Objective:To explore the clinicopathologic features differences between tall cell variant of papillary thyroid cancer (TCV-PTC) and PTC with tall cell features (PTC-TCF) and the factors influencing efficacy of 131I therapy in patients with TCV-PTC and PTC-TCF. Methods:A retrospective analysis was conducted on 84 patients (28 males, 56 females, age 43.5(35.0, 55.0) years) with pathologically confirmed TCV-PTC or PTC-TCF and who were treated with 131I therapy from January 2018 to June 2023 in the Department of Nuclear Medicine, the Affiliated Hospital of Qingdao University. The patients were divided into structural incomplete response (SIR) group and non-SIR group according to 131I treatment response. Data differences were analyzed by Wilcoxon rank sum test, Fisher exact test, or Mann-Whitney U test. Variables with P<0.1 were enrolled in logistic multivariate regression analysis. The ROC curve was used to obtain the cut-off value of stimulated thyroglobulin (sTg). Results:A total of 37 patients with non-SIR and 6 patients with SIR were found in TCV-PTC group ( n=43), and 33 non-SIR and 8 SIR cases were found in PTC-TCF group ( n=41). Univariate analysis revealed that sTg differed significantly between non-SIR patients and SIR patients in TCV-PTC group ( Z=-2.81, P=0.003), while no significant differences observed for sex, age, multifocality, capsular invasion, T stage, N stage, B-Raf proto-oncogene, serine/threonine-protein kinase (BRAF) V600E mutation, initial recurrence risk, number of metastatic lymph nodes, maximum tumor diameter ( Z values: from -0.74 to -0.11, all P>0.05). In TCV-PTC group, sTg also differed significantly between non-SIR patients and SIR patients ( Z=-4.40, P<0.001), while the other clinical factors above and the proportion of tall cells showed no significant difference ( Z values: from -1.90 to -0.22, all P>0.05). The logistic regression analysis confirmed sTg as an independent risk factor of SIR in both TCV-PTC group (odds ratio ( OR) = 25.156, 95% CI: 2.245-281.812, P=0.009) and PTC-TCF group ( OR=19.214, 95% CI: 2.537-145.502, P=0.004). The ROC curve indicated that the cut-off value of sTg for predicting SIR was 20.75μg/L in TCV-PTC group and 18.55μg/L in PTC-TCF group. Conclusions:sTg is the independent risk factor for predicting the poor prognosis of patients with TCV-PTC (sTg≥20.75μg/L) and PTC-TCF (sTg≥18.55μg/L). However, other clinical characteristics show no statistical difference between TCV-PTC group and PTC-TCF group, suggesting that the invasiveness of PTC-TCF may not be lower than that of TCV-PTC, which close attention should be paid to in clinical practice.

Objective:To develop a deep learning-based segmentation model MT-UNet to automatically segment bone metastases and benign bone lesions in bone scintigraphy with SPECT/CT.Methods:A total of 93 patients (48 males and 45 females, age 28-84 years) who underwent bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from June 2023 to December 2023 were enrolled retrospectively in this study, with a total of 184 bone lesions (94 benign lesions and 90 metastatic tumors). The MT-UNet was employed to segment bone lesions in SPECT, CT and SPECT/CT images respectively. Comparative analysis with 8 segmentation models was performed. The training set and validation set were divided by using 5-fold cross-validation and transfer learning was introduced to further enhance the robustness of the model. An additional cohort of 22 patients (15 males and 7 females, age 37-87 years) who received bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from April 2023 to May 2023 were included, comprising 40 bone lesions (22 benign lesions and 18 metastatic tumors) as the test set of MT-UNet. Segmentation performance of different models was assessed using accuracy, sensitivity, specificity, AUC, intersection over union and Dice similarity coefficient (DSC). Delong test was used to compare the segmentation efficacy among different models in the test set.Results:In the validation set, MT-UNet demonstrated DSC of 0.940, 0.962, and 0.963 for SPECT, CT, and SPECT/CT bone lesion segmentation, respectively, which were outperformed other models. Following transfer learning implementation, the SPECT/CT model′s DSC was improved to 0.984. In the test set, MT-UNet maintained comparable segmentation performance to the validation set, with significant AUC differences among the three models ( Z values: from -15.42 to -9.27, all P<0.01). Compared with conventional image interpretation, MT-UNet-based segmentation reduced physician interpretation time from 164min to 102min. Conclusion:MT-UNet has shown good performance in automatic segmentation of bone metastases and benign bone lesions, and is expected to become an important part of SPECT/CT image intelligent diagnosis system for bone metastases.

