack of statistical comparison between AUC values (Figure 2).\u003c/p\u003e\n\u003cp\u003eCorrelation analysis revealed no significant association between tumor size and SUVmax values. For tumor size, the correlation with FDG SUVmax was weak (r = 0.04, p = 0.897), and similarly, with FAPI SUVmax was low (r = 0.27, p = 0.402), indicating no meaningful relationship. In addition, the direct comparison between FDG and FAPI SUVmax values also demonstrated a negligible correlation (r = 0.07, p = 0.829) (Table 4.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e Correlation between SUVmax values (FDG vs FAPI) and tumor size.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"556\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFDG SUVmax r (p)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFAPI SUVmax r (p)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003eTumor size (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.04 (p = 0.897)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e0.27 (p = 0.402)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003eFAPI SUVmax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003er = 0.07 (p = 0.829)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eGC remains one of the most common malignancies worldwide, particularly in East Asia, Eastern Europe, and parts of South America. Adenocarcinoma accounts for more than 95% of cases, and synchronous peritoneal metastases are observed in approximately 15\u0026ndash;30% of patients at diagnosis [7]. Other frequent metastatic sites include the liver and lungs [8]. These metastatic patterns, particularly peritoneal dissemination, have a substantial impact on staging accuracy and therapeutic decision-making.\u003c/p\u003e\n\u003cp\u003eAccurate staging of GC is critical for determining prognosis and guiding treatment strategies. Conventional imaging modalities such as contrast-enhanced computed tomography (CT), magnetic resonance imaging (MRI), and endoscopic ultrasound (EUS) are widely used. However, CT has limited sensitivity in detecting peritoneal metastases and small nodal disease [9]. MRI has shown promise in evaluating peritoneal and hepatic lesions [10], while EUS is effective for local staging but operator-dependent [11]. Laparoscopic staging remains the gold standard for peritoneal dissemination but is invasive and not routinely performed. In this context, molecular imaging techniques have emerged as valuable complementary tools.\u003c/p\u003e\n\u003cp\u003e\u0026sup1;⁸F-FDG PET/CT provides functional imaging based on glucose metabolism and plays a role in GC staging. However, its diagnostic performance is influenced by tumor biology, including histological subtype, tumor size, and physiological gastric uptake [12\u0026ndash;14]. In particular, diffuse-type and mucinous tumors often demonstrate low FDG avidity. Moreover, \u0026sup1;⁸F-FDG PET/CT has limited sensitivity for peritoneal metastases, which represents a major limitation in surgical planning [15]. Therefore, \u003csup\u003e18\u003c/sup\u003eFDG PET/CT cannot be considered a stand-alone modality for staging GC.\u003c/p\u003e\n\u003cp\u003eThe introduction of ⁶⁸Ga-FAPI PET/CT represents a novel stromal-targeted imaging approach. By binding to fibroblast activation protein expressed in cancer-associated fibroblasts (CAFs), which may constitute a substantial portion of tumor mass in GC [16\u0026ndash;18], FAPI imaging provides high TBR. Previous studies have demonstrated increased uptake and improved lesion conspicuity with FAPI, particularly in FDG-negative tumors [19, 20].\u003c/p\u003e\n\u003cp\u003eIn the present study, \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT demonstrated significantly higher tracer uptake and TBR compared to \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT across primary tumors and metastatic lesions. These findings are consistent with prior reports by Chen et al. [21] and Kuten et al. [22], who also observed higher SUVmax values and improved detection, particularly in peritoneal disease.\u003c/p\u003e\n\u003cp\u003eIn lesion-based analysis, \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT identified a higher number of nodal and distant metastatic lesions compared to \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT. However, these differences did not reach statistical significance (p = 0.25), likely due to the limited sample size. Therefore, our findings should be interpreted as hypothesis-generating rather than definitive evidence of superiority.