Prediction of pathological response to neoadjuvant immunochemotherapy with baseline and post-treatment 18F-FDG PET imaging biomarkers in patients with locally advanced gastric cancer
Abstract Background Neoadjuvant immunochemotherapy (NICT) has shown promising therapeutic benefits in patients with locally advanced gastric cancer (LAGC). Our study aimed to predict the pathological response to NICT in LAGC before surgery by correlating the metabolic parameters of baseline and post...
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2025-02-01
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| Online Access: | https://doi.org/10.1186/s12885-025-13765-1 |
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| author | Mimi Xu Yafei Zhang Kui Zhao Haiping Jiang Guangfa Wang Yan Wu Yu Wang Nian Liu Xinhui Su |
| author_facet | Mimi Xu Yafei Zhang Kui Zhao Haiping Jiang Guangfa Wang Yan Wu Yu Wang Nian Liu Xinhui Su |
| author_sort | Mimi Xu |
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| description | Abstract Background Neoadjuvant immunochemotherapy (NICT) has shown promising therapeutic benefits in patients with locally advanced gastric cancer (LAGC). Our study aimed to predict the pathological response to NICT in LAGC before surgery by correlating the metabolic parameters of baseline and post-treatment 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) of the primary lesion with the pathological response following radical surgery. Methods Thirty-six LAGC patients who received three cycles of NICT (combination of sintilimab and CapeOx), followed by radical surgery, were included in this study. Both baseline 18F-FDG PET/CT (bPET) and post-treatment 18F-FDG PET/CT (pPET) were conducted, the metabolic parameters derived from the PET/CT scans, including the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) on bPET and pPET (bSUVmax and pSUVmax, bMTV and pMTV, bTLG and pTLG), as well as their reductions post-treatment (ΔSUVmax, ΔMTV, and ΔTLG), were assessed for their correlation with treatment efficacy and tumor regression grade (TRG) following NICT. Results Out of the 36 patients, 13 patients had a good response (GR), which included 5 cases with TRG 0 and 8 cases with TRG 1. Conversely, 23 patients exhibited a poor response (PR), with 20 patients having TRG 2 and 3 patients having TRG 3. Univariate analysis revealed that pMTV and pTLG in the GR group were significantly lower compared to the PR group (all p < 0.05). The identified cutoff values of pMTV and pTLG were 1.68 cm³ (area under the cure (AUC) = 0.683) and 4.71 cm³ (AUC = 0.683) for the GR and PR groups, respectively. On receiver operating characteristic (ROC) curve analyses, these values corresponded to sensitivity, specificity, and accuracy of 68.8%, 80.0%, and 73.1%, respectively, with no statistically significant differences between them after the DeLong test and McNemar test (all p > 0.05). Furthermore, bSUVmax, bMTV, bTLG, ΔSUVmax, ΔMTV, and ΔTLG in the TRG 0 group were significantly higher than those in the TRG 1 group (all p < 0.05). Upon performing ROC curve analyses for the TRG 0 group, the thresholds for bSUVmax, bMTV, bTLG, ΔSUVmax, ΔMTV, and ΔTLG were determined to be 7.8 (AUC = 0.916), 36.76 (AUC = 0.768), 105.55 (AUC = 0.819), 4.82 (AUC = 0.923), 22.64 (AUC = 0.807), and 104.7 (AUC = 0.845), with no statistically significant differences between them after the DeLong test (all p > 0.05). These thresholds demonstrated high sensitivity (80% for bMTV and 100% for others), specificity (83.9%, 71.0%, 67.7%, 83.9%, 61.3%, and 71.0%), and accuracy (86.1%, 66.7%, 72.2%, 86.1%, 66.7%, and 75.0%) in predicting TRG 0 after NICT, with no statistically significant differences between them after the McNemar test (all p > 0.05). Conclusions Imaging biomarkers from the combination of baseline and post-treatment 18F-FDG PET/CT showed potential in predicting pathological response to NICT in LAGC patients before surgery. |
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| issn | 1471-2407 |
| language | English |
| publishDate | 2025-02-01 |
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| spelling | doaj-art-e074fd63da8e46a09d36d0fb94a0872f2025-08-20T02:01:35ZengBMCBMC Cancer1471-24072025-02-0125111410.1186/s12885-025-13765-1Prediction of pathological response to neoadjuvant immunochemotherapy with baseline and post-treatment 18F-FDG PET imaging biomarkers in patients with locally advanced gastric cancerMimi Xu0Yafei Zhang1Kui Zhao2Haiping Jiang3Guangfa Wang4Yan Wu5Yu Wang6Nian Liu7Xinhui Su8Department of Nuclear Medicine, The First Affiliated Hospital, Zhejiang University School of MedicineDepartment of Nuclear Medicine, The First Affiliated Hospital, Zhejiang University School of MedicineDepartment of Nuclear Medicine, The First Affiliated Hospital, Zhejiang University School of MedicineOncology Department, The First Affiliated Hospital, Zhejiang University School of MedicineDepartment of Nuclear Medicine, The First Affiliated Hospital, Zhejiang University School of MedicineDepartment of Nuclear Medicine, The First Affiliated