Volumetric parameters on 18F-FDG PET/CT predict the survival of patients with gastric cancer associated with their expression status of c-MET

Incremental value of PET primary lesion-based radiomics signature to conventional metabolic parameters and traditional risk factors for preoperative prediction of lymph node metastases in gastric cancer

BACKGROUND

Precise preoperative prediction of lymph node metastasis (LNM) is crucial for optimal diagnosis and treatment in patients with gastric cancer (GC), in which existing imaging methods have certain limitations. We hypothesized that PET primary lesion-based radiomics signature could provide incremental value to conventional metabolic parameters and traditional risk indicators in predicting LNM in patients with GC.

METHODS

This retrospective study was performed in 127 patients with GC who underwent preoperative PET/CT. Basic clinical data and PET conventional metabolic parameters were collected. Radiomics signature was constructed by the least absolute shrinkage and selection operator algorithm (LASSO) logistic regression. Based on the postoperative histological results, the patients were divided into LNM group and non-lymph node metastasis (NLNM) group. Receiver-operating characteristic (ROC) was used to evaluate the discriminatory ability of Radiomics score (Rad-score) for predicting LNM and determine whether adding Rad-score to PET conventional metabolic parameters and traditional risk factors could improve the predictive value in LNM. The Integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were calculated to further confirm the incremental value of Rad-score for predicting LNM in GC.

RESULTS

The LNM group had higher Rad-score than NLNM group [(0.35 (-0.13-0.85) vs. -0.61 (-1.92-0.18), P < 0 .001)]. After adjusted for gender, age, BMI, and FBG, multivariable logistic regression analysis illustrated that Rad-score (OR: 6.38, 95% CI: 2.73-14.91, P < 0.0001) was independent risk factors for LNM in GC. Adding PET conventional parameters to traditional risk factors increased the predictive value of LNM in GC (AUC 0.751 vs 0.651, P = 0.02). Additional inclusion of Rad-score to conventional metabolic parameters and traditional risk indicators significantly improved the AUC (0.882 vs 0.751; P = 0.006). Bootstrap resampling (times = 500) was used for internal verification, 95% confidence interval (CI) was 0.802-0.948, with the sensitivity equaled to 89.5%, and positive predictive value (PPV) was 93.5%. When Rad-score was added to conventional metabolic parameters and traditional risk indicators, net reclassification improvement (NRI) was 0.293 (P = 0.0040) and integrated discrimination improvement (IDI) was 0.293 (P = 0.0045).

CONCLUSION

In GC patients, PET Radiomics signature of the primary lesion-based was significantly associated with LNM and could improve the prediction of LNM above PET conventional metabolic parameters and traditional risk factors, which could provide incremental value for individual diagnosis and treatment of GC.

LncRNA HOTTIP Knockdown Attenuates Acute Myocardial Infarction via Regulating miR-92a-2/c-Met Axis

Increasing investigations have focused on long non-coding RNAs (lncRNAs) in various human diseases, including acute myocardial infarction (AMI). Although lncRNA HOTTIP has been identified to play an important role in coronary artery diseases, its role and specific mechanism in AMI remain unclear. To investigate the potential role of HOTTIP in MI, HOTTIP expression in hypoxia-treated cardiomyocytes and myocardial tissues of MI mice was evaluated. The potential targets of HOTTIP and miR-92a-2 were predicted using Starbase and Targetscan. To further determine the cardio-protective effects of HOTTIP in vivo, si-HOTTIP and miR-92a-2 mimics were individually or co-injected into mice through intramyocardial injection. Moreover, their roles were further confirmed in rescue experiments. HOTTIP was significantly upregulated in ischemic myocardium of MI mice and hypoxia-induced cardiomyocytes. Moreover, HOTTIP knockdown markedly promoted cardiomyocyte growth and inhibited cardiomyocyte apoptosis in vitro. Luciferase reporter assay showed that HOTTIP could directly sponge miR-92a-2 to negatively regulate miR-92a-2 expression. In addition, c-Met was identified as a direct target of miR-92a-2, and their correlation was confirmed by luciferase reporter assay. MiR-92a-2 overexpression significantly enhanced the protective effect of HOTTIP knockdown against AMI through partially inhibiting c-Met expression. Our results demonstrated that HOTTIP downregulation attenuated AMI progression via the targeting miR-92a-2/c-Met axis and suggested that HOTTIP might be a potential therapeutic target for AMI.

Relationship between total lesion glycolysis of primary lesions based on 18F-FDG PET/CT and lymph node metastasis in gastric adenocarcinoma: a cross-sectional preliminary study

OBJECTIVES

We explored the relationship between lymph node metastasis (LNM) and total lesion glycolysis (TLG) of primary lesions determined by 18fluoro-2-deoxyglucose PET/computed tomography (18F-FDG PET/CT) in patients with gastric adenocarcinoma, and evaluated the independent effect of this association.

METHODS

This retrospective study included 106 gastric adenocarcinoma patients who were examined by preoperative 18F-FDG PET/CT imaging between April 2016 and April 2020. We measured TLG of primary gastric lesions and evaluated its association with LNM. Multivariate logistic regression and a two-piece-wise linear regression were performed to evaluate the relationship between TLG of primary lesions and LNM.