\u003c/p\u003e\n\u003cp\u003eImportantly, discordant findings were observed in a subset of patients, in which metastatic lesions\u0026mdash;particularly peritoneal and bone involvement\u0026mdash;were detected by FAPI but not by FDG. Notably, no FDG-positive/FAPI-negative cases were observed. These discordant cases may be clinically relevant, as peritoneal metastases represent a key determinant in treatment planning, and even small differences in detection may significantly influence therapeutic decisions.\u003c/p\u003e\n\u003cp\u003eROC analysis demonstrated higher AUC values for FAPI PET/CT compared to FDG PET/CT, suggesting improved discriminative performance. However, this finding should be interpreted cautiously given the limited cohort size and absence of statistical comparison between AUC values. Rather than replacing FDG PET/CT, our findings suggest that FAPI imaging may provide complementary diagnostic information, particularly in biologically heterogeneous tumors and in cases with low FDG avidity. Several meta-analyses have reported higher sensitivity of FAPI PET/CT compared to FDG in gastric cancer [23-27]. However, our study contributes to the literature by providing real-world data and highlighting clinically relevant discordant cases, particularly in peritoneal metastases. This may be particularly relevant in clinical scenarios where treatment decisions rely heavily on accurate detection of peritoneal disease.\u003c/p\u003e\n\u003cp\u003eGao et al. [23] pooled 141 patients and demonstrated significantly higher sensitivity for FAPI compared to FDG (0.95 vs. 0.84). This meta-analysis concluded that \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT was significantly more sensitive than \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT in assessing primary gastric tumors, lymph nodes, and distant metastases, but the difference in the specificity of lymph node metastasis was not significant. Ruan et al. [24] confirmed FAPI\u0026rsquo;s superiority across T, N, and M staging, while Pang et al. [25] and Lin et al. [26] both showed enhanced detection of primary and metastatic disease. Watabe et al. [27] demonstrated FAPI\u0026rsquo;s markedly higher sensitivity for peritoneal metastases compared to FDG. \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT shows higher accumulation in primary sites and metastatic lesions compared with \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT, especially for the detection of peritoneal carcinomatosis.\u0026nbsp;In our cohort, FAPI showed significantly higher tracer uptake in both primary tumors and metastases\u0026nbsp;(Figure 3).\u003c/p\u003e\n\u003cp\u003eSel\u0026ccedil;uk et al. [28] demonstrated that FAPI PET/CT led to stage modification in a significant proportion of FDG-negative or equivocal cases. Although a formal staging change analysis was beyond the scope of our study, the detection of additional lesions by FAPI in our cohort suggests a potential impact on clinical decision-making.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTranslational Perspective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBeyond diagnostic performance, our findings suggest a potential translational impact of \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT in gastric cancer. Improved detection of peritoneal metastases may contribute to more accurate preoperative staging, potentially preventing unnecessary surgical interventions. In this context, FAPI PET/CT may enhance patient selection and support individualized treatment strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Implications and Future Directions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe clinical implications of these findings are noteworthy. Incorporating FAPI PET/CT into the diagnostic workflow may improve detection of otherwise occult disease. In addition, its high TBR may facilitate radiotherapy planning and opens the door for theranostic applications using FAP-targeted radioligands. However, larger prospective studies are required to validate these findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite these promising findings, our study has several limitations. It is a retrospective, single-center study with a relatively small sample size, which may limit the generalizability of the results. Histopathological confirmation of all metastatic lesions was not feasible, introducing a potential risk of verification bias. In addition, although FAPI uptake is strongly tumor-associated, it is not entirely specific, as inflammatory and fibrotic processes may also demonstrate tracer uptake [31]. Furthermore, this study focused primarily on diagnostic performance and did not evaluate the relationship between imaging findings and treatment response or survival outcomes. Finally, the absence of long-term follow-up data precludes assessment of prognostic implications.