A cutting-edge 68Ga-labeled bicyclic peptide PET molecular probe for noninvasive assessment of Nectin4 expression.

The diagnosis and treatment of triple negative breast cancer (TNBC) are huge challenges due to the lack of identifiable molecular targets. The high expression of Nectin4 in a variety of tumors, including TNBC, is associated with the occurrence, invasion, progression and poor prognosis of tumors. Therefore, Nectin4 is an emerging biomarker for the diagnosis and treatment of TNBC. A PET imaging method to non-invasively quantify Nectin4 expression levels may aid in TNBC diagnosis and classification. In this study, a novel bicyclic peptide molecular probe [68Ga]Ga-DN68 was used to evaluate the expression of Nectin4 in tumors. The radiolabeling rate of [68Ga]Ga-DN68 was over 97 %, while maintaining more than 99 % radiochemical purity. In vitro experiments showed that [68Ga]Ga-DN68 could effectively target Nectin4 in tumor cells, and the cellular uptake of MC38-Nectin4 cells (Nectin4+) was significantly higher than that of MC38 cells (Nectin4-). Biodistribution and PET imaging studies consistently showed that [68Ga]Ga-DN68 was specifically accumulated in MC38-Nectin4 and MDA-MB-468 tumors, which was significantly higher than that of MC38. When co-injected with cold DN68, the specific accumulation could block the tumor uptake of MDA-MB-468. Notably, the signal-to-noise ratio at the tumor site gradually increased over time, reaching a peak at 1 h. These results strongly suggest that [68Ga]Ga-DN68 has broad application prospects as a PET tracer in TNBC imaging.

A novel 68Ga-labeled cyclic peptide molecular probe based on the computer-aided design for noninvasive imaging of PD-L1 expression in tumors.

Programmed death-ligand 1 (PD-L1) serves as a crucial biomarker for guiding the screening of cancer patients and the stratification of immunotherapy. However, due to the high heterogeneity of tumors, the current gold standard for detecting PD-L1 expression (immunohistochemistry) fails to comprehensively evaluate the overall PD-L1 expression levels in the body. Fortunately, the use of PD-L1 targeted radiotracers enables quantitative, real-time, and noninvasive assessment of PD-L1 expression levels and dynamics in tumors. Notably, analyzing the binding mode between the precursor and the target protein to find linker binding sites that do not affect the activity of the target molecule can greatly enhance the successful development of molecular probes. This study introduced a groundbreaking cyclic peptide molecular probe called 68Ga-DOTA-PG1. It was derived from the BMS-71 cyclic peptide and was specifically designed to evaluate the expression of PD-L1 in tumors. The radiolabeling yield of 68Ga-DOTA-PG1 surpassed 97% while maintaining a radiochemical purity of over 99%. In vitro experiments demonstrated the effective targeting of PD-L1 in tumor cells by 68Ga-DOTA-PG1, with significantly higher cellular uptake observed in A375-hPD-L1 cells (PD-L1 + ) compared to A375 cells (PD-L1-). Biodistribution and PET imaging studies consistently showed specific accumulation of 68Ga-DOTA-PG1 in A375-hPD-L1 tumors, with a maximum uptake of 11.06 ± 1.70% ID/g at 2 h, significantly higher than the tumor uptake in A375 cells (1.70 ± 0.17% ID/g). These results strongly indicated that 68Ga-DOTA-PG1 held great promise as a PET radiotracer for imaging PD-L1-positive tumors.

Assessment of androgen receptor expression in breast cancer patients using 18 F-FDG PET/CT radiomics and clinicopathological characteristics.

