Dataset Information

Radio-pathomic approaches in pediatric neuro-oncology: Opportunities and challenges.

ABSTRACT: With medical software platforms moving to cloud environments with scalable storage and computing, the translation of predictive artificial intelligence (AI) models to aid in clinical decision-making and facilitate personalized medicine for cancer patients is becoming a reality. Medical imaging, namely radiologic and histologic images, has immense analytical potential in neuro-oncology, and models utilizing integrated radiomic and pathomic data may yield a synergistic effect and provide a new modality for precision medicine. At the same time, the ability to harness multi-modal data is met with challenges in aggregating data across medical departments and institutions, as well as significant complexity in modeling the phenotypic and genotypic heterogeneity of pediatric brain tumors. In this paper, we review recent pathomic and integrated pathomic, radiomic, and genomic studies with clinical applications. We discuss current challenges limiting translational research on pediatric brain tumors and outline technical and analytical solutions. Overall, we propose that to empower the potential residing in radio-pathomics, systemic changes in cross-discipline data management and end-to-end software platforms to handle multi-modal data sets are needed, in addition to embracing modern AI-powered approaches. These changes can improve the performance of predictive models, and ultimately the ability to advance brain cancer treatments and patient outcomes through the development of such models.

SUBMITTER: Familiar AM

PROVIDER: S-EPMC10576517 | biostudies-literature | 2023 Jan-Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Radio-pathomic approaches in pediatric neuro-oncology: Opportunities and challenges.

Familiar Ariana M AM Mahtabfar Aria A Fathi Kazerooni Anahita A Kiani Mahsa M Vossough Arastoo A Viaene Angela A Storm Phillip B PB Resnick Adam C AC Nabavizadeh Ali A

Neuro-oncology advances 20230101 1

With medical software platforms moving to cloud environments with scalable storage and computing, the translation of predictive artificial intelligence (AI) models to aid in clinical decision-making and facilitate personalized medicine for cancer patients is becoming a reality. Medical imaging, namely radiologic and histologic images, has immense analytical potential in neuro-oncology, and models utilizing integrated radiomic and pathomic data may yield a synergistic effect and provide a new mod ...[more]

PMID: 37841693

Similar Datasets

Project description:BackgroundEnsuring equitable access to treatments and therapies in the constantly evolving field of neuro-oncology is an imperative global health issue. With its unique demographic, cultural, socioeconomic, and infrastructure characteristics, Sub-Saharan Africa faces distinct challenges. This literature review highlights specific barriers to neuro-oncology care in the region and explores potential opportunities for enhancing access.MethodsPredetermined keyword searches were employed to screen titles and abstracts using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework. Inclusion criteria were studies published between January 1, 2003, and June 20, 2023, specifically addressing the capacity and challenges of neuro-oncology in the Sub-Saharan African region. The data sources queried were PubMed and Google Scholar. Systematic reviews and meta-analyses were deliberately excluded. All authors conducted independent screening and structured data extraction meticulously.ResultsOur paper identified multiple challenges that impede access to quality treatment for brain tumors. These include constrained resources, insufficient training of healthcare professionals, certain cultural beliefs, and a general lack of awareness about brain tumors, all contributing to delayed diagnosis and treatment. Furthermore, the lack of detailed data on the incidence and prevalence of primary central nervous system tumors impairs the accurate assessment of disease burden and precise identification of areas requiring improvement. However, we discovered that ongoing research, advocacy, enhanced training, mentorship, and collaborative efforts present valuable opportunities for substantial progress in neuro-oncology access.ConclusionsWhile we provide a glimpse of the current state, we hope these results will help stimulate dialogue and catalyze initiatives to surmount highlighted obstacles and improve neuro-oncology outcomes across Sub-Saharan Africa.

Dataset Information

Radio-pathomic approaches in pediatric neuro-oncology: Opportunities and challenges.

Publications

Radio-pathomic approaches in pediatric neuro-oncology: Opportunities and challenges.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets