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Brain connectivity tracks effects of chemotherapy separately from behavioral measures.

ABSTRACT: Several studies in cancer research have suggested that cognitive dysfunction following chemotherapy, referred to in lay terms as "chemobrain", is a serious problem. At present, the changes in integrative brain function that underlie such dysfunction remain poorly understood. Recent developments in neuroimaging suggest that patterns of functional connectivity can provide a broadly applicable neuromarker of cognitive performance and other psychometric measures. The current study used multivariate analysis methods to identify patterns of disruption in resting state functional connectivity of the brain due to chemotherapy and the degree to which the disruptions can be linked to behavioral measures of distress and cognitive performance. Sixty two women (22 healthy control, 18 patients treated with adjuvant chemotherapy, and 22 treated without chemotherapy) were evaluated with neurocognitive measures followed by self-report questionnaires and open eyes resting-state fMRI scanning at three time points: diagnosis (M0, pre-adjuvant treatment), 1?month (M1), and 7?months (M7) after treatment. The results indicated deficits in cognitive health of breast cancer patients immediately after chemotherapy that improved over time. This psychological trajectory was paralleled by a disruption and later recovery of resting-state functional connectivity, mostly in the parietal and frontal brain regions. Mediation analysis showed that the functional connectivity alteration pattern is a separable treatment symptom from the decreased cognitive health. Current study indicates that more targeted support for patients should be developed to ameliorate these multi-faceted side effects of chemotherapy treatment on neural functioning and cognitive health.

SUBMITTER: Kardan O

PROVIDER: S-EPMC6412071 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Brain connectivity tracks effects of chemotherapy separately from behavioral measures.

Kardan Omid O Reuter-Lorenz Patricia A PA Peltier Scott S Churchill Nathan W NW Misic Bratislav B Askren Mary K MK Jung Mi Sook MS Cimprich Bernadine B Berman Marc G MG

NeuroImage. Clinical 20190106

Several studies in cancer research have suggested that cognitive dysfunction following chemotherapy, referred to in lay terms as "chemobrain", is a serious problem. At present, the changes in integrative brain function that underlie such dysfunction remain poorly understood. Recent developments in neuroimaging suggest that patterns of functional connectivity can provide a broadly applicable neuromarker of cognitive performance and other psychometric measures. The current study used multivariate ...[more]

PMID: 30642760

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Project description:Graph theoretical approaches have successfully revealed abnormality in brain connectivity, in particular, for contrasting patients from healthy controls. Besides the group comparison analysis, a correlational study is also challenging. In studies with patients, for example, finding brain connections that indeed deepen specific symptoms is interesting. The correlational study is also beneficial since it does not require controls, which are often difficult to find, especially for old-age patients with cognitive impairment where controls could also have cognitive deficits due to normal ageing. However, one of the major difficulties in such correlational studies is too conservative multiple comparison correction. In this paper, we propose a novel method for identifying brain connections that are correlated with a specific cognitive behavior by employing cluster-based statistics, which is less conservative than other methods, such as Bonferroni correction, false discovery rate procedure, and extreme statistics. Our method is based on the insight that multiple brain connections, rather than a single connection, are responsible for abnormal behaviors. Given brain connectivity data, we first compute a partial correlation coefficient between every edge and the behavioral measure. Then we group together neighboring connections with strong correlation into clusters and calculate their maximum sizes. This procedure is repeated for randomly permuted assignments of behavioral measures. Significance levels of the identified sub-networks are estimated from the null distribution of the cluster sizes. This method is independent of network construction methods: either structural or functional network can be used in association with any behavioral measures. We further demonstrated the efficacy of our method using patients with subcortical vascular cognitive impairment. We identified sub-networks that are correlated with the disease severity by exploiting diffusion tensor imaging techniques. The identified sub-networks were consistent with the previous clinical findings having valid significance level, while other methods did not assert any significant findings.

Dataset Information

Brain connectivity tracks effects of chemotherapy separately from behavioral measures.

Publications

Brain connectivity tracks effects of chemotherapy separately from behavioral measures.

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