Compactness index: a radiosurgery outcome predictor for patients with unruptured brain arteriovenous malformations

Po-Wei Huang, Syu-Jyun Peng, David Hung-Chi Pan, Huai-Che Yang, Jo-Ting Tsai, Cheng-Ying Shiau, I-Chang Su, Ching-Jen Chen, Hsiu-Mei Wu, Chung Jung Lin, Wen-Yuh Chung, Wan-Yuo Guo, Wei-Lun Lo, Shao-Wen Lai, Cheng-Chia Lee

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

OBJECTIVE
The goal of the study was to define and quantify brain arteriovenous malformation (bAVM) compactness and to assess its effect on outcomes after Gamma Knife radiosurgery (GKRS) for unruptured bAVMs.

METHODS
Unsupervised machine learning with fuzzy c-means clustering was used to differentiate the tissue constituents of bAVMs on T2-weighted MR images. The percentages of vessel, brain, and CSF were quantified. The proposed compactness index, defined as the ratio of vasculature tissue to brain tissue, categorized bAVM morphology into compact, intermediate, and diffuse types according to the tertiles of this index. The outcomes of interest were complete obliteration and radiation-induced changes (RICs).
Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalJournal of Neurosurgery
DOIs
Publication statusPublished - 2022

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