Semiautomatic neck curve reconstruction for intracranial aneurysm rupture risk assessment based on morphological parameters
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Morphological parameters of intracranial aneurysms (IAs) are well established for rupture risk assessment. However, a manual measurement is error-prone, not reproducible and cumbersome. For an automatic extraction of morphological parameters, a 3D neck curve reconstruction approach to delineate the aneurysm from the parent vessel is required.
We present a 3D semiautomatic aneurysm neck curve reconstruction for the automatic extraction of morphological parameters which was developed and evaluated with an experienced neuroradiologist. We calculate common parameters from the literature and include two novel angle-based parameters: the characteristic dome point angle and the angle difference of base points.
We applied our method to 100 IAs acquired with rotational angiography in clinical routine. For validation, we compared our approach to manual segmentations yielding highly significant correlations. We analyzed 95 of these datasets regarding rupture state. Statistically significant differences were found in ruptured and unruptured groups for maximum diameter, maximum height, aspect ratio and the characteristic dome point angle. These parameters were also found to statistically significantly correlate with each other.
The new 3D neck curve reconstruction provides robust results for all datasets. The reproducibility depends on the vessel tree centerline and the user input for the initial dome point and parameters characterizing the aneurysm neck region. The characteristic dome point angle as a new metric regarding rupture risk assessment can be extracted. It requires less computational effort than the complete neck curve reconstruction.
KeywordsIntracranial aneurysm Neck curve Morphological parameters Rupture risk assessment
The work was funded by the Federal Ministry of Education and Research within the Forschungscampus STIMULATE under Grant No. “13GW0095A.”
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. For this type of study, formal consent is not required.
Informed consent was obtained from all individual participants included in the study.
- 12.Berg P, Saalfeld S, Voß S, Redel T, Preim B, Janiga G, Beuing O (2017) Does the DSA reconstruction kernel affect hemodynamic predictions in intracranial aneurysms? an analysis of geometry and blood flow variations. J Neurointerventional Surg. https://doi.org/10.1136/neurintsurg-2017-012996 CrossRefGoogle Scholar
- 15.Saalfeld P, Luz M, Berg P, Preim B, Saalfeld S (2017) Guidelines for quantitative evaluation of medical visualizations on the example of 3D aneurysm surface comparisons. Comput Graph Forum 27(5):347Google Scholar
- 16.Glaßer S, Berg P, Voß S, Serowy S, Janiga G, Preim B, Beuing O (2016) From imaging to hemodynamics—how reconstruction kernels influence the blood flow predictions in intracranial aneurysms. Curr Dir Biomed Eng 2(1):163Google Scholar
- 17.Glaßer S, Berg P, Neugebauer M, Preim B (2015) Reconstruction of 3D surface meshes for blood flow simulations of intracranial aneurysms. In: Proceeding of the computer- and robot-assisted surgery (CURAC), pp 163–168Google Scholar
- 19.Neugebauer M, Diehl V, Skalej M, Preim B (2010) Geometric reconstruction of the ostium of cerebral aneurysms. In: Proceeding of the vision modeling visualization (VMV), pp 307–314Google Scholar
- 24.Jerman T, Pernuš F, Likar B, Špiclin Ž (2015) Computer-aided detection and quantification of intracranial aneurysms. In: Proceeding of the medical image computing and computer-assisted intervention (MICCAI). Lecture notes in computer science, vol 9350, pp 3–10Google Scholar
- 27.Cohen J (1988) Statistical power analysis for the behavioral sciences. Erlbaum, New YorkGoogle Scholar