Objective:To determine if preoperative 68Ga-fibroblast activation protein inhibitor (FAPI)-04 PET/MR could contribute to predicting pathological complete response (pCR) in patients with gastrointestinal cancer undergoing neoadjuvant immunotherapy. Methods:In this retrospective study, 35 patients (23 males, 12 females, age (59.1±7.9) years) with gastrointestinal cancer who underwent 68Ga-FAPI-04 PET/MR after receiving neoadjuvant immunotherapy between February 2021 and January 2024 were enrolled. Clinical data, PET imaging parameters including SUV, peak of SUV normalized by lean body mass (SUL peak), FAPI-positive tumor volume (FTV), and total FAPI-positive lesion burden (TLF), and pathological data were collected and analyzed. Patients were divided into pCR group and non-pCR group, and the independent-sample t test or Mann-Whitney U test was performed to compare those parameters between the 2 groups. ROC curve analysis (Delong test) was performed to evaluate the diagnostic efficiency of each parameter to predict pCR. Results:The overall pCR rate of the neoadjuvant therapy was 40.0%(14/35). In the visual evaluation, 68Ga-FAPI-04 PET was limited in predicting pCR, showing false positivity in 12 patients and false negative in 1 patent. While SUV max( t=2.50, P=0.018), SUL peak( t=3.11, P=0.004), FTV( U=3.00, P=0.030) and TLF( U=2.96, P=0.042) in non-pCR group were all higher than those in pCR group. The predictive efficiency of FTV <1.925cm 3 for pCR was better than the efficiency of PET visual evaluation ( Z=3.61, P<0.001), with the prediction accuracy of 82.86%(29/35). Conclusions:68Ga-FAPI-04 PET/MR may provide an effective clinical tool for guiding further treatment of patients with gastrointestinal cancer undergoing neoadjuvant immunotherapy. The quantitative features derived from 68Ga-FAPI-04 PET appear promising in predicting pCR, which are expected to provide a reference for avoiding surgery.

Objective:To evaluate the clinical value of 11C-methyl- L-methionine (MET) PET/MR in the differential diagnosis between neoplastic and non-neoplastic brain lesions. Methods:From July 2017 to May 2022, a total of 34 patients (19 males, 15 females, age 8-81 years) who received 11C-MET PET/MR imaging for suspected brain tumors in Union Hospital, Tongji Medical College, Huazhong University of Science and Technology were retrospectively enrolled. Postoperative pathological or clinical follow-up results were used as the gold standard. Diagnostic performance of 11C-MET PET/MR and contrast-enhanced MRI was evaluated by ROC curve analysis and Delong test, as well as the diagnostic performance of PET metabolic parameters (SUV and target to background ratio (TBR)), MRI multi-sequence parameters (cerebral blood flow (CBF), relative CBF (rCBF), apparent diffusion coefficient (ADC), relative ADC (rADC), choline/creatine (Cho/Cr) and choline/ N-acetylaspartate (Cho/NAA)) and their combination. Results:A total of 35 lesions of 34 patients were enrolled, including 12 (34.3%) non-neoplastic lesions and 23(65.7%) neoplastic lesions. The diagnostic sensitivity, specificity, and accuracy for 11C-MET PET/MR were 91.3%(21/23), 12/12, and 94.3%(33/35), in contrast to 16/18, 2/10, and 64.3%(18/28) for contrast-enhanced MRI. Maximum TBR (TBR max) showed the highest discriminative value (AUC=0.877, 95% CI: 0.692-1.000). The combination of TBR max, minimum ADC (ADC min), rCBF, and Cho/NAA could achieve a higher diagnostic performance (AUC=0.918, 95% CI: 0.816-1.000), although the difference was not statistically significant ( Z=-0.42, P=0.676). Conclusion:Multiple quantitative parameters of 11C-MET PET/MR are beneficial to distinguish neoplastic from non-neoplastic brain lesions, and their combination may improve the diagnostic confidence.