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003e \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT demonstrates higher tracer uptake and improved TBR contrast compared to \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT in GC. Although lesion detection rates were numerically higher with FAPI, statistical significance was not reached in this cohort. These findings support a potential complementary role of FAPI PET/CT, particularly in detecting peritoneal disease and in cases with low FDG avidity. Further large-scale prospective studies are needed to define its clinical utility.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics Approval and Consent to Participate\u003c/h2\u003e \u003cp\u003eThis study did not receive any specific funding from public, commercial, or not-for-profit organizations. The present retrospective study was conducted with the approval of the Clinical Research Ethics Committee of Gaziantep University (Approval No: 2025/171) and adhered to the ethical standards set forth in the Declaration of Helsinki.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eE.K. and E.E.Y. contributed to study conception and design. E.K., E.Y., and B.E.S. were involved in data collection and image analysis. E.K. performed the statistical analysis and drafted the manuscript. U.E. and E.Ş. supervised the study and contributed to critical revision of the manuscript. V.M.\u0026Ccedil;. contributed to data interpretation and manuscript editing. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData Availability StatementThe data that support the findings of this study are available from the corresponding author upon reasonable request. The data are not publicly available due to privacy and ethical restrictions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209\u0026ndash;49. \u003c/li\u003e\n\u003cli\u003eSmyth EC, Nilsson M, Grabsch HI, van Grieken NCT, Lordick F. Gastric cancer. Lancet. 2020;396(10251):635\u0026ndash;48. \u003c/li\u003e\n\u003cli\u003eStahl A, Ott K, Schwaiger M, Weber WA, Becker K, Link T, Siewert JR, et al. FDG PET imaging of locally advanced gastric carcinomas: correlation with endoscopic and histopathological findings. Eur J Nucl Med Mol Imaging. 2003;30(2):288-95. \u003c/li\u003e\n\u003cli\u003eLoktev A, Lindner T, Burger EM, Altmann A, Giesel FL, Kratochwil C, et al. Development of fibroblast activation protein\u0026ndash;targeted radiotracers with improved tumor retention. J Nucl Med. 2019;60(10):1421\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eKratochwil C, Flechsig P, Lindner T, Abderrahim L, Altmann A, Mier W, et al. \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT: Tracer uptake in 28 different kinds of cancer. J Nucl Med. 2019;60(6):801\u0026ndash;5. \u003c/li\u003e\n\u003cli\u003eKuyumcu S, Sanli Y, Subramaniam RM. Fibroblast-activated protein inhibitor PET/CT: Cancer Diagnosis and management. Front Oncol. 2021;11:758958. \u003c/li\u003e\n\u003cli\u003eManzanedo I, Pereira F, Perez-Viejo E, Serrano A. Gastric cancer with peritoneal metastases: Current status and prospects for treatment. Cancers. 2023;15(6):1777.\u003c/li\u003e\n\u003cli\u003eRiihim\u0026auml;ki M, Hemminki A, Sundquist K, Sundquist J, Hemminki K. Metastatic spread in patients with gastric cancer. Oncotarget. 2016;7(32):52307\u0026ndash;52316. \u003c/li\u003e\n\u003cli\u003eKim HJ, Kim AY, Oh ST, Kim JS, Kim KW, Kim PN, et al. Gastric cancer staging at multi-detector row CT gastrography: comparison of transverse and volumetric CT scanning Radiology. 2005;236(3):879\u0026ndash;86. \u003c/li\u003e\n\u003cli\u003eGiganti F, Ambrossi A, Chiari D, Orsenigo E, Esposito A, Mazza E, et al. Apparent diffusion coefficient by diffusion-weighted magnetic resonance imaging as a sole biomarker for staging and prognosis of gastric cancer. Chin J Cancer Res. 2017 29(2):118\u0026ndash;126.\u003c/li\u003e\n\u003cli\u003ePolkowski M, Palucki J, Butruk E. Transabdominal ultrasound for visualizing gastric submucosal tumors diagnosed by endosonography: can surveillance be simplified? Endoscopy. 