Annals of Biomedical Engineering

, Volume 39, Issue 5, pp 1457–1469 | Cite as

3D Shape Analysis of Intracranial Aneurysms Using the Writhe Number as a Discriminant for Rupture

  • Alexandra Lauric
  • Eric L. Miller
  • Merih I. Baharoglu
  • Adel M. Malek
Article

Abstract

Intracranial aneurysms are polymorphic focal arterial dilations, which harbor a variable risk of rupture leading to high morbidity and mortality. Increased detection of incidental aneurysms by non-invasive imaging has created a need for rupture risk stratification tools, in addition to simple aneurysm size, to guide optimal treatment strategy. To this end, shape analysis has emerged as a possible differentiator of rupture likelihood. A novel set of morphological parameters based on the writhe number are introduced here to describe aneurysms and discriminate rupture status. Classification in 117 saccular aneurysms (52 ruptured and 65 unruptured) is based on statistical analysis of writhe number distribution on the aneurysm surface. Aneurysms are analyzed both in isolation and including a portion of their parent vessel. Sidewall and bifurcation aneurysm subtypes were found to be best described by disjoint sets of shape parameters, yielding a morphological dichotomy between the two aneurysm classes. Writhe number analysis results in 86.7% accuracy on sidewall (SW) aneurysms and 71.2% accuracy on bifurcation (BF) aneurysms. This represents a 12% accuracy increase for both subtypes compared to the performance of seven established 2D and 3D indexes. The results support the utility of writhe number aneurysm shape analysis, with potential clinical value in rupture risk stratification.

Keywords

Intracranial aneurysms Morphological characterization Histogram statistics Shape analysis Writhe number 

Supplementary material

10439_2010_241_MOESM1_ESM.pdf (1.1 mb)
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Copyright information

© Biomedical Engineering Society 2011

Authors and Affiliations

  • Alexandra Lauric
    • 1
  • Eric L. Miller
    • 2
  • Merih I. Baharoglu
    • 3
  • Adel M. Malek
    • 3
  1. 1.Department of Computer ScienceTufts UniversityMedfordUSA
  2. 2.Department of Electrical and Computer EngineeringTufts UniversityMedfordUSA
  3. 3.Department of NeurosurgeryTufts Medical CenterBostonUSA

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