Literature DB >> 31867232

A novel neuroimaging assessment of predictive risk factors associated with intraoperative massive hemorrhage in intracranial solid hemangioblastoma.

Qiang Gao1, Lan Zhang2, Guoqing Wang1, Dingkang Xu1, Mengzhao Feng1, Fang Wang1, Qingjie Wei1, Xianzhi Liu1, Fuyou Guo1.   

Abstract

BACKGROUND: A solid hemangioblastoma (SH) is a benign and highly vascularized tumor. Microsurgical treatment of SH is still challenging due to excessive intraoperative bleeding.
METHODS: Sixty-six consecutive patients with SH were retrospectively analyzed. The volume of intraoperative blood loss (IBL) and the features detected by magnetic resonance imaging (MRI) were evaluated by a neurosurgeon and multiple neuroradiologists.
RESULTS: Four striking MRI features-peritumoral edema, the flow-void effect, large draining veins, and a visible feeding artery-were related to excessive IBL. Regarding the weighted values of these risk factors, the flow-void effect was the factor most significantly correlated with IBL (P<0.01, R=0.418). The feeding artery also contributed substantially to excessive IBL (P<0.05, R=0.412). The next most influential factor was the presence of large draining veins (P<0.05, R=0.350), followed by peritumoral edema (P<0.05, R=0.308). The four major risk factors-the flow-void effect, feeding arteries, large draining veins, and peritumoral edema-were assigned point values of 3, 3, 2, and 1, respectively, for a maximum total score of 9 points. A higher total score indicates that a higher volume of bleeding is more likely to occur during surgery.
CONCLUSIONS: This study reports the potential neuroimaging-based risk factors leading to abundant IBL in SH by neuroimaging assessment. The study proposes a novel scoring system to predict IBL, potentially decreasing the risk involved in the surgical treatment of SH. 2019 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Entities:  

Keywords:  Solid hemangioblastomas (SHs); intraoperative blood loss (IBL); neuroimaging assessment; neurosurgery; surgical risk prediction

Year:  2019        PMID: 31867232      PMCID: PMC6902149          DOI: 10.21037/qims.2019.09.05

Source DB:  PubMed          Journal:  Quant Imaging Med Surg        ISSN: 2223-4306


  20 in total

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