Challenges with segmenting intraoperative ultrasound for brain tumours.
Intraoperative ultrasound
Segmentation
Tumour margin uncertainty
Journal
Acta neurochirurgica
ISSN: 0942-0940
Titre abrégé: Acta Neurochir (Wien)
Pays: Austria
ID NLM: 0151000
Informations de publication
Date de publication:
01 Aug 2024
01 Aug 2024
Historique:
received:
05
05
2024
accepted:
22
06
2024
medline:
2
8
2024
pubmed:
2
8
2024
entrez:
1
8
2024
Statut:
epublish
Résumé
Objective - Addressing the challenges that come with identifying and delineating brain tumours in intraoperative ultrasound. Our goal is to both qualitatively and quantitatively assess the interobserver variation, amongst experienced neuro-oncological intraoperative ultrasound users (neurosurgeons and neuroradiologists), in detecting and segmenting brain tumours on ultrasound. We then propose that, due to the inherent challenges of this task, annotation by localisation of the entire tumour mass with a bounding box could serve as an ancillary solution to segmentation for clinical training, encompassing margin uncertainty and the curation of large datasets. Methods - 30 ultrasound images of brain lesions in 30 patients were annotated by 4 annotators - 1 neuroradiologist and 3 neurosurgeons. The annotation variation of the 3 neurosurgeons was first measured, and then the annotations of each neurosurgeon were individually compared to the neuroradiologist's, which served as a reference standard as their segmentations were further refined by cross-reference to the preoperative magnetic resonance imaging (MRI). The following statistical metrics were used: Intersection Over Union (IoU), Sørensen-Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD). These annotations were then converted into bounding boxes for the same evaluation. Results - There was a moderate level of interobserver variance between the neurosurgeons
Identifiants
pubmed: 39090435
doi: 10.1007/s00701-024-06179-8
pii: 10.1007/s00701-024-06179-8
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
317Subventions
Organisme : UK Research and Innovation
ID : EP/S023283/1)
Organisme : Royal Society
ID : (URFR2 01014])
Informations de copyright
© 2024. The Author(s).
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