Dataset Information

A multi-institutional pediatric dataset of clinical radiology MRIs by the Children's Brain Tumor Network.

ABSTRACT: Pediatric brain and spinal cancers remain the leading cause of cancer-related death in children. Advancements in clinical decision-support in pediatric neuro-oncology utilizing the wealth of radiology imaging data collected through standard care, however, has significantly lagged other domains. Such data is ripe for use with predictive analytics such as artificial intelligence (AI) methods, which require large datasets. To address this unmet need, we provide a multi-institutional, large-scale pediatric dataset of 23,101 multi-parametric MRI exams acquired through routine care for 1,526 brain tumor patients, as part of the Children's Brain Tumor Network. This includes longitudinal MRIs across various cancer diagnoses, with associated patient-level clinical information, digital pathology slides, as well as tissue genotype and omics data. To facilitate downstream analysis, treatment-naïve images for 370 subjects were processed and released through the NCI Childhood Cancer Data Initiative via the Cancer Data Service. Through ongoing efforts to continuously build these imaging repositories, our aim is to accelerate discovery and translational AI models with real-world data, to ultimately empower precision medicine for children.

SUBMITTER: Familiar AM

PROVIDER: S-EPMC10723526 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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A multi-institutional pediatric dataset of clinical radiology MRIs by the Children's Brain Tumor Network.

Familiar Ariana M AM Kazerooni Anahita Fathi AF Anderson Hannah H Lubneuski Aliaksandr A Viswanathan Karthik K Breslow Rocky R Khalili Nastaran N Bagheri Sina S Haldar Debanjan D Kim Meen Chul MC Arif Sherjeel S Madhogarhia Rachel R Nguyen Thinh Q TQ Frenkel Elizabeth A EA Helili Zeinab Z Harrison Jessica J Farahani Keyvan K Linguraru Marius George MG Bagci Ulas U Velichko Yury Y Stevens Jeffrey J Leary Sarah S Lober Robert M RM Campion Stephani S Smith Amy A AA Morinigo Denise D Rood Brian B Diamond Kimberly K Pollack Ian F IF Williams Melissa M Vossough Arastoo A Ware Jeffrey B JB Mueller Sabine S Storm Phillip B PB Heath Allison P AP Waanders Angela J AJ Lilly Jena J Mason Jennifer L JL Resnick Adam C AC Nabavizadeh Ali A

ArXiv 20231002

Pediatric brain and spinal cancers remain the leading cause of cancer-related death in children. Advancements in clinical decision-support in pediatric neuro-oncology utilizing the wealth of radiology imaging data collected through standard care, however, has significantly lagged other domains. Such data is ripe for use with predictive analytics such as artificial intelligence (AI) methods, which require large datasets. To address this unmet need, we provide a multi-institutional, large-scale pe ...[more]

PMID: 38106459

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Dataset Information

A multi-institutional pediatric dataset of clinical radiology MRIs by the Children's Brain Tumor Network.

Publications

A multi-institutional pediatric dataset of clinical radiology MRIs by the Children's Brain Tumor Network.

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