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.

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.

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.

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.

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.

Imaging Characteristics and Prognostic Value of Isolated Pulmonary Metastasis from Colorectal Cancer Demonstrated with18F-FDG PET/CT.

Objective: Solitary pulmonary lesions (SPNs) in patients with a history of colorectal cancer (CRC) may be attributed to metastatic lung tumors, primary lung cancer, or benign nodules. We aimed to analyze the imaging characteristics of SPNs in CRC patients to differentiate these pulmonary nodules and evaluate the prognostic value of isolated pulmonary metastasis from CRC using 18F-FDG PET/CT. Methods: From January 2013 to January 2021, 62 CRC patients with SPNs demonstrated with 18F-FDG PET/CT were retrospectively enrolled in the present study. We compared the radiological and clinical characteristics of these patients. In addition, survival time and prognostic factors were statistically analyzed using the Kaplan-Meier method and multivariable Cox proportional hazards models. Results: There were 33 cases of isolated lung metastasis, 20 cases of second primary lung cancer (SPLC), and nine cases of benign nodules. The proportion of nodules with a maximal diameter greater than the median value was lower in the isolated lung metastasis group compared with the SPLC group (p < 0.05), showing polygonal shape, ill-defined margin, pleural indentation, air bronchogram, speculation, and ground-glass opacity. Patients with isolated lung metastasis had a significantly higher maximal diameter of lung lesion, SUVmax of lung lesion, and 18F-FDG uptake compared with the benign nodule group (p < 0.05). Multivariate analysis revealed that the following two factors were significant independent predictors of PLC: air bronchogram (hazard ratio [HR] =22.327; 95% confidence interval [CI]: 1.910-261.061; p = 0.013) and spiculation (HR =6.148; 95% CI 1.469-25.725; p = 0.013). Initial TNM stage IV (HR =19.831, 95% CI 1.061-370.782; p = 0.046) was extremely associated with a decreased lifespan of CRC patients with isolated lung metastasis. Conclusions: The result showed that CT features, including air bronchogram and spiculated margins, could be used to differentiate SPLC from single isolated lung metastasis in CRC patients. In patients with isolated lung metastasis, primary CRC TNM stage IV was associated with a poorer prognosis, and patients with such conditions might need more care.

Prognostic Value of Radiomic Features of 18F-FDG PET/CT in Patients With B-Cell Lymphoma Treated With CD19/CD22 Dual-Targeted Chimeric Antigen Receptor T Cells.

OBJECTIVE: In the present study, we aimed to evaluate the prognostic value of PET/CT-derived radiomic features for patients with B-cell lymphoma (BCL), who were treated with CD19/CD22 dual-targeted chimeric antigen receptor (CAR) T cells. Moreover, we explored the relationship between baseline radiomic features and the occurrence probability of cytokine release syndrome (CRS). METHODS: A total of 24 BCL patients who received 18F-FDG PET/CT before CAR T-cell infusion were enrolled in the present study. Radiomic features from PET and CT images were extracted using LIFEx software, and the least absolute shrinkage and selection operator (LASSO) regression was used to select the most useful predictive features of progression-free survival (PFS) and overall survival (OS). Receiver operating characteristic curves, Cox proportional hazards model, and Kaplan-Meier curves were conducted to assess the potential prognostic value. RESULTS: Contrast extracted from neighbourhood grey-level different matrix (NGLDM) was an independent predictor of PFS (HR = 15.16, p = 0.023). MYC and BCL2 double-expressor (DE) was of prognostic significance for PFS (HR = 7.02, p = 0.047) and OS (HR = 10.37, p = 0.041). The combination of NGLDM_ContrastPET and DE yielded three risk groups with zero (n = 7), one (n = 11), or two (n = 6) factors (p < 0.0001 and p = 0.0004, for PFS and OS), respectively. The PFS was 85.7%, 63.6%, and 0%, respectively, and the OS was 100%, 90.9%, and 16.7%, respectively. Moreover, there was no significant association between PET/CT variables and CRS. CONCLUSIONS: In conclusion, radiomic features extracted from baseline 18F-FDG PET/CT images in combination with genomic factors could predict the survival outcomes of BCL patients receiving CAR T-cell therapy.

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.

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.