OBJECTIVE: In the present study, we mainly aimed to predict the expression of androgen receptor (AR) in breast cancer (BC) patients by combing radiomic features and clinicopathological factors in a non-invasive machine learning way. MATERIALS AND METHODS: A total of 48 BC patients, who were initially diagnosed by 18F-FDG PET/CT, were retrospectively enrolled in this study. LIFEx software was used to extract radiomic features based on PET and CT data. The most useful predictive features were selected by the LASSO (least absolute shrinkage and selection operator) regression and t-test. Radiomic signatures and clinicopathologic characteristics were incorporated to develop a prediction model using multivariable logistic regression analysis. The receiver operating characteristic (ROC) curve, Hosmer-Lemeshow (H-L) test, and decision curve analysis (DCA) were conducted to assess the predictive efficiency of the model. RESULTS: In the univariate analysis, the metabolic tumor volume (MTV) was significantly correlated with the expression of AR in BC patients (p < 0.05). However, there only existed feeble correlations between estrogen receptor (ER), progesterone receptor (PR), and AR status (p = 0.127, p = 0.061, respectively). Based on the binary logistic regression method, MTV, SHAPE_SphericityCT (CT Sphericity from SHAPE), and GLCM_ContrastCT (CT Contrast from grey-level co-occurrence matrix) were included in the prediction model for AR expression. Among them, GLCM_ContrastCT was an independent predictor of AR status (OR = 9.00, p = 0.018). The area under the curve (AUC) of ROC in this model was 0.832. The p-value of the H-L test was beyond 0.05. CONCLUSIONS: A prediction model combining radiomic features and clinicopathological characteristics could be a promising approach to predict the expression of AR and noninvasively screen the BC patients who could benefit from anti-AR regimens.

Pilot study of a novel nanobody 68 Ga-NODAGA-SNA006 for instant PET imaging of CD8+ T cells.

PURPOSE: Positron emission tomography (PET) with specific diagnostic probes for quantifying CD8+ T cells has emerged as a powerful technique for monitoring the immune response. However, most CD8+ T cell radiotracers are based on antibodies or antibody fragments, which are slowly cleared from circulation. Herein, we aimed to develop and assess 68 Ga-NODAGA-SNA006 for instant PET (iPET) imaging of CD8+ T cells. METHODS: A novel nanobody without a hexahistidine (His6) tag, SNA006-GSC, was designed, site-specifically conjugated with NODAGA-maleimide and radiolabelled with 68 Ga. The PET imaging profiles of 68 Ga-NODAGA-SNA006 were evaluated in BALB/c MC38-CD8+/CD8- tumour models and cynomolgus monkeys. Three volunteers with lung cancer underwent whole-body PET/CT imaging after 68 Ga-NODAGA-SNA006 administration. The biodistribution, pharmacokinetics and dosimetry of patients were also investigated. In addition, combined with immunohistochemistry (IHC), the quantitative performance of the tracer for monitoring CD8 expression was evaluated in BALB/c MC38-CD8+/CD8- and human subjects. RESULTS: 68 Ga-NODAGA-SNA006 was prepared with RCP > 98% and SA > 100 GBq/µmol. 68 Ga-NODAGA-SNA006 exhibited specific uptake in MC38-CD8+ xenografts tumours, CD8-rich tissues (such as the spleen) in monkeys and CD8+ tumour lesions in patients within 1 h. Fast washout from circulation was observed in three volunteers (t1/2 < 20 min). A preliminary quantitative linear relationship (R2 = 0.9668, p < 0.0001 for xenografts and R2 = 0.7924, p = 0.0013 for lung patients) appeared between 68 Ga-NODAGA-SNA006 uptake and CD8 expression. 68 Ga-NODAGA-SNA006 was well tolerated by all patients. CONCLUSION: 68 Ga-NODAGA-SNA006 PET imaging can instantly quantify CD8 expression with an ideal safety profile and is expected to be important for dynamically tracking CD8+ T cells and monitoring immune responses for individualised cancer immunotherapy. TRIAL REGISTRATION: NCT05126927 (19 November 2021, retrospectively registered).

Review: Radionuclide Molecular Imaging Targeting HER2 in Breast Cancer with a Focus on Molecular Probes into Clinical Trials and Small Peptides.

As the most frequently occurring cancer worldwide, breast cancer (BC) is the leading cause of cancer-related death in women. The overexpression of HER2 (human epidermal growth factor receptor 2) is found in about 15% of BC patients, and it is often associated with a poor prognosis due to the effect on cell proliferation, migration, invasion, and survival. As a result of the heterogeneity of BC, molecular imaging with HER2 probes can non-invasively, in real time, and quantitatively reflect the expression status of HER2 in tumors. This will provide a new approach for patients to choose treatment options and monitor treatment response. Furthermore, radionuclide molecular imaging has the potential of repetitive measurements, and it can help solve the problem of heterogeneous expression and conversion of HER2 status during disease progression or treatment. Different imaging probes of targeting proteins, such as monoclonal antibodies, antibody fragments, nanobodies, and affibodies, are currently in preclinical and clinical development. Moreover, in recent years, HER2-specific peptides have been widely developed for molecular imaging techniques for HER2-positive cancers. This article summarized different types of molecular probes targeting HER2 used in current clinical applications and the developmental trend of some HER2-specific peptides.

