Quilis-Quesada, Vicent

Abstract Background Precise delineation of non-contrast-enhancing tumor (nCET) in glioblastoma (GB) is critical for maximal safe resection, yet routine imaging cannot reliably separate infiltrative tumor from vasogenic edema. The aim of this study was to develop and validate an automated method to identify peritumoral subregions compatible with nCET and assess its prognostic value. Methods Pre-operative T2-weighted and FLAIR MRI from 940 patients with newly diagnosed GB in four multicenter cohorts were analyzed. A deep-learning model segmented enhancing tumor, edema and necrosis; a non-local, spatially varying finite mixture model was applied to identify edema subregions characterized by relatively lower FLAIR hyperintensity, hypothesized to reflect nCET-related tissue. The ratio of these subregions to total edema volume defined the T2/FLAIR Heterogeneity Index (TFHI). Associations between TFHI and overall survival (OS) were examined with Kaplan–Meier curves and multivariable Cox regression. Results Higher TFHI values stratified patients with shorter OS. In the NCT03439332, TFHI above the optimal threshold was associated with a twofold increased hazard of death (hazard ratio [HR] 2.07, 95 % confidence interval 1.33-3.21; P = .0013) and a reduction in median survival of 98 days. Significant, though smaller, prognostic effects were confirmed in GLIOCAT & BraTS (HR= 1.37; P = .047), OUS (HR = 1.37; P = .0032) and pooled analysis (HR= 1.26; P = .0008). TFHI remained an independent predictor after adjustment for age, extent of resection and MGMT methylation. Conclusions We present a reproducible, server-hosted tool for automated identification of imaging-defined, putative nCET-related peritumoral subregions and TFHI biomarker extraction that enables independent prognostic stratification. This approach provides a quantitative framework for studying peritumoral heterogeneity in GB.

Abstract BACKGROUND The Smith-Robinson 1 approach (SRA) is the most widely used route to access the anterior cervical spine. Although several authors have described this approach, there is a lack of the stepwise anatomic description of this operative technique. With the advent of new technologies in neuroanatomy education, such as volumetric models (VMs), the understanding of the spatial relation of the different neurovascular structures can be simplified. OBJECTIVE To describe the anatomy of the SRA through the creation of VMs of anatomic dissections. METHODS A total of 4 postmortem heads and a cervical replica were used to perform and record the SRA approach to the C4-C5 level. The most relevant steps and anatomy of the SRA were recorded using photogrammetry to construct VM. RESULTS The SRA was divided into 6 major steps: positioning, incision of the skin, platysma, and muscle dissection with and without submandibular gland eversion and after microdiscectomy with cage positioning. Anatomic model of the cervical spine and anterior neck multilayer dissection was also integrated to improve the spatial relation of the different structures. CONCLUSION In this study, we review the different steps of the classic SRA and its variations to different cervical levels. The VMs presented allow clear visualization of the 360-degree anatomy of this approach. This new way of representing surgical anatomy can be valuable resources for education and surgical planning.