Ovarian cancer is the most lethal malignancy affecting the female reproductive system. Pharmacological inhibitors targeting CDK4/6 have demonstrated promising efficacy across various cancer types. However, their clinical benefits in ovarian cancer patients fall short of expectations, with only a subset of patients experiencing these advantageous effects. This study aims to provide further clinical and biological evidence for antineoplastic effects of a CDK4/6 inhibitor (TQB4616) in ovarian cancer and explore underlying mechanisms involved. Patient-derived ovarian cancer organoid models were established to evaluate the effectiveness of TQB3616. Potential key genes related to TQB3616 sensitivity were identified through RNA-seq analysis, and TRIM4 was selected as a candidate gene for further investigation. Subsequently, co-immunoprecipitation and GST pull-down assays confirmed that TRIM4 binds to hnRNPDL and promotes its ubiquitination through RING and B-box domains. RIP assay demonstrated that hnRNPDL binded to CDKN2C isoform 2 and suppressed its expression by alternative splicing. Finally, in vivo studies confirmed that the addition of siTRIM4 significantly improved the effectiveness of TQB3616. Overall, our findings suggest that TRIM4 modulates ubiquitin-mediated degradation of hnRNPDL and weakens sensitivity to CDK4/6 inhibitors in ovarian cancer treatment. TRIM4 may serve as a valuable biomarker for predicting sensitivity to CDK4/6 inhibitors in ovarian cancer.
Humans ; Female ; Ovarian Neoplasms/pathology* ; Animals ; Tripartite Motif Proteins/genetics* ; Mice ; Cyclin-Dependent Kinase 4/antagonists & inhibitors* ; Cell Line, Tumor ; Cyclin-Dependent Kinase 6/antagonists & inhibitors* ; Protein Kinase Inhibitors/pharmacology* ; Ubiquitin/metabolism* ; Xenograft Model Antitumor Assays ; Ubiquitination ; Antineoplastic Agents/pharmacology*

Objective:To determine if preoperative 68Ga-fibroblast activation protein inhibitor (FAPI)-04 PET/MR could contribute to predicting pathological complete response (pCR) in patients with gastrointestinal cancer undergoing neoadjuvant immunotherapy. Methods:In this retrospective study, 35 patients (23 males, 12 females, age (59.1±7.9) years) with gastrointestinal cancer who underwent 68Ga-FAPI-04 PET/MR after receiving neoadjuvant immunotherapy between February 2021 and January 2024 were enrolled. Clinical data, PET imaging parameters including SUV, peak of SUV normalized by lean body mass (SUL peak), FAPI-positive tumor volume (FTV), and total FAPI-positive lesion burden (TLF), and pathological data were collected and analyzed. Patients were divided into pCR group and non-pCR group, and the independent-sample t test or Mann-Whitney U test was performed to compare those parameters between the 2 groups. ROC curve analysis (Delong test) was performed to evaluate the diagnostic efficiency of each parameter to predict pCR. Results:The overall pCR rate of the neoadjuvant therapy was 40.0%(14/35). In the visual evaluation, 68Ga-FAPI-04 PET was limited in predicting pCR, showing false positivity in 12 patients and false negative in 1 patent. While SUV max( t=2.50, P=0.018), SUL peak( t=3.11, P=0.004), FTV( U=3.00, P=0.030) and TLF( U=2.96, P=0.042) in non-pCR group were all higher than those in pCR group. The predictive efficiency of FTV <1.925cm 3 for pCR was better than the efficiency of PET visual evaluation ( Z=3.61, P<0.001), with the prediction accuracy of 82.86%(29/35). Conclusions:68Ga-FAPI-04 PET/MR may provide an effective clinical tool for guiding further treatment of patients with gastrointestinal cancer undergoing neoadjuvant immunotherapy. The quantitative features derived from 68Ga-FAPI-04 PET appear promising in predicting pCR, which are expected to provide a reference for avoiding surgery.

Objective:To evaluate the clinical value of 11C-methyl- L-methionine (MET) PET/MR in the differential diagnosis between neoplastic and non-neoplastic brain lesions. Methods:From July 2017 to May 2022, a total of 34 patients (19 males, 15 females, age 8-81 years) who received 11C-MET PET/MR imaging for suspected brain tumors in Union Hospital, Tongji Medical College, Huazhong University of Science and Technology were retrospectively enrolled. Postoperative pathological or clinical follow-up results were used as the gold standard. Diagnostic performance of 11C-MET PET/MR and contrast-enhanced MRI was evaluated by ROC curve analysis and Delong test, as well as the diagnostic performance of PET metabolic parameters (SUV and target to background ratio (TBR)), MRI multi-sequence parameters (cerebral blood flow (CBF), relative CBF (rCBF), apparent diffusion coefficient (ADC), relative ADC (rADC), choline/creatine (Cho/Cr) and choline/ N-acetylaspartate (Cho/NAA)) and their combination. Results:A total of 35 lesions of 34 patients were enrolled, including 12 (34.3%) non-neoplastic lesions and 23(65.7%) neoplastic lesions. The diagnostic sensitivity, specificity, and accuracy for 11C-MET PET/MR were 91.3%(21/23), 12/12, and 94.3%(33/35), in contrast to 16/18, 2/10, and 64.3%(18/28) for contrast-enhanced MRI. Maximum TBR (TBR max) showed the highest discriminative value (AUC=0.877, 95% CI: 0.692-1.000). The combination of TBR max, minimum ADC (ADC min), rCBF, and Cho/NAA could achieve a higher diagnostic performance (AUC=0.918, 95% CI: 0.816-1.000), although the difference was not statistically significant ( Z=-0.42, P=0.676). Conclusion:Multiple quantitative parameters of 11C-MET PET/MR are beneficial to distinguish neoplastic from non-neoplastic brain lesions, and their combination may improve the diagnostic confidence.

