Event Title

Generating and analyzing high resolution structural connectomes for breast cancer patients to assess cognitive impairment

Session Number

Project ID: CMPS 7

Advisor(s)

Dr. Lei Wang; NIACAL: Neuroimaging Applied Computational Anatomy Lab, Feinberg School of Medicine

Julie Petersen; NIACAL: Neuroimaging Applied Computational Anatomy Lab, Feinberg School of Medicine

Discipline

Computer Science

Start Date

22-4-2020 8:30 AM

End Date

22-4-2020 8:45 AM

Abstract

Post-surgery adjuvant therapy produces changes in cognitive function in up to 70% women with breast cancer. The nature of these changes is a relatively new area of research, with very few studies assessing the neural correlates of adjuvant hormonal therapy or determining how to identify individuals at risk for treatment-related cognitive impairment. This project is part of an ongoing HippoPCI study which uses magnetic resonance imaging (MRI) and structural and functional assessments that are sensitive to the integrity of the hippocampal-cortical circuitry to identify predictors and mechanisms of cognitive impairment in breast cancer patients receiving hormonal treatment. As part of HippoPCI, this project centers around creating a connectome for diffusion tensor images (DTI) using the high-resolution structural connectome (HRSC) methodology to visualize and assess the changes in connectivity from hormonal therapy. The HRSC quantifies the connectivity between each neuron using individual network elements such as nodes. We converted the incidence matrices for each of the subjects into connectivity matrices and degree maps and generated an average degree map for the population. Group analysis is being conducted using individual comparisons between each subject and the controls.

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Apr 22nd, 8:30 AM Apr 22nd, 8:45 AM

Generating and analyzing high resolution structural connectomes for breast cancer patients to assess cognitive impairment

Post-surgery adjuvant therapy produces changes in cognitive function in up to 70% women with breast cancer. The nature of these changes is a relatively new area of research, with very few studies assessing the neural correlates of adjuvant hormonal therapy or determining how to identify individuals at risk for treatment-related cognitive impairment. This project is part of an ongoing HippoPCI study which uses magnetic resonance imaging (MRI) and structural and functional assessments that are sensitive to the integrity of the hippocampal-cortical circuitry to identify predictors and mechanisms of cognitive impairment in breast cancer patients receiving hormonal treatment. As part of HippoPCI, this project centers around creating a connectome for diffusion tensor images (DTI) using the high-resolution structural connectome (HRSC) methodology to visualize and assess the changes in connectivity from hormonal therapy. The HRSC quantifies the connectivity between each neuron using individual network elements such as nodes. We converted the incidence matrices for each of the subjects into connectivity matrices and degree maps and generated an average degree map for the population. Group analysis is being conducted using individual comparisons between each subject and the controls.