{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":["Moawad AW"],"funding":["NCI NIH HHS"],"pubmed_abstract":["The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Haus"],"journal":["ArXiv"],"pagination":["arXiv:2306.00838v3"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10312806"],"repository":["biostudies-literature"],"pubmed_title":["The Brain Tumor Segmentation - Metastases (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI."],"pmcid":["PMC10312806"],"funding_grant_id":["R21 CA259964","U01 CA242871"],"pubmed_authors":["Li HB","Pfluger I","Janas A","Maros ME","Bisschop J","Vilanilam GK","Amiruddin R","Farage L","LaMontagne P","Krycia M","Shih R","Dellepiane F","Krantchev K","Godfrey D","Haider MA","Patel U","Kida L","Iv M","Van Leemput K","Sanchez-Garcia LM","Shiroishi MS","Villanueva-Meyer J","Dhemesh Y","Teytelboym O","Ramakrishnan D","Schrickel EB","Nandolia KK","Gass J","Young R","Lin M","Sabouhi S","Jacobs SM","Patel MD","Deptula L","Yousry S","Perez-Garcia VM","Rawie E","Turner B","Azizova A","Corr F","Fung SH","Ghonim M","Kam A","Sollmann N","Miller E","Chung V","McArthur M","Joyner D","Ashraf K","Ashraf N","Gulati V","Lost J","So TY","Wiggins W","Petrucci S","Bansal A","Frick A","Koukoulithras I","Kollia S","Nouh AMA","Vacca S","Besada C","Lincoln CM","Patro SN","Shafique U","Bergquist T","Moassefi M","Aneja S","Tillmans N","Saluja R","Thompson G","Marcus DS","Shawali IH","Velichko YS","Rohatgi S","Holler W","Thacker J","Chen J","Small JE","Malhotra A","Mateo-Camacho YS","Shinohara RT","Anwar SM","Weiss D","Chakrabarty S","Roohani B","Petrovic B","Anazodo U","Li X","Memon F","Kersting K","Avesta A","Ozsarlak O","Crawley A","Adewole M","Raymond S","Krumpelman C","Foltyn-Dumitru M","Dahl RH","Liu X","Jiang Z","Karargyris A","Letourneau-Guillon L","Bukatz J","Kassem H","Badawy M","Al-Rubaiey S","Kandemirli SG","Yordanov N","Conte GM","Aboian M","Pasquini L","Pati S","Schwartz ED","Farahani K","Okar A","Lohmann P","Morsi SM","Suthar PP","Calabrese E","Osenberg K","Lai L","Postma AA","Perez-Carillo GJG","Bendszus M","Gray RI","Rudie JD","Dusoi A","de Verdier MC","Mahajan A","Sharifi Y","Johnson DR","Chu S","Soumala T","Bakas S","Lerebo W","Kofler F","Willms K","Ezhov I","Hierro F","Marsiglia M","Moy H","Feltrin F","Nada A","Sotiras A","Dako F","Maresca R","Cramer J","Altes T","Druzgal J","Faghani S","Abayazeed AH","Reitman Z","Sheller M","Baid U","Meier Z","Kazerooni AF","Kwan BYM","Menze BH","Albrecht J","Elhalawani H","Zohrabian VM","Manteghinejad A","Saha A","Pappafava F","Nikanpour Y","Cassinelli Pedersen G","Lomer NB","Aristizabal A","LaBella D","Gkampenis A","Jekel L","Wiestler B","Brugnara G","Alnoury M","Wu L","Wang C","Munteanu A","Kaur M","Westerhoff M","Gennaro N","Singh G","Abouelatta A","Isufi E","Rauschecker A","Fehringer P","Chiang V","Iglesias JE","Merkaj S","Maria-Zamfirescu RC","von Reppert M","Ikuta I","Worede F","Hsieh KJ","McDonnell O","Taherzadeh M","Maleki N","Tanwar M","Vollmuth P","Weinberg BD","Fong A","Youssef A","Nimchinsky EA","Asla MM","Barkhof F","Elakhdar T","Eddy J","Sayah A","Moawad AW","Floyd S","Moron FEA","Cho J","Link KEE","Linguraru MG","White ML","Brußeler MMT","Shaked Z","Bousabarah K","Khalili N","Tahon NH","Piraud M","Armindo RD","McHugh M","Lall NU","Mansour A","Naqvi SR","Tarabishy AR","Valerie J","Warren D","Cimflova P","Johanson E"],"additional_accession":[]},"is_claimable":false,"name":"The Brain Tumor Segmentation - Metastases (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI.","description":"The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Haus","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Dec","modification":"2026-04-08T15:33:30.441Z","creation":"2026-04-08T04:51:10.41Z"},"accession":"S-EPMC10312806","cross_references":{"pubmed":["37396600"]}}