Diagnostic Value and Clinical Significance of Combined Detection of Serum Markers CYFRA21-1, SCC Ag, NSE, CEA and ProGRP in Non-Small Cell Lung Carcinoma.

BACKGROUND: The aim of the study is to explore the diagnostic value and clinical significance of combined detection of serum markers CYFRA21-1, SCC Ag, NSE, CEA and ProGRP in non-small cell lung cancer. METHODS: CYFRA21-1, SCC Ag, NSE, CEA, and ProGRP levels of 113 patients with lung cancer, 110 patients with benign lung diseases, and 90 healthy volunteers were detected by electrochemiluminescence assay. The correlations between positive expressions and clinical and pathological parameters were analyzed. The diagnostic values of CYFRA21-1, SCC, NSE, CEA, and ProGRP were evaluated by plotting ROC curves. RESULTS: The positive expression rates of CYFRA21-1, SCC Ag, NSE, CEA, and ProGRP in the lung cancer group significantly exceeded those of benign lung disease and healthy groups (p < 0.05). In the lung cancer group, CYFRA21-1, SCC Ag, NSE, CEA, and ProGRP levels significantly varied in patients with different degrees of invasion and clinical stages in the presence/absence of lymph node metastasis (p < 0.05). AUCs of diagnosis by CYFRA21-1, ProGRP, CEA, SCC Ag, and NSE were 0.737 [95% CI (0.582 - 0.893)], 0.829 [95% CI (0.742 - 0.915)], 0.848 [95% CI (0.739 - 0.956)], 0.758 [95% CI (0.642 - 0.874)], and 0.857 [95% CI (0.764 - 0.951)], respectively, with the optimal cutoff values of 11.38 µg/mL, 103.47 pg/mL, 5.78 ng/mL, 3.92 ng/mL, and 13.36 ng/mL, respectively. The combined diagnostic sensitivity and accuracy both exceeded those based on individual markers, but the combined diagnostic specificity was slightly lower than those using CYFRA21-1, SCC Ag, and ProGRP alone. CONCLUSIONS: CYFRA21-1, SCC Ag, NSE, CEA, and ProGRP levels of patients with lung cancer increased abnormally. The combined detection effectively improved diagnostic accuracy and sensitivity.

Reference Intervals of Cytokeratin-19 Fragment (CYFRA 21-1) in Healthy Adults in China.

BACKGROUND: The reference intervals for serum cytokeratin-19 fragment (CYFRA 21-1) have not been established in Chinese population. This study aimed to measure serum CYFRA 21-1 levels in healthy Chinese subjects. METHODS: This cross-sectional, four-center study in two Chinese provinces enrolled participants (aged 18 - 85 years) with normal liver/kidney function and normal results for routine blood tests/urinalysis. Serum CYFRA 211 level was measured by ARCHITECT immunoassay (Abbott Diagnostics). RESULTS: The study included 3,366 participants. The median (interquartile range) value for serum CYFRA 21-1 level was 1.38 (1.00 - 1.89) ng/mL and tended to increase with age. The upper limit of the 97.5th percentile was 3.55 ng/mL and tended to increase with age. Serum CYFRA 21-1 median level varied between the four centers from 1.22 (0.89, 1.71) to 1.55 (1.12, 2.18) ng/mL, while the 97.5th percentile varied from 3.24 to 4.09 ng/mL. CYFRA 21-1 level correlated weakly with age and creatinine level. CONCLUSIONS: These new data can help to establish the 'normal range' of serum CYFRA 21-1 in people in China.

Application of 18F-FDG PET/CT imaging radiomics in the differential diagnosis of single-nodule pulmonary metastases and second primary lung cancer in patients with colorectal cancer.

