Connectivity based on glucose dynamics reveals exaggerated sensorimotor network coupling on subject-level in Parkinson’s disease
Purpose While fMRI provides information on the temporal changes in blood oxygenation, 2- [18F]fluoro-2-deoxy-D-glucose ([ 18 F]FDG)-PET has traditionally offered a static snapshot of brain glucose consumption. As a result, studies investigating metabolic brain networks as potential biomarkers for ne...
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Published in | European journal of nuclear medicine and molecular imaging Vol. 51; no. 12; pp. 3630 - 3642 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.10.2024
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
ISSN | 1619-7070 1619-7089 1619-7089 |
DOI | 10.1007/s00259-024-06796-6 |
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Abstract | Purpose
While fMRI provides information on the temporal changes in blood oxygenation, 2- [18F]fluoro-2-deoxy-D-glucose ([
18
F]FDG)-PET has traditionally offered a static snapshot of brain glucose consumption. As a result, studies investigating metabolic brain networks as potential biomarkers for neurodegeneration have primarily been conducted at the group level. However, recent pioneering studies introduced time-resolved [
18
F]FDG-PET with constant infusion, which enables metabolic connectivity studies at the individual level.
Methods
In the current study, this technique was employed to explore Parkinson’s disease (PD)-related alterations in individual metabolic connectivity, in comparison to inter-subject measures and hemodynamic connectivity. Fifteen PD patients and 14 healthy controls with comparable cognition underwent sequential resting-state dynamic PET with constant infusion and functional MRI. Intrinsic networks were identified by independent component analysis and interregional connectivity calculated for summed static PET images, PET time series and functional MRI.
Results
Our findings revealed an intrinsic sensorimotor network in PD patients that has not been previously observed to this extent. In PD, a significantly higher number of connections in cortical motor areas was observed compared to elderly control subjects, as indicated by both static PET and functional MRI (
p
Bonferroni−Holm
= 0.027), as well as constant infusion PET and functional MRI connectomes (
p
Bonferroni−Holm
= 0.012). This intensified coupling was associated with disease severity (
ρ
= 0.56,
p
= 0.036).
Conclusion
Metabolic connectivity, as revealed by both static and dynamic PET, provides unique information on metabolic network activity. Subject-level metabolic connectivity based on constant infusion PET may serve as a potential marker for the metabolic network signature in neurodegeneration. |
---|---|
AbstractList | PurposeWhile fMRI provides information on the temporal changes in blood oxygenation, 2- [18F]fluoro-2-deoxy-D-glucose ([18F]FDG)-PET has traditionally offered a static snapshot of brain glucose consumption. As a result, studies investigating metabolic brain networks as potential biomarkers for neurodegeneration have primarily been conducted at the group level. However, recent pioneering studies introduced time-resolved [18F]FDG-PET with constant infusion, which enables metabolic connectivity studies at the individual level.MethodsIn the current study, this technique was employed to explore Parkinson’s disease (PD)-related alterations in individual metabolic connectivity, in comparison to inter-subject measures and hemodynamic connectivity. Fifteen PD patients and 14 healthy controls with comparable cognition underwent sequential resting-state dynamic PET with constant infusion and functional MRI. Intrinsic networks were identified by independent component analysis and interregional connectivity calculated for summed static PET images, PET time series and functional MRI.ResultsOur findings revealed an intrinsic sensorimotor network in PD patients that has not been previously observed to this extent. In PD, a significantly higher number of connections in cortical motor areas was observed compared to elderly control subjects, as indicated by both static PET and functional MRI (pBonferroni−Holm = 0.027), as well as constant infusion PET and functional MRI connectomes (pBonferroni−Holm = 0.012). This intensified coupling was associated with disease severity (ρ = 0.56, p = 0.036).ConclusionMetabolic connectivity, as revealed by both static and dynamic PET, provides unique information on metabolic network activity. Subject-level metabolic connectivity based on constant infusion PET may serve as a potential marker for the metabolic network signature in neurodegeneration. Purpose While fMRI provides information on the temporal changes in blood oxygenation, 