2002;34(12):979-83. \u003c/li\u003e\n\u003cli\u003eWu C.X., Zhu Z.H. Diagnosis and evaluation of gastric cancer by positron emission tomography. World J. Gastroenterol. 2014;20(16):4574\u0026ndash;4585. \u003c/li\u003e\n\u003cli\u003eKim HW, Won KS, Song B-I, Kang YN. Correlation of primary tumor FDG uptake with histopathologic features of advanced gastric cancer. Nucl Med Mol Imaging. 2015;49(2):135-42. \u003c/li\u003e\n\u003cli\u003eKim SK, Kang KW, Lee JS, Kim HK, Chang HJ, Choi JY, et al. Assessment of lymph node metastases using 18F-FDG PET in patients with advanced gastric cancer: Eur J Nucl Med Mol Imaging. 2006 Feb;33(2):148-55.\u003c/li\u003e\n\u003cli\u003eLim JS, Kim MJ, Yun MJ, Oh YT, Kim JH, Hwang HS, et al. Comparison of CT and 18F-FDG PET for detecting peritoneal metastasis on the preoperative evaluation for gastric carcinoma. Korean J Radiol 2006;7(4):249-256.\u003c/li\u003e\n\u003cli\u003eLindner T, Loktev A, Altmann A, Giesel F, Kratochwil C, Debus J, et al. Development of quinoline-based theranostic ligands for targeting fibroblast activation protein. J Nucl Med. 2018;59(9):1415\u0026ndash;22. \u003c/li\u003e\n\u003cli\u003ePure E, Blomberg R. Pro-tumorigenic roles of fibroblast activation protein in cancer: back to the basics. Oncogene. 2018 Aug;37(32):4343-4357.\u003c/li\u003e\n\u003cli\u003eKalluri R. The biology and function of fibroblasts in cancer. Nat Rev Cancer. 2016;16(9):582\u0026ndash;98. \u003c/li\u003e\n\u003cli\u003eGiesel FL, Kratochwill C, Schlittenhardt\u003csup\u003e \u003c/sup\u003e J, Dendl\u003csup\u003e \u003c/sup\u003e K, Eiber\u003csup\u003e \u003c/sup\u003e M, Staudinger F, et al. Head-to-head intra-individual comparison of biodistribution and tumor uptake of \u003csup\u003e68\u003c/sup\u003eGa-FAPI and \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT in cancer patients. Eur J Nucl Med Mol Imaging. 2021 Dec;48(13):4377-4385.\u003c/li\u003e\n\u003cli\u003eGiesel FL, Kratochwill C, Lindner T, Marschalek MM, Loktev A, Lehnert W, et al.\u003csup\u003e 68\u003c/sup\u003eGa-FAPI PET/CT: Biodistribution and Preliminary Dosimetry Estimate of 2 DOTA-Containing FAP-Targeting Agents in Patients with Various Cancers. J Nucle Med. 2019;60(3):386-392.\u003c/li\u003e\n\u003cli\u003eChen H, Pang Y, Li J, Kang F, Xu W, Meng TJ, et al. Comparison of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-FAPI and [\u003csup\u003e18\u003c/sup\u003eF]FDG uptake in patients with gastric signet-ring-cell carcinoma: a multicenter retrospective study. Eur Radiol. 2023;33(2):1329-1341.\u003c/li\u003e\n\u003cli\u003eKuten J, Levine C, Shamni O, Pelles S, Wolf I, Lahat G, et al. Head-to-head comparison of [\u003csup\u003e68\u003c/sup\u003eGa]Ga-FAPI-04 and [\u003csup\u003e18\u003c/sup\u003eF]-FDG PET/CT in evaluating the extent of disease in gastric adenocarcinoma Eur J Nucl Med Mol Imaging. 2022 Jan;49(2):743-750.\u003c/li\u003e\n\u003cli\u003eGao C, Liu H, Zhou L, Huang W, Liu X. Head to head comparison of \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT with \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT in primary and metastatic lesions of gastric tumor: A systematic review and meta-analysis. Hell J Nucl Med 2024;27(1):35-45.\u003c/li\u003e\n\u003cli\u003eRuan D, Zhao L, Cai J, Xu W, Sun L, Li J, et al. Evaluation of FAPI PET imaging in gastric cancer: a systematic review and meta-analysis. Theranostics. 2023;13:4694-4710.\u003c/li\u003e\n\u003cli\u003ePang Y, Zhao L, Luo Z, Hao B, Wu H, Lin Q, et al. Comparison of \u003csup\u003e68\u003c/sup\u003eGa-FAPI and \u003csup\u003e18\u003c/sup\u003eF-FDG uptake in gastric, duodenal, and colorectal cancers. Radiology. 2021;298(2):393\u0026ndash;402. \u003c/li\u003e\n\u003cli\u003eLin R, Lin Z, Chen Z, Zheng S, Zhang J, Zang J, et al. [\u003csup\u003e68\u003c/sup\u003eGa]Ga-DOTA-FAPI-04 PET/CT in the evaluation of gastric cancer: comparison with [\u003csup\u003e18\u003c/sup\u003eF]FDG PET/CT. Eur J Nucl Med Mol Imaging. 2022;49(8)2960-2971.\u003c/li\u003e\n\u003cli\u003eWatabe T, Giesel FL. Fibroblast activation protein inhibitor PET/CT in gastric cancer. PET Clin 2023;18(3):337-344. \u003c/li\u003e\n\u003cli\u003eSel\u0026ccedil;uk NA, Beydağı G, Ak\u0026ccedil;ay K, Demirci E, Gormez A, Oven BB, et al. Impact of \u003csup\u003e68\u003c/sup\u003eGa-FAPi PET/CT on staging or restaging digestive system tumors in patients with negative or equivocal \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT findings. Mol Imaging Radionucl Ther\u003cem\u003e.