Panciani, Pier Paolo

Background: Multiple radiomics models have been proposed for grading glioma using different algorithms, features, and sequences of magnetic resonance imaging. The research seeks to assess the present overall performance of radiomics for grading glioma. Methods: A systematic literature review of the databases Ovid MEDLINE PubMed, and Ovid EMBASE for publications published on radiomics for glioma grading between 2012 and 2023 was performed. The systematic review was carried out following the criteria of Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Results: In the meta-analysis, a total of 7654 patients from 40 articles, were assessed. R-package mada was used for modeling the joint estimates of specificity (SPE) and sensitivity (SEN). Pooled event rates across studies were performed with a random-effects meta-analysis. The heterogeneity of SPE and SEN were based on the χ2 test. Overall values for SPE and SEN in the differentiation between high-grade gliomas (HGGs) and low-grade gliomas (LGGs) were 84% and 91%, respectively. With regards to the discrimination between World Health Organization (WHO) grade 4 and WHO grade 3, the overall SPE was 81% and the SEN was 89%. The modern non-linear classifiers showed a better trend, whereas textural features tend to be the best-performing (29%) and the most used. Conclusions: Our findings confirm that present radiomics’ diagnostic performance for glioma grading is superior in terms of SEN and SPE for the HGGs vs. LGGs discrimination task when compared to the WHO grade 4 vs. 3 task.

Background/Objectives: Tuberculum sellae meningiomas (TSMs) constitute 5–10% of intracranial meningiomas, often causing visual impairment. Traditional microsurgical transcranial approaches (MTAs) have been effective, but the emergence of innovative surgical trajectories, such as endoscopic endonasal approaches (EEAs), has sparked debate. While EEAs offer advantages like reduced brain retraction, they are linked to higher cerebrospinal fluid leak (CSF leak) risk. This meta-analysis aims to comprehensively compare the efficacy and safety of EEAs and MTAs for the resection of TSMs, offering insights into their respective outcomes and complications. Methods: A comprehensive literature review of the databases PubMed, Ovid MEDLINE, and Ovid EMBASE was conducted for articles published on TSMs treated with either EEA or MTA until 2024. The systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Meta-analysis was performed to estimate pooled event rates and assess heterogeneity. Fixed- and random-effects were used to assess 95% confidential intervals (CIs) of presenting symptoms, outcomes, and complications. Results: A total of 291 papers were initially identified, of which 18 studies spanning from 2000 to 2024 met the inclusion criteria. The exclusion of 180 articles was due to reasons such as irrelevance, non-reporting of selected results, systematic literature review or meta-analysis, and a lack of details on method/results. The 18 studies comprised a total sample of 1093 patients: 444 patients who underwent EEAs and 649 patients who underwent MTAs for TSMs. Gross total resection (GTR) rates ranged from 80.9% for EEAs to 79.8% for MTAs. The rate of visual improvement was 86.6% in the EEA group and 65.4% in the MTA group. The recurrence rate in the EEA group was 6.9%, while it was 5.1% in MTA group. The postoperative complications analyzed were CSF leak, infections, dysosmia, intracranial hemorrhage (ICH), and endocrine disorders. The rate of CSF leak was 9.8% in the EEA group and 2.1% in MTA group. The rate of infections in the EEA group was 5.7%, while it was 3.7% in the MTA group. The rate of dysosmia ranged from 10.3% for MTAs to 12.9% for EEAs. The rate of ICH in the EEA group was 0.9%, while that in the MTA group was 3.8%. The rate of endocrine disorders in the EEA group was 10.8%, while that in the MTA group was 10.2%. No significant difference was detected in the rate of GTR between the EEA and MTA groups (OR 1.15, 95% CI 0.7–0.95; p = 0.53), while a significant benefit in visual outcomes was shown in EEAs (OR 3.54, 95% CI 2.2–5.72; p < 0.01). There was no significant variation in the recurrence rate between EEA and MTA groups (OR 0.92, 95% CI 0.19–4.46; p = 0.89). While a considerably increased chance of CSF leak from EEAs was shown (OR 4.47, 95% CI 2.52–7.92; p < 0.01), no significant difference between EEA and MTA groups was detected in the rate of infections (OR 1.92, 95% CI 0.73–5.06; p = 0.15), the rate of dysosmia (OR 1.25, 95% CI 0.31–4.99; p = 0.71), the rate of ICH (OR 0.61, 95% CI 0.20–1.87; p = 0.33), and the rate of endocrine disorders (OR 1.16, 95% CI 0.69–1.95; p = 0.53). Conclusions: This meta-analysis suggests that both EEAs and MTAs are viable options for TSM resection, with distinct advantages and drawbacks. The EEAs demonstrate superior visual outcomes in selected cases while GTR and recurrence rates support the overall effectiveness of MTAs and EEAs. Endoscopic endonasal approaches had a higher chance of CSF leaks, but there are no appreciable variations in other complications. These results provide additional insights regarding patient outcomes in the intricate clinical setting of TSMs.

Abstract Purpose: Numerous radiomics-based models have been proposed to discriminate between central nervous system (CNS) gliomas and primary central nervous system lymphomas (PCNSLs). Given the heterogeneity of the existing models, we aimed to define their overall performance and identify the most critical variables to pilot future algorithms. Methods: A systematic review of the literature and a meta-analysis were conducted, focusing on studies reporting on radiomics to differentiate gliomas from PCNSLs. A comprehensive literature search was performed through PubMed, Ovid MEDLINE, Ovid EMBASE, Web of Science, and Scopus databases. Overall sensitivity (SEN) and specificity (SPE) were estimated. Event rates were pooled using a random-effects meta-analysis, and the heterogeneity was assessed using the χ2 test. Results: The overall SEN and SPE for differentiation between CNS gliomas and PCNSLs were 88% (95% CI = 0.83 – 0.91) and 87% (95% CI = 0.83 – 0.91), respectively. The best-performing features were the Gray Level Run Length Matrix (GLRLM; ACC 97%), followed by the Neighboring Gray Tone Difference Matrix (NGTDM; ACC 93%), and shape-based features (ACC 91%). The 18F-FDG-PET/CT was the best-performing imaging modality (ACC 97%), followed by the MRI CE-T1W (AUC 87% - 95%). Most studies applied a cross-validation analysis (92%). Conclusion: The current SEN and SPE of radiomics to discriminate CNS gliomas from PCNSLs are high, making radiomics a helpful method to differentiate these tumor types. The best-performing features are the GLRLM, NGTDM, and shape-based features. The 18F-FDG-PET/CTimaging modality is the best-performing, while the MRI CE-T1W is the most used.