Constrained estimation of intracranial aneurysm surface deformation using 4D-CTA

Journal article

Xie, H., Wu, H., Wang, J., Mendieta, J.B., Yu, H., Xiang, Y., Anbananthan, H., Zhang, J., Zhao, H., Zhu, Z., Huang, Q., Fang, R., Zhu, C. and Li, Z. (2024). Constrained estimation of intracranial aneurysm surface deformation using 4D-CTA. Computer Methods and Programs in Biomedicine. 244, p. 107975. https://doi.org/10.1016/j.cmpb.2023.107975
AuthorsXie, H., Wu, H., Wang, J., Mendieta, J.B., Yu, H., Xiang, Y., Anbananthan, H., Zhang, J., Zhao, H., Zhu, Z., Huang, Q., Fang, R., Zhu, C. and Li, Z.
Abstract

Background and objective
Intracranial aneurysms are relatively common life-threatening diseases, and assessing aneurysm rupture risk and identifying the associated risk factors is essential. Parameters such as the Oscillatory Shear Index, Pressure Loss Coefficient, and Wall Shear Stress are reliable indicators of intracranial aneurysm development and rupture risk, but aneurysm surface irregular pulsation has also received attention in aneurysm rupture risk assessment.

Methods
The present paper proposed a new approach to estimate aneurysm surface deformation. This method transforms the estimation of aneurysm surface deformation into a constrained optimization problem, which minimizes the error between the displacement estimated by the model and the sparse data point displacements from the four-dimensional CT angiography (4D-CTA) imaging data.

Results
The effect of the number of sparse data points on the results has been discussed in both simulation and experimental results, and it shows that the proposed method can accurately estimate the surface deformation of intracranial aneurysms when using sufficient sparse data points.

Conclusions
Due to a potential association between aneurysm rupture and surface irregular pulsation, the estimation of aneurysm surface deformation is needed. This paper proposed a method based on 4D-CTA imaging data, offering a novel solution for the estimation of intracranial aneurysm surface deformation.

Year2024
JournalComputer Methods and Programs in Biomedicine
Journal citation244, p. 107975
PublisherElsevier
ISSN1872-7565
Digital Object Identifier (DOI)https://doi.org/10.1016/j.cmpb.2023.107975
Publication dates
Print10 Dec 2023
Publication process dates
Accepted07 Dec 2023
Deposited08 Jan 2024
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Open
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