Automated Quantification of Reduced Sulcal Volume Identifies Early Brain Injury after Aneurysmal Subarachnoid Hemorrhage

Jane Y. Yuan, Yasheng Chen, Atul Kumar, Zach Zlepper, Keshav Jayaraman, Wint Y. Aung, Julian V. Clarke, Michelle Allen, Umeshkumar Athiraman, Joshua Osbun, Gregory J. Zipfel, Rajat Dhar

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Background and Purpose: Early brain injury may be a more significant contributor to poor outcome after aneurysmal subarachnoid hemorrhage (aSAH) than vasospasm and delayed cerebral ischemia. However, studying this process has been hampered by lack of a means of quantifying the spectrum of injury. Global cerebral edema (GCE) is the most widely accepted manifestation of early brain injury but is currently assessed only through subjective, qualitative or semi-quantitative means. Selective sulcal volume (SSV), the CSF volume above the lateral ventricles, has been proposed as a quantitative biomarker of GCE, but is time-consuming to measure manually. Here we implement an automated algorithm to extract SSV and evaluate the age-dependent relationship of reduced SSV on early outcomes after aSAH. Methods: We selected all adults with aSAH admitted to a single institution with imaging within 72 hours of ictus. Scans were assessed for qualitative presence of GCE. SSV was automatically segmented from serial CTs using a deep learning-based approach. Early SSV was the lowest SSV from all early scans. Modified Rankin Scale score of 4 to 6 at hospital discharge was classified as a poor outcome. Results: Two hundred forty-four patients with aSAH were included. Sixty-five (27%) had GCE on admission while 24 developed it subsequently within 72 hours. Median SSV on admission was 10.7 mL but frequently decreased, with minimum early SSV being 3.0 mL (interquartile range, 0.3-11.9). Early SSV below 5 mL was highly predictive of qualitative GCE (area under receiver-operating-characteristic curve, 0.90). Reduced early SSV was an independent predictor of poor outcome, with a stronger effect in younger patients. Conclusions: Automated assessment of SSV provides an objective biomarker of GCE that can be leveraged to quantify early brain injury and dissect its impact on outcomes after aSAH. Such quantitative analysis suggests that GCE may be more impactful to younger patients with SAH.

Original languageEnglish
Pages (from-to)1380-1389
Number of pages10
JournalStroke
DOIs
StateAccepted/In press - 2021

Keywords

  • brain edema
  • cerebrospinal fluid
  • deep learning
  • intracranial aneurysm
  • subarachnoid hemorrhage

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