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E-061 towards the pre-surgical treatment planning of cerebral aneurysms using high fidelity simulations.

Overview of attention for article published in Journal of NeuroInterventional Surgery, July 2014
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  • Among the highest-scoring outputs from this source (#41 of 438)
  • Good Attention Score compared to outputs of the same age (71st percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

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9 Mendeley
E-061 towards the pre-surgical treatment planning of cerebral aneurysms using high fidelity simulations.
Published in
Journal of NeuroInterventional Surgery, July 2014
DOI 10.1136/neurintsurg-2014-011343.128
Pubmed ID

Chong B, Babiker H, Frakes D, Ryan J, Gonzalez F


: Over the last decade, advances in medical imaging have led to a 75% increase in early diagnosis of cerebral aneurysms (CAs) along with a growing arsenal of medical devices that can now treat a wider range of CA cases. Endovascular treatment planning has shown limited progress. Current treatment planning is driven by prior training, convention and experience. Despite the best of plans, the process can involve an element of trial and error during treatment that increases procedural time, treatment costs, and the risk of procedural complications. Further, treatment planning can be unsuccessful in many cases with recurrence rates as high as 21.9% and retreatment rates of 11.0%. Therefore, there is a critical need to improve endovascular treatment planning. Here we present a novel simulation algorithm that enhances clinical capabilities for personalised pre-surgical treatment planning. In the first step of the algorithm, a computational anatomy is generated from MR or CT image data. Next, the computational anatomy is used to simulate treatment using novel device-specific finite element (FE) models that consider the structural properties of the treatment device, its mechanics, and the clinical deployment strategy. Changes in blood flow are then simulated using computational fluid dynamics (CFD). Lastly, mechanical and fluid dynamic simulation results are used to evaluate the outcomes of different treatment options. The simulation algorithm was validated against in-vitro deployments of embolic coils, stents, and the Pipeline embolization device in 3 idealised and 2 anatomical CA models. Results showed excellent agreement between FE device simulations and physical device deployments. Fluid dynamics were also compared between CFD simulations and in-vitro flow velocity and pressure measurements in the treated CA models. Results showed good agreement in mean aneurysmal velocity magnitude and intra-aneurysmal pressure. Detailed 3D structural validations against microCT data will also be presented. The value of the simulation algorithm for treatment planning is demonstrated for 3 patient cases. In case 1, stent-assisted coiling (Figure 1a) and flow diverter treatment options (Figure 1b) are evaluated for a wide-neck posterior communicating artery (PCA) aneurysm (Figure 1). In case 2, the simulation algorithm is used to predict changes in fluid dynamics after 12 coil deployments in a large basilar-tip aneurysm. Clinical and simulations results of that case showed a persisting flow jet into the aneurysmal sac after treatment. In case 3, the simulation algorithm is used to compare stent-assisted coiling and coiling-alone in a basilar tip aneurysm. neurintsurg;6/Suppl_1/A67-a/F1F1F1 Abstract E-061 Figure 1 DISCLOSURES: B. Chong: 1; C; Mayo Clinic Center for Individualised Medicine, Arizona State University. 4; C; Endovantage LLC. H. Babiker: 4; C; Endovantage LLC. D. Frakes: 4; C; Endovantage, LLC. J. Ryan: 5; C; Endovantage LLC. F. Gonzalez: 4; C; Endovantage LLC.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 33%
Student > Bachelor 2 22%
Student > Doctoral Student 2 22%
Student > Ph. D. Student 1 11%
Other 1 11%
Other 0 0%
Readers by discipline Count As %
Medicine and Dentistry 5 56%
Economics, Econometrics and Finance 1 11%
Computer Science 1 11%
Neuroscience 1 11%
Unspecified 1 11%
Other 0 0%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 August 2014.
All research outputs
of 4,507,652 outputs
Outputs from Journal of NeuroInterventional Surgery
of 438 outputs
Outputs of similar age
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Outputs of similar age from Journal of NeuroInterventional Surgery
of 17 outputs
Altmetric has tracked 4,507,652 research outputs across all sources so far. This one has received more attention than most of these and is in the 64th percentile.
So far Altmetric has tracked 438 research outputs from this source. They receive a mean Attention Score of 1.4. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 113,225 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.