Automatic determination of the dynamic geometry of abdominal aortic aneurysm from MR with application to wall stress simulations

Putter, Sander de; Breeuwer, Marcel; Kose, Ursula; Laffargue, Franck; Rouet, Jean-Michel; Hoogeveen, Romhild M.; Bosch, H. van den; Buth, Jaap; Vosse, F.N. van de; Gerritsen, Frans

doi:10.1016/j.ics.2005.03.256

Cited by 8 publications

(12 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Automatic segmentation of the AAA outer wall on the basis of 2D/3D SSFP MRI data appeared to be feasible with an accuracy comparable to what has been reported in literature for CTA (four MR data sets, mean segmentation error below 1 mm) [23,27,28,49]. The resolution of the MRI data was too low to allow segmentation of the outer wall below the bifurcation into the legs.…”

Section: Wall-stress Modelingsupporting

confidence: 65%

“…For MRI, the outer wall segmentation is performed using the dark intensity ring that is present in the 2D SSFP image around the AAA as image feature. The external force attracts the 3DAO towards this dark ring [28].…”

Section: Segmentationmentioning

confidence: 99%

“…For CTA, the image intensity itself is used as feature; the deformation is terminated at the transition from the expected lumen intensity (Hounsfield value) to the expected thrombus or wall intensity [23]. For MRI, first an edge feature image is created and the deformation is terminated at the position of the lumen-thrombus or lumen-inner wall edge [28]. The final step is the segmentation of the AAA outer wall by deforming the earlier segmented lumen 3DAO towards the AAA outer wall boundary (Fig.…”

Section: Segmentationmentioning

confidence: 99%

“…Taking this variation into account may further increase the accuracy. We were able to segment the varying lumen geometry from the 3D SSFP image data [28], but so far we have not used it in our flow simulations. Finally, the use of more realistic constitutive models for blood may also increase the accuracy of the simulations.…”

Section: Wall-stress Modelingmentioning

confidence: 99%

See 3 more Smart Citations

Towards patient-specific risk assessment of abdominal aortic aneurysm

Breeuwer

Putter

Kose

et al. 2008

Med Biol Eng Comput

View full text Add to dashboard Cite

Document VersionPublisher's PDF, also known as Version of Record (includes final page, issue and volume numbers)Please check the document version of this publication:• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication Citation for published version (APA):Breeuwer, M., Putter, de, S., Kose, U., Speelman, L., Visser, K., Gerritsen, F. A., ... Vosse, van de, F. N. (2008). Towards patient-specific risk assessment of abdominal aortic aneurysm. Medical and Biological Engineering and Computing, 46(11), 1085-1095. DOI: 10.1007/s11517-008-0393-0 General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Abstract Diagnosis of vascular disease and selection and planning of therapy are to a large extent based on the geometry of the diseased vessel. Treatment of a particular vascular disease is usually considered if the geometrical parameter that characterizes the severity of the disease, e.g. % vessel narrowing, exceeds a threshold. The thresholds that are used in clinical practice are based on epidemiological knowledge, which has been obtained by clinical studies including large numbers of patients. They may apply ''on average'', but they can be sub-optimal for individual patients. To realize more patient-specific treatment decision criteria, more detailed knowledge may be required about the vascular hemodynamics, i.e. the blood flow and pressure in the diseased vessel and the biomechanical reaction of the vessel wall to this flow and pressure. Over the last decade, a substantial number of publications have appeared on hemodynamic modeling. Some studies have provided first evidence that this modeling may indeed be used to support therapeutic decisions. The goal of the research reported in this paper is to go one step further, namely to investigate the feasibilit...

show abstract

Section: Wall-stress Modelingsupporting

confidence: 65%

Section: Segmentationmentioning

confidence: 99%

Section: Segmentationmentioning

confidence: 99%

Section: Wall-stress Modelingmentioning

confidence: 99%

See 2 more Smart Citations

Towards patient-specific risk assessment of abdominal aortic aneurysm

Breeuwer

Putter

Kose

et al. 2008

Med Biol Eng Comput

View full text Add to dashboard Cite

show abstract

“…The other relevant MR imaging parameters have been described in a previous publication. 6 The contrast-enhanced CT images have a resolution of 0.6 x 0.6 x 3 mm.…”

Section: Imagesmentioning

confidence: 99%

Patient-specific models of wall stress in abdominal aortic aneurysm: a comparison between MR and CT

et al. 2006

Self Cite

View full text Add to dashboard Cite

Finite element method based patient-specific wall stress in abdominal aortic aneurysm (AAA) may provide a more accurate rupture risk predictor than the currently used maximum transverse diameter. In this study, we have investigated the sensitivity of the wall stress in AAA with respect to geometrical variations. We have acquired MR and CT images for four patients with AAA. Three individual users have delineated the AAA vessel wall contours on the image slices. These contours were used to generate synthetic feature images for a deformable model based segmentation method. We investigated the reproducibility and the influence of the user variability on the wall stress. For sufficiently smooth models of the AAA wall, the peak wall stress is reproducible for three out of the four AAA geometries. The 0.99 percentiles of the wall stress show excellent reproducibility for all four AAAs. The variations induced by user variability are larger than the errors caused by the segmentation variability. The influence of the user variability appears to be similar for MR and CT. We conclude that the peak wall stress in AAA is sensitive to small geometrical variations. To increase reproducibility it appears to be best not to allow too much geometrical detail in the simulations. This could be achieved either by using a sufficiently smooth geometry representation or by using a more robust statistical parameter derived from the wall stress distribution.

show abstract

Image Processing on Diagnostic Workstations

Romeny

2008

Medical Radiology

View full text Add to dashboard Cite

Automatic determination of the dynamic geometry of abdominal aortic aneurysm from MR with application to wall stress simulations

Cited by 8 publications

References 9 publications

Towards patient-specific risk assessment of abdominal aortic aneurysm

Towards patient-specific risk assessment of abdominal aortic aneurysm

Patient-specific models of wall stress in abdominal aortic aneurysm: a comparison between MR and CT

Image Processing on Diagnostic Workstations

Contact Info

Product

Resources

About