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PurposeThe aim of the present study is to evaluate the safety and efficacy of iodine-125 brachytherapy for newly diagnosed brain metastasis in patients with non-small cell lung cancer (NSCLC).Materials and methodsThe study included 158 NSCLC patients diagnosed with brain metastasis from December 2003 to August 2017. Ninety-nine patients underwent external beam radiotherapy (EBRT group), and 59 patients received iodine-125 brachytherapy (125I group). In addition, the 6- and 12-month progression-free survival (PFS) rates and the 12- and 24-month overall survival (OS) rates were compared between the EBRT group and the 125I group. Median OS and PFS were analyzed using the Kaplan−Meier method with a log-rank test.ResultsThe 6-month PFS rate was significantly higher in the 125I group (p = 0.002) than in the EBRT group, while no differences were found in the 12-month PFS rate (p = 0.184). Additionally, the 12- (p = 0.839) and 24-month (p = 0.284) OS rates were not significantly different between the two groups. No significant differences in median OS (p = 0.525) or PFS (p = 0.425) were found between the two groups.ConclusionsIodine-125 brachytherapy is an alternative therapy for patients unable to undergo surgical resection.

ObjectiveTo evaluate the application value of monoexponential, fractional order calculus (FROC) diffusion models and PET imaging to distinguish between benign and malignant solitary pulmonary lesions (SPLs) and malignant SPLs with different pathological types and explore the correlation between each parameter and Ki67 expression.MethodsA total of 112 patients were enrolled in this study. Prior to treatment, all patients underwent a dedicated thoracic 18F-FDG PET/MR examination. Five parameters [including apparent diffusion coefficient (ADC) derived from the monoexponential model; diffusion coefficient (D), a microstructural quantity (μ), and fractional order parameter (β) derived from the FROC model and maximum standardized uptake value (SUVmax) derived from PET] were compared between benign and malignant SPLs and different pathological types of malignant SPLs. Independent sample t test, Mann-Whitney U test, DeLong test and receiver operating characteristic (ROC) curve analysis were used for statistical evaluation. Pearson correlation analysis was used to calculate the correlations between Ki-67 and ADC, D, μ, β, and SUVmax.ResultsThe ADC and D values were significantly higher and the μ and SUVmax values were significantly lower in the benign group [1.57 (1.37, 2.05) μm2/ms, 1.59 (1.52, 1.72) μm2/ms, 5.06 (3.76, 5.66) μm, 5.15 ± 2.60] than in the malignant group [1.32 (1.03, 1.51) μm2/ms, 1.43 (1.29, 1.52) μm2/ms, 7.06 (5.87, 9.45) μm, 9.85 ± 4.95]. The ADC, D and β values were significantly lower and the μ and SUVmax values were significantly higher in the squamous cell carcinoma (SCC) group [1.29 (0.66, 1.42) μm2/ms, 1.32 (1.02, 1.42) μm2/ms, 0.63 ± 0.10, 9.40 (7.76, 15.38) μm, 11.70 ± 5.98] than in the adenocarcinoma (AC) group [1.40 (1.28, 1.67) μm2/ms, 1.52 (1.44, 1.64) μm2/ms, 0.70 ± 0.10, 5.99 (4.54, 6.87) μm, 8.76 ± 4.18]. ROC curve analysis showed that for a single parameter, μ exhibited the best AUC value in discriminating between benign and malignant SPLs groups and AC and SCC groups (AUC = 0.824 and 0.911, respectively). Importantly, the combination of monoexponential, FROC models and PET imaging can further improve diagnostic performance (AUC = 0.872 and 0.922, respectively). The Pearson correlation analysis showed that Ki67 was positively correlated with μ value and negatively correlated with ADC and D values (r = 0.402, -0.346, -0.450, respectively).ConclusionThe parameters D and μ derived from the FROC model were superior to ADC and SUVmax in distinguishing benign from malignant SPLs and adenocarcinoma from squamous cell carcinoma, in addition, the combination of multiple parameters can further improve diagnostic performance. The non-Gaussian FROC diffusion model is expected to become a noninvasive quantitative imaging technique for identifying SPLs.

