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Primary and metastatic brain tumors can overlap in traditional imaging features detected on preoperative conventional magnetic resonance imaging (MRI). The research objective was to determine whether morphological vascular characteristics present in routine preoperative imaging using traditional MRI sequences are predictive of primary versus metastatic brain tumors; secondarily to determine association of conventional and vascular-related imaging parameters with intraoperative blood loss, pathological invasion, and World Health Organization (WHO) tumor grade. A retrospective review analyzed 100 consecutive intracranial tumor surgeries, 50 WHO grade II-IV gliomas and 50 intracranial metastases. Two blinded expert readers independently evaluated preoperative MRIs, obtained via standard morphological imaging sequences, for adjacent or intra-tumoral arterial aneurysm, peritumoral venous ectasia, prominence, or engorgement ("aberrant peritumoral vessels"), and prominent intra-tumoral flow voids. Multivariate analysis was performed to develop models predictive of glioma and glioblastoma (GBM). Aberrant peritumoral vessels and prominent intra-tumoral flow voids were statistically significant predictors of glioma in univariate analyses (p = 0.048, p = 0.001, respectively) and when combined in multivariate analysis (OR = 5.23, p = 0.001), particularly for GBM (OR = 9.08, p < 0.001). Multivariate modeling identified prominent intra-tumoral flow voids and FLAIR invasion as the strongest combined predictors of gliomas and GBM. Aberrant peritumoral vessels and larger tumor volume predicted higher intraoperative blood loss in all analyses. No vascular-related parameters predicted pathological invasion on multivariate analysis. Aberrant peritumoral vessels and prominent intra-tumoral flow voids were predictive of gliomas, specifically GBM. These vascular characteristics, evaluated on routine clinical preoperative MRI imaging, may aid in distinguishinggliomafrom brainmetastases andmay predict intraoperative blood loss.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10947781 | PMC |
| http://dx.doi.org/10.1016/j.jocn.2020.04.051 | DOI Listing |
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