\u003c/em\u003e 2025; 34(1):31\u0026ndash;37. \u003c/li\u003e\n\u003cli\u003eR\u0026ouml;hrich M, Syed M, Liew DP, Giesel FL, Liermann J, Choyke PL, et al. \u003csup\u003e68\u003c/sup\u003eGa-FAPI-PET/CT improves diagnostic staging and radiotherapy planning of adenoid cystic carcinomas - Imaging analysis and histological validation. Radiother Oncol. 2021;192-201.\u003c/li\u003e\n\u003cli\u003ePriv\u0026eacute; BM, Boussihmad MA, Timmermans B, van Gemert WA, Peters SMB, Derks YHW. Fibroblast activation protein-targeted radionuclide therapy: background, opportunities, and challenges of first (pre)clinical studies. Eur J Nucl Med Mol Imaging. 2023;50(7):1906-1918.\u003c/li\u003e\n\u003cli\u003eKessler L, Ferdinandus J, Hirmas N, Zarrad F, Nader M, Kersting D, et al. Pitfalls and Common Findings in \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET: A Pictorial Analysis. J Nucl Med. 2022;63(6):890-896.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"68Ga-FAPI PET/CT, 18F-FDG PET/CT, gastric cancer, molecular imaging, CAFs, TBR","lastPublishedDoi":"10.21203/rs.3.rs-9357738/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9357738/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThis study aimed to compare lesion detection and uptake characteristics of \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT and \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT in patients undergoing imaging for gastric cancer (GC) staging.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 24 patients with histopathologically confirmed GC were retrospectively evaluated. All patients underwent \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT followed by \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT within a short interval as part of their clinical staging workup. Lesion detection rates and semi-quantitative parameters, including SUVmax and tumor-to-background ratio (TBR), were compared between the two modalities.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT demonstrated significantly higher SUVmax values than \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT across primary tumors and metastatic lesions (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). TBRs were also markedly higher for FAPI due to lower physiological background activity. In lesion-based analysis, \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT identified a higher number of nodal and distant metastases compared to \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT; however, these differences did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.25). Notably, discordant findings were observed in a subset of patients, in which lesions\u0026mdash;particularly peritoneal metastases\u0026mdash;were detected by FAPI but not by FDG. ROC analysis demonstrated higher AUC values for FAPI (0.87) compared to FDG (0.79), suggesting improved discriminative performance.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003e \u003csup\u003e68\u003c/sup\u003eGa-FAPI PET/CT provides higher tracer uptake and improved TBR compared to \u003csup\u003e18\u003c/sup\u003eF-FDG PET/CT in GC. Although lesion detection rates were numerically higher with FAPI, statistical significance was not reached in this cohort. These findings suggest a potential complementary role of FAPI PET/CT, particularly in detecting peritoneal disease and in cases with low FDG avidity. Larger prospective studies are warranted to clarify its clinical impact.\u003c/p\u003e","manuscriptTitle":"Comparative Analysis of Lesion Detection and Uptake Characteristics of 68Ga-FAPI PET/CT versus 18F-FDG PET/CT in Gastric Cancer: A Preliminary Translational Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-24 00:43:58","doi":"10.21203/rs.3.rs-9357738/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7945f48d-8b72-481b-8b43-dc8e4227143b","owner":[],"postedDate":"April 24th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-04T09:35:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T09:06:13+00:00","index":22,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T09:42:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-24 00:43:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9357738","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9357738","identity":"rs-9357738","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}