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Abstract #4520

Multimodal Correlation and Connectivity Analysis on Simultaneously Recorded MR-PET data

Ravichandran Rajkumar1,2, Elena Rota Kops3, Jürgen Scheins4, Lutz Tellmann4, Christoph Lerche4, Karl-Josef Langen4,5, Hans Herzog4, N. Jon Shah4,6,7,8, and Irene Neuner2,4

1Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Jülich GmbH, Jülich, Germany, 2Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany, 3Forschungszentrum Juelich GmbH, Institute of Neuroscience and Medicine - 4, Jülich, Germany, 4Institute of Neuroscience and Medicine 4 (INM4), Forschungszentrum Jülich GmbH, Jülich, Germany, 5Department of Nuclear Medicine, RWTH Aachen University, Aachen, Germany, 6Institute of Neuroscience and Medicine 11, Forschungszentrum Jülich GmbH, Jülich, Germany, 7Department of Neurology, RWTH Aachen University, Aachen, Germany, 8Monash Biomedical Imaging, School of Psychological Sciences, Monash University, Melbourne, Australia

On a simultaneously recorded resting state MR-PET data, the functional connectivity metrics (namely ReHo, fALFF, and DC) from fMRI and the glucose metabolism from FDG – PET are calculated and correlated in the default mode network (DMN) regions of the brain. Results shows high connectivity of the DMN hubs is coupled with a high glucose consumption. Further investigations in patients are necessary to explore the potential of simultaneous imaging as a biomarker for disease staging, treatment response and monitoring

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