DSAI-02 LOCATION-SPECIFIC BIOMARKER ATLAS OF THE BRAIN

Abstract A new way to understand the brain may emerge if a location-specific biomarker atlas of the brain can be developed. Emerging technologies combined with new innovations and ML/AI techniques can enable the creation of such an atlas. The architecture of a system that enables the non-invasive data acquisition of the location-specific biomarkers and analysis of such data using ML/AI techniques is described. The key technology that makes building such atlases possible is the accurate and non-invasive focused ultrasound-based blood-brain barrier opening (BBB). The BBB can be opened safely and accurately with focused ultrasound and microbubbles at a desired location in the brain. Biomarkers can pass through the open BBB into the circulatory system and subsequently be sampled from a peripheral site. The biomarker makeup and concentration associated with the location of the opening can thus be determined. An atlas can be built by repeating the procedure over multiple time points and patients. Thus, a location-specific biomarker atlas of the brain can be developed. The data in the atlas can be obtained for various attributes such as disease type, including brain cancers, disease stage, age, and gender. Once created with sufficient data and associated information, the atlas can serve as a reference for understanding the biomarker composition of the brain for one or multiple attributes. Currently, the knowledge of what the biomarkers mean is limited, as location-specific biomarkers for the brain have not been readily available. As location-specific biomarker data is collected over multiple individuals and multiple diseases, ML/AI techniques will be used to discover biomarker patterns and associations to various conditions in the brain. Tools such as clinical decision support tools can be built utilizing the atlas data and can potentially guide therapy decisions, aid in developing new drugs, and can be used for disease monitoring.

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Publication Details

Journal
Neuro-Oncology Advances
Published
2025-08-01
DOI
https://doi.org/10.1093/noajnl/vdaf123.035
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

DSAI-02 LOCATION-SPECIFIC BIOMARKER ATLAS OF THE BRAIN

Bhaskar Ramamurthy
Neuro-Oncology Advances
Radiomics and Machine Learning in Medical Imaging
article

DSAI-02 LOCATION-SPECIFIC BIOMARKER ATLAS OF THE BRAIN

Bhaskar Ramamurthy
article en

Abstract

Abstract A new way to understand the brain may emerge if a location-specific biomarker atlas of the brain can be developed. Emerging technologies combined with new innovations and ML/AI techniques can enable the creation of such an atlas. The architecture of a system that enables the non-invasive data acquisition of the location-specific biomarkers and analysis of such data using ML/AI techniques is described. The key technology that makes building such atlases possible is the accurate and non-invasive focused ultrasound-based blood-brain barrier opening (BBB). The BBB can be opened safely and accurately with focused ultrasound and microbubbles at a desired location in the brain. Biomarkers can pass through the open BBB into the circulatory system and subsequently be sampled from a peripheral site. The biomarker makeup and concentration associated with the location of the opening can thus be determined. An atlas can be built by repeating the procedure over multiple time points and patients. Thus, a location-specific biomarker atlas of the brain can be developed. The data in the atlas can be obtained for various attributes such as disease type, including brain cancers, disease stage, age, and gender. Once created with sufficient data and associated information, the atlas can serve as a reference for understanding the biomarker composition of the brain for one or multiple attributes. Currently, the knowledge of what the biomarkers mean is limited, as location-specific biomarkers for the brain have not been readily available. As location-specific biomarker data is collected over multiple individuals and multiple diseases, ML/AI techniques will be used to discover biomarker patterns and associations to various conditions in the brain. Tools such as clinical decision support tools can be built utilizing the atlas data and can potentially guide therapy decisions, aid in developing new drugs, and can be used for disease monitoring.

Neuro-Oncology AdvancesVol. 7(Supplement_2)
Corden Pharma (United States) (US)
Openalex Percentile: Top 71%
Radiomics and Machine Learning in Medical Imaging
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