2024
Brain Connectomics Improve the Prediction of High‐Risk Depression Profiles in the First Year following Breast Cancer Diagnosis
Liang M, Chen P, Tang Y, Tang X, Molassiotis A, Knobf M, Liu M, Hu G, Sun Z, Yu Y, Ye Z. Brain Connectomics Improve the Prediction of High‐Risk Depression Profiles in the First Year following Breast Cancer Diagnosis. Depression And Anxiety 2024, 2024: 1-11. DOI: 10.1155/2024/3103115.Peer-Reviewed Original ResearchBreast cancer diagnosisLatent growth mixture modelingMultivoxel pattern analysisDepression profilesCancer diagnosisBrain connectomeBaseline resting-state functional magnetic resonance imagingResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingAssessment of depressionFrontal medial cortexBrain connectivity patternsGrowth mixture modelingDepression trajectoriesFrontal poleBrain areasRs-fMRIBreast cancerConnectivity patternsHigh riskLow riskBrainConnectomeMagnetic resonance imagingMedial cortex
2023
Brain connectomics improve prediction of 1-year decreased quality of life in breast cancer: A multi-voxel pattern analysis
Liang M, Tang Y, Chen P, Tang X, Knobf M, Hu G, Sun Z, Liu M, Yu Y, Ye Z. Brain connectomics improve prediction of 1-year decreased quality of life in breast cancer: A multi-voxel pattern analysis. European Journal Of Oncology Nursing 2023, 68: 102499. PMID: 38199087, DOI: 10.1016/j.ejon.2023.102499.Peer-Reviewed Original ResearchNet reclassification improvementIntegrated discrimination improvementBreast cancerQuality of lifeBrain areasResting-state connectivity patternsLong-term QOL outcomesState functional magnetic resonance imagingMultivoxel pattern analysisConventional risk factorsBreast cancer patientsBrain connectomicsSuperior frontal gyrusFunctional magnetic resonance imagingMagnetic resonance imagingMulti-centre samplePotential intervention targetsReclassification improvementCancer patientsQOL outcomesRisk factorsQoL assessmentDiscrimination improvementParacingulate gyrusResonance imaging