Journal of Clinical Medicine (Apr 2022)

Standardized Classification of Cerebral Vasospasm after Subarachnoid Hemorrhage by Digital Subtraction Angiography

  • Helena Merkel,
  • Dirk Lindner,
  • Khaled Gaber,
  • Svitlana Ziganshyna,
  • Jennifer Jentzsch,
  • Simone Mucha,
  • Thilo Gerhards,
  • Sabine Sari,
  • Annika Stock,
  • Felicitas Vothel,
  • Lea Falter,
  • Ulf Quäschling,
  • Karl-Titus Hoffmann,
  • Jürgen Meixensberger,
  • Dirk Halama,
  • Cindy Richter

DOI
https://doi.org/10.3390/jcm11072011
Journal volume & issue
Vol. 11, no. 7
p. 2011

Abstract

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Background: During the last decade, cerebral vasospasm after aneurysmal subarachnoid hemorrhage (SAH) was a current research focus without a standardized classification in digital subtraction angiography (DSA). This study was performed to investigate a device-independent visual cerebral vasospasm classification for endovascular treatment. Methods: The analyses are DSA based rather than multimodal. Ten defined points of intracranial arteries were measured in 45 patients suffering from cerebral vasospasm after SAH at three time points (hospitalization, before spasmolysis, control after six months). Mathematical clustering of vessel diameters was performed to generate four objective grades for comparison. Six interventional neuroradiologists in two groups scored 237 DSAs after a new visual classification (grade 0–3) developed on a segmental pattern of vessel contraction. For the second group, a threshold-based criterion was amended. Results: The raters had a reproducibility of 68.4% in the first group and 75.2% in the second group. The complementary threshold-based criterion increased the reproducibility by about 6.8%, while the rating deviated more from the mathematical clustering in all grades. Conclusions: The proposed visual classification scheme of cerebral vasospasm is suitable as a standard grading procedure for endovascular treatment. There is no advantage of a threshold-based criterion that compensates for the effort involved. Automated vessel analysis is superior to compare inter-group results in research settings.

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