Semiautomatic neck curve reconstruction for intracranial aneurysm rupture risk assessment based on morphological parameters

PurposeMorphological 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.MethodsWe 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.ResultsWe 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.ConclusionsThe 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.

[1]  Philipp Berg,et al.  Multiple intracranial aneurysms: a direct hemodynamic comparison between ruptured and unruptured vessel malformations , 2017, International Journal of Computer Assisted Radiology and Surgery.

[2]  Jacob Cohen Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[3]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[4]  M. L. Raghavan,et al.  Three-Dimensional Geometrical Characterization of Cerebral Aneurysms , 2004, Annals of Biomedical Engineering.

[5]  Alexandra Lauric,et al.  Ruptured status discrimination performance of aspect ratio, height/width, and bottleneck factor is highly dependent on aneurysm sizing methodology. , 2012, Neurosurgery.

[6]  Bernhard Preim,et al.  From imaging to hemodynamics – how reconstruction kernels influence the blood flow predictions in intracranial aneurysms , 2016 .

[7]  Bernhard Preim,et al.  Reconstruction of 3D Surface Meshes for Bood Flow Simulations of Intracranial Aneurysms , 2015, CURAC.

[8]  J. Xiang,et al.  High WSS or Low WSS? Complex Interactions of Hemodynamics with Intracranial Aneurysm Initiation, Growth, and Rupture: Toward a Unifying Hypothesis , 2014, American Journal of Neuroradiology.

[9]  Bernhard Preim,et al.  Recommendations for accurate numerical blood flow simulations of stented intracranial aneurysms , 2013, Biomedizinische Technik. Biomedical engineering.

[10]  三浦 洋一,et al.  Low wall shear stress is independently associated with the rupture status of middle cerebral artery aneurysms , 2013 .

[11]  Alejandro F. Frangi,et al.  Automatic Aneurysm Neck Detection Using Surface Voronoi Diagrams , 2011, IEEE Transactions on Medical Imaging.

[12]  David A. Steinman,et al.  An image-based modeling framework for patient-specific computational hemodynamics , 2008, Medical & Biological Engineering & Computing.

[13]  B. Hoh,et al.  BOTTLENECK FACTOR AND HEIGHT‐WIDTH RATIO: ASSOCIATION WITH RUPTURED ANEURYSMS IN PATIENTS WITH MULTIPLE CEREBRAL ANEURYSMS , 2007, Neurosurgery.

[14]  Bernhard Preim,et al.  Geometric Reconstruction of the Ostium of Cerebral Aneurysms , 2010, VMV.

[15]  C. Putman,et al.  Quantitative Characterization of the Hemodynamic Environment in Ruptured and Unruptured Brain Aneurysms , 2010, American Journal of Neuroradiology.

[16]  Bostjan Likar,et al.  Computer-Aided Detection and Quantification of Intracranial Aneurysms , 2015, MICCAI.

[17]  Bernhard Preim,et al.  Guidelines for Quantitative Evaluation of Medical Visualizations on the Example of 3D Aneurysm Surface Comparisons , 2018, Comput. Graph. Forum.

[18]  M. L. Raghavan,et al.  Quantified aneurysm shape and rupture risk. , 2005, Journal of neurosurgery.

[19]  O. Ganslandt,et al.  Difference in aneurysm characteristics between ruptured and unruptured aneurysms in patients with multiple intracranial aneurysms , 2018, Surgical neurology international.

[20]  Fujimaro Ishida,et al.  Low Wall Shear Stress Is Independently Associated With the Rupture Status of Middle Cerebral Artery Aneurysms , 2013, Stroke.

[21]  S Saalfeld,et al.  Does the DSA reconstruction kernel affect hemodynamic predictions in intracranial aneurysms? An analysis of geometry and blood flow variations , 2017, Journal of NeuroInterventional Surgery.

[22]  Christof Karmonik,et al.  Morphological and Hemodynamic Discriminators for Rupture Status in Posterior Communicating Artery Aneurysms , 2016, PloS one.

[23]  J Max Findlay,et al.  The aspect ratio (dome/neck) of ruptured and unruptured aneurysms. , 2003, Journal of neurosurgery.

[24]  Kai Lawonn,et al.  AmniVis – A System for Qualitative Exploration of Near‐Wall Hemodynamics in Cerebral Aneurysms , 2013, Comput. Graph. Forum.

[25]  Christof Karmonik,et al.  A technique for improved quantitative characterization of intracranial aneurysms. , 2004, AJNR. American journal of neuroradiology.

[26]  A Siddiqui,et al.  Differences in Morphologic and Hemodynamic Characteristics for “PHASES-Based” Intracranial Aneurysm Locations , 2017, American Journal of Neuroradiology.

[27]  Kai Lawonn,et al.  Automatic generation of anatomic characteristics from cerebral aneurysm surface models , 2012, International Journal of Computer Assisted Radiology and Surgery.

[28]  J. Mocco,et al.  MORPHOLOGY PARAMETERS FOR INTRACRANIAL ANEURYSM RUPTURE RISK ASSESSMENT , 2008, Neurosurgery.

[29]  Alejandro F. Frangi,et al.  Performance assessment of isolation methods for geometrical cerebral aneurysm analysis , 2013, Medical & Biological Engineering & Computing.

[30]  J. Mocco,et al.  Hemodynamic–Morphologic Discriminants for Intracranial Aneurysm Rupture , 2011, Stroke.

[31]  Norlisah Ramli,et al.  Benefits of 3D rotational DSA compared with 2D DSA in the evaluation of intracranial aneurysm. , 2012, Academic radiology.