{"doi":"10.1038/s41597-024-03350-9","title":"A multi-institutional meningioma MRI dataset for automated multi-sequence image segmentation","abstract":"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.","journal":"Scientific Data","year":2024,"id":484050,"datarank":0.6923874296839958,"base_score":2.995732273553991,"endowment":2.995732273553991,"self_citation_contribution":0.4493598410330987,"citation_network_contribution":0.2430275886508971,"self_endowment_contribution":0.4493598410330987,"citer_contribution":0.2430275886508971,"corpus_percentile":71.0837781387793,"corpus_rank":3739,"citation_count":19,"citer_count":18,"citers_with_citation_signal":7,"citers_with_endowment":7,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.5915,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":79.1667,"fair_percentile":97.67655151329869,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":563368,"name":"Omaditya Khanna","orcid":"0000-0002-6062-5382","position":1,"is_corresponding":false},{"id":1160080,"name":"Shan McBurney-Lin","orcid":"0000-0001-9829-5748","position":2,"is_corresponding":false},{"id":772298,"name":"Ryan McLean","orcid":null,"position":3,"is_corresponding":false},{"id":703209,"name":"Pierre Nedelec","orcid":"0000-0002-8535-1541","position":4,"is_corresponding":false},{"id":1160082,"name":"Arif Rashid","orcid":"0000-0002-3976-2956","position":5,"is_corresponding":false},{"id":874074,"name":"Nourel Hoda Tahon","orcid":"0009-0002-5863-0219","position":6,"is_corresponding":false},{"id":474492,"name":"Talissa A. Altes","orcid":"0000-0002-8969-8673","position":7,"is_corresponding":false},{"id":566046,"name":"Ujjwal Baid","orcid":"0000-0001-5246-2088","position":8,"is_corresponding":false},{"id":1160750,"name":"Radhika Bhalerao","orcid":null,"position":9,"is_corresponding":false},{"id":1325575,"name":"Yaseen Dhemesh","orcid":"0000-0003-2263-0452","position":10,"is_corresponding":false},{"id":536197,"name":"Scott Floyd","orcid":"0000-0002-8067-2426","position":11,"is_corresponding":false},{"id":701126,"name":"Devon Godfrey","orcid":"0000-0001-6406-1126","position":12,"is_corresponding":false},{"id":1160078,"name":"Fathi Hilal","orcid":"0000-0002-3325-984X","position":13,"is_corresponding":false},{"id":1160083,"name":"Anastasia Janas","orcid":"0000-0002-9932-2784","position":14,"is_corresponding":false},{"id":345391,"name":"Anahita Fathi Kazerooni","orcid":"0000-0001-7131-2261","position":15,"is_corresponding":false},{"id":907113,"name":"Collin Kent","orcid":"0000-0003-2628-6679","position":16,"is_corresponding":false},{"id":259415,"name":"John P. Kirkpatrick","orcid":"0000-0002-4019-0350","position":17,"is_corresponding":false},{"id":64853,"name":"Florian Kofler","orcid":"0000-0003-0642-7884","position":18,"is_corresponding":false},{"id":1325576,"name":"Kevin Leu","orcid":"0000-0002-0523-1575","position":19,"is_corresponding":false},{"id":1098148,"name":"Nazanin Maleki","orcid":null,"position":20,"is_corresponding":false},{"id":51419,"name":"Bjoern Menze","orcid":"0000-0003-4136-5690","position":21,"is_corresponding":false},{"id":1160081,"name":"Maxence Pajot","orcid":"0009-0001-3331-9128","position":22,"is_corresponding":false},{"id":1400,"name":"Zachary J. Reitman","orcid":"0000-0002-9122-9550","position":23,"is_corresponding":false},{"id":259727,"name":"Jeffrey D. Rudie","orcid":"0000-0001-8609-8421","position":24,"is_corresponding":false},{"id":275042,"name":"Rachit Saluja","orcid":"0000-0002-2567-9465","position":25,"is_corresponding":false},{"id":932562,"name":"Yury Velichko","orcid":"0000-0002-2287-5727","position":26,"is_corresponding":false},{"id":345257,"name":"Chunhao Wang","orcid":"0000-0002-6945-7119","position":27,"is_corresponding":false},{"id":553775,"name":"Pranav Warman","orcid":"0000-0001-5199-2474","position":28,"is_corresponding":false},{"id":274932,"name":"Nico Sollmann","orcid":"0000-0002-8120-2223","position":29,"is_corresponding":false},{"id":1326208,"name":"David Diffley","orcid":null,"position":30,"is_corresponding":false},{"id":1325577,"name":"Khanak Nandolia","orcid":"0000-0002-8627-2992","position":31,"is_corresponding":false},{"id":1262355,"name":"Daniel Warren","orcid":"0000-0002-6973-6900","position":32,"is_corresponding":false},{"id":1325578,"name":"Ali Shabbir Hussain","orcid":"0000-0002-3335-8768","position":33,"is_corresponding":false},{"id":1326209,"name":"John Pascal Fehringer","orcid":null,"position":34,"is_corresponding":false},{"id":1326210,"name":"Yulia