OBJECTIVE: It is crucially essential to differentially diagnose single-nodule pulmonary metastases (SNPMs) and second primary lung cancer (SPLC) in patients with colorectal cancer (CRC), which has important clinical implications for treatment strategies. In this study, we aimed to establish a feasible differential diagnosis model by combining 18F-fluorodeoxyglucose positron-emission tomography (18F-FDG PET) radiomics, computed tomography (CT) radiomics, and clinical features. MATERIALS AND METHODS: CRC patients with SNPM or SPLC who underwent 18F-FDG PET/CT from January 2013 to July 2022 were enrolled in this retrospective study. The radiomic features were extracted by manually outlining the lesions on PET/CT images, and the radiomic modeling was realized by various screening methods and classifiers. In addition, clinical features were analyzed by univariate analysis and logistic regression (LR) analysis to be included in the combined model. Finally, the diagnostic performances of these models were illustrated by the receiver operating characteristic (ROC) curves and the area under the curve (AUC). RESULTS: We studied data from 61 patients, including 36 SNPMs and 25 SPLCs, with an average age of 65.56 ± 10.355 years. Spicule sign and ground-glass opacity (GGO) were significant independent predictors of clinical features (P = 0.012 and P < 0.001, respectively) to build the clinical model. We achieved a PET radiomic model (AUC = 0.789), a CT radiomic model (AUC = 0.818), and a PET/CT radiomic model (AUC = 0.900). The PET/CT radiomic models were combined with the clinical model, and a well-performing model was established by LR analysis (AUC = 0.940). CONCLUSIONS: For CRC patients, the radiomic models we developed had good performance for the differential diagnosis of SNPM and SPLC. The combination of radiomic and clinical features had better diagnostic value than a single model.

Prognostic significance of diffuse increased fluorine-18-fluorodeoxyglucose (18F-FDG) uptake within the reticuloendothelial system in lymphoma patients.

Background: As constituents of the reticuloendothelial system, the spleen and bone marrow (BM) have been recognized as integral components of the systemic inflammatory response in cancer contexts, thereby serving as predictive indicators for assessing cancer prognosis. Fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) has attained widespread utilization for staging, assessing treatment response, and prognostication in lymphoma patients. Several investigations have proposed that focal increased 18F-FDG uptake in the BM or spleen may correlate with malignant involvement in lymphoma. However, scant data exist regarding the implications of diffuse BM and splenic uptake. This study aimed to explore the relationships between metabolic parameters of the spleen and BM on 18F-FDG PET/CT and inflammatory markers, and to assess their prognostic value in patients with lymphoma. Methods: A retrospective analysis was conducted on 118 patients newly diagnosed with malignant lymphoma, who underwent 18F-FDG PET/CT and exhibited diffuse increased splenic or BM uptake in 18F-FDG PET/CT imaging. The mean standardized uptake value (SUV) of the spleen, BM, and liver was calculated. The association between metabolic variables and systemic inflammatory markers was investigated, and the prognostic significance of clinicopathological and PET parameters was assessed using overall survival (OS) and progression-free survival (PFS). Results: A statistically significant correlation was found between the spleen-to-liver SUV ratio (SLR) and inflammatory markers such as C-reactive protein (r=0.264, P=0.007) and platelet-to-lymphocyte ratio (r=0.227, P=0.021). No significant correlation was observed between BM-to-liver SUV ratio (BLR) and hematologic parameters, while concordance analysis revealed a fair agreement between BLR and bone marrow biopsy (BMB) (Cohen's Kappa-κ =0.271, P=0.002). In patients with aggressive non-Hodgkin lymphoma, both SLR [P=0.017, HR 2.715, 95% confidence interval (CI): 0.875-8.428] and BLR (P=0.044, HR 0.795, 95% CI: 0.348-1.813) were significantly linked to OS, while SLR (P=0.019, HR 2.223, 95% CI: 1.139-4.342) emerged as a significant prognostic factor for PFS. Conclusions: This study highlighted that diffuse increased splenic 18F-FDG uptake in lymphoma patients was closely associated with inflammation, whereas diffuse BM uptake was likely attributable to BM infiltration rather than inflammatory changes. Furthermore, both parameters held promise as prognostic indicators for patients with aggressive lymphoma.

The relationship between sarcopenia and metabolic parameters of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and the prognostic value of sarcopenia in early-stage non-small cell lung cancer.