Post-transplantation Fluorine-18 Fluorodeoxyglucose Positron Emission Tomography in Patients with Lymphoblastic Lymphoma is an Independent Prognostic Factor with an Impact on Progression-Free Survival but not Overall Survival.

Purpose: In the present study, we mainly aimed to evaluate the prognostic value of 2-deoxy-2-[18F]fluoro-D-glucose ([18F]F-FDG) positron emission tomography (PET)/computed tomography (CT) after allogeneic stem cell transplantation (allo-SCT) in lymphoblastic lymphoma (LBL) patients using Deauville Scores (DS). Materials and Methods: A total of 63 LBL patients who benefited from 18F-FDG PET-CT after allo-SCT in our institution between April 2010 and August 2020 were enrolled in this retrospective study. These above-mentioned patients were divided into two groups based on the Deauville criteria. Diagnostic efficiency of 18F-FDG PET/CT and integrated CT in detecting lymphoma were calculated. Consistencies were evaluated by comparing 18F-FDG PET/CT and integrated CT results through kappa coefficient. Kaplan-Meier method was used in survival analysis, and the log-rank method was adopted in comparisons. Prognostic factor analysis was performed by the Cox regression model. Results: The sensitivity, specificity, positive predictive value, negative predictive value, accuracy of post-SCT 18F-FDG PET-CT were 100%(12/12), 92.2%(47/51), 75.0%(12/16), 100%(47/47) and 93.7%(59/63). The consistency of 18F-FDG PET-CT and integrated CT was moderate(Kappa = .702，P < .001). Positive post-SCT 18F-FDG PET-CT was associated with lower progression-free survival (PFS) but not overall survival (OS) (p = .000 and p = .056, respectively). The 3-year PFS of the PET-positive group and PET-negative group was 18.8% and 70.2%, respectively. Multivariate analysis showed that post-SCT PET-CT findings was an independent prognostic factor for PFS (p = .000; HR, 3.957; 95%CI, 1.839-8.514). Other factors independently affecting PFS were sex (p = .018; HR, 2.588; 95% CI, 1.181 - 5.670) and lactate dehydrogenase (LDH) (p = .005; HR, 3.246; 95% CI, 1.419 - 7.426). However, none of the above-mentioned factors were associated with OS. Conclusions: Collectively, we found that 18F-FDG PET-CT after allo-SCT was a strong indicator for PFS, but not OS, which might provide important evidence for the selection of subsequent treatment regimen for LBL patients. Trial registration number: ChiCTR2100046709.

Evaluation of PD-L1 Expression Level in Patients With Non-Small Cell Lung Cancer by 18F-FDG PET/CT Radiomics and Clinicopathological Characteristics.

PURPOSE: In the present study, we aimed to evaluate the expression of programmed death-ligand 1 (PD-L1) in patients with non-small cell lung cancer (NSCLC) by radiomic features of 18F-FDG PET/CT and clinicopathological characteristics. METHODS: A total 255 NSCLC patients (training cohort: n = 170; validation cohort: n = 85) were retrospectively enrolled in the present study. A total of 80 radiomic features were extracted from pretreatment 18F-FDG PET/CT images. Clinicopathologic features were compared between the two cohorts. The least absolute shrinkage and selection operator (LASSO) regression was used to select the most useful prognostic features in the training cohort. Radiomics signature and clinicopathologic risk factors were incorporated to develop a prediction model by using multivariable logistic regression analysis. The receiver operating characteristic (ROC) curve was used to assess the prognostic factors. RESULTS: A total of 80 radiomic features were extracted in the training dataset. In the univariate analysis, the expression of PD-L1 in lung tumors was significantly correlated with the radiomic signature, histologic type, Ki-67, SUVmax, MTV, and TLG (p< 0.05, respectively). However, the expression of PD-L1 was not correlated with age, TNM stage, and history of smoking (p> 0.05). Moreover, the prediction model for PD-L1 expression level over 1% and 50% that combined the radiomic signature and clinicopathologic features resulted in an area under the curve (AUC) of 0.762 and 0.814, respectively. CONCLUSIONS: A prediction model based on PET/CT images and clinicopathological characteristics provided a novel strategy for clinicians to screen the NSCLC patients who could benefit from the anti-PD-L1 immunotherapy.