Objective:To develop and validate a novel PET tracer, N-cyclohexyl-4-((2, 4-dichlorophenyl)(4-(fluoro- 18F)phenyl)methyl)piperazine-1-carboxamide ( 18F-SQKJ-2), targeting cannabinoid type 1 (CB1) receptors for diagnosing psychiatric disorders associated with fear memory. Methods:18F-SQKJ-2 was prepared using a nucleophilic substitution radiochemical synthesis method. For the CB1 receptor blocking experiment, 7 ICR mice were divided into blocking group ( n=4; rimonabant for blocking treatment) and control group 1 ( n=3; no rimonabant blocking treatment). The affinity and specificity of 18F-SQKJ-2 for CB1 receptors were analyzed based on the differences in 18F-SQKJ-2 uptake (percentage injected dose per gram of tissue, %ID/g) by various organs between two groups. The metabolic stability of 18F-SQKJ-2 in vitro was studied using animal tissue homogenates. Ten C57 mice were used to establish fear memory mouse models (fear group, n=6; control group 2, n=4), and the percentage of freezing time was compared between 2 groups. MicroPET scans were used to detect the intracranial distribution of 18F-SQKJ-2, and the relative uptake in each brain region compared to total brain uptake was calculated. Statistical analysis was conducted to compare the differences in CB1 receptor relative total brain uptake in fear-related brain regions between 2 groups. Independent-sample t test and Mann-Whitney U test were used to analyze the data. Results:18F-SQKJ-2 was successfully synthesized with a radiochemical purity ≥98.0% and a corrected radioactive yield of (12.3±6.0)%( n=4). In vitro metabolic stability experiments showed that 18F-SQKJ-2 was basically stable in the liver, blood, and brain within 60min. The CB1 receptor blocking experiment demonstrated that the uptake of 18F-SQKJ-2 in the brains of mice in blocking group was significantly lower than that in control group 1 ((0.95±0.28) vs (3.44±1.16) %ID/g; t=-3.57, P=0.023). The percentage of freezing time in fear group was significantly higher than that in control group 2 (43.28%(39.46%, 52.93%) vs 2.74%(1.52%, 4.85%); Z=-2.45, P=0.010). 18F-SQKJ-2 microPET imaging showed that the uptake of 18F-SQKJ-2 in the cerebral cortex of mice in fear group was significantly increased compared with that in control group 2 ((5.83±0.47)% vs (5.00±0.52)%; t=2.42, P=0.046). Conclusion:18F-SQKJ-2 is successfully prepared with acceptable radiochemical purity and metabolic stability, demonstrating potential for visualizing and quantifying fear memory.

