Rupture risk assessment for AComA aneurysms with morphological, hemodynamic and structural mechanical analysis Article Swipe
József Nagy
,
Nico Stroh-Holly
,
Wolfgang Fenz
,
Stefan Thumfart
,
Julia Maier
,
Zoltán Major
,
Harald Stefanits
,
Maria Gollwitzer
,
Johannes Oberndorfer
,
Vanessa Mazanec
,
Michael Giretzlehner
,
Michael Sonnberger
,
Philip Rauch
,
Andreas Gruber
,
Matthias Gmeiner
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0331297
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0331297
Introduction The Anterior Communicating Artery complex (AComA) is one of the most common intracranial aneurysms locations. Accurate rupture risk assessment in patients with cerebral aneurysms is essential for optimizing treatment decisions. Computational fluid dynamics has significantly advanced insight into aneurysmal hemodynamics. Many studies concentrate predominantly on blood flow patterns, frequently neglecting the biomechanical properties of the aneurysm wall. Fluid-structure interaction analysis combines hemodynamic behavior with wall mechanics, potentially facilitating a more thorough evaluation of rupture risk assessment. Methods In this study, we employed advanced techniques to investigate several single and composite parameters to predict the rupture risk of AComA aneurysms in a cohort of 150 patients treated at the Kepler University Hospital in Linz, Austria. For this reason, clinical, morphological, hemodynamic, and structural mechanical parameters were assessed. Results A subsequent workflow analysis, consisting of comparative analysis, collinearity analysis, predictive modeling, composite parameter, performance evaluation, and internal threshold validation, revealed the Gaussian curvature GLN (AUC = 0.91) with a sensitivity of 0.93 and specificity of 0.83 as a best-performing single parameter for aneurysm rupture prediction. Composite parameters like WGD (combination of wall shear stress, Gaussian curvature, and wall displacement) achieved an AUC of 0.89, and WG (combination of wall shear stress and Gaussian curvature) an AUC of 0.88. An internal validation with 25 independent ruptured aneurysms was performed, and the previous results were confirmed with very high sensitivity values of 0.92 for GLN. Conclusion Our findings indicate that the investigated morphological, hemodynamic, and structural, mechanical parameters could provide a potential tool for evaluating rupture risk for AComA aneurysms. The single morphological parameter GLN offers, followed by composite parameters WGD and WG, excellent prediction power for the aneurysm rupture state, as confirmed by internal validation. Further studies are warranted to evaluate the prospective clinical application of these parameters.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1371/journal.pone.0331297
- https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0331297&type=printable
- OA Status
- gold
- References
- 53
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4413940180
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4413940180Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1371/journal.pone.0331297Digital Object Identifier
- Title
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Rupture risk assessment for AComA aneurysms with morphological, hemodynamic and structural mechanical analysisWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
-
2025-09-02Full publication date if available
- Authors
-
József Nagy, Nico Stroh-Holly, Wolfgang Fenz, Stefan Thumfart, Julia Maier, Zoltán Major, Harald Stefanits, Maria Gollwitzer, Johannes Oberndorfer, Vanessa Mazanec, Michael Giretzlehner, Michael Sonnberger, Philip Rauch, Andreas Gruber, Matthias GmeinerList of authors in order
- Landing page
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https://doi.org/10.1371/journal.pone.0331297Publisher landing page
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https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0331297&type=printableDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0331297&type=printableDirect OA link when available
- Concepts
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Hemodynamics, Aneurysm, Shear stress, Internal medicine, Cardiology, Medicine, Radiology, Mechanics, PhysicsTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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53Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.Anterior | 2 |
| abstract_inverted_index.Austria. | 114 |
| abstract_inverted_index.Gaussian | 150, 183, 201 |
| abstract_inverted_index.Hospital | 111 |
| abstract_inverted_index.achieved | 188 |
| abstract_inverted_index.advanced | 36, 83 |
| abstract_inverted_index.analysis | 60 |
| abstract_inverted_index.aneurysm | 56, 171, 275 |
| abstract_inverted_index.behavior | 63 |
| abstract_inverted_index.cerebral | 23 |
| abstract_inverted_index.clinical | 291 |
| abstract_inverted_index.combines | 61 |
| abstract_inverted_index.dynamics | 33 |
| abstract_inverted_index.employed | 82 |
