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Peer-reviewedCC BY 4.0PLOS One

Segmentation and morphological analysis of recanalized coiled aneurysms: Towards an automatic tool for clipping planning in microsurgery

  • Matthieu Coupet1
  • Manel Meftah2
  • Camille Lopez3
  • Ludivine Maintier4
  • Aziliz Guezou-Philippe5
  • Julien Ognard6
  • Jean-Christophe Gentric
  • Valérin Burdin
  • Elsa Magro
  • Guillaume Dardenne
6 affiliations
  1. 1LaTIM - UMR 1101 INSERM, Brest, France
  2. 2IMT Atlantique, Brest, France
  3. 3Department of Neurosurgery, Hôpital Cavale Blanche, Brest University Hospital, Brest, France
  4. 4Department of Radiology, Hôpital Cavale Blanche, Brest University Hospital, Brest, France
  5. 5Service d’Imagerie Médicale, Hôpital d’Instruction des Armées Legouest, rue des Frères-Lacretelle, Metz, France
  6. 6University of Brest GETBO - INSERM UMR1304, Brest, France
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Abstract

Intracranial aneurysms are dilatations of cerebral arteries that may rupture, leading to subarachnoid hemorrhage and high mortality. Endovascular coiling is widely used to prevent rupture; however, many treated aneurysms experience recanalization, which often necessitates follow-up interventions or surgical clipping. Despite its clinical importance, the segmentation and morphological characterization of recanalized coiled aneurysms remain largely unexplored. In this study, we introduce an automated framework for the segmentation of recanalized coiled aneurysms from three-dimensional rotational angiography (3D-RA) images and the extraction of morphological descriptors relevant to surgical planning. The method is based on the nnU-Net architecture, trained to segment the vascular tree, coil mass, and recanalized lumen. Quantitative postprocessing enables the computation of clinically relevant parameters, including coil–neck distance, recanalization volume, and maximum neck diameter, which contribute to the assessment of clipping feasibility. Preliminary results show encouraging segmentation performance and consistent estimation of morphological parameters across the evaluated cases, supporting the potential of the proposed framework for preoperative assessment of recanalized coiled aneurysms.

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Cite

BibTeXRIS
BibTeX
@article{coupet2026segmentation,
  title = {{Segmentation and morphological analysis of recanalized coiled aneurysms: Towards an automatic tool for clipping planning in microsurgery}},
  author = {Matthieu Coupet and Manel Meftah and Camille Lopez and Ludivine Maintier and Aziliz Guezou-Philippe and Julien Ognard and Jean-Christophe Gentric and Valérin Burdin and Elsa Magro and Guillaume Dardenne},
  journal = {PLOS One},
  year = {2026},
  month = sep,
  doi = {10.1371/journal.pone.0358945},
  url = {https://doi.org/10.1371/journal.pone.0358945},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Segmentation and morphological analysis of recanalized coiled aneurysms: Towards an automatic tool for clipping planning in microsurgery
AU  - Matthieu Coupet
AU  - Manel Meftah
AU  - Camille Lopez
AU  - Ludivine Maintier
AU  - Aziliz Guezou-Philippe
AU  - Julien Ognard
AU  - Jean-Christophe Gentric
AU  - Valérin Burdin
AU  - Elsa Magro
AU  - Guillaume Dardenne
PY  - 2026
DA  - 2026/09/23
JO  - PLOS One
DO  - 10.1371/journal.pone.0358945
UR  - https://doi.org/10.1371/journal.pone.0358945
AB  - Intracranial aneurysms are dilatations of cerebral arteries that may rupture, leading to subarachnoid hemorrhage and high mortality. Endovascular coiling is widely used to prevent rupture; however, many treated aneurysms experience recanalization, which often necessitates follow-up interventions or surgical clipping. Despite its clinical importance, the segmentation and morphological characterization of recanalized coiled aneurysms remain largely unexplored. In this study, we introduce an automated framework for the segmentation of recanalized coiled aneurysms from three-dimensional rotational angiography (3D-RA) images and the extraction of morphological descriptors relevant to surgical planning. The method is based on the nnU-Net architecture, trained to segment the vascular tree, coil mass, and recanalized lumen. Quantitative postprocessing enables the computation of clinically relevant parameters, including coil–neck distance, recanalization volume, and maximum neck diameter, which contribute to the assessment of clipping feasibility. Preliminary results show encouraging segmentation performance and consistent estimation of morphological parameters across the evaluated cases, supporting the potential of the proposed framework for preoperative assessment of recanalized coiled aneurysms.
SN  - 1932-6203
ER  -