Background: Patients with lung cancer face a heightened risk of developing sarcopenia. Despite this known risk, the impact of sarcopenia on the long-term prognosis of lung cancer patients, specifically concerning progression-free survival (PFS) and overall survival (OS), remains unclear. The primary objective of our study was to examine the correlation between metabolic parameters derived from 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and sarcopenia, as well as the prognostic value of sarcopenia in patients with surgically resected early-stage non-small cell lung cancer (NSCLC). Methods: In this retrospective cross-sectional study, we analyzed 187 NSCLC patients who underwent 18F-FDG PET/CT at the First Affiliated Hospital of Soochow University between March 2019 and October 2023. Patients were divided into two groups based on the presence (n=46) or absence (n=141) of sarcopenia. The correlation between sarcopenia, metabolic parameters, and patient characteristics was evaluated using chi-square and Mann-Whitney U tests. Survival analyses, including PFS and OS, were conducted using Kaplan-Meier analysis and Cox proportional hazards regression. Based on sarcopenia, metabolic parameters and patient characteristics, patients were classified into high-risk (n=28), intermediate-risk (n=121), and low-risk (n=38) groups. Results: Our analysis identified gender, body mass index (BMI), psoas Hounsfield unit (HU), and maximum standardized uptake value of the psoas major muscle (SUVmax-Muscle) as independent predictors of sarcopenia (P<0.05 for all). A nomogram model, utilizing these parameters, was constructed to predict sarcopenia. Survival analysis further demonstrated that total lesion glycolysis [hazard ratio (HR) =2.499; 95% confidence interval (CI): 2.014-3.267; P=0.016], sarcopenia (HR =3.323; 95% CI: 1.748-6.316; P<0.001), and programmed death ligand-1 (PD-L1) expression (HR =0.093; 95% CI: 0.012-0.698; P=0.021) emerged as independent predictors of OS in early-stage NSCLC. Notably, patients categorized as high-risk, characterized by elevated total lesion glycolysis, presence of sarcopenia, and PD-L1 positivity, exhibited a significantly poorer prognosis compared to the intermediate-risk (P<0.05) and low-risk groups (P<0.05). Conclusions: Our findings indicated an inverse relationship between SUVmax-Muscle or psoas HU with the incidence of sarcopenia in NSCLC patients. Additionally, total lesion glycolysis, sarcopenia, and PD-L1 expression were identified as independent prognostic factors for OS in early-stage NSCLC. The risk stratification model, incorporating total lesion glycolysis, sarcopenia, and PD-L1 expression, assumed a pivotal role in guiding personalized therapy decisions and post-treatment monitoring.

Imaging and Monitoring HER2 Expression in Tumors during HER2 Antibody-Drug Conjugate Therapy Utilizing a Radiolabeled Site-Specific Single-Domain Antibody Probe: 68Ga-NODAGA-SNA004-GSC.

The overexpression of HER2 is pivotal in the initiation and progression of breast cancer. Developing HER2-targeted radiotracers is crucial for noninvasive assessment of HER2 expression, patient selection for HER2-targeted therapy, monitoring treatment response, and identifying resistance. Here, we reported a nonsite-specific coupled radiotracer, 68Ga-NOTA-SNA004-His6, and a site-specific coupled radiotracer, 68Ga-NODAGA-SNA004-GSC, based on a novel HER2 nanobody, SNA004. Both radiotracers exhibited high affinity, specific targeting, and rapid clearance in vitro and in vivo. Additionally, these tracers and trastuzumab showed noncompetitive binding to HER2. Compared to 68Ga-NOTA-SNA004-His6, 68Ga-NODAGA-SNA004-GSC demonstrated significantly reduced renal and liver uptake. PET/CT imaging with 68Ga-NODAGA-SNA004-GSC sensitively detected the responsiveness of various tumor models to trastuzumab and its antibody-drug conjugates (ADCs). Overall, the site-specific coupled radiotracer 68Ga-NODAGA-SNA004-GSC offered significant advantages in biodistribution and signal-to-noise ratio, making it a valuable tool for monitoring HER2 expression levels before, during, and after trastuzumab and ADC treatment.

Analysis of Positive Results of 18F-FDG PET/CT Imaging after Hematopoietic Stem Cell Transplantation in Lymphoma.