Objective:To evaluate whether there is a difference between the lesion volumes detected by 18F-FDG PET/CT imaging and 11C-choline PET/CT imaging based on different threshold delineation methods in patients with nasopharyngeal carcinoma, and to recommend a more clinically appropriate threshold method with reference to lesion volume detected by enhanced MRI. Methods:A retrospective study was conducted on 37 patients(27 males, 10 females, age (51.2±11.9) years) with nasopharyngeal carcinoma diagnosed in Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, between October 2015 and May 2017. All patients underwent nasopharyngeal enhanced MRI, 18F-FDG PET/CT and 11C-choline PET/CT scans. Advantage Workstation 4.6 software was used to fuse images of the 3 imaging examinations. The lesion contour was sketched manually based on enhanced MRI sequences to obtain VMRI, and the lesion was sketched in PET images to obtain the corresponding metabolic tumor volume (MTV) by absolute threshold method, relative threshold method and background threshold method respectively. The correlation between ROIs sketched by different threshold methods and ROI in MRI was evaluated by using the Dice similarity coefficient (DSC). Friedman test or repeated measures analysis of variance (corrected by Greenhouse-Geisser) was employed to analyze the differences of MTV or DSC obtained by using 3 threshold methods. Wilcoxon signed-rank test or paired t-test was used to compare the data of different imaging methods. Results:In 18F-FDG PET/CT results, MTVs obtained by using the absolute threshold method, relative threshold method, and background threshold method were 13.21(5.47, 23.16), 10.13(5.67, 16.81), and 13.68(5.77, 25.52)mm 3, respectively, with significant differences ( χ2=17.89, P<0.001). The corresponding DSC differences for the 3 methods were also significant (0.43±0.19, 0.38±0.17 and 0.44±0.17; F=16.35, P<0.001). In 11C-choline PET/CT results, MTV differences based on the 3 threshold methods were significantly different (14.96(6.80, 32.27), 16.28(12.23, 32.47) and 18.97(14.38, 37.02)mm 3;χ2=10.45, P=0.005), and the DSC differences were also significant (0.52±0.21, 0.58±0.13 and 0.62±0.13; F=16.37, P<0.001). The differences in MTV and DSC between FDG and choline groups were also significant ( Z=-3.87, t=-5.57, both P<0.001). The differences between MTVs of 18F-FDG imaging/ 11C-choline imaging and VMRI (24.35(14.48, 36.89)mm 3) were all significantly different ( Z values: from -5.03 to -2.59, all P<0.05). Conclusions:Compared with 18F-FDG PET/CT, the preoperative 11C-choline PET/CT imaging in patients with nasopharyngeal carcinoma is closer to enhanced MRI (gold standard) in the lesion delineation. Compared with ROIs of the other 2 threshold delineation methods, the ROI obtained by the background threshold method is closer to that in enhanced MRI.

Molecular probes targeting the 18×10 3 translocator protein (TSPO) have the ability to identify and monitor tissue inflammation. Their application has expanded from neurological disorders to cardiovascular diseases (CVD), showing promising clinical translational potential in both diagnosis and therapeutic evaluation. This paper introduces the application and value of PET imaging using various generations of TSPO-targeted molecular probes in CVD, including atherosclerosis, acute myocardial infarction, large vessel vasculitis, and others.

Gliomas, with their infiltrative growth and malignant potential, present considerable therapeutic challenges. Maximal safe resection is essential for optimizing patient survival and quality of life. Despite this, existing intraoperative visualization techniques suffer from limited sensitivity and accuracy. Label-free Raman spectroscopy has emerged as a non-invasive, rapidly diagnostic, and highly accurate technique. It accurately diagnoses tumors, identifies infiltration margins, and classifies molecular subtypes, enhancing the precision of glioma surgery. This review summarizes the latest advances and applications of label-free Raman spectroscopy in glioma surgery.

Objective:To systematically evaluate the safety and efficacy of the novel fibroblast activation protein (FAP)-targeted tracer 64Cu-FAP inhibitor (FAPI)-XT117 in patients with malignant solid tumors, and to compare with 18F-FDG. Methods:This self-controlled study was conducted on fifteen patients (8 males, 7 females; age (60 ±9) years) with malignant solid tumors from the First Affiliated Hospital of Guangzhou Medical University between July 2023 and December 2023. Each subject underwent 64Cu-FAPI-XT117 PET/CT at 30, 60, and 120min post-injection and was assigned to three dose cohorts (111MBq, 148MBq, and 185MBq; 5 patients in each cohort), and safety assessments were conducted within 24h after injection. In addition, all patients underwent 18F-FDG PET/CT at 60min post-injection. Time-activity curves were generated for 64Cu-FAPI-XT117, and the dosimetry was calculated. Image quality was evaluated using a 5-point Likert scale, and the optimal injected activity and imaging time point were determined. The paired t test was used to compare differences of the lesion detection count and SUV max between 64Cu-FAPI-XT117 and 18F-FDG PET/CT. Results:64Cu-FAPI-XT117 was well tolerated, with no adverse events reported. Time-activity curves of 68Ga-FAPI-XT117 revealed prominent uptake in the uterus, while the background activity in other organs remained low, with the whole-body effective dose of (0.0084±0.0021)mSv/MBq. The optimal imaging time point for 64Cu-FAPI-XT117 PET/CT was 60min post-injection, with an optimal administered activity of 111MBq. Compared with 18F-FDG, 64Cu-FAPI-XT117 demonstrated significantly higher uptake and more lesions in lymph-node metastases (SUV max: 8.6±3.8 vs 15.3±6.8, t=2.33, P=0.048; number of lesions: 8.3±5.4 vs 15.0±6.4; t=4.21, P=0.003) and distant metastases (SUV max: 11.8±3.7 vs 20.9±7.2, t=3.66, P=0.022; number of lesions: 7.0±3.2 vs 12.4±3.7, t=2.86, P=0.046). Conclusions:64Cu-FAPI-XT117 PET/CT is well tolerated in patients with solid tumors, with a controllable radiation risk. Moreover, it outperforms 18F-FDG PET/CT in the assessment of metastases.