Alzheimer's disease(AD)is a common chronic neurodegenerative disorder.PET,a non-invasive molecular imaging technique,plays a significant role in diagnosing AD by revealing characteristic pathological changes.Meanwhile,radiomics technology can extract a vast amount of information that is difficult to recognize by the naked eye,and provides an objective and quantitative method for analyzing PET image features of AD patients.This article introduces the general steps of radiomics and common tools for PET image analysis applied in the assessment of AD.It also reviews the current research status of radiomics based on PET imaging in the diagnosis and prognosis prediction of AD,focusing on amyloid β,tau proteins and cerebral glucose metabolism.Furthermore,the article discusses future challenges in this field.

Objective:To evaluate the diagnostic efficacy of the multiparametric MRI (mpMRI) deep learning artificial intelligence (AI) analysis system combined with 68Ga-prostate specific membrane antigen (PSMA) PET for prostate cancer. Methods:Data of 103 patients (age: 45-85 years) who underwent 68Ga-PSMA PET/MR at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology from May 2018 to October 2023 for suspected or confirmed prostate cancer were retrospectively collected. ROI was delineated to measure SUV max of primary tumor or prostate, and a deep learning AI system was applied to analyze MR images of the prostate. The diagnostic efficacies of T 2 weighted imaging (WI), diffusion WI (DWI), mpMRI, PET SUV max, and PET/MR for prostate cancer were assessed, with using the pathological results as the gold standard. Results:Among 103 patients, 82 cases (79.61%) were with prostate cancer. PET unimodality demonstrated the best specificity (100%, 21/21), positive predictive value (100%, 58/58), and AUC (0.860, 95% CI: 0.777-0.920). The mpMRI AI analysis provided rapid diagnostic results and the sensitivity and accuracy were improved by combining with PET (sensitivities of PET, mpMRI and the combination of the two were 70.73%(58/82), 86.59%(71/82), and 92.68%(76/82), respectively; the accuracies were 76.70%(79/103), 81.55%(84/103) and 86.41%(89/103), respectively). Among 44 patients with negative PET, 30 patients received an accurate diagnosis when the results of mpMRI AI analysis were added. Conclusions:68Ga-PSMA PET demonstrates good specificity for prostate cancer and mpMRI AI analysis is time-saving. The combined application improves the diagnostic sensitivity and accuracy, which provides a valuable tool for 68Ga-PSMA PET/MR image analysis.

Objective:To explore the impact of different segmentation methods on differential diagnostic efficiency of 18F-FDG PET/MR radiomics to distinguish Parkinson′s disease (PD) from multiple system atrophy (MSA). Methods:From December 2017 to June 2019, 90 patients (60 with PD and 30 with MSA; 37 males, 53 females; age (55.8±9.5) years) who underwent 18F-FDG PET/MR in Union Hospital, Tongji Medical College, Huazhong University of Science and Technology were retrospectively collected. Patients were randomized to training set and validation set in a ratio of 7∶3. The bilateral putamina and caudate nuclei, as the ROIs, were segmented by automatic segmentation of brain regions based on anatomical automatic labeling (AAL) template and manual segmentation using ITK-SNAP software. A total of 1 172 radiomics features were extracted from T 1 weighted imaging (WI) and 18F-FDG PET images. The minimal redundancy maximal relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) algorithm were used for features selection and radiomics signatures (Radscore) construction, with 10-fold cross-validation for preventing overfitting. The diagnostic performance of the models was assessed by ROC curve analysis, and the differences between models were calculated by Delong test. Results:There were 63 cases in training set (42 PD, 21 MSA) and 27 cases in validation set (18 PD, 9 MSA). The Radscore values were significantly different between the PD group and the MSA group in all training set and validation set of radiomics models ( 18F-FDG_Radscore and T 1WI_Radscore) based on automatic or manual segmentation methods ( z values: from -5.15 to -2.83, all P<0.05). ROC curve analysis showed that AUCs of 18F-FDG_Radscore and T 1WI_Radscore based on automatic segmentation in training and validation sets were 0.848, 0.840 and 0.892, 0.877, while AUCs were 0.900, 0.883 and 0.895, 0.870 based on manual segmentation. There were no significant differences in training and validation sets between Radiomics models based on different segmentation methods ( z values: 0.04-0.77, all P>0.05). Conclusions:The 18F-FDG PET/MR radiomics models based on different segmentation methods achieve promising diagnostic efficacy for distinguishing PD from MSA. The radiomics analysis based on automatic segmentation shows greater potential and practical value in the differential diagnosis of PD and MSA in view of the advantages including time-saving, labor-saving, and high repeatability.