PURPOSE: The purpose of this study was to differentiate between false-positive and true-positive positron emission tomography (PET) results after hematopoietic stem cell transplantation (SCT) for lymphoma involvement by analyzing several clinical variables and specific imaging features. PATIENTS AND METHODS: Patients with lymphoma who received SCT and underwent post-transplantation 18F-FDG PET/CT scans between January 2013 and April 2021 at our institution were included. Associations between PET positivity and related clinical information were assessed using t-tests and χ2 tests. The significance of variables differentiating benign lesions from malignant FDG-avid lesions was evaluated by logistic regression analysis. Survival probabilities were derived from Kaplan-Meier curves and compared using the log-rank test. RESULTS: A total of 185 patients (235 post-transplantation PET/CT scans) were enrolled in our present study. Compared with those with true-positive PET results, patients with false-positive PET results exhibited a better prognosis. For the autologous SCT group, false-positive cases were more commonly seen when FDG-avid foci appeared outside the sites of the original disease (p = 0.004), and the integrated CT imaging showed negative results (p = 0.000). In multivariate logistic regression analysis, integrated CT results were the only significant factor. For the allogeneic SCT group, false-positive cases were significantly more commonly seen when DS = 4 (p = 0.046), FDG-avid foci appeared outside the sites of the original disease (p = 0.022), and the integrated CT imaging showed negative results (p = 0.001). In a multivariate logistic regression analysis, whether FDG-avid foci were in the sites of the original disease and integrated CT results were both significant factors. CONCLUSION: False-positive FDG uptake in post-transplantation PET was not uncommon. Several variables could provide an important reference to differentiate false-positive from true-positive post-SCT PET results for lymphoma involvement. TRIAL REGISTRATION NUMBER: ChiCTR2300067355.

Radiomic signatures based on pretreatment 18F-FDG PET/CT, combined with clinicopathological characteristics, as early prognostic biomarkers among patients with invasive breast cancer.

Purpose: The aim of this study was to investigate the predictive role of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in the prognostic risk stratification of patients with invasive breast cancer (IBC). To achieve this, we developed a clinicopathologic-radiomic-based model (C-R model) and established a nomogram that could be utilized in clinical practice. Methods: We retrospectively enrolled a total of 91 patients who underwent preoperative 18F-FDG PET/CT and randomly divided them into training (n=63) and testing cohorts (n=28). Radiomic signatures (RSs) were identified using the least absolute shrinkage and selection operator (LASSO) regression algorithm and used to compute the radiomic score (Rad-score). Patients were assigned to high- and low-risk groups based on the optimal cut-off value of the receiver operating characteristic (ROC) curve analysis for both Rad-score and clinicopathological risk factors. Univariate and multivariate Cox regression analyses were performed to determine the association between these variables and progression-free survival (PFS) or overall survival (OS). We then plotted a nomogram integrating all these factors to validate the predictive performance of survival status. Results: The Rad-score, age, clinical M stage, and minimum standardized uptake value (SUVmin) were identified as independent prognostic factors for predicting PFS, while only Rad-score, age, and clinical M stage were found to be prognostic factors for OS in the training cohort. In the testing cohort, the C-R model showed superior performance compared to single clinical or radiomic models. The concordance index (C-index) values for the C-R model, clinical model, and radiomic model were 0.816, 0.772, and 0.647 for predicting PFS, and 0.882, 0.824, and 0.754 for OS, respectively. Furthermore, decision curve analysis (DCA) and calibration curves demonstrated that the C-R model had a good ability for both clinical net benefit and application. Conclusion: The combination of clinicopathological risks and baseline PET/CT-derived Rad-score could be used to evaluate the prognosis in patients with IBC. The predictive nomogram based on the C-R model further enhanced individualized estimation and allowed for more accurate prediction of patient outcomes.

Development of a radiomic-clinical nomogram for prediction of survival in patients with diffuse large B-cell lymphoma treated with chimeric antigen receptor T cells.

BACKGROUND: In our current work, an 18F-FDG PET/CT radiomics-based model was developed to assess the progression-free survival (PFS) and overall survival (OS) of patients with relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL) who received chimeric antigen receptor (CAR)-T cell therapy. METHODS: A total of 61 DLBCL cases receiving 18F-FDG PET/CT before CAR-T cell infusion were included in the current analysis, and these patients were randomly assigned to a training cohort (n = 42) and a validation cohort (n = 19). Radiomic features from PET and CT images were obtained using LIFEx software, and radiomics signatures (R-signatures) were then constructed by choosing the optimal parameters according to their PFS and OS. Subsequently, the radiomics model and clinical model were constructed and validated. RESULTS: The radiomics model that integrated R-signatures and clinical risk factors showed superior prognostic performance compared with the clinical models in terms of both PFS (C-index: 0.710 vs. 0.716; AUC: 0.776 vs. 0.712) and OS (C-index: 0.780 vs. 0.762; AUC: 0.828 vs. 0.728). For validation, the C-index of the two approaches was 0.640 vs. 0.619 and 0.676 vs. 0.699 for predicting PFS and OS, respectively. Moreover, the AUC was 0.886 vs. 0.635 and 0.778 vs. 0.705, respectively. The calibration curves indicated good agreement, and the decision curve analysis suggested that the net benefit of radiomics models was higher than that of clinical models. CONCLUSIONS: PET/CT-derived R-signature could be a potential prognostic biomarker for R/R DLBCL patients undergoing CAR-T cell therapy. Moreover, the risk stratification could be further enhanced when the PET/CT-derived R-signature was combined with clinical factors.