Bronstein","orcid":null,"position":35,"is_corresponding":false},{"id":1326211,"name":"Lisa Deptula","orcid":null,"position":36,"is_corresponding":false},{"id":1325579,"name":"Evan G. Stein","orcid":"0000-0002-1260-4907","position":37,"is_corresponding":false},{"id":1325580,"name":"Mahsa Taherzadeh","orcid":"0000-0002-1037-5899","position":38,"is_corresponding":false},{"id":1326212,"name":"Eduardo Portela de Oliveira","orcid":null,"position":39,"is_corresponding":false},{"id":1326213,"name":"Aoife Haughey","orcid":null,"position":40,"is_corresponding":false},{"id":710193,"name":"Marinos Kontzialis","orcid":"0000-0001-9792-4979","position":41,"is_corresponding":false},{"id":669432,"name":"Luca Saba","orcid":"0000-0003-2870-3771","position":42,"is_corresponding":false},{"id":1325581,"name":"Benjamin Turner","orcid":"0000-0003-2181-0099","position":43,"is_corresponding":false},{"id":1326214,"name":"Melanie Brüßeler","orcid":null,"position":44,"is_corresponding":false},{"id":1325582,"name":"Shehbaz Ansari","orcid":"0000-0002-1319-6319","position":45,"is_corresponding":false},{"id":1325583,"name":"Athanasios Gkampenis","orcid":"0009-0005-0668-425X","position":46,"is_corresponding":false},{"id":1326215,"name":"David Maximilian Weiss","orcid":null,"position":47,"is_corresponding":false},{"id":1326216,"name":"Aya Mansour","orcid":null,"position":48,"is_corresponding":false},{"id":1326217,"name":"Islam H. Shawali","orcid":null,"position":49,"is_corresponding":false},{"id":1325584,"name":"Nikolay Yordanov","orcid":"0009-0009-1406-4754","position":50,"is_corresponding":false},{"id":240420,"name":"Joel M. Stein","orcid":"0000-0002-0741-1780","position":51,"is_corresponding":false},{"id":1325585,"name":"Roula Hourani","orcid":"0000-0002-5802-2611","position":52,"is_corresponding":false},{"id":1326218,"name":"Mohammed Yahya Moshebah","orcid":null,"position":53,"is_corresponding":false},{"id":1326219,"name":"Ahmed Magdy Abouelatta","orcid":null,"position":54,"is_corresponding":false},{"id":1325586,"name":"Tanvir Rizvi","orcid":"0000-0002-0335-8310","position":55,"is_corresponding":false},{"id":1285299,"name":"Klara Willms","orcid":null,"position":56,"is_corresponding":false},{"id":1326220,"name":"Dann C. Martin","orcid":null,"position":57,"is_corresponding":false},{"id":1326221,"name":"Abdullah Okar","orcid":null,"position":58,"is_corresponding":false},{"id":1058116,"name":"Gennaro D’Anna","orcid":"0000-0001-9890-9359","position":59,"is_corresponding":false},{"id":1325587,"name":"Ahmed Taha","orcid":"0000-0002-4108-5456","position":60,"is_corresponding":false},{"id":1325588,"name":"Yasaman Sharifi","orcid":"0000-0001-5563-6311","position":61,"is_corresponding":false},{"id":768902,"name":"Shahriar Faghani","orcid":"0000-0003-3275-2971","position":62,"is_corresponding":false},{"id":1325589,"name":"Dominic Kite","orcid":"0000-0001-8627-1036","position":63,"is_corresponding":false},{"id":312129,"name":"Marco C. Pinho","orcid":"0000-0002-4645-1638","position":64,"is_corresponding":false},{"id":1129509,"name":"Muhammad Ammar Haider","orcid":"0000-0002-8006-6426","position":65,"is_corresponding":false},{"id":1160077,"name":"Michelle Alonso‐Basanta","orcid":"0000-0001-9214-7656","position":66,"is_corresponding":false},{"id":263969,"name":"Javier Villanueva‐Meyer","orcid":"0000-0002-1212-4233","position":67,"is_corresponding":false},{"id":259726,"name":"Andreas M. Rauschecker","orcid":"0000-0003-0633-9876","position":68,"is_corresponding":false},{"id":1160084,"name":"Ayman Nada","orcid":"0000-0002-9296-9227","position":69,"is_corresponding":false},{"id":289882,"name":"Mariam Aboian","orcid":"0000-0002-4877-8271","position":70,"is_corresponding":false},{"id":286337,"name":"Adam E. Flanders","orcid":"0000-0002-4679-0787","position":71,"is_corresponding":false},{"id":103874,"name":"Spyridon Bakas","orcid":"0000-0001-8734-6482","position":72,"is_corresponding":false},{"id":297411,"name":"Evan Calabrese","orcid":"0000-0002-1464-0354","position":73,"is_corresponding":false},{"id":110324,"name":"Dominic LaBella","orcid":"0000-0003-1713-9538","position":0,"is_corresponding":true}],"reference_count":25,"raw_metadata":null,"created_at":"2026-07-19T02:07:38.055693Z","pmid":"38750041","pmcid":"PMC11096318","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":88.8889,"fair_a":75.0,"fair_i":60.0,"fair_r":50.0,"fair_zscore":1.77,"fair_rationale":{"fair_score":79.17,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":88.89,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"Calabrese, E. & LaBella, D. 