Objective:To investigate the diagnostic and prognostic value of 68Ga-fibroblast activation protein inhibitor (FAPI) PET for hepatobiliary malignancies. Methods:From July 2020 to February 2023, 33 patients (23 males, 10 females; age (55.4±13.5) years) with suspected or confirmed liver or biliary tract malignancies who underwent 68Ga-FAPI PET in Union Hospital, Tongji Medical College, Huazhong University of Science and Technology were retrospectively analyzed. PET images were evaluated by 3 experienced nuclear medicine physicians, and the results of biopsy or postoperative pathology, clinical and imaging follow-up were used as the gold standard. One-way analysis of variance and least significant difference t test were used to compare the differences among groups. Survival analysis was performed using Kaplan-Meier curves and the log-rank test. Results:Of 33 patients, 14 performed PET for initial diagnosis and staging, and 19 for restaging. There were 14 patients with hepatocellular carcinoma (HCC), 13 patients with cholangiocarcinoma (CCA), and 6 patients with gallbladder carcinoma (GBC). The primary tumor of HCC, CCA and GBC all showed significant 68Ga-FAPI uptake, with no statistically significant difference in SUV max among groups ( F=1.58, P=0.250). The sensitivities of 68Ga-FAPI PET for initial diagnosis and restaging of hepatobiliary malignancies were 14/14 and 15/15, respectively. Compared with conventional imaging, 68Ga-FAPI PET changed the diagnosis and staging in 29.2%(7/24) patients. The treatment strategy was changed in 30.3%(10/33) patients with malignant tumors due to 68Ga-FAPI PET findings. Follow-up showed 22 cases survived and 11 cases died, with the overall survival of 355.56(80.00, 516.97) d, and 1- and 2-year survival rates were 68.2% and 57.9%, respectively. Semi-quantitative 68Ga-FAPI PET parameters such as SUV max, target-liver ratio (TLR), and target-blood ratio (TBR) had no significant prognostic value, but the prognosis of the group without distant metastases diagnosed by 68Ga-FAPI PET was significantly better than that of the group with distant metastasis ( P=0.032). Conclusion:68Ga-FAPI PET has high sensitivity for the diagnosis of hepatobiliary malignancies, which can help guide treatment decisions and prognosis evaluation.

Objective:To study whether Bayesian penalized likelihood (BPL) and its optimized reconstruction algorithm can improve the reconstructed image quality of low count total-body PET.Methods:Eight patients (5 males, 3 females, age (67.2±6.3) years) who underwent hybrid 18F-FDG PET/MR total-body scans at Department of Nuclear Medicine in Union Hospital, Tongji Medical College, Huazhong University of Science and Technology were collected retrospectively from January to June in 2023. Total-body PET/MR images of them were included and list-mode data were reconstructed with four methods, namely 25% counts conventional reconstruction (group 1), 100% counts conventional reconstruction (group 2), 25% counts BPL reconstruction (group 3), and 25% counts optimized BPL reconstruction (group 4). At last, 32 total-body PET images were obtained. SUV max and SUV mean in different ROIs and tumor metabolic volume (MTV) were measured. Total lesion glycolysis (TLG) and parameters of image quality including the ratio of lesion to background (L/B) and image signal-to-noise ratio (SNR) were calculated. Then the differences in all the parameters among the four groups were analyzed by repeated measures analysis of variance and Friedman test. Quantitative differences between BPL reconstruction and optimized BPL with the 100% counts conventional reconstruction were compared respectively by using the Bland-Altman (BA) plot. Results:For the inter-group comparison, except for SUV mean in the muscle ( F=0.38, P=0.767), SUV max and SUV mean in other ROIs were statistically different ( F values: 8.15-36.08, χ2=18.15, all P<0.01), as well as MTV and L/B ( χ2 values: 10.65, 13.35, P values: 0.014, 0.004), but not for TLG ( χ2=4.95, P=0.175) or SNR ( F=2.64, P=0.076). For the pairwise comparison, the differences between group 2 and group 3 were the most significant (all P<0.05). Compared with group 2, there were no significant differences for SUV max and SUV mean of the cerebellar cortex and lesions in group 4 (all P>0.05), as well as MTV and L/B (both P>0.05). In addition, compared with group 1, SUV max of liver and muscle in group 2 were decreased (both P<0.05), while there were no significant differences in group 4 (all P>0.05). BA plots showed that the differences of SUV, MTV, and TLG between group 4 and group 2 were smaller obviously than those between group 3 and group 2. Conclusion:BPL reconstruction can improve low focus detection sensitivity induced by low counts, but it will cause significant changes for PET quantification, which can be solved by optimized BPL reconstruction.