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Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).

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Correlation Between Neurocognitive Outcomes and Neuroaxonal Connectome Alterations After Whole Brain Radiotherapy: A

Sreenija Yarlagadda¹, Starlie Belnap², John Candela²

¹Miami Cancer Institute, Baptist Health South Florida, Miami, FL 33176, USA.

|June 13, 2025

Summary

Whole brain radiotherapy (WBRT) alters brain connectivity, impacting neurocognitive functions. This study used connectomics to map these changes, revealing correlations between network anomalies and cognitive decline.

Keywords:

brain mapping brain networks connectomics diffusion tensor imaging magnetic resonance neurocognitive outcomes whole brain radiotherapy

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Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

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Published on: August 12, 2019

Area of Science:

Neuroscience
Medical Imaging
Radiotherapy

Background:

Connectomics, the study of brain connectivity, is a rapidly advancing field.
Whole brain radiotherapy (WBRT) is a common cancer treatment, but its effects on brain structure and function are not fully understood.

Purpose of the Study:

To prospectively evaluate the impact of WBRT on the human brain connectome using advanced imaging techniques.
To correlate changes in brain connectivity with neurocognitive outcomes following WBRT.

Main Methods:

Combined diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) to assess structural and functional brain connectivity.
Utilized a machine learning algorithm to create individualized brain network maps and compare them to the Human Connectome Project database.
Performed connectome analysis and neurocognitive testing at baseline and 3 months post-WBRT.

Main Results:

The multiple demand network exhibited the highest anomaly frequency (46%) at baseline.
WBRT led to increased proportional anomaly frequencies across multiple brain networks.
Significant correlations were observed between declines in learning and memory domains and changes in the subcortical network.

Conclusions:

This proof-of-concept study demonstrates that WBRT significantly alters brain connectivity, as evidenced by connectome analysis.
Changes in brain network anomalies post-WBRT correlate with observed neurocognitive deficits.
Further research in larger cohorts is warranted to explore correlations with white matter changes and tumor characteristics.