The Differential Diagnostic Value of Radiomics Signatures Between Single-Nodule Pulmonary Metastases and Second Primary Lung Cancer in Patients with Colorectal Cancer.

BACKGROUND: Differential diagnosis of single-nodule pulmonary metastasis (SNPM) and second primary lung cancer (SPLC) in patients with colorectal cancer (CRC) prior to lung surgery is relatively complex. Radiomics is an emerging technique for image information analysis, while it has not yet been applied to construct a differential diagnostic model between SNPM and SPLC in patients with CRC. In the present study, we aimed to extract radiomics signatures from thin-section computed tomography (CT) images of the chest. These radiomics signatures were combined with clinical features to construct a composite differential diagnostic model. METHOD: A total of 91 patients with CRC, including 66 patients with SNPM and 25 patients with SPLC, were enrolled in this study. Patients were randomly assigned to the training cohort (n = 63) and validation cohort (n = 28) at a ratio of 7 to 3. Moreover, 107 radiomics features were extracted from the chest thin-section CT images. The least absolute shrinkage and selection operator (LASSO) regression was used to filter these features, and clinical features were screened by univariate analysis. The screened radiomics and clinical features were combined to construct a multifactorial logistic regression composite model. The receiver operating characteristic (ROC) curves were adopted to evaluate the models, and the corresponding nomograms were created. RESULTS: A series of 6 radiomics characteristics was screened by LASSO. After univariate logistic regression analysis, the composite model finally included 4 radiomics features and 4 clinical features. In the training cohort, the area under the curve scores of ROC curves were 0.912 (95% confidence interval [CI]: 0.813-0.969), 0.884 (95% CI: 0.778-0.951), and 0.939 (95% CI: 0.848-0.984) for models derived from radiomics, clinical, and combined features, respectively. Similarly, these values were 0.756 (95% CI: 0.558-0.897), 0.888 (95% CI: 0.711-0.975), and 0.950 (95% CI: 0.795-0.997) in the validation cohort, respectively. CONCLUSIONS: We constructed a model for differential diagnosis of SNPM and SPLC in patients with CRC using radiomics and clinical features. Moreover, our findings provided a new assessment tool for patients with CRC in the future.

18-F fluorodeoxyglucose positron emission tomography/computed tomography findings of bilateral primary fallopian tube carcinoma and metastasis to the uterus: a case report and literature review.

Existing literature on primary carcinoma of the fallopian tube is limited because of the rarity of this disease. We report a patient with intermittent vaginal bleeding and vaginal discharge who underwent transvaginal ultrasound, magnetic resonance imaging, and 18-F-fluorodeoxyglucose positron emission tomography/computed tomography (18-F FDG PET/CT) in our hospital. Ultrasound showed a bilateral fallopian tube mass and a uterine lesion. Magnetic resonance imaging revealed typical sausage-shaped bilateral adnexal masses, but overlooked a small lesion in the uterus in the initial diagnosis. FDG PET/CT findings not only showed bilateral fallopian tube masses and uterine lesions, but also ruled out distant metastasis. Postoperative pathology confirmed bilateral primary high-grade serous adenocarcinoma of the fallopian tube with implants in the uterus. These findings suggest that 18-F FDG PET/CT imaging could be a good approach for the diagnosis and staging of primary carcinoma of the fallopian tube.

The correlation between PD-L1 expression and metabolic parameters of 18FDG PET/CT and the prognostic value of PD-L1 in non-small cell lung cancer.

