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Purpose: This study was conducted to assess the relationship and prognostic significance between preoperative serum albumin to globulin ratio (AGR) and high-resolution computed tomography (HRCT) features of non-small cell lung cancer (NSCLC).Materials and Methods: Demographic parameters, laboratory values including AGR and other clinical variables were evaluated in 180 patients with NSCLC, and 72 of these patients had results of radiology parameters detected with HRCT [including emphysema, tumor disappearance rate (TDR), CT values and CT enhanced values of the tumor mass] were assessed for survival analyses. The 72 patients were divided into two groups: normal lung group and emphysema group. The discriminatory values for AGR between these two groups were assessed by Mann-Whitney U test The relationship between TDR and AGR in NSCLC patients was evaluated by Pearson correlation analysis.Results: In multivariate analysis, TDR (p = 0.033), AGR (p = 0.038), emphysema (p = 0.009), and N stage (P = 0.026) were independent predictors of overall survival (OS). AGR was higher in NSCLC patients without emphysema than NSCLC patients with emphysema (z = -2.979, P = 0.003). TDR demonstrated that there was a positive relationship with AGR (r = 0.307, p = 0.009). A nomogram with AGR, TDR, emphysema, and N stage was established to predict 5-year survival.Conclusions: There is a relationship between CT features and AGR in NSCLC. The integrative nomogram combined with CT images, clinical and hematologic features improved survival prediction in NSCLC patients, which offers a non-invasive, comprehensive, and convenient evaluation for individualized management of NSCLC patients. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the midterm efficacy and prognostic evaluation of patients with diffuse large B-cell lymphoma (DLBCL) by three image analysis methods: International Harmonization Project (IHP), Deauville 5-Point Scale (5-PS) and Δ SUVmax criteria in 18F-FDG PET/CT.Methods: This was a retrospective analysis of 141 patients with DLBCL. All patients were given 3-4 cycles of chemotherapy and 18F-FDG PET/CT. According to three criteria, the patients were divided into negative and positive groups, respectively. Statistical methods were used to assess the midterm efficacy and prognosis factors.Results: During the midterm follow-up, a total of 109 people achieved CR. Three methods showed statistically significant differences in OS and PFS for the interim PET/CT, and Δ SUVmax criterion was an independent risk factor for the prognosis of DLBCL patients.Conclusion: In our research, IHP, 5-PS and Δ SUVmax criteria all had a significant predictive value, while Δ SUVmax criterion had more advantages in evaluating the midterm efficacy and predicting prognosis for patients with DLBCL in interim PET/CT. But it should be noticed that Δ SUVmax criterion needs more strict guidelines in multicenter trials. The optimal cutoff value of Δ SUVmax% we recommended was 81.54%, which helped to judge the midterm efficacy. [ABSTRACT FROM AUTHOR]

Purpose: On MR imaging, peritumoral T2 hyperintensity surrounding glioblastoma is known to contain tumor cell infiltrates, thus contributing to poor prognosis. This study aimed to determine the incremental prognostic value of radiomics on peritumoral T2 hyperintensity in pretreatment glioblastoma.Methods: One hundred fourteen pathologically confirmed glioblastoma patients were retrospectively selected from March 2008 to May 2018 (our institution, n = 61; the Cancer Imaging Archive, n = 53). All patients were randomly divided into either training (n = 80) or test set (n = 34). Manually segmented peritumoral T2 hyperintensity yielded 106 radiomic features per patient. A random forest variable selection was used to select the most relevant radiomic features. Four Cox proportional hazards models were fitted with clinical features, clinical features with tumor/peritumoral volumes, radiomics, and all of them combined. Kaplan-Meier survival curves of the models were plotted with log-rank tests. All models were validated on a test set using prediction error curves over survival times.Results: A random forest variable selection yielded five relevant features among the 106 radiomic features (two shape, two gray-level and one first order features). These radiomic features increased survival prediction accuracy when they were added onto clinical and tumor/peritumoral volumetric features (combined model, P = 0.011). On test set, the combined model showed lower mean survival prediction error rate (0.14) than clinical (0.191) or radiomic (0.178) model.Conclusions: The clinical model with radiomic features demonstrated improved survival predictive performance than the model without radiomic features, thus suggesting incremental prognostic value of peritumoral radiomics as MR imaging biomarker in pretreatment glioblastoma. [ABSTRACT FROM AUTHOR]