ObjectivesTo develop and validate a radiomics nomogram combining radiomics features and clinical factors for preoperative evaluation of Ki-67 expression status and prognostic prediction in clear cell renal cell carcinoma (ccRCC).MethodsTwo medical centers of 185 ccRCC patients were included, and each of them formed a training group (n = 130) and a validation group (n = 55). The independent predictor of Ki-67 expression status was identified by univariate and multivariate regression, and radiomics features were extracted from the preoperative CT images. The maximum relevance minimum redundancy (mRMR) and the least absolute shrinkage and selection operator algorithm (LASSO) were used to identify the radiomics features that were most relevant for high Ki-67 expression. Subsequently, clinical model, radiomics signature (RS), and radiomics nomogram were established. The performance for prediction of Ki-67 expression status was validated using area under curve (AUC), calibration curve, Delong test, decision curve analysis (DCA). Prognostic prediction was assessed by survival curve and concordance index (C-index).ResultsTumour size was the only independent predictor of Ki-67 expression status. Five radiomics features were finally identified to construct the RS (AUC: training group, 0.821; validation group, 0.799). The radiomics nomogram achieved a higher AUC (training group, 0.841; validation group, 0.814) and clinical net benefit. Besides, the radiomics nomogram provided a highest C-index (training group, 0.841; validation group, 0.820) in predicting prognosis for ccRCC patients.ConclusionsThe radiomics nomogram can accurately predict the Ki-67 expression status and exhibit a great capacity for prognostic prediction in patients with ccRCC and may provide value for tailoring personalized treatment strategies and facilitating comprehensive clinical monitoring for ccRCC patients.

Objective:To investigate the prognostic value of primary and metastatic metabolic parameters of 18F-fluorodeoxyglucose(FDG) PET/CT imaging before chemoradiotherapy in patients with esophageal squamous cell carcinoma (ESCC). Methods:A retrospective analysis was performed on 106 patients [98 males, 8 females, aged (63.9±8.8) years] with metastatic ESCC who received radiochemotherapy and underwent 18F-FDG PET/CT from November 2013 to April 2021 in the Affiliated Hospital of Qingdao University. Clinical factors included age, sex, primary location, clinical stage, degree of differentiation, and treatment. Using 40% maximum standardized uptake value (SUV max) as the threshold, delineate the region of interest (ROI) of the primary and metastatic lesions of esophageal cancer before treatment. Metabolic parameters included SUV max of primary lesion, metabolic tumor volume (MTV) of primary lesion (MTV p), total lesion glycolysis (TLG) of primary lesion (TLG p), MTV of whole body (MTV wb), TLG of whole body (TLG wb), and SUV max, MTV, TLG ratio of metastatic lesion to primary lesion (R-SUV max, R-MTV, R-TLG). Kaplan-Meier method and Log-Rank test were used for univariate analysis and multivariate analysis was conducted by Cox proportional hazards model to predict the prognostic factors affecting progression-free survival (PFS) and overall survival (OS) of patients. Results:Univariate analysis showed that T stage, MTV p, TLG p, MTV wb, TLG wb and R-TLG were prognostic factors for PFS and OS in ESCC patients receiving chemoradiotherapy ( χ2=4.105-27.992, all P<0.05). Multivariate analysis showed that T stage and R-TLG were independent prognostic factors for PFS ( HR=2.210, 95% CI: 1.307-3.737, P=0.003; HR=3.118, 95% CI: 1.414-6.875, P=0.005) and OS ( HR=1.885, 95% CI: 1.072-3.317, P=0.028; HR= 2.584, 95% CI: 1.186-5.629, P=0.017) in ESCC patients. Combined with T stage and R-TLG, the patients were divided into low-risk, medium-risk and high-risk groups. The results showed that there were statistically significant differences in PFS and OS among the groups ( χ2=38.392, 19.857; both P<0.001). Conclusion:T stage and 18F-FDG PET/CT metabolic parameter R-TLG were independent prognostic factors for PFS and OS in ESCC patients before chemoradiotherapy.

Objective:To investigate the value of 18F-FDG PET/CT imaging signs and metabolic parameters in predicting tumor spread through air spaces (STAS) of stage Ⅰ lung adenocarcinoma. Methods:From January 2019 to December 2021, clinical, imaging and metabolic parameters of 381 patients (126 males, 255 females, age (61.2±9.2) years) with stage Ⅰ lung adenocarcinoma were retrospectively analyzed in the Affiliated Hospital of Qingdao University. According to the postoperative pathological results, patients were divided into STAS positive group and STAS negative group. According to the operation time, patients were divided into training set ( n=254) and verification set ( n=127). χ2 test or Mann-Whitney U test was used to compare the differences of different parameters between patients with STAS positive and negative, and binary logistic regression analysis was used to select the predictors of STAS status. The prediction model was established, and ROC curve was used to evaluate the predictive efficacy. Results:There were 49(19.3%, 49/254) patients with STAS positive and 205(80.7%, 205/254) patients with STAS negative in the training set, while those were 35(27.6%, 35/127) and 92(72.4%, 92/127) in the verification set. In the training set, the differences of age ( z=-2.30, P=0.021), type of lesions ( χ2=6.81, P=0.009), spiculation ( χ2=12.64, P<0.001), bronchus truncation ( χ2=6.98, P=0.008), ground glass ribbon sign ( χ2=26.93, P<0.001) and SUV max ( z=-4.62, P<0.001) between the two groups were statistically significant. Multivariate logistic regression analysis showed that age (odds ratio ( OR)=1.048, 95% CI: 1.004-1.094, P=0.032), ground glass ribbon sign ( OR=3.857, 95% CI: 1.693-8.788, P=0.001) and SUV max ( OR=1.133, 95% CI: 1.001-1.282, P=0.049) were independent predictors of STAS status in stage Ⅰ lung adenocarcinoma patients. The logistic regression model was P=1/(1+ e - x), x=-5.292+ 0.480×age (year)+ 1.493×ground glass ribbon sign+ 0.170×SUV max. The AUCs of the model in the training set and verification set were 0.770 and 0.801, with the sensitivity of 81.6%(40/49) and 82.9%(29/35), and the specificity of 69.8%(143/205) and 65.2%(60/92), respectively. Conclusion:Age, ground glass ribbon sign and SUV max have good predictive effects on the occurrence of STAS in stage Ⅰ lung adenocarcinoma.

Abstract Purpose To investigate the prognostic value of baseline 18F-FDG PET/CT in patients with esophageal squamous cell carcinoma (ESCC) treated with definitive (chemo)radiotherapy. Methods A total of 98 ESCC patients with cTNM stage T1-4, N1-3, M0 who received definitive (chemo)radiotherapy after 18F-FDG PET/CT examination from December 2013 to December 2020 were retrospectively analyzed. Clinical factors included age, sex, histologic differentiation grade, tumor location, clinical stage, and treatment strategies. Parameters obtained by 18F-FDG PET/CT included SUVmax of primary tumor (SUVTumor), metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUVmax of lymph node (SUVLN), PET positive lymph nodes (PLNS) number, the shortest distance between the farthest PET positive lymph node and the primary tumor in three-dimensional space after the standardization of the patient BSA (SDmax(LN-T)). Univariate and multivariate analysis was conducted by Cox proportional hazard model to explore the significant factors affecting overall survival (OS) and progression-free survival (PFS) in ESCC patients. Results Univariate analysis showed that tumor location, SUVTumor, MTV, TLG, PLNS number, SDmax (LN-T) were significant predictors of OS and tumor location, and clinical T stage, SUVTumor, MTV, TLG, SDmax (LN-T) were significant predictors of PFS (all p < 0.1). Multivariate analysis showed that MTV and SDmax (LN-T) were independent prognostic factors for OS (HR = 1.018, 95% CI 1.006–1.031; p = 0.005; HR = 6.988, 95% CI 2.119–23.042; p = 0.001) and PFS (HR = 1.019, 95% CI 1.005–1.034; p = 0.009; HR = 5.819, 95% CI 1.921–17.628; p = 0.002). Combined with independent prognostic factors MTV and SDmax (LN-T), we can further stratify patient risk. Conclusions Before treatment, 18F-FDG PET/CT has important prognostic value for patients with ESCC treated with definitive (chemo)radiotherapy. The lower the value of MTV and SDmax (LN-T), the better the prognosis of patients.

