Zhijun Yao, Bin Hu, Xuejiao Chen, Yuanwei Xie, Lei Fang
{"title":"健康和癌症中代谢脑网络的模块化重构:静息状态PET研究","authors":"Zhijun Yao, Bin Hu, Xuejiao Chen, Yuanwei Xie, Lei Fang","doi":"10.1109/BIBM.2016.7822665","DOIUrl":null,"url":null,"abstract":"Recent studies suggested that cognitive impairments and memory difficulties in cancer survivors were associated with topology changes of brain network, particularly in terms of the functional and structural abnormalities. However, little is known about the modular reconfiguration of metabolic brain network among this population. In this study, we recruited 78 patients with pre-treatment cancer and 80 age- and gender-matched normal controls (NCs), and constructed the metabolic brain networks derived from resting-state 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to assess the alters of modularity pattern in cancer. The measurements of the participation index (PI) and mutual information (MI) were calculated for the cancer and NC groups. Compared with NC group, one module composed by the hippocampus, the amygdala and frontal and temporal regions was absented in cancer group. Moreover, cancer patients showed abnormal topology pattern in their metabolic networks (i.e., increased local efficiency and reduced global efficiency). Although node-wise PI shared positive correlated with normalized metabolism uptake in both groups, the more energy consumption were observed in metabolism network of cancer group that might be indicative of reduced capability of information processing. In addition, the between-group MIs were gradually increased over a range of thresholds. Our results suggested that modular pattern of the metabolic brain network seemed to re-shape its organization in cancer, which might uncover the neurobiological mechanisms underlying cancer-related cognitive dysfunction.","PeriodicalId":345384,"journal":{"name":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Modular reconfiguration of metabolic brain networks in health and cancer: A resting-state PET study\",\"authors\":\"Zhijun Yao, Bin Hu, Xuejiao Chen, Yuanwei Xie, Lei Fang\",\"doi\":\"10.1109/BIBM.2016.7822665\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent studies suggested that cognitive impairments and memory difficulties in cancer survivors were associated with topology changes of brain network, particularly in terms of the functional and structural abnormalities. However, little is known about the modular reconfiguration of metabolic brain network among this population. In this study, we recruited 78 patients with pre-treatment cancer and 80 age- and gender-matched normal controls (NCs), and constructed the metabolic brain networks derived from resting-state 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to assess the alters of modularity pattern in cancer. The measurements of the participation index (PI) and mutual information (MI) were calculated for the cancer and NC groups. Compared with NC group, one module composed by the hippocampus, the amygdala and frontal and temporal regions was absented in cancer group. Moreover, cancer patients showed abnormal topology pattern in their metabolic networks (i.e., increased local efficiency and reduced global efficiency). Although node-wise PI shared positive correlated with normalized metabolism uptake in both groups, the more energy consumption were observed in metabolism network of cancer group that might be indicative of reduced capability of information processing. In addition, the between-group MIs were gradually increased over a range of thresholds. Our results suggested that modular pattern of the metabolic brain network seemed to re-shape its organization in cancer, which might uncover the neurobiological mechanisms underlying cancer-related cognitive dysfunction.\",\"PeriodicalId\":345384,\"journal\":{\"name\":\"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"volume\":\"91 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBM.2016.7822665\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2016.7822665","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modular reconfiguration of metabolic brain networks in health and cancer: A resting-state PET study
Recent studies suggested that cognitive impairments and memory difficulties in cancer survivors were associated with topology changes of brain network, particularly in terms of the functional and structural abnormalities. However, little is known about the modular reconfiguration of metabolic brain network among this population. In this study, we recruited 78 patients with pre-treatment cancer and 80 age- and gender-matched normal controls (NCs), and constructed the metabolic brain networks derived from resting-state 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to assess the alters of modularity pattern in cancer. The measurements of the participation index (PI) and mutual information (MI) were calculated for the cancer and NC groups. Compared with NC group, one module composed by the hippocampus, the amygdala and frontal and temporal regions was absented in cancer group. Moreover, cancer patients showed abnormal topology pattern in their metabolic networks (i.e., increased local efficiency and reduced global efficiency). Although node-wise PI shared positive correlated with normalized metabolism uptake in both groups, the more energy consumption were observed in metabolism network of cancer group that might be indicative of reduced capability of information processing. In addition, the between-group MIs were gradually increased over a range of thresholds. Our results suggested that modular pattern of the metabolic brain network seemed to re-shape its organization in cancer, which might uncover the neurobiological mechanisms underlying cancer-related cognitive dysfunction.