| abstract_inverted_index.evaluate | 288 |
| abstract_inverted_index.findings | 234 |
| abstract_inverted_index.followed | 263 |
| abstract_inverted_index.indicate | 235 |
| abstract_inverted_index.internal | 145, 208, 281 |
| abstract_inverted_index.patients | 21, 105 |
| abstract_inverted_index.previous | 219 |
| abstract_inverted_index.revealed | 148 |
| abstract_inverted_index.ruptured | 213 |
| abstract_inverted_index.thorough | 71 |
| abstract_inverted_index.workflow | 130 |
| abstract_inverted_index.Composite | 174 |
| abstract_inverted_index.analysis, | 131, 135, 137 |
| abstract_inverted_index.aneurysms | 14, 24, 99, 214 |
| abstract_inverted_index.assessed. | 126 |
| abstract_inverted_index.clinical, | 118 |
| abstract_inverted_index.composite | 90, 140, 265 |
| abstract_inverted_index.confirmed | 222, 279 |
| abstract_inverted_index.curvature | 151 |
| abstract_inverted_index.essential | 26 |
| abstract_inverted_index.excellent | 270 |
| abstract_inverted_index.modeling, | 139 |
| abstract_inverted_index.parameter | 169, 260 |
| abstract_inverted_index.patterns, | 48 |
| abstract_inverted_index.potential | 248 |
| abstract_inverted_index.threshold | 146 |
| abstract_inverted_index.treatment | 29 |
| abstract_inverted_index.warranted | 286 |
| abstract_inverted_index.Conclusion | 232 |
| abstract_inverted_index.University | 110 |
| abstract_inverted_index.aneurysmal | 39 |
| abstract_inverted_index.aneurysms. | 256 |
| abstract_inverted_index.assessment | 19 |
| abstract_inverted_index.consisting | 132 |
| abstract_inverted_index.curvature) | 202 |
| abstract_inverted_index.curvature, | 184 |
| abstract_inverted_index.decisions. | 30 |
| abstract_inverted_index.evaluating | 251 |
| abstract_inverted_index.evaluation | 72 |
| abstract_inverted_index.frequently | 49 |
| abstract_inverted_index.locations. | 15 |
| abstract_inverted_index.mechanical | 123, 243 |
| abstract_inverted_index.mechanics, | 66 |
| abstract_inverted_index.neglecting | 50 |
| abstract_inverted_index.optimizing | 28 |
| abstract_inverted_index.parameter, | 141 |
| abstract_inverted_index.parameters | 91, 124, 175, 244, 266 |
| abstract_inverted_index.performed, | 216 |
| abstract_inverted_index.prediction | 271 |
| abstract_inverted_index.predictive | 138 |
| abstract_inverted_index.properties | 53 |
| abstract_inverted_index.structural | 122 |
| abstract_inverted_index.subsequent | 129 |
| abstract_inverted_index.techniques | 84 |
| abstract_inverted_index.validation | 209 |
| abstract_inverted_index.application | 292 |
| abstract_inverted_index.assessment. | 76 |
| abstract_inverted_index.comparative | 134 |
| abstract_inverted_index.concentrate | 43 |
| abstract_inverted_index.evaluation, | 143 |
| abstract_inverted_index.hemodynamic | 62 |
| abstract_inverted_index.independent | 212 |
| abstract_inverted_index.interaction | 59 |
| abstract_inverted_index.investigate | 86 |
| abstract_inverted_index.parameters. | 295 |
| abstract_inverted_index.performance | 142 |
| abstract_inverted_index.potentially | 67 |
| abstract_inverted_index.prediction. | 173 |
| abstract_inverted_index.prospective | 290 |
| abstract_inverted_index.sensitivity | 158, 226 |
| abstract_inverted_index.specificity | 162 |
| abstract_inverted_index.structural, | 242 |
| abstract_inverted_index.validation, | 147 |
| abstract_inverted_index.validation. | 282 |
| abstract_inverted_index.(combination | 178, 195 |
| abstract_inverted_index.Introduction | 0 |
| abstract_inverted_index.collinearity | 136 |
| abstract_inverted_index.facilitating | 68 |
| abstract_inverted_index.hemodynamic, | 120, 240 |
| abstract_inverted_index.intracranial | 13 |
| abstract_inverted_index.investigated | 238 |
| abstract_inverted_index.Communicating | 3 |
| abstract_inverted_index.Computational | 31 |
| abstract_inverted_index.biomechanical | 52 |
| abstract_inverted_index.displacement) | 187 |
| abstract_inverted_index.hemodynamics. | 40 |
| abstract_inverted_index.morphological | 259 |
| abstract_inverted_index.predominantly | 44 |
| abstract_inverted_index.significantly | 35 |
| abstract_inverted_index.morphological, | 119, 239 |
| abstract_inverted_index.Fluid-structure | 58 |
| abstract_inverted_index.best-performing | 167 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5007247902, https://openalex.org/A5050170961, https://openalex.org/A5035248885, https://openalex.org/A5107515413, https://openalex.org/A5114435580, https://openalex.org/A5020422608, https://openalex.org/A5060849376, https://openalex.org/A5013461852, https://openalex.org/A5070522708, https://openalex.org/A5062967586, https://openalex.org/A5090771197, https://openalex.org/A5100914621, https://openalex.org/A5010482924, https://openalex.org/A5101712883, https://openalex.org/A5102960537 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 15 |
| corresponding_institution_ids | https://openalex.org/I121883995, https://openalex.org/I4210140024 |
| citation_normalized_percentile.value | 0.52987645 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |