Clinical Study of Trap (FAPI) 3 PET Imaging in Noninvasive Diagnosis of Malignant Tumors
Clinical Study of Trap (FAPI) 3 PET Imaging in Noninvasive Diagnosis of Malignant Tumors
Positron Emission Tomography (PET) is a functional imaging technology for diagnosing and monitoring tumors. In clinical applications for malignant tumors, PET includes staging, response assessment, and prognosis prediction, providing attractive semi-quantitative biomarkers for both clinical and research platforms. Understanding the fundamentals of imaging science and evaluating the strengths and limitations of imaging modalities is crucial for optimizing research assessments. With the widespread use of functional techniques and the development of novel PET biomarkers, PET-based research evaluations will be further enhanced. The field of oncology has undergone a revolution through molecular imaging, which evaluates tumor biology, while traditional radiological imaging focuses on morphological anatomy . Molecular imaging employs non-invasive visualization at cellular or subcellular levels to observe physiological or pathological processes, whereas PET/CT serves as a hybrid imaging tool that provides complementary information on both function and structure . [18F] Fluorodeoxyglucose (FDG), first developed in the late 1970s as a tracer for brain region metabolism, remains the most widely used PET tracer with diverse applications in both oncology and non-oncology fields . Despite its undeniable clinical utility, FDG uptake serves as an alternative indicator for glucose transport/metabolism rather than being specific to malignant tumors. Continuous exploration of cellular targets has led to the discovery of fibroblast activation protein (FAP). Cancer-associated fibroblasts are present in many tumors, particularly those with strong fibrotic-promoting responses such as breast cancer, colorectal cancer, pancreatic cancer, prostate cancer, and lung cancer. Consequently, FAP expression has been observed in over 90% of epithelial tumors. To date, FAP expression has been associated with poor tumor prognosis in colorectal cancer, pancreatic cancer, hepatocellular carcinoma, and ovarian cancer . Although more research is needed, this advantage makes cancer-associated fibroblasts an ideal target for anti-tumor therapy. In practical applications, low FAP expression in fibroblasts or healthy tissues facilitates imaging of subtle pathological changes. Cancer-associated fibroblasts (CAFs), a key component of the tumor microenvironment, account for over half the mass in various tumor types. Previous studies indicate that CAFs play significant roles in tumor growth, immune suppression, and cancer invasion . Therefore, CAFs may become emerging targets for tumor diagnosis and treatment. Fibroblast activation protein (FAP) is overexpressed in CAFs of multiple epithelial cancers but shows weak expression in healthy tissues, making it a promising target in cancer research. Recent years have seen expanded molecular imaging studies targeting FAP in tumor diagnosis . The excellent tumor-targeting efficacy of FAP has been confirmed through multiple clinical trials . The results clearly establish FAPI as a highly promising tumor-targeting ligand with significant potential applications in translational oncology. However, its therapeutic efficacy remains under investigation. An ideal radiopharmaceutical for cancer treatment should demonstrate excellent targeting specificity and relatively long tumor retention time. Previous studies have shown that radiolabeled FAPI variants (FAPI-04 and FAPI-46) accumulate rapidly and satisfactorily in tumors while showing low physiological uptake in normal tissues. However, previous FAP-related tracers exhibited relatively short tumor retention times . Our aim is to design a FAPI trimer, Trap-(FAPI)3, to optimize pharmacokinetics and evaluate whether this novel drug demonstrates superior advantages over its monomeric analogs in tumor imaging diagnosis and staging.
4.1 Research Site and Population This study enrolled patients with confirmed malignant tumors at the Army Specialized Medical Center between April 2025 and April 2027, as verified by biopsy or surgical pathology. 4.2 Sample Size Determination Using PASS software, the investigators calculated the required sample size by selecting the "Test for a single-sample Sensitivity and Specificity" under Diagnostic Tests (ROC). Based on prior literature and pilot studies, the sensitivity (Sensitivity) of 18F RCCB6 imaging for predicting treatment efficacy was estimated at 85%, with a specificity (Specificity) of 75%. With confidence levels α=0.05, β=0.2, and p=0.25, the null hypotheses for both sensitivity and specificity were set at 50%. Data analysis yielded a required sample size of 32.4.3 Survey Content 4.3.1 Clinical Data Collection All patients' disease progression, laboratory tests (tumor markers), pathological findings, and relevant immunohistochemical data were recorded. Image analysis and observation metrics: Trap- (FAPI) 3 PET/CT or PET/MR images were independently reviewed and processed by two experienced nuclear medicine physicians. The following indicators were recorded and evaluated: 1) Visual image analysis: including lesion location, size, morphology, and uptake extent; 2) Semi-quantitative analysis: measuring standard uptake value (SUV) of lesions and the ratio between lesion SUV and liver/blood pool SUV. 4.3.3 Pathological Analysis After collecting pathological specimens from primary lesions and metastatic lymph nodes post-surgery, formalin fixation and paraffin embedding were performed before sectioning into 4μm-thick slices for FAP staining. 4.4 Data Management and Statistical Analysis The Department of Nuclear Medicine at the Army Specialized Medical Center was responsible for data management and analysis. A spreadsheet system was established to centrally manage all enrolled patients 'basic information, laboratory tests, PET/CT/MR imaging results, postoperative pathology, and immunohistochemistry. Original PET/CT/MR images of all enrolled patients were archived. Statistical analysis was conducted using SPSS20.0 software. Qualitative data were presented as frequency using chi-square or Fisher's exact test. Quantitative data were analyzed using Kolmogorov-Smirnov normality tests, with normally distributed data expressed as (x±s). Independent samples t-tests were employed for normal distribution verification; non-normal distribution data were represented by median (upper/lower quartiles) using Wilcoxon rank sum tests. Pearson correlation analysis evaluated the correlation between lesion FAP expression levels and PET imaging. Receiver-operated characteristic (ROC) curves were used to assess diagnostic performance, calculating area under the curve (AUC), sensitivity, specificity, and thresholds for each variable. The diagnostic efficacy of PET/MRI and PET/CT was compared by Medcalc software. P <0.05 was statistically significant.
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