Objective:To explore the potential of the novel fibroblast activation protein (FAP)-targeted theranostic agent 68Ga/ 177Lu-1, 4, 7, 10-tetraazacyclododecane-1, 4, 7, 10-tetraacetic acid (DOTA)-2P (FAP inhibitor (FAPI)) 2 in microsatellite stable (MSS) colorectal cancer, and to evaluate the efficacy and underlying mechanism of 177Lu-DOTA-2P(FAPI) 2 in combination with immune checkpoint inhibitors (ICIs). Methods:This study was a randomized, parallel-group design. DOTA-2P(FAPI) 2 was labeled with 68Ga or 177Lu respectively. The binding performance of DOTA-2P(FAPI) 2 to FAP was validated through in vitro cell experiments. FAP-positive CT26-FAP tumor-bearing mouse model was constructed, and microPET imaging and biodistribution were performed. The in vivo antitumor efficacy was assessed for the 177Lu-DOTA-2P(FAPI) 2 monotherapy, α programmed death-ligand 1 (PD-L1) monotherapy, and the combination of 177Lu-DOTA-2P(FAPI) 2 with αPD-L1 therapy groups. Changes in the tumor microenvironment were analyzed using single-cell RNA sequencing to elucidate the mechanism of the combined treatment. Independent-sample t test was used to analyze data. Survival analysis was performed using the log-rank test. Results:The labeling yields of 68Ga/ 177Lu-DOTA-2P(FAPI) 2 were both >90%, with the radiochemical purities both >95%. In vitro cellular uptake and blocking assays showed that FAPI-46 significantly inhibited the binding of 68Ga-DOTA-2P(FAPI) 2 to FAP in CT26-FAP cells, with the cellular uptake values at 60min of (51.5±0.8)% and (1.0±0.3)%, respectively ( t=102.40, P<0.001). MicroPET imaging showed that the tumor uptake of 68Ga-DOTA-2P(FAPI) 2 remained stable even at 4 h post-injection, with a significantly higher uptake value compared to 68Ga-FAPI-46 ((7.3±1.6) vs (3.7±0.2) percentage activity of injection dose per gram of tissue (%ID/g); t=3.87, P=0.018). The biodistribution results indicated significant tumor uptake of 177Lu-DOTA-2P(FAPI) 2 even at 24 h post-injection ((4.30±0.52)%ID/g). The combination of 177Lu-DOTA-2P(FAPI) 2 and αPD-L1 achieved the 30-day survival rate of 100%, which was significantly superior to that of the control group (saline injection; χ2=9.53, P=0.002). Further mechanistic studies revealed that the combination therapy reprogramed the tumor microenvironment, enhanced anti-tumor intercellular communication, and activated signaling pathways such as Fas-FasL between T cells/natural killer (NK) cells and tumor cells, thereby synergistically inhibiting tumor progression. Conclusions:68Ga/ 177Lu-DOTA-2P(FAPI) 2 exhibits theranostic potential for MSS colorectal cancer. The combination of 177Lu-DOTA-2P(FAPI) 2 with ICIs may significantly prolong survival, demonstrating significant potential for clinical translation.

