Tumour heterogeneity in glioblastoma assessed by MRI texture analysis: a potential marker of survival

Objective: The main objective of this retrospective work was the study of three-dimensional (3D) heterogeneity measures of post-contrast pre-operative MR images acquired with T1 weighted sequences of patients with glioblastoma (GBM) as predictors of clinical outcome. Methods: 79 patients from 3 hospitals were included in the study. 16 3D textural heterogeneity measures were computed including run-length matrix (RLM) features (regional heterogeneity) and co-occurrence matrix (CM) features (local heterogeneity). The significance of the results was studied using Kaplan?Meier curves and Cox proportional hazards analysis. Correlation between the variables of the study was assessed using the Spearman?s correlation coefficient. Results: Kaplan?Meyer survival analysis showed that 4 of the 11 RLM features and 4 of the 5 CM features considered were robust predictors of survival. The median survival differences in the most significant cases were of over 6 months. Conclusion: Heterogeneity measures computed on the post-contrast pre-operative T1 weighted MR images of patients with GBM are predictors of survival. Advances in knowledge: Texture analysis to assess tumour heterogeneity has been widely studied. However, most works develop a two-dimensional analysis, focusing only on one MRI slice to state tumour heterogeneity. The study of fully 3D heterogeneity textural features as predictors of clinical outcome is more robust and is not dependent on the selected slice of the tumour

Glioblastoma: does the pre-treatment geometry matter? A postcontrast T1 MRI-based study.

BACKGROUND The potential of a tumour's volumetric measures obtained from pretreatment MRI sequences of glioblastoma (GBM) patients as predictors of clinical outcome has been controversial. Mathematical models of GBM growth have suggested a relation between a tumour's geometry and its aggressiveness. METHODS A multicenter retrospective clinical study was designed to study volumetric and geometrical measures on pretreatment postcontrast T1 MRIs of 117 GBM patients. Clinical variables were collected, tumours segmented, and measures computed including: contrast enhancing (CE), necrotic, and total volumes; maximal tumour diameter; equivalent spherical CE width and several geometric measures of the CE "rim". The significance of the measures was studied using proportional hazards analysis and Kaplan-Meier curves. RESULTS Kaplan-Meier and univariate Cox survival analysis showed that total volume [p = 0.034, Hazard ratio (HR) = 1.574], CE volume (p = 0.017, HR = 1.659), spherical rim width (p = 0.007, HR = 1.749), and geometric heterogeneity (p = 0.015, HR = 1.646) were significant parameters in terms of overall survival (OS). Multivariable Cox analysis for OS provided the later two parameters as age-adjusted predictors of OS (p = 0.043, HR = 1.536 and p = 0.032, HR = 1.570, respectively). CONCLUSION Patients with tumours having small geometric heterogeneity and/or spherical rim widths had significantly better prognosis. These novel imaging biomarkers have a strong individual and combined prognostic value for GBM patients. KEY POINTS • Three-dimensional segmentation on magnetic resonance images allows the study of geometric measures. • Patients with small width of contrast enhancing areas have better prognosis. • The irregularity of contrast enhancing areas predicts survival in glioblastoma patients

Pseudomonas aeruginosa antibiotic susceptibility profiles, genomic epidemiology and resistance mechanisms: a nation-wide five-year time lapse analysisResearch in context

Summary: Background: Pseudomonas aeruginosa healthcare-associated infections are one of the top antimicrobial resistance threats world-wide. In order to analyze the current trends, we performed a Spanish nation-wide high-resolution analysis of the susceptibility profiles, the genomic epidemiology and the resistome of P. aeruginosa over a five-year time lapse. Methods: A total of 3.180 nonduplicated P. aeruginosa clinical isolates from two Spanish nation-wide surveys performed in October 2017 and 2022 were analyzed. MICs of 13 antipseudomonals were determined by ISO-EUCAST. Multidrug resistance (MDR)/extensively drug resistance (XDR)/difficult to treat resistance (DTR)/pandrug resistance (PDR) profiles were defined following established criteria. All XDR/DTR isolates were subjected to whole genome sequencing (WGS). Findings: A decrease in resistance to all tested antibiotics, including older and newer antimicrobials, was observed in 2022 vs 2017. Likewise, a major reduction of XDR (15.2% vs 5.9%) and DTR (4.2 vs 2.1%) profiles was evidenced, and even more patent among ICU isolates [XDR (26.0% vs 6.0%) and DTR (8.9% vs 2.6%)] (p < 0.001). The prevalence of Extended-spectrum β-lactamase/carbapenemase production was slightly lower in 2022 (2.1%. vs 3.1%, p = 0.064). However, there was a significant increase in the proportion of carbapenemase production among carbapenem-resistant strains (29.4% vs 18.1%, p = 0.0246). While ST175 was still the most frequent clone among XDR, a slight reduction in its prevalence was noted (35.9% vs 45.5%, p = 0.106) as opposed to ST235 which increased significantly (24.3% vs 12.3%, p = 0.0062). Interpretation: While the generalized decrease in P. aeruginosa resistance, linked to a major reduction in the prevalence of XDR strains, is encouraging, the negative counterpart is the increase in the proportion of XDR strains producing carbapenemases, associated to the significant advance of the concerning world-wide disseminated hypervirulent high-risk clone ST235. Continued high-resolution surveillance, integrating phenotypic and genomic data, is necessary for understanding resistance trends and analyzing the impact of national plans on antimicrobial resistance. Funding: MSD and the Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación and Unión Europea—NextGenerationEU