OBJECTIVES: In the present study, we aimed to investigate the relationship between metabolic parameters of 18F-fluorodeoxyglucose positron emission computed tomography (18F-FDG PET/CT) and the expression of programmed death ligand-1 (PD-L1), as well as the prognostic value of PD-L1, in patients with surgically resected non-small-cell lung cancer (NSCLC). MATERIALS AND METHODS: A total of 169 NSCLC patients who received preoperative 18F-FDG PET were retrospectively enrolled in the present study. The correlation between PD-L1 and patient characteristics was evaluated. Based on the expression of PD-L1 and metabolic parameters, patients were classified into low-, medium-, or high-risk groups. RESULTS: The maximum standardized uptake value (SUVmax) and total lesion glycolysis (TLG) were significantly higher in NSCLC patients with high PD-L1 expression compared with the low expression group (P < 0.001 for all). Multivariate analysis revealed that pleural invasion (P < 0.001) and SUVmax (P < 0.001) were independent predictors of PD-L1 expression. Survival analysis showed that tumor stage (P = 0.004) and pleural invasion (P = 0.007) were independent prognostic indicators of progression-free survival (PFS). Tumor stage (P = 0.001), TLG (P = 0.039), and PD-L1 expression (P = 0.001) were independent prognostic indicators of overall survival (OS). Patients of the high-risk group with high PD-L1 expression and high TLG had a poor prognosis compared with the low-risk group (P < 0.05) and medium-risk group (P < 0.05). CONCLUSIONS: In NSCLC patients, the SUVmax of 18F-FDG PET/CT was a predictor of PD-L1 expression. The expression of PD-L1 and TLG were independent prognostic factors of OS. The risk stratification standard based on the PD-L1 expression and TLG provided valuable insights into the development of personalized treatment and follow-up. REGISTRATION NUMBER: ChiCTR2100051554.

Molecular imaging of immune checkpoints in oncology: Current and future applications.

Immune checkpoint (IC) blockade therapy has become the first-line treatment for various cancers. However, the low response rate and acquired drug resistance severely restrict the clinical application of immune checkpoint inhibitors (ICIs). Nuclide molecular imaging of ICs can provide non-invasive and whole-body visualization of in vivo IC dynamic biodistribution. Therefore, molecular imaging of ICs can predict and monitor responses to ICIs as a complementary tool to existing immunohistochemical techniques. Herein, we outlined the current status and recent advances in molecular imaging of the "first-generation" and "next-generation" ICs in preclinical and clinical studies.

A Rare Case of Thymic Rosai-Dorfman Disease Mimicking Malignancy on 18F-FDG PET/CT.

Background Rosai-Dorfman disease (RDD), the massive lymphadenopathy characterized by the proliferation of sinus histiocytosis, is a relatively idiopathic benign disease with unknown etiology. We reported a rare case of thymic RDD detected by 18F-FDG PET/CT. A 23-year-old man with right-sided chest pain underwent 18F-FDG PET/CT scan, showing increased 18F-FDG uptake in an anterior mediastinal mass corresponding to a thymic lesion at an enhanced CT scan. The patient was referred to surgery with the clinical suspicion of thymic malignancy. The histological examination and immunohistochemical results confirmed RDD. Conclusions This was the first case report of RDD isolated to the thymus and initially presented with chest pain. Moreover, there was no characteristic painless neck lymphadenopathy at any stage of the disease course. Thus, for young patients with thymus mass, RDD should be considered a rare but possible diagnosis.

Prognostic value of 18F-FDG PET/CT radiomic model based on primary tumor in patients with non-small cell lung cancer: A large single-center cohort study.

Objectives: In the present study, we aimed to determine the prognostic value of the 18F-FDG PET/CT-based radiomics model when predicting progression-free survival (PFS) and overall survival (OS) in patients with non-small cell lung cancer (NSCLC). Methods: A total of 368 NSCLC patients who underwent 18F-FDG PET/CT before treatment were randomly assigned to the training (n = 257) and validation (n = 111) cohorts. Radiomics signatures from PET and CT images were obtained using LIFEx software, and then clinical and complex models were constructed and validated by selecting optimal parameters based on PFS and OS to construct radiomics signatures. Results: In the training cohort, the C-index of the clinical model for predicting PFS and OS in NSCLC patients was 0.748 and 0.834, respectively, and the AUC values ​​were 0.758 and 0.846, respectively. The C-index of the complex model for predicting PFS and OS was 0.775 and 0.881, respectively, and the AUC values ​​were 0.780 and 0.891, respectively. The C-index of the clinical model for predicting PFS and OS in the validation group was 0.729 and 0.832, respectively, and the AUC values ​​were 0.776 and 0.850, respectively. The C-index of the complex model for predicting PFS and OS was 0.755 and 0.867, respectively, and the AUC values ​​were 0.791 and 0.874, respectively. Moreover, decision curve analysis showed that the complex model had a higher net benefit than the clinical model. Conclusions: 18F-FDG PET/CT radiomics before treatment could predict PFS and OS in NSCLC patients, and the predictive power was higher when combined with clinical factors.