Abstract Background To compare the clinical value of recombinant human granulocyte colony-stimulating factor (rhG-CSF) and pegylated rhG-CSF(PEG-rhG-CSF) in early-stage breast cancer (EBC) patients receiving adjuvant chemotherapy, compare the efficacy of PEG-rhG-CSF with different dose and explore the timing of rhG-CSF rescue treatment. Methods Patients in two PEG-rhG-CSF subgroups were given 3 mg or 6 mg PEG-rhG-CSF within 24 ~ 48 h after chemotherapy for preventing myelosuppression, while patients in the rhG-CSF group were given rhG-CSF. Observation indicators include the incidence of febrile neutropenia (FN) and grade 3/4 chemotherapy-induced-neutropenia (CIN), the overall levels and nadir values of white blood cells (WBC) and absolute neutrophil count (ANC), comparison of WBC and ANC curves over time, the incidence of CIN-related complications, the incidence of adverse events in each group and the timing of rescue treatment for rhG-CSF. Results There was no significant difference in the incidence of FN in the first cycle among the groups (P = 0.203). But the incidence of ≥ 3 grade CIN in two PEG-rhG-CSF subgroups was significantly lower than that in the rhG-CSF group (P < 0.001). The overall WBC and ANC levels in the PEG-rhG-CSF group were significantly higher than those in the rhG-CSF group (P < 0.001). In terms of CIN-related complications, less chemotherapy delay rate (1.1 vs. 7.5%, P = 0.092), less dose reduction rate (6.9 vs. 7.5%, P = 1.000), less antibiotic use rate (3.4 vs. 17.5%, P = 0.011) and less proportion of rhG-CSF rescue therapy (24.1 vs. 85.0%, P < 0.001) in the PEG-rhG-CSF group, and there were no significant differences between PEG-rhG-CSF subgroups. In the incidence of adverse events among the groups, there were no statistical differences. All patients undergoing rhG-CSF rescue treatment were mainly 4 grade (63.6%) and 3 grade (25.5%) CIN, and 10.9% of patients with 1 ~ 2 grade CIN who had high infection risk or had been infected. Conclusion PEG-rhG-CSF has better efficacy and equal tolerance compared with rhG-CSF in preventing CIN in EBC patients receiving EC regimen. Moreover, a half-dose 3 mg PEG-rhG-CSF also had good efficacy. Last, patients with ≥ 3 grade CIN and others who have been assessed to be at high risk of infection or have co-infection should consider rhG-CSF or even antibiotic rescue treatment.

OBJECTIVES:The aim of the study was to evaluate the association between the radiomics-based intratumoral heterogeneity (ITH) and the recurrence risk in hepatocellular carcinoma (HCC) patients after liver transplantation (LT), and to assess its incremental to the Milan, University of California San Francisco (UCSF), Metro-Ticket 2.0, and Hangzhou criteria. METHODS:A multicenter cohort of 196 HCC patients were investigated. The endpoint was recurrence-free survival (RFS) after LT. A CT-based radiomics signature (RS) was constructed and assessed in the whole cohort and in the subgroups stratified by the Milan, UCSF, Metro-Ticket 2.0, and Hangzhou criteria. The R-Milan, R-UCSF, R-Metro-Ticket 2.0, and R-Hangzhou nomograms which combined RS and the four existing risk criteria were developed respectively. The incremental value of RS to the four existing risk criteria in RFS prediction was evaluated. RESULTS:RS was significantly associated with RFS in the training and test cohorts as well as in the subgroups stratified by the existing risk criteria. The four combined nomograms showed better predictive capability than the existing risk criteria did with higher C-indices (R-Milan [training/test] vs. Milan, 0.745/0.765 vs. 0.677; R-USCF vs. USCF, 0.748/0.767 vs. 0.675; R-Metro-Ticket 2.0 vs. Metro-Ticket 2.0, 0.756/0.783 vs. 0.670; R-Hangzhou vs. Hangzhou, 0.751/0.760 vs. 0.691) and higher clinical net benefit. CONCLUSIONS:The radiomics-based ITH can predict outcomes and provide incremental value to the existing risk criteria in HCC patients after LT. Incorporating radiomics-based ITH in HCC risk criteria may facilitate candidate selection, surveillance, and adjuvant trial design. KEY POINTS:• Milan, USCF, Metro-Ticket 2.0, and Hangzhou criteria may be insufficient for outcome prediction in HCC after LT. • Radiomics allows for the characterization of tumor heterogeneity. • Radiomics adds incremental value to the existing criteria in outcome prediction.

Complex interactions occur between tumor cells and the tumor microenvironment. Studies have focused on the mechanism of metabolic symbiosis between tumors and the tumor microenvironment. During tumor development, the metabolic pattern undergoes significant changes, and the optimal metabolic mode of the tumor is selected on the basis of its individual environment. Tumor cells can adapt to a specific microenvironment through metabolic adjustment to achieve compatibility. In this study, the effects of tumor glucose metabolism, lipid metabolism, and amino acid metabolism on the tumor microenvironment and related mechanisms were reviewed. Selective targeting of tumor cell metabolic reprogramming is an attractive direction for tumor therapy. Understanding the mechanism of tumor metabolic adaptation and determining the metabolism symbiosis mechanism between tumor cells and the surrounding microenvironment may provide a new approach for treatment, which is of great significance for accelerating the development of targeted tumor metabolic drugs and administering individualized tumor metabolic therapy.