A multi-institutional meningioma MRI dataset for automated multi-sequence image segmentation.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
15 May 2024
15 May 2024
Historique:
received:
20
02
2024
accepted:
07
05
2024
medline:
16
5
2024
pubmed:
16
5
2024
entrez:
15
5
2024
Statut:
epublish
Résumé
Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by expert manually refined segmentations of three distinct meningioma sub-compartments: enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Basic demographic data are provided including age at time of initial imaging, sex, and CNS WHO grade. The goal of releasing this dataset is to facilitate the development of automated computational methods for meningioma segmentation and expedite their incorporation into clinical practice, ultimately targeting improvement in the care of meningioma patients.
Identifiants
pubmed: 38750041
doi: 10.1038/s41597-024-03350-9
pii: 10.1038/s41597-024-03350-9
doi:
Types de publication
Journal Article
Dataset
Langues
eng
Sous-ensembles de citation
IM
Pagination
496Subventions
Organisme : Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
ID : NCI/ITCR U01CA242871
Organisme : Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
ID : NCI K08CA256045
Organisme : Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
ID : U01CA242871
Organisme : Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
ID : U24CA279629
Informations de copyright
© 2024. The Author(s).
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