Generating and Analyzing High-Resolution Structural Connectomes for Breast Cancer Patients to Assess Cognitive Impairment
Advisor(s)
Dr. Lei Wang; Northwestern University
Discipline
Computer Science
Start Date
21-4-2021 10:05 AM
End Date
21-4-2021 10:20 AM
Abstract
Breast cancer patients have reported symptoms such as fatigue, insomnia, and depression while undergoing adjuvant therapy. Previous research has found that chemotherapy, a treatment for breast cancer, can lead to cognitive decline. However, the neurologic effects of other adjuvant therapies, such as hormone therapy, have yet to be fully explored. The objective of this study was to use diffusion tensor imaging (DTI) to assess structural connectivity changes through a wholebrain analysis and identify mechanisms of cognitive impairment in breast cancer patients receiving hormone treatment. High-resolution structural connectivity analysis was applied to the DTI scans from two groups: breast cancer patients who were undergoing hormone therapy at the time of study and healthy controls without a history of cancer. The incidence matrices were processed according to high-resolution structural connectivity analysis and converted into connectivity matrices, which quantify the connectivity between each neuron using individual network nodes. Group analysis was conducted using individual correlations between subject-specific degree maps and a population average degree map. Identifying the effects of hormone therapy on brain structural connectivity in breast cancer patients is vital to the development of future treatments to improve the quality of life for patients.
Generating and Analyzing High-Resolution Structural Connectomes for Breast Cancer Patients to Assess Cognitive Impairment
Breast cancer patients have reported symptoms such as fatigue, insomnia, and depression while undergoing adjuvant therapy. Previous research has found that chemotherapy, a treatment for breast cancer, can lead to cognitive decline. However, the neurologic effects of other adjuvant therapies, such as hormone therapy, have yet to be fully explored. The objective of this study was to use diffusion tensor imaging (DTI) to assess structural connectivity changes through a wholebrain analysis and identify mechanisms of cognitive impairment in breast cancer patients receiving hormone treatment. High-resolution structural connectivity analysis was applied to the DTI scans from two groups: breast cancer patients who were undergoing hormone therapy at the time of study and healthy controls without a history of cancer. The incidence matrices were processed according to high-resolution structural connectivity analysis and converted into connectivity matrices, which quantify the connectivity between each neuron using individual network nodes. Group analysis was conducted using individual correlations between subject-specific degree maps and a population average degree map. Identifying the effects of hormone therapy on brain structural connectivity in breast cancer patients is vital to the development of future treatments to improve the quality of life for patients.