The Therapeutic Efficacy of 18F-FDG Combined With 18F-FAPI PET/MR in Neoadjuvant Therapy for Gastric Cancer

The Therapeutic Efficacy of 18F-FDG Combined With 18F-FAPI PET/MR in Neoadjuvant Therapy for Gastric Cancer

Gastric cancer is the fifth most common cancer worldwide and the third leading cause of cancer-related deaths. Although surgical treatment can benefit the survival of the vast majority of patients, currently only early gastric cancer patients can be cured directly through endoscopic resection or surgery alone. Neoadjuvant therapy reduces tumor volume and improves tumor response rate through preoperative radiotherapy and chemotherapy, thereby increasing R0 resection rate and improving overall survival, without increasing postoperative complications and mortality. Timely imaging re staging during neoadjuvant therapy can allow patients to enter the surgical stage earlier, thereby reducing their preoperative burden. According to the different stages of neoadjuvant therapy, clinical staging can be divided into baseline stage (cBSstage) and clinical rest stage (cReStage) after neoadjuvant therapy.

At present, the conventional imaging methods for diagnosing cBStage in gastric cancer include CT, endoscopic ultrasonography (EUS), and MRI. The NCCN guidelines recommend CT for cBStage, with a diagnostic accuracy of 77.1% to 88.9%. Similarly, EUS and MRI were also used for cBStage, with accuracy rates of 65.0% to 92.1% and 71.4% to 82.6%, respectively. The application of diffusion-weighted imaging (DWI) has improved the accuracy of MRI diagnosis of cBStage to 93%.

However, due to the destruction of the gastric wall structure by neoadjuvant therapy, accurate imaging re staging is difficult. Currently, accurate tumor regression grading can only be obtained through surgical resection of pathological specimens. For cReT after neoadjuvant therapy, the diagnostic accuracy of EUS is only 63% (T2: 44%, T3: 68%, T4: 90%). Due to the presence of chronic inflammatory reactions, such as tumor cell apoptosis, necrosis, fibrosis, etc., in both the tumor and the critical normal gastric wall after neoadjuvant therapy, imaging cannot accurately identify the level of gastric wall, leading to the current low value of CT for cReT. Meanwhile, due to the fact that the pathological reactions of lymph nodes after neoadjuvant therapy are mainly subacute inflammatory reactions accompanied by scar tissue formation, and not all lymph node volumes that experience these pathological reactions will rapidly decrease, the accuracy of CT diagnosis of cReN is only 44%, while the sensitivity and specificity of EUS diagnosis of cReN are 50% and 56%, respectively.

In addition, positron emission tomography (PET) can reflect the abnormal metabolism, protein synthesis, DNA repair, and cell proliferation of tumors at the molecular level, providing important information in tumor grading diagnosis, prognosis evaluation, treatment decision-making, and efficacy monitoring. The conventional positron tracer 18F-FDG can reflect the glucose metabolism ability of different tissues, while most types of malignant tumors exhibit high metabolism. Therefore, 18F-FDG can be used for the diagnosis, staging, and treatment monitoring of cancer. However, in gastric cancer patients, 18F-FDG has certain limitations, including 1) interference with physiological or inflammatory uptake of the gastric wall; 2) Low uptake of 18F-FDG is present in signet ring cell carcinoma, mucinous adenocarcinoma, or other poorly differentiated cancers with high mucus content; 3) There are cases of false positive FDG after immunotherapy. In the study of SUV changes in the tumor area before and after treatment, it was found that patients with postoperative pathological regression grades 1-5 Δ SUVs are between 0-70%.

Tumor associated fibroblasts are closely related to tumor growth, invasion, and distant metastasis, and their activation requires the involvement of fibroblast activation protein (FAP). Therefore, radiolabeled fibroblast activation protein inhibitor (FAPI) can achieve in vivo FAP targeted tracing and quantification by specifically binding to FAP. Currently, a large number of studies have shown that 18F-FAPI is superior to 18F-FDG in the staging and re staging of gastric cancer. Furthermore, prospective studies have shown a certain relationship between tumor regression grade (TRG) and 18F-FAPI rate of change parameters (SUVmax, SUVavg, SUVR).

Therefore, in the early stage of this study, 18F-FAPI combined with 18F-FDG PET/MRI imaging was used to evaluate the efficacy of neoadjuvant therapy for gastric cancer, preoperative assessment of tumor regression grade after treatment, and re staging to guide the development of further clinical treatment plans.

This study is a prospective, single study and has been approved by the ethics committee. The subjects of this studywere from January 1,2024 to January 1,2026.The detailed description is as follows:

1. Patients: A patient with primary gastric adenocarcinoma who underwent surgical resection after neoadjuvant treatment at the Army Specialized Medical Center from January 2024 to January 2026.
2. Clinical data colection: Record the course of disease, laboratory tests (tumor markers), pre neoadjuvant MRI enhancement, PET/MR examination, postoperative pathology, and related immunohistochemistry of all patients.
3. PETMR image analysis: Record and evaluate the following indicators:the maximum, mean standardized uptakevalue (SUVmax, SUVmean) and standard uptake value ratio.
4. Pathological analysis: After collecting pathological specimens of the primary lesion and metastatic lymph nodes after surgery, they were fixed with formalin solution and embedded in paraffin, and three slices with a thickness of 4 were taken μ Slice of m. The first slice was stained with HE; The second slice was stained for glucose transporter 1 (GLUT1); The third slice was stained with Fibroblast Activation Protein (FAP). And record the primary lesion regression grade (TRG).
5. Statiscal analysis: Statistical analysis: Use descriptive statistical methods to compare the age of patients and the standardized uptake values of FDG and FAPI. Normal distribution data is represented as mean ± standard deviation, while non normal distribution data is represented as median with IQR. Compare the normal distribution data between two groups using paired two sample t-test, and compare the non normal distribution data between two groups using McNemar test. Using a four grid table McNemar χ Compare the diagnostic efficacy of 18F-FDG PET and 18F-FAPI PET through 2 tests, calculate and compare the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 18F-FDG and 18F-FAPI PET. Due to the potential impact of tumor type on diagnosis, subgroup analysis was conducted on the diagnostic efficacy of 18F-FDG PET and 18F-FAPI PET. Due to the possibility of multiple metastatic lesions in a given participant, the diagnostic results may be correlated within the participant. Therefore, sensitivity analysis of metastatic lesions is also performed based on a generalized linear mixed effects model by combining this correlation between different lesions within the same participant. Double tailed P<0.05 indicates a statistically significant difference.

Inclusion Criteria:

• Diagnosed primary gastric adenocarcinoma patients (cT2N+non-surgical treatment, cT3NanyMany and above staging)
• Staging of MRI enhanced examination before neoadjuvant therapy
• Restaging of preoperative 18F-FAPI and 18F-FDG PET/MRI examination
• Postoperative resection was performed after neoadjuvant therapy, with postoperative pathology, regression grading, and related immunohistochemistry
• Patient age ≥ 18 years old
• The patient voluntarily participates and signs an informed consent form.

Exclusion Criteria:

• Severe comorbidities may interfere with treatment or affect disease-specific health-related quality of life
• Drug requirements that interfere with the research protocol
• Pregnant or lactating male subjects who are expected to conceive or cause their spouse to conceive during the planned trial period
• The imaging quality is poor and cannot be used for diagnosis and evaluation.