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[majority verdict 'yes' (4/5 passes agreed)]","anchors":["RDA-F4-01M — FAIR Data Maturity Model: metadata is offered so it can be harvested and indexed (","NIH DMS Policy Element 4 (NOT-OD-21-014) — name the repository where data will be archived","NSTC Desirable Characteristics of Data Repositories (2022) — 'Long-Term Sustainability', 'Reten"],"scored":true,"signal":null},{"key":"f_data_availability_statement","label":"Data-availability statement","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"The BraTS Meningioma Pre-operative Dataset training (1,000/1,424, 70%) and validation (141/1,424, 10%) data are publicly available on Synapse 14.","grounded":true,"rationale":"The Data Records section points to a repository record with a DOI.","anchors":["Colavizza, Hrynaszkiewicz, Staden, Whitaker & McGillivray (2020), 'The citation advantage of li","Springer Nature research data policy — Data Availability Statements: standard statement templat","RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes"],"scored":false,"signal":null},{"key":"f_discovery_metadata","label":"Description of the dataset as an object","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"The BraTS Meningioma Pre-operative Dataset training (1,000/1,424, 70%) and validation (141/1,424, 10%) data are publicly available on Synapse 14.","grounded":true,"rationale":"The dataset description is given in running prose rather than an itemised inventory of files, variables, or records. 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[majority verdict 'no' (4/5 passes agreed)]","anchors":["RDA-R1.3-01M — 'Metadata complies with a community standard' (priority Essential)","RDA-R1.3-01D — 'Data complies with a community standard'","RDA-I2-01M — '(Meta)data use vocabularies that follow FAIR principles'"],"scored":false,"signal":null},{"key":"i_qualified_references","label":"Identifiers for the resources the data depend on","kind":"llm","weight":0.5,"fraction":1.0,"verdict":"yes","evidence":"The nnU-Net model as used for initial pre-automated segmentation is publicly available at (https://github.com/ecalabr/nnUNet_models).","grounded":true,"rationale":"A URL identifier is given for the code repository used in the study. [majority verdict 'yes' (4/5 passes agreed)]","anchors":["RDA-I3-01M — '(meta)data include references to other (meta)data'","RDA-I3-03M — 'metadata includes qualified references to other metadata'","FsF-I3-01M — F-UJI: 'Metadata includes links between the data and its related entities'"],"scored":false,"signal":null}]},"R":{"name":"Reusable","score":50.0,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No license for the data is stated in the paper; the article's CC-BY license applies to the article, not the data.","anchors":["RDA-R1.1-01M — 'Metadata includes information about the licence under which the data can be reu","RDA-R1.1-02M — 'Metadata refers to a standard reuse licence'","RDA-R1.1-03M — 'Metadata refers to a machine-understandable reuse licence'"],"scored":true,"signal":null},{"key":"r_provenance_methods","label":"Provenance of the data","kind":"llm","weight":1.0,"fraction":1.0,"verdict":"yes","evidence":"nnU-Net (version 1) (https://github.com/MIC-DKFZ/nnUNet/tree/nnunetv1)","grounded":true,"rationale":"A specific software tool and version is named for producing the data.","anchors":["RDA-R1.2-01M — 'Metadata includes provenance information according to community- specific standa","FsF-R1.2-01M — F-UJI: 'Metadata includes provenance information about data creation or generati","W3C PROV-O (W3C Recommendation, 2013) — the entity/activity/agent model of provenance"],"scored":false,"signal":null},{"key":"r_documentation_codebook","label":"Documentation / codebook","kind":"llm","weight":1.0,"fraction":0.5,"verdict":"partial","evidence":"The 'Meningioma supplementary clinical data and imaging parameters for training and validation sets.xlsx' file on the Synapse data repository describes the case level clinical patient data and the image parameters for the training and validation cases 14.","grounded":false,"rationale":"A documentation file (Excel spreadsheet) is named as accompanying the data on the repository. 