The identification of quantitative non-invasive imaging biomarkers, including radiomics, may complement molecular characterization and thereby improve clinical management of neuro-oncological patients. We aimed to identify imaging predictors with improved performance over clinical parameters to stratify patients with brain metastases into high and low-risk groups for overall survival (OS). 422 patients recruited by two neuro-oncological centers were included with first diagnosis of brain metastases from different primary tumors. From each patient, 15 clinical parameters and a total of 321 radiomic features extracted from cerebral MRI were employed in prediction models to classify patients into low- and high-risk groups for OS. The best performing model was a bootstrap aggregating model including only clinical features (test set: macro F-1 = 0.62, accuracy = 0.72), while the combined and radiomic datasets led to poorer results (test set: macro F-1 = 0.60, accuracy = 0.67; test set: macro F-1 = 0.62, accuracy = 0.52, respectively). However, in the subgroup of melanoma patients (n = 54), the radiomic dataset showed better predictive power over clinical and combined dataset (test set: macro F-1 score = 0.71, accuracy = 0.77). 80% and 67% of melanoma patients were correctly classified into the low- and the high-risk group for OS, respectively. Clinical features remained the strongest predictors of risk across patients with brain metastases from different primary tumors. Although, in melanoma patients, radiomic features provided better prediction of the survival outcome compared to clinical parameters alone.
J. Heugenhauser, Sabrina Herbst, T. Drucks et al.· Clinical and Experimental Me...· 0 citations
Background/Objectives: Neurological impairment after glioma resection is a common postoperative event, but many deficits improve during recovery. The present study investigated whether transient and persistent postoperative neurological deficits differ in their association with overall survival (OS) and progression-free survival (PFS). Methods: We retrospectively reviewed data from patients who underwent initial surgical treatment for glioma in our institution. Neurological function was evaluated using documented clinical examinations performed before surgery, in the immediate postoperative period, and during routine follow-up 3–6 months after the procedure. Results: The study cohort comprised 496 patients, of whom 44.4% were women. The mean age at surgery was 60 years (95% CI, 58–61), and the average follow-up period was 21 months (95% CI, 19–23). According to the 2021 WHO classification, 80.0% of tumors were grade 4, 11.1% were grade 3, and 7.3% were grade 2. IDH mutations were absent in 81% of cases. Median survival for the entire cohort was 34 months (95% CI, 30–38). Preoperative neurological deficits, including hemiparesis, were not significantly associated with OS. Postoperative deficits that were resolved by the follow-up assessment showed no relationship with either OS or PFS, irrespective of IDH mutation status. In contrast, neurological deficits that persisted at follow-up were independently associated with shorter OS and PFS among patients with IDH-wild-type gliomas (p < 0.001), whereas no significant association was observed in the IDH-mutant subgroup. Similarly, when new neurological deficits were present at follow-up, poorer OS and PFS were predicted only in patients with IDH-wild-type tumors (p < 0.001). Conclusions: Temporary neurological deterioration following glioma surgery does not appear to adversely influence overall or progression-free survival, regardless of IDH status. However, persistent postoperative deficits, as well as newly acquired deficits that remain evident during follow-up, are strong indicators of an unfavorable prognosis in patients with IDH-wild-type gliomas.
J. Klingenschmid, M. Demetz, N. Pichler et al.· Journal of Clinical Medicine· 0 citations
In this contemporary multicenter cohort of 201 patients, surgical resection of cerebellar metastases achieved a median survival of about one year, and functional status and systemic disease burden remain the strongest predictors of outcome.
T. Araceli, Matthias Demetz, J. Rösler et al.· Neuro-Oncology Advances· 0 citations