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Updated: May 19, 2026
A Volumetric Method for Quantification of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage
Published on: July 28, 2018
Quantification of cerebral volumes on MRI 6 months after aneurysmal subarachnoid hemorrhage
Jeroen de Bresser1, Koen L Vincken, Anne J Kaspers
1Image Sciences Institute, Department of Neurology and Neurosurgery, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, The Netherlands. J.deBresser@umcutrecht.nl
Background And Purpose:
MRI can be used to assess structural damage to the brain after aneurysmal subarachnoid hemorrhage. We tuned, validated, and applied k-Nearest Neighbor-based segmentation to quantify cerebral volumes on MRI 6 months after aneurysmal subarachnoid hemorrhage.
Methods:
After tuning, the accuracy of k-Nearest Neighbor-based segmentation was assessed with manual segmentations. Next, supratentorial cerebral parenchymal, peripheral cerebrospinal fluid, and lateral ventricular volumes of 55 patients were compared with those of 25 age- and sex-matched control subjects and related to clinical outcome (modified Rankin Scale).
Results:
k-Nearest Neighbor-based segmentation showed good agreement with manual segmentations. Compared with control subjects, patients had a larger lateral ventricular volume (difference: log-transformed values 0.54; 95% CI,0.33-0.75), smaller peripheral cerebrospinal fluid volume (-26 mL; 95% CI, -40 to -11), and similar cerebral parenchymal volume (2 mL; 95% CI, -10 to 15). In patients, parenchymal (median split; OR, 38.8; 95% CI, 4.6-329.0) and ventricular volumes (7.4; 95% CI, 1.6-33.5) correlated with functional outcome.
Conclusions:
k-Nearest Neighbor-based segmentation provides accurate cerebral volume measurements after aneurysmal subarachnoid hemorrhage. In this proof-of-principle study of this volumetric technique, we demonstrated volume changes relative to controls, which correlated with functional outcome.
Insights
k-Nearest Neighbor segmentation accurately quantifies brain volumes after aneurysmal subarachnoid hemorrhage. Ventricular and parenchymal volumes correlated with patient functional outcomes, aiding in prognosis.
Area of Science:
- Neuroimaging
- Radiology
- Medical Image Analysis
Background:
- Aneurysmal subarachnoid hemorrhage (aSAH) causes structural brain damage.
- Magnetic Resonance Imaging (MRI) is crucial for assessing this damage.
- Quantifying cerebral volumes aids in understanding long-term effects.
Purpose of the Study:
- To tune, validate, and apply k-Nearest Neighbor (k-NN) segmentation for cerebral volume quantification.
- To assess the accuracy of k-NN segmentation against manual methods.
- To compare cerebral volumes in aSAH patients with controls and relate them to clinical outcomes.
Main Methods:
- k-NN segmentation algorithm was tuned and validated using manual segmentations.
- Supratentorial cerebral parenchymal, peripheral cerebrospinal fluid (CSF), and lateral ventricular volumes were measured.
- Volumes were compared between 55 aSAH patients and 25 controls, and correlated with modified Rankin Scale scores.
Main Results:
- k-NN segmentation demonstrated good agreement with manual segmentations.
- aSAH patients showed larger lateral ventricular volumes and smaller peripheral CSF volumes compared to controls.
- Parenchymal and ventricular volumes in patients correlated significantly with functional outcomes.
Conclusions:
- k-NN based segmentation is an accurate method for measuring cerebral volumes post-aSAH.
- This volumetric technique reveals significant brain volume changes in aSAH patients.
- Observed volume changes correlate with functional recovery, offering prognostic value.
