BackgroundFibroblast activation protein (FAP) is commonly expressed in activated stromal fibroblasts in various epithelial tumours. Recently, 68Ga-FAPI-04 has been used for tumour imaging in positron emission tomography/computed tomography (PET/CT). This study aimed to compare the diagnostic performances of 68Ga-FAPI-04 PET/CT and 18F-FDG PET/CT in hepatocellular carcinoma (HCC), and to assess factors associated with 68Ga-FAPI-04 uptake in HCC.Materials and MethodsTwenty-nine patients with suspiciously HCC who received both 18F-FDG and 68Ga-FAPI-04 PET/CT were included in this retrospective study. The results were interpreted by two experienced nuclear medicine physicians independently. The maximum and mean standardized uptake values (SUVmax and SUVmean) were measured in the lesions and liver background, respectively. The tumour-to-background ratio (TBR) was then calculated as lesion’s SUVmax divided by background SUVmean.ResultsA total of 35 intrahepatic lesions in 25 patients with HCC were finally involved in the statistical analysis. 68Ga-FAPI-04 PET/CT showed a higher sensitivity than 18F-FDG PET/CT in detecting intrahepatic HCC lesions (85.7% vs. 57.1%, P = 0.002), including in small (≤ 2 cm in diameter; 68.8% vs. 18.8%, P = 0.008) and well- or moderately-differentiated (83.3% vs. 33.3%, P = 0.031) tumors. SUVmax was comparable between 68Ga-FAPI-04 and 18F-FDG (6.96 ± 5.01 vs. 5.89 ± 3.38, P > 0.05), but the TBR was significantly higher in the 68Ga-FAPI-04 group compared with the 18F-FDG group (11.90 ± 8.35 vs. 3.14 ± 1.59, P < 0.001). SUVmax and the TBR in 68Ga-FAPI-04 positive lesions were associated with tumour size (both P < 0.05), but not the remaining clinical and pathological features (all P > 0.05).Conclusions68Ga-FAPI-04 PET/CT is more sensitive than 18F-FDG PET/CT in detecting HCC lesions, and 68Ga-FAPI-04 uptake is correlated mainly with tumour size.

Background/Aims: The function of BRAF V600E as a prognostic biomarker continues controversial by reason of conflicting results in the published articles. Methods: A systematical literature search for relevant articles was performed in PubMed, Cochrane Library, Google Scholar, Medline and Embase updated to August 5, 2015. The Chi-square test and I² were employed to examine statistical heterogeneity. Pooled ORs with their corresponding 95% confidence intervals (95%CIs) were calculated to assess the relationship between clinicopathological features and BRAF^V600E mutation. Subgroup analyses by ethnicity were also performed to explore the potential sources of heterogeneity. Furthermore, publication bias was detected using the funnel plot and all statistical analyses were conducted by the software of R 3.12. Results: Of 25,241 cases with PTC, 15,290 (60.6%) were positive for BRAF mutation and 9,951 (39.4%) were tested negative for BRAF mutation. Negative status of BRAF^V600E mutation negative was significantly associated with gender (OR = 0.90, 95%CI = 0.83-0.97) and concomitant hashimoto thyroiditis (OR = 0.53, 95%CI = 0.43-0.64). By contrast, positive status of BRAF^V600E mutation was a significant predictor of multifocality (OR = 1.23; 95%CI = 1.14-1.32), extrathyroidal extension (OR = 2.23; 95%CI = 1.90-2.63), TNM stage (OR = 1.67; 95%CI = 1.53-1.81), lymph node metastasis (OR = 1.67; 95%CI = 1.45-1.93), vascular invasion (OR = 1.47; 95%CI = 1.22-1.79) and recurrence/persistence (OR = 2.33; 95%CI = 1.71-3.18). However, there was no significant association between BRAF^V600E mutation and factors including age > 45 (OR = 0.98; 95%CI = 0.89-1.07), tumor size (OR = 0.84; 95%CI = 0.64-1.09) and distant metastasis (OR = 1.23; 95%CI = 0.67-2.27). Conclusion: This meta-analysis confirmed significant associations between BRAF^V600E mutation and female gender, multifocality, ETE, LNM, TNM stage, concomitant hashimoto thyroiditis, vascular invasion and recurrence/persistence, suggesting the predictive value of BRAF^V600Emutation for PTC prognosis.

To explore the mechanism of lnc SNHG20 in the regulation of proliferation, invasion, and migration of breast cancer cells. mRNA levels of SNHG20, miR-495, and HER2 were detected by qRT-PCR. Protein level of HER2 was measured by Western blot. Cell proliferation, invasion, and migration were detected by CCK-8 assay, Boyden chamber assay, and Transwell assay. The combination between SNHG20 and miR-495 was confirmed by RNA pull down assay. The combination between miR-495 and HER2 was confirmed by luciferase report assays. We also established breast cancer-bearing mice model and analyzed tumor volumes. Our data showed SNHG20 expression was significantly upregulated, miR-495 expression was significantly downregulated, and HER2 expression was significantly upregulated in breast cancer tissues and cell lines. Besides, SNHG20 promoted the proliferation, invasion, and migration of breast cancer cells. We also found SNHG20 negatively regulated miR-495, and miR-495 could negatively regulate HER2. Moreover, we discovered that SNHG20 regulated HER2 via miR-495. SNHG20 regulated proliferation, invasion, and migration of breast cancer cells via miR-495/HER2. Finally, we confirmed the mechanism of SNHG20 in the regulation of proliferation, invasion, and migration in breast cancer-bearing mice model. SNHG20 regulates HER2 via miR-495 to promote proliferation, invasion, and migration of breast cancer cells.

BackgroundMetal objects implanted in the bodies of patients usually generate severe streaking artifacts in reconstructed images of X-ray computed tomography, which degrade the image quality and affect the diagnosis of disease. Therefore, it is essential to reduce these artifacts to meet the clinical demands.MethodsIn this work, we propose a Gaussian diffusion sinogram inpainting metal artifact reduction algorithm based on prior images to reduce these artifacts for fan-beam computed tomography reconstruction. In this algorithm, prior information that originated from a tissue-classified prior image is used for the inpainting of metal-corrupted projections, and it is incorporated into a Gaussian diffusion function. The prior knowledge is particularly designed to locate the diffusion position and improve the sparsity of the subtraction sinogram, which is obtained by subtracting the prior sinogram of the metal regions from the original sinogram. The sinogram inpainting algorithm is implemented through an approach of diffusing prior energy and is then solved by gradient descent. The performance of the proposed metal artifact reduction algorithm is compared with two conventional metal artifact reduction algorithms, namely the interpolation metal artifact reduction algorithm and normalized metal artifact reduction algorithm. The experimental datasets used included both simulated and clinical datasets.ResultsBy evaluating the results subjectively, the proposed metal artifact reduction algorithm causes fewer secondary artifacts than the two conventional metal artifact reduction algorithms, which lead to severe secondary artifacts resulting from impertinent interpolation and normalization. Additionally, the objective evaluation shows the proposed approach has the smallest normalized mean absolute deviation and the highest signal-to-noise ratio, indicating that the proposed method has produced the image with the best quality.ConclusionsNo matter for the simulated datasets or the clinical datasets, the proposed algorithm has reduced the metal artifacts apparently.