title: A segmentation-based volumetric approach to localize and quantify cerebral vasospasm based on tomographic imaging data.
abstract: BACKGROUND
  Quantification of cerebral vasospasm after subarachnoid hemorrhage (SAH) is crucial in animal studies as well as clinical routine. We have developed a method for computer-based volumetric assessment of intracranial blood vessels from cross-sectional imaging data. Here we demonstrate the quantification of vasospasm from micro computed tomography (micro-CT) data in a rodent SAH model and the transferability of the volumetric approach to clinical data.
  
  
  METHODS
  We obtained rodent data by performing an ex vivo micro-CT of murine brains after sham surgery or SAH by endovascular filament perforation on day 3 post hemorrhage. Clinical CT angiography (CTA) was performed for diagnostic reasons unrelated to this study. We digitally reconstructed and segmented intracranial vascular trees, followed by calculating volumes of defined vessel segments by standardized protocols using Amira® software.
  
  
  RESULTS
  SAH animals demonstrated significantly smaller vessel diameters compared with sham (MCA: 134.4±26.9μm vs.165.0±18.7μm, p<0.05). We could highlight this difference by analyzing vessel volumes of a defined MCA-ICA segment (SAH: 0.044±0.017μl vs. sham: 0.07±0.006μl, p<0.001). Analysis of clinical CTA data allowed us to detect and volumetrically quantify vasospasm in a series of 5 SAH patients. Vessel diameters from digital reconstructions correlated well with those measured microscopically (rodent data, correlation coefficient 0.8, p<0.001), or angiographically (clinical data, 0.9, p<0.001).
  
  
  CONCLUSIONS
  Our methodological approach provides accurate anatomical reconstructions of intracranial vessels from cross-sectional imaging data. It allows volumetric assessment of entire vessel segments, hereby highlighting vasospasm-induced changes objectively in a murine SAH model. This method could also be a helpful tool for analysis of clinical CTA.
authors.affiliation: Department of Neurosurgery, University Medical Center of Mainz, Mainz, Germany.
authors.forename: Axel
authors.initials: A
authors.lastname: Neulen
authors.affiliation: Department of Neurosurgery, University Medical Center of Mainz, Mainz, Germany.
authors.forename: Tobias
authors.initials: T
authors.lastname: Pantel
authors.affiliation: Department of Neurosurgery, University Medical Center of Mainz, Mainz, Germany.
authors.forename: Michael
authors.initials: M
authors.lastname: Kosterhon
authors.affiliation: Department of Neuroradiology, University Medical Center of Mainz, Mainz, Germany.
authors.forename: Stefanie
authors.initials: S
authors.lastname: Kirschner
authors.affiliation: Department of Neuroradiology, University Medical Center of Mainz, Mainz, Germany.
authors.forename: Marc A
authors.initials: MA
authors.lastname: Brockmann
authors.affiliation: Department of Neurosurgery, University Medical Center of Mainz, Mainz, Germany.
authors.forename: Sven R
authors.initials: SR
authors.lastname: Kantelhardt
authors.affiliation: Department of Neurosurgery, University Medical Center of Mainz, Mainz, Germany.
authors.forename: Alf
authors.initials: A
authors.lastname: Giese
authors.affiliation: Department of Anesthesiology, University Medical Center of Mainz, Mainz, Germany.
authors.forename: Serge C
authors.initials: SC
authors.lastname: Thal
mesh_terms: D015901:Angiography, Digital Subtraction; D000818:Animals; D001921:Brain / Q000000981:diagnostic imaging; D003331:Coronary Vessels / Q000502:physiology; D004195:Disease Models, Animal; D005260:Female; D021621:Imaging, Three-Dimensional; D007427:Intracranial Pressure / Q000502:physiology; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D013345:Subarachnoid Hemorrhage / Q000150:complications; D020301:Vasospasm, Intracranial / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000209:etiology; D055114:X-Ray Microtomography