ObjectiveTo explore the value of PET/MRI, including diffusion kurtosis imaging (DKI), diffusion weighted imaging (DWI) and positron emission tomography (PET), for distinguishing between benign and malignant solitary pulmonary lesions (SPLs) and predicting the histopathological grading of malignant SPLs.Material and methodsChest PET, DKI and DWI scans of 73 patients with SPL were performed by PET/MRI. The apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), maximum standard uptake value (SUVmax), metabolic total volume (MTV) and total lesion glycolysis (TLG) were calculated. Student’s t test or the Mann–Whitney U test was used to analyze the differences in parameters between groups. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy. Logistic regression analysis was used to evaluate independent predictors.ResultsThe MK and SUVmax were significantly higher, and the MD and ADC were significantly lower in the malignant group (0.59 ± 0.13, 10.25 ± 4.20, 2.27 ± 0.51[×10-3 mm2/s] and 1.35 ± 0.33 [×10-3 mm2/s]) compared to the benign group (0.47 ± 0.08, 5.49 ± 4.05, 2.85 ± 0.60 [×10-3 mm2/s] and 1.67 ± 0.33 [×10-3 mm2/s]). The MD and ADC were significantly lower, and the MTV and TLG were significantly higher in the high-grade malignant SPLs group (2.11 ± 0.51 [×10-3 mm2/s], 1.35 ± 0.33 [×10-3 mm2/s], 35.87 ± 42.24 and 119.58 ± 163.65) than in the non-high-grade malignant SPLs group (2.46 ± 0.46 [×10-3 mm2/s], 1.67 ± 0.33[×10-3 mm2/s], 20.17 ± 32.34 and 114.20 ± 178.68). In the identification of benign and malignant SPLs, the SUVmax and MK were independent predictors, the AUCs of the combination of SUVmax and MK, SUVmax, MK, MD, and ADC were 0.875, 0.787, 0.848, 0.769, and 0.822, respectively. In the identification of high-grade and non-high-grade malignant SPLs, the AUCs of MD, ADC, MTV, and TLG were 0.729, 0.680, 0.693, and 0.711, respectively.ConclusionDWI, DKI, and PET in PET/MRI are all effective methods to distinguish benign from malignant SPLs, and are also helpful in evaluating the pathological grading of malignant SPLs.

Neutrophils are prominent components of solid tumors and exhibit distinct phenotypes in different tumor milieu. We have previously shown that tumor extracellular vesicles (EVs) could induce pro-tumor activation of neutrophils; however, the role of tumor EV-elicited neutrophils in tumor immunity remains unclear. Herein, we reported that gastric cancer cell-derived EVs (GC-EVs) induced the expression of programmed death-ligand 1 (PD-L1) on neutrophils. GC-EVs transported high-mobility group box-1 (HMGB1) to activate signal transducer and activator of transcription 3 (STAT3) and upregulate PD-L1 gene expression in neutrophils. Blocking STAT3 pathway and silencing HMGB1 reversed GC-EV-induced PD-L1 expression on neutrophils. GC-EV-elicited neutrophils suppressed T cell proliferation, activation, and function in vitro, which could be antagonized by a specific PD-L1 antibody. Furthermore, GC tissue-derived EVs also showed similar effects. Taken together, our results indicate that EVs from the GC microenvironment induce PD-L1 expression on neutrophils to suppress T-cell immunity, which provides a new insight into the pro-tumor roles of neutrophils in GC and sheds light on the multifaceted roles of EVs in orchestrating an immunosuppressive microenvironment.