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[majority verdict 'partial' (2/5 passes agreed)]","gain":0.0,"priority":"essential","scored":false},{"key":"i_community_standard_vocabulary","dimension":"I","label":"Community standard / vocabulary","action":"Adopt and NAME your domain's data standard — the minimum-information checklist, metadata schema, or ontology your community uses (MIAME/MINSEQE, ISA-Tab, BIDS, an OBO ontology, HL7 FHIR/OMOP) — and say which one you followed. A reporting checklist standardises your paper; it does nothing for your data. In neuroimaging, describe the data with BIDS, NIfTI or DICOM.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No data/metadata community standard such as MIAME, BIDS, or an ontology is named; the paper mentions clinical and imaging standards (CNS WHO, DICOM) but not as a community standard for the data. [majority verdict 'no' (4/5 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"r_documentation_codebook","dimension":"R","label":"Documentation / codebook","action":"Ship a README and a data dictionary IN the deposit — every file, every variable, its units, its allowed values, its missing-value codes. It is the cheapest single thing that makes a dataset usable by someone who was not in the lab, and a table buried in the article does not travel with the data.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The 'Meningioma supplementary clinical data and imaging parameters for training and validation sets.xlsx' file on the Synapse data repository describes the case level clinical patient data and the image parameters for the training and validation cases 14.","why":"A documentation file (Excel spreadsheet) is named as accompanying the data on the repository. [downgraded to 'partial' — no verifiable quote from the paper]","gain":0.0,"priority":"important","scored":false},{"key":"a_controlled_access_for_sensitive","dimension":"A","label":"Gatekeeper for sensitive data","action":"Route sensitive data through an institutional gatekeeper — deposit in a controlled- access repository (dbGaP, EGA) with a Data Access Committee and a published DUA — rather than through the corresponding author's inbox. An author-gated dataset dies with the author's email address, and 'on reasonable request' has been shown repeatedly not to yield data.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The data are publicly available and no gatekeeper is named; the paper states the data are openly accessible on Synapse.","gain":0.0,"priority":"useful","scored":false},{"key":"a_timeline_retention","dimension":"A","label":"Availability timing & retention","action":"State when the data become available AND how long they will be retained — cite the repository's preservation policy. NIH DMS Element 4 asks for both; most papers give neither.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No sentence states how long the data will persist or when they become available beyond the current release. [majority verdict 'no' (3/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","Version the deposit and cite the exact version analysed (a version-specific DOI, or an accession with its version suffix). A reader reproducing your work against 'the current release' is reproducing it against a different dataset.","Add a 'Data Records' section: itemise every file in the deposit and every variable or sample it holds, with counts and units. Describe the dataset as an object in its own right, not as a by-product of the findings — this is what makes it discoverable to someone who is not looking for your paper.","Adopt and NAME your domain's data standard — the minimum-information checklist, metadata schema, or ontology your community uses (MIAME/MINSEQE, ISA-Tab, BIDS, an OBO ontology, HL7 FHIR/OMOP) — and say which one you followed. A reporting checklist standardises your paper; it does nothing for your data. In neuroimaging, describe the data with BIDS, NIfTI or DICOM.","Ship a README and a data dictionary IN the deposit — every file, every variable, its units, its allowed values, its missing-value codes. It is the cheapest single thing that makes a dataset usable by someone who was not in the lab, and a table buried in the article does not travel with the data."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"unpaywall_pdf"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"unpaywall_pdf","fair_has_llm":true,"fair_computed_at":"2026-07-20T11:56:11.643074Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}