Objective:To compare the diagnostic efficacy of 18F-fibroblast activation protein inhibitor (FAPI) PET/MR and contrast-enhanced CT in detecting metachronous ovarian metastasis after gastric signet-ring cell carcinoma (GSRCC) surgery, and to evaluate its impact on clinical decision-making. Methods:This study employed a diagnostic test design. A retrospective analysis was conducted on 26 female patients with suspected metachronous ovarian metastasis following GSRCC resection between January 2023 and June 2025 in Renji Hospital, Shanghai Jiao Tong University School of Medicine. All patients underwent both 18F-FAPI PET/MR and contrast-enhanced CT within 2 weeks. Using histopathology or clinical imaging follow-up (≥6 months) as the reference standard, the diagnostic performance of both modalities was compared (McNemar test, Fisher exact test and Delong test), and changes in clinical management were analyzed. Results:Metachronous ovarian metastasis was confirmed in 12 patients (22 lesions). 18F-FAPI PET/MR showed significantly higher sensitivity (90.9%(20/22) vs 72.7%(16/22); χ2=4.10, P=0.043), specificity (100%(30/30) vs 50.0%(15/30); χ2=13.01, P<0.001), and accuracy (96.2%(50/52) vs 59.6%(31/52); χ2=15.43, P<0.001), compared to contrast-enhanced CT, with a significantly higher AUC (0.964 vs 0.815; Z=2.85, P=0.015). It also demonstrated superior detection of extraovarian metastases, including anastomotic recurrence, peritoneal spread, and lymph node involvement ( P values: 0.004-0.031), and identified 5 additional rare-site metastases in 3 patients that were missed by contrast-enhanced CT. Based on 18F-FAPI PET/MR findings, clinical management was adjusted in 6 patients with metastasis. Conclusion:18F-FAPI PET/MR outperforms contrast-enhanced CT in diagnosing metachronous ovarian metastasis and performing whole-body restaging in post-surgical GSRCC patients, therapy provides critical evidence for informing decision-making.

Objective:To investigate the value of a cross-combination machine learning approach in constructing a PET radiomics score (RadScore) for predicting early treatment response and prognosis in patients with primary gastrointestinal diffuse large B-cell lymphoma (PGI-DLBCL).Methods:This retrospective cohort study was conducted on 108 patients (59 males and 49 females, age (55.6±12.1) years) diagnosed with PGI-DLBCL between November 2016 and December 2021 at Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University ( n=85) and West China Hospital, Sichuan University ( n=23). Patients were divided into a training set ( n=86) and a validation set ( n=22) with the ratio of 8∶2 using stratified random sampling method. Seven machine learning models were employed to generate 49 feature selection-classification candidates, and the optimal candidate was selected to construct the RadScore, with five-fold cross-validation applied to determine the best-performing model. Logistic regression analysis was performed to identify risk factors for early treatment response, and a radiomics nomogram was developed by integrating RadScore with clinical predictors. Survival results between different groups of RadScore was compared by log-rank test. Results:Nineteen predictive features were selected from 111 radiomic features to construct the RadScore. In the training set, lactate dehydrogenase (LDH) (odds ratio ( OR)=3.53, 95% CI: 1.21-10.31, P=0.021), intestinal involvement ( OR=3.04, 95% CI: 1.04-8.88, P=0.042), total lesion glycolysis (TLG; OR=6.73, 95% CI: 2.23-20.29, P<0.001) and RadScore ( OR=15.11, 95% CI: 3.95-57.80, P<0.001) were identified as independent risk factors for predicting early treatment response. The combined model integrating RadScore, LDH, intestinal involvement, and TLG demonstrated good discriminatory ability for early treatment response (AUC=0.860 in the training set; AUC=0.902 in the validation set). Significant differences were observed in progression-free survival (PFS) and overall survival (OS) between different RadScore groups ( χ2 values: 13.92 and 8.56, both P<0.01). Conclusions:The machine learning-based RadScore may effectively predict survival outcomes in patients with PGI-DLBCL. The combined model integrating RadScore, clinical factors, and metabolic indicators can predict early treatment response in PGI-DLBCL patients.