Objective: To explore the value of PET/MRI, including diffusion kurtosis imaging (DKI), diffusion weighted imaging (DWI) and positron emission tomography (PET), for distinguishing between benign and malignant solitary pulmonary lesions (SPLs) and predicting the histopathological grading of malignant SPLs. Material and methods: Chest PET, DKI and DWI scans of 73 patients with SPL were performed by PET/MRI. The apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), maximum standard uptake value (SUVmax), metabolic total volume (MTV) and total lesion glycolysis (TLG) were calculated. Student's t test or the Mann-Whitney U test was used to analyze the differences in parameters between groups. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy. Logistic regression analysis was used to evaluate independent predictors. Results: The MK and SUVmax were significantly higher, and the MD and ADC were significantly lower in the malignant group (0.59 ± 0.13, 10.25 ± 4.20, 2.27 ± 0.51[×10-3 mm²/s] and 1.35 ± 0.33 [×10-3 mm²/s]) compared to the benign group (0.47 ± 0.08, 5.49 ± 4.05, 2.85 ± 0.60 [×10-3 mm²/s] and 1.67 ± 0.33 [×10-3 mm²/s]). The MD and ADC were significantly lower, and the MTV and TLG were significantly higher in the high-grade malignant SPLs group (2.11 ± 0.51 [×10-3 mm²/s], 1.35 ± 0.33 [×10-3 mm²/s], 35.87 ± 42.24 and 119.58 ± 163.65) than in the non-high-grade malignant SPLs group (2.46 ± 0.46 [×10-3 mm²/s], 1.67 ± 0.33[×10-3 mm²/s], 20.17 ± 32.34 and 114.20 ± 178.68). In the identification of benign and malignant SPLs, the SUVmax and MK were independent predictors, the AUCs of the combination of SUVmax and MK, SUVmax, MK, MD, and ADC were 0.875, 0.787, 0.848, 0.769, and 0.822, respectively. In the identification of high-grade and non-high-grade malignant SPLs, the AUCs of MD, ADC, MTV, and TLG were 0.729, 0.680, 0.693, and 0.711, respectively. Conclusion: DWI, DKI, and PET in PET/MRI are all effective methods to distinguish benign from malignant SPLs, and are also helpful in evaluating the pathological grading of malignant SPLs. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the application value of monoexponential, fractional order calculus (FROC) diffusion models and PET imaging to distinguish between benign and malignant solitary pulmonary lesions (SPLs) and malignant SPLs with different pathological types and explore the correlation between each parameter and Ki67 expression. Methods: A total of 112 patients were enrolled in this study. Prior to treatment, all patients underwent a dedicated thoracic 18F-FDG PET/MR examination. Five parameters [including apparent diffusion coefficient (ADC) derived from the monoexponential model; diffusion coefficient (D), a microstructural quantity (m), and fractional order parameter (b) derived from the FROC model and maximum standardized uptake value (SUVmax) derived from PET] were compared between benign and malignant SPLs and different pathological types of malignant SPLs. Independent sample t test, Mann-Whitney U test, DeLong test and receiver operating characteristic (ROC) curve analysis were used for statistical evaluation. Pearson correlation analysis was used to calculate the correlations between Ki-67 and ADC, D, m, b, and SUVmax. Results: The ADC and D values were significantly higher and the m and SUVmax values were significantly lower in the benign group [1.57 (1.37, 2.05) mm2/ms, 1.59 (1.52, 1.72) mm2/ms, 5.06 (3.76, 5.66) mm, 5.15 ± 2.60] than in the malignant group [1.32 (1.03, 1.51) mm2/ms, 1.43 (1.29, 1.52) mm2/ms, 7.06 (5.87, 9.45) mm, 9.85 ± 4.95]. The ADC, D and b values were significantly lower and the m and SUVmax values were significantly higher in the squamous cell carcinoma (SCC) group [1.29 (0.66, 1.42) mm2/ms, 1.32 (1.02, 1.42) mm2/ms, 0.63 ± 0.10, 9.40 (7.76, 15.38) mm, 11.70 ± 5.98] than in the adenocarcinoma (AC) group [1.40 (1.28, 1.67) mm2/ms, 1.52 (1.44, 1.64) mm2/ms, 0.70 ± 0.10, 5.99 (4.54, 6.87) mm, 8.76 ± 4.18]. ROC curve analysis showed that for a single parameter, m exhibited the best AUC value in discriminating between benign and malignant SPLs groups and AC and SCC groups (AUC = 0.824 and 0.911, respectively). Importantly, the combination of monoexponential, FROC models and PET imaging can further improve diagnostic performance (AUC = 0.872 and 0.922, respectively). The Pearson correlation analysis showed that Ki67 was positively correlated with m value and negatively correlated with ADC and D values (r = 0.402, -0.346, -0.450, respectively). Conclusion: The parameters D and m derived from the FROC model were superior to ADC and SUVmax in distinguishing benign from malignant SPLs and adenocarcinoma from squamous cell carcinoma, in addition, the combination of multiple parameters can further improve diagnostic performance. The non-Gaussian FROC diffusion model is expected to become a noninvasive quantitative imaging technique for identifying SPLs. [ABSTRACT FROM AUTHOR]