RESULTS

Of the 106 patients, 75 cases (71%) had LNM and 31 cases (29%) did not have LNM. Univariate analyses revealed that a per-SD increase in TLG was independently associated with LNM [odds ratio (OR) = 2.37; 95% confidence interval (CI), 1.42-3.98; P = 0.0010]. After full adjustment of confounding factors, multivariate analyses exhibited that TLG of primary lesions was still significantly associated with LNM (OR per-SD: 2.20; 95% CI, 1.16-4.19; P = 0.0164). Generalized additive model indicated a nonlinear relationship and saturation effect between TLG of primary lesions and LNM. When TLG of primary lesions was <23.2, TLG was significantly correlated with LNM (OR = 1.26; 95% CI, 1.07-1.48; P = 0.0053), whereas when TLG of primary lesions was ≥ 23.2, the probability of LNM was greater than 60%, gradually reached saturation effect, as high as 80% or more.

CONCLUSIONS

In this preliminary study, there were saturation and segmentation effects between TLG of primary lesions determined by preoperative 18F-FDG PET/CT and LNM. When TLG of primary lesions was ≥ 23.2, the probability of LNM was greater than 60%, gradually reached saturation effect, as high as 80% or more. TLG of primary lesions is helpful in the preoperative diagnosis of LNM in patients with gastric adenocarcinoma.

Segmentation of Gastric Computerized Tomography Images under Intelligent Algorithms in Evaluation of Efficacy of Decitabine Combined with Paclitaxel in Treatment of Gastric Cancer

To analyze the evaluation of artificial intelligence algorithm combined with gastric computed tomography (CT) image in clinical chemotherapy for advanced gastric cancer, 112 patients with advanced gastric cancer were selected as the research object. Among which, 56 patients in the experimental group received paclitaxel (PTX) combined with decitabine sequential decitabine maintenance therapy. Fifty-six patients in the control group received first-line treatment with decitabine combined with cisplatin. The image segmentation algorithm based on fast interactive dictionary selection was used to process gastric CT images. Complete response (CR), partial response (PR), stable disease (SD), progressive disease (PD), response rate (RR), disease control rate (DCR), and overall survival (OS) after treatment were recorded. The true-positive rate (TPR) and coincidence ratio (CR) of the proposed algorithm for image segmentation were significantly higher than those of the mean shift algorithm and the iCoseg algorithm. The mean edge distance (MED) and edge distance variance (EDV) were significantly lower than the mean shift algorithm and the iCoseg algorithm, and the differences were considerable (P < 0.05). The number of CR (5 cases), PR (13 cases), RR (18 cases), and DCR (44 cases) in the experimental group was significantly higher than that in the control group, while the number of PD (12 cases) was significantly lower than that in the control group (P < 0.05). The number of patients complicated with hematological toxicity, leucopenia, thrombocytopenia, and digestive tract reaction in the experimental group was less than that in the control group (P < 0.05). From the comparison of long-term efficacy, the survival rate of patients in both groups showed a decreasing trend within 24 months, but the decreasing trend of survival rate of patients in the experimental group was better than that in the control group. In short, the proposed algorithm had better segmentation performance than traditional algorithms. Compared with first-line treatment with decitabine and cisplatin, PTX in combination with decitabine sequential citabine maintenance regimens had better disease control rates, lower toxicity, and more effective improvements in patient quality of life and longer survival in patients with advanced gastric cancer.

18F-FDG PET/CT for primary staging of patients with testicular germ cell tumors: the predictors of 18F-FDG PET positivity and prognostic value of PET derived metabolic parameters

PURPOSE

The aim of this study was to investigate the role of histopathologic and biochemical parameters for predicting F-FDG PET positivity for primary staging in patients with newly diagnosed testicular germ cell tumors (TGCT). It was also aimed to evaluate the prognostic value of PET derived metabolic features in this patient group.

MATERIALS AND METHODS

The imaging findings of 51 patients who were diagnosed as TGCT and underwent F-FDG PET/CT for primary staging after surgery between 2009 and 2019 were evaluated retrospectively. In terms of the presence of F-FDG uptake consistent with metastasis, the patients were divided into two groups as 'PET-positive' and 'PET-negative'. In 'PET-positive' patients, highest maximum standardized uptake values of metastatic lesions, whole-body total metabolic tumor volumes (wb-TMTV) and total lesion glycolysis (wb-TLG) were extracted. Pathological tumor types, pathological T stages (pT), tumor marker (TM) levels (AFP, hCG, LDH) after orchiectomy and overall survival (OS) times in months were also recorded. The predictive value of variables for OS was evaluated using the Kaplan-Meier survival analysis.

RESULTS

PET positivity was observed in 28% of pT1 and in 83.3% in pT2-T3 tumors (P < 0.001). In the logistic regression analysis to predict 'PET positivity', pT stage and ≥2 elevated TMs were found as independent significant predictors. Survival analysis demonstrated that wb-TMTV, wb-TLG and TMs were significantly associated with prognosis for OS.

CONCLUSION

The likelihood of PET positivity was significantly higher in patients with elevated TMs and pT2-T3 stages compared to those with normal TMs and pT1 tumors. PET derived quantitative metabolic-volumetric parameters can be used as biomarkers to identify patients with poor prognosis in TGCT.