Hospital, Zhejiang University School of MedicineThe Second Affiliated Hospital of Zhejiang Chinese Medical UniversityDepartment of Nuclear Medicine, The First Affiliated Hospital, Zhejiang University School of MedicineDepartment of Nuclear Medicine, The First Affiliated Hospital, Zhejiang University School of MedicineAbstract Background Neoadjuvant immunochemotherapy (NICT) has shown promising therapeutic benefits in patients with locally advanced gastric cancer (LAGC). Our study aimed to predict the pathological response to NICT in LAGC before surgery by correlating the metabolic parameters of baseline and post-treatment 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) of the primary lesion with the pathological response following radical surgery. Methods Thirty-six LAGC patients who received three cycles of NICT (combination of sintilimab and CapeOx), followed by radical surgery, were included in this study. Both baseline 18F-FDG PET/CT (bPET) and post-treatment 18F-FDG PET/CT (pPET) were conducted, the metabolic parameters derived from the PET/CT scans, including the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) on bPET and pPET (bSUVmax and pSUVmax, bMTV and pMTV, bTLG and pTLG), as well as their reductions post-treatment (ΔSUVmax, ΔMTV, and ΔTLG), were assessed for their correlation with treatment efficacy and tumor regression grade (TRG) following NICT. Results Out of the 36 patients, 13 patients had a good response (GR), which included 5 cases with TRG 0 and 8 cases with TRG 1. Conversely, 23 patients exhibited a poor response (PR), with 20 patients having TRG 2 and 3 patients having TRG 3. Univariate analysis revealed that pMTV and pTLG in the GR group were significantly lower compared to the PR group (all p < 0.05). The identified cutoff values of pMTV and pTLG were 1.68 cm³ (area under the cure (AUC) = 0.683) and 4.71 cm³ (AUC = 0.683) for the GR and PR groups, respectively. On receiver operating characteristic (ROC) curve analyses, these values corresponded to sensitivity, specificity, and accuracy of 68.8%, 80.0%, and 73.1%, respectively, with no statistically significant differences between them after the DeLong test and McNemar test (all p > 0.05). Furthermore, bSUVmax, bMTV, bTLG, ΔSUVmax, ΔMTV, and ΔTLG in the TRG 0 group were significantly higher than those in the TRG 1 group (all p < 0.05). Upon performing ROC curve analyses for the TRG 0 group, the thresholds for bSUVmax, bMTV, bTLG, ΔSUVmax, ΔMTV, and ΔTLG were determined to be 7.8 (AUC = 0.916), 36.76 (AUC = 0.768), 105.55 (AUC = 0.819), 4.82 (AUC = 0.923), 22.64 (AUC = 0.807), and 104.7 (AUC = 0.845), with no statistically significant differences between them after the DeLong test (all p > 0.05). These thresholds demonstrated high sensitivity (80% for bMTV and 100% for others), specificity (83.9%, 71.0%, 67.7%, 83.9%, 61.3%, and 71.0%), and accuracy (86.1%, 66.7%, 72.2%, 86.1%, 66.7%, and 75.0%) in predicting TRG 0 after NICT, with no statistically significant differences between them after the McNemar test (all p > 0.05). Conclusions Imaging biomarkers from the combination of baseline and post-treatment 18F-FDG PET/CT showed potential in predicting pathological response to NICT in LAGC patients before surgery.https://doi.org/10.1186/s12885-025-13765-1Gastric cancerPET/CTImmunochemotherapyMetabolic parameters |
| spellingShingle | Mimi Xu Yafei Zhang Kui Zhao Haiping Jiang Guangfa Wang Yan Wu Yu Wang Nian Liu Xinhui Su Prediction of pathological response to neoadjuvant immunochemotherapy with baseline and post-treatment 18F-FDG PET imaging biomarkers in patients with locally advanced gastric cancer BMC Cancer Gastric cancer PET/CT Immunochemotherapy Metabolic parameters |
| title | Prediction of pathological response to neoadjuvant immunochemotherapy with baseline and post-treatment 18F-FDG PET imaging biomarkers in patients with locally advanced gastric cancer |
| title_full | Prediction of pathological response to neoadjuvant immunochemotherapy with baseline and post-treatment 18F-FDG PET imaging biomarkers in patients with locally advanced gastric cancer |
| title_fullStr | Prediction of pathological response to neoadjuvant immunochemotherapy with baseline and post-treatment 18F-FDG PET imaging biomarkers in patients with locally advanced gastric cancer |
| title_full_unstemmed | Prediction of pathological response to neoadjuvant immunochemotherapy with baseline and post-treatment 18F-FDG PET imaging biomarkers in patients with locally advanced gastric cancer |
| title_short | Prediction of pathological response to neoadjuvant immunochemotherapy with baseline and post-treatment 18F-FDG PET imaging biomarkers in patients with locally advanced gastric cancer |
| title_sort | prediction of pathological response to neoadjuvant immunochemotherapy with baseline and post treatment 18f fdg pet imaging biomarkers in patients with locally advanced gastric cancer |
| topic | Gastric cancer PET/CT Immunochemotherapy Metabolic parameters |
| url | https://doi.org/10.1186/s12885-025-13765-1 |
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