Preservation of cognition is an important outcome measure in eloquent area glioma surgery. Glioma patients may have pre-operative deficits in one or more cognitive domains which could deteriorate post-operatively. It is assumed that these impairments recover within 3 months; some studies however, still detected cognitive decline. Longer follow-up is necessary to elucidate the conclusive effects of surgery. 45 patients with gliomas (low- and high-grade, but without contrast enhancement at diagnosis) in eloquent areas were assessed pre-operatively, 3 months and 1 year post-operatively with a neuropsychological test-protocol. Patients' performance was compared to normal population and between test-moments. Univariate analyses were performed between cognitive change and tumor-characteristics (localization, grade, volume, extent of resection [EOR]) and treatment-related factors (radio-/chemotherapy). Pre- and post-operatively, impairments were found in all cognitive domains; language, memory, attention and executive functions (p < 0.05). Post-operatively, permanent improvement was observed on a memory test (verbal recall: t = -1.931, p = 0.034), whereas deterioration was found on a language test (category fluency: t = 2.517, p = 0.030). Between 3 months and 1 year, patients improved on 2 language tests (naming: t = -2.781, p = 0.026 and letter fluency: t = -1.975, p = 0.047). There was no influence of tumor- or treatment-related factors on cognitive change. The findings underline the importance of cognitive testing at longer term post-operatively, as cognitive recovery took longer than 3 months, especially within the language domain. However, this longitudinal follow-up study showed that glioma surgery is possible without major long-term damage of cognitive functions. Tumor characteristics and EOR are no additional risk factors for cognitive outcome.
Tumour-related cognitive deficits are present in a majority of HGG patients preceding surgery. Surgery does not result in cognitive deterioration in the short term in most patients.
Treatment decisions for patients with presumed glioblastoma are based on tumor characteristics available from a preoperative MR scan. Tumor characteristics, including volume, location, and resectability, are often estimated or manually delineated. This process is time consuming and subjective. Hence, comparison across cohorts, trials, or registries are subject to assessment bias. In this study, we propose a standardized Glioblastoma Surgery Imaging Reporting and Data System (GSI-RADS) based on an automated method of tumor segmentation that provides standard reports on tumor features that are potentially relevant for glioblastoma surgery. As clinical validation, we determine the agreement in extracted tumor features between the automated method and the current standard of manual segmentations from routine clinical MR scans before treatment. In an observational consecutive cohort of 1596 adult patients with a first time surgery of a glioblastoma from 13 institutions, we segmented gadolinium-enhanced tumor parts both by a human rater and by an automated algorithm. Tumor features were extracted from segmentations of both methods and compared to assess differences, concordance, and equivalence. The laterality, contralateral infiltration, and the laterality indices were in excellent agreement. The native and normalized tumor volumes had excellent agreement, consistency, and equivalence. Multifocality, but not the number of foci, had good agreement and equivalence. The location profiles of cortical and subcortical structures were in excellent agreement. The expected residual tumor volumes and resectability indices had excellent agreement, consistency, and equivalence. Tumor probability maps were in good agreement. In conclusion, automated segmentations are in excellent agreement with manual segmentations and practically equivalent regarding tumor features that are potentially relevant for neurosurgical purposes. Standard GSI-RADS reports can be generated by open access software.
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