Automatic Aneurysm Neck Detection Using Surface Voronoi Diagrams

A new automatic approach for saccular intracranial aneurysm isolation is proposed in this work. Due to the inter- and intra-observer variability in manual delineation of the aneurysm neck, a definition based on a minimum cost path around the aneurysm sac is proposed that copes with this variability and is able to make consistent measurements along different data sets, as well as to automate and speedup the analysis of cerebral aneurysms. The method is based on the computation of a minimal path along a scalar field obtained on the vessel surface, to find the aneurysm neck in a robust and fast manner. The computation of the scalar field on the surface is obtained using a fast marching approach with a speed function based on the exponential of the distance from the centerline bifurcation between the aneurysm dome and the parent vessels. In order to assure a correct topology of the aneurysm sac, the neck computation is constrained to a region defined by a surface Voronoi diagram obtained from the branches of the vessel centerline. We validate this method comparing our results in 26 real cases with manual aneurysm isolation obtained using a cut-plane, and also with results obtained using manual delineations from three different observers by comparing typical morphological measures.

[1]  Karsten Grove,et al.  A generalized sphere theorem , 1977 .

[2]  J M Bland,et al.  Statistical methods for assessing agreement between two methods of clinical measurement , 1986 .

[3]  Piet W. Verbeek,et al.  An Efficient Uniform Cost Algorithm Applied to Distance Transforms , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  G. Duckwiler,et al.  Guglielmi detachable coil embolization of acute intracranial aneurysm: perioperative anatomical and clinical outcome in 403 patients. , 1997, Journal of neurosurgery.

[5]  A. Algra,et al.  Prevalence and risk of rupture of intracranial aneurysms: a systematic review. , 1998, Stroke.

[6]  F. Kajiya,et al.  Effects of size and shape (aspect ratio) on the hemodynamics of saccular aneurysms: a possible index for surgical treatment of intracranial aneurysms. , 1999, Neurosurgery.

[7]  F. Mémoli,et al.  Fast computation of weighted distance functions and geodesics on implicit hyper-surfaces: 730 , 2001 .

[8]  Johnson Huang,et al.  The Probability of Sudden Death from Rupture of Intracranial Aneurysms: A Meta-analysis , 2002, Neurosurgery.

[9]  S. Russell,et al.  Smaller cerebral aneurysms producing more extensive subarachnoid hemorrhage following rupture: a radiological investigation and discussion of theoretical determinants. , 2003, Journal of neurosurgery.

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

[11]  S. Koskinen,et al.  Detection of Intracranial Aneurysms with Two-dimensional and Three-dimensional Multislice Helical Computed Tomographic Angiography , 2004, Neurosurgery.

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

[13]  Alejandro F. Frangi,et al.  Efficient pipeline for image-based patient-specific analysis of cerebral aneurysm hemodynamics: technique and sensitivity , 2005, IEEE Transactions on Medical Imaging.

[14]  Javier Oliván Bescós,et al.  Volume measurement of intracranial aneurysms from 3D rotational angiography: improvement of accuracy by gradient edge detection. , 2005, AJNR. American journal of neuroradiology.

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

[16]  Kaleem Siddiqi,et al.  Flux driven automatic centerline extraction , 2005, Medical Image Anal..

[17]  V. Seifert,et al.  Size and location of ruptured and unruptured intracranial aneurysms measured by 3-dimensional rotational angiography. , 2006, Surgical neurology.

[18]  C. Karmonik,et al.  Hemodynamics in a cerebral artery before and after the formation of an aneurysm. , 2006, AJNR. American journal of neuroradiology.

[19]  Tudor Zamfirescu,et al.  On the critical points of a Riemannian surface , 2006 .

[20]  Albert C. S. Chung,et al.  Augmented vessels for quantitative analysis of vascular abnormalities and endovascular treatment planning , 2006, IEEE Transactions on Medical Imaging.

[21]  Wiro J. Niessen,et al.  Level set based cerebral vasculature segmentation and diameter quantification in CT angiography , 2006, Medical Image Anal..

[22]  Alejandro F Frangi,et al.  Non-parametric geodesic active regions: Method and evaluation for cerebral aneurysms segmentation in 3DRA and CTA , 2007, Medical Image Anal..

[23]  Robert-Paul Berretty,et al.  Fully-Automatic Correction of the Erroneous Border Areas of an Aneurysm , 2007, Bildverarbeitung für die Medizin.

[24]  Alejandro F. Frangi,et al.  Morphological Characterization of Intracranial Aneurysms Using 3-D Moment Invariants , 2007, IEEE Transactions on Medical Imaging.

[25]  Jenn Stroud Rossmann,et al.  Numerical simulation of saccular aneurysm hemodynamics: influence of morphology on rupture risk. , 2007, Journal of biomechanics.

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

[27]  Y Hoi,et al.  An objective approach to digital removal of saccular aneurysms: technique and applications. , 2009, The British journal of radiology.

[28]  Isabelle Bloch,et al.  A review of 3D vessel lumen segmentation techniques: Models, features and extraction schemes , 2009, Medical Image Anal..

[29]  David A. Steinman,et al.  A Framework for Geometric Analysis of Vascular Structures: Application to Cerebral Aneurysms , 2009, IEEE Transactions on Medical Imaging.

[30]  Alejandro F. Frangi,et al.  Morphodynamic Analysis of Cerebral Aneurysm Pulsation From Time-Resolved Rotational Angiography , 2009, IEEE Transactions on Medical Imaging.

[31]  Toshio Kobayashi,et al.  Fluid-structure interaction modeling of blood flow and cerebral aneurysm: Significance of artery and aneurysm shapes , 2009 .

[32]  T. Ishikawa,et al.  Can temporal fluctuation in spatial wall shear stress gradient initiate a cerebral aneurysm? A proposed novel hemodynamic index, the gradient oscillatory number (GON). , 2009, Journal of biomechanics.

[33]  Jong Beom Ra,et al.  Three-Dimensional Blood Vessel Quantification via Centerline Deformation , 2009, IEEE Transactions on Medical Imaging.

[34]  C. Putman,et al.  Hemodynamics of Cerebral Aneurysms. , 2009, Annual review of fluid mechanics.

[35]  Aly A. Farag,et al.  Variational Curve Skeletons Using Gradient Vector Flow , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[36]  Eric L. Miller,et al.  Automated detection of intracranial aneurysms based on parent vessel 3D analysis , 2010, Medical Image Anal..

[37]  Ioannis A. Kakadiaris,et al.  Computer-aided planning for endovascular treatment of intracranial aneurysms (CAPETA) , 2010, Medical Imaging.

[38]  Ioannis A. Kakadiaris,et al.  Neck localization and geometry quantification of intracranial aneurysms , 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[39]  D. Newell,et al.  Cerebral aneurysms. , 2006, The New England journal of medicine.

[40]  M. Pritz.  Cerebral aneurysm classification based on angioarchitecture. , 2011, Journal of Stroke & Cerebrovascular Diseases.