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Predicting Patient Reported Outcomes of Cognitive Function Using Connectome-Based Predictive Modeling in Breast

Ashley M Henneghan1, Chris Gibbons2, Rebecca A Harrison3

  • 1School of Nursing, University of Texas at Austin, 1710 Red River St., Austin, TX, 78712, USA. ahenneghan@utexas.edu.

Brain Topography
|November 21, 2019
PubMed
Summary
This summary is machine-generated.

Baseline brain scans may predict cognitive issues in breast cancer patients. Resting-state fMRI before treatment can identify individuals at risk for cancer-related cognitive impairment (CRCI), aiding early intervention.

Keywords:
Breast cancerCancer related cognitive impairmentConnectomeConnectome-based predictive modelingExecutive functionMemory

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Area of Science:

  • Neuroscience
  • Oncology
  • Medical Imaging

Background:

  • Cancer-related cognitive impairment (CRCI) affects patient care and incurs significant costs.
  • Predicting CRCI is crucial for timely intervention and improved patient outcomes.
  • Previous research has not fully explored predictive neuroimaging markers for CRCI.

Purpose of the Study:

  • To determine if baseline resting-state functional magnetic resonance imaging (fMRI) can predict patient-reported CRCI in breast cancer patients.
  • To assess cognitive function changes over time in breast cancer patients undergoing chemotherapy versus those not receiving chemotherapy.
  • To identify neuroimaging predictors of executive dysfunction and memory decline.

Main Methods:

  • Recruited 76 newly diagnosed breast cancer patients and 50 healthy controls.
  • Collected self-reported cognitive function (executive dysfunction, memory) and psychological distress data at three time points.
  • Acquired resting-state fMRI data, converted to connectome matrices, and applied connectome-based predictive modeling (CPM) and support vector regression (SVR).

Main Results:

  • Chemotherapy patients showed increased executive dysfunction over time; memory function declined in both patient groups compared to controls.
  • CPM models successfully predicted executive dysfunction and memory function scores (r > 0.31, p < 0.002).
  • SVR RBF demonstrated high performance in predicting executive dysfunction (r=0.68) and memory function (r=0.44).

Conclusions:

  • Baseline resting-state fMRI shows potential for predicting patient-reported cognitive outcomes in breast cancer survivors.
  • Neuroimaging markers may help identify patients requiring surveillance or early intervention for treatment-related cognitive effects.
  • This approach could personalize care and mitigate the impact of CRCI.