2- [18F]fluoro-2-deoxy-D-glucose ([ 18 F]FDG)-PET has traditionally offered a static snapshot of brain glucose consumption. As a result, studies investigating metabolic brain networks as potential biomarkers for neurodegeneration have primarily been conducted at the group level. However, recent pioneering studies introduced time-resolved [ 18 F]FDG-PET with constant infusion, which enables metabolic connectivity studies at the individual level. Methods In the current study, this technique was employed to explore Parkinson’s disease (PD)-related alterations in individual metabolic connectivity, in comparison to inter-subject measures and hemodynamic connectivity. Fifteen PD patients and 14 healthy controls with comparable cognition underwent sequential resting-state dynamic PET with constant infusion and functional MRI. Intrinsic networks were identified by independent component analysis and interregional connectivity calculated for summed static PET images, PET time series and functional MRI. Results Our findings revealed an intrinsic sensorimotor network in PD patients that has not been previously observed to this extent. In PD, a significantly higher number of connections in cortical motor areas was observed compared to elderly control subjects, as indicated by both static PET and functional MRI ( p Bonferroni−Holm = 0.027), as well as constant infusion PET and functional MRI connectomes ( p Bonferroni−Holm = 0.012). This intensified coupling was associated with disease severity ( ρ = 0.56, p = 0.036). Conclusion Metabolic connectivity, as revealed by both static and dynamic PET, provides unique information on metabolic network activity. Subject-level metabolic connectivity based on constant infusion PET may serve as a potential marker for the metabolic network signature in neurodegeneration. While fMRI provides information on the temporal changes in blood oxygenation, 2- [18F]fluoro-2-deoxy-D-glucose ([ F]FDG)-PET has traditionally offered a static snapshot of brain glucose consumption. As a result, studies investigating metabolic brain networks as potential biomarkers for neurodegeneration have primarily been conducted at the group level. However, recent pioneering studies introduced time-resolved [ F]FDG-PET with constant infusion, which enables metabolic connectivity studies at the individual level. In the current study, this technique was employed to explore Parkinson's disease (PD)-related alterations in individual metabolic connectivity, in comparison to inter-subject measures and hemodynamic connectivity. Fifteen PD patients and 14 healthy controls with comparable cognition underwent sequential resting-state dynamic PET with constant infusion and functional MRI. Intrinsic networks were identified by independent component analysis and interregional connectivity calculated for summed static PET images, PET time series and functional MRI. Our findings revealed an intrinsic sensorimotor network in PD patients that has not been previously observed to this extent. In PD, a significantly higher number of connections in cortical motor areas was observed compared to elderly control subjects, as indicated by both static PET and functional MRI (p = 0.027), as well as constant infusion PET and functional MRI connectomes (p = 0.012). This intensified coupling was associated with disease severity (ρ = 0.56, p = 0.036). Metabolic connectivity, as revealed by both static and dynamic PET, provides unique information on metabolic network activity. Subject-level metabolic connectivity based on constant infusion PET may serve as a potential marker for the metabolic network signature in neurodegeneration. While fMRI provides information on the temporal changes in blood oxygenation, 2- [18F]fluoro-2-deoxy-D-glucose ([18F]FDG)-PET has traditionally offered a static snapshot of brain glucose consumption. As a result, studies investigating metabolic brain networks as potential biomarkers for neurodegeneration have primarily been conducted at the group level. However, recent pioneering studies introduced time-resolved [18F]FDG-PET with constant infusion, which enables metabolic connectivity studies at the individual level.PURPOSEWhile fMRI provides information on the temporal changes in blood oxygenation, 2- [18F]fluoro-2-deoxy-D-glucose ([18F]FDG)-PET has traditionally offered a static snapshot of brain glucose consumption. As a result, studies investigating metabolic brain networks as potential biomarkers for neurodegeneration have primarily been conducted at the group level. However, recent pioneering studies introduced time-resolved [18F]FDG-PET with constant infusion, which enables metabolic connectivity studies at the individual level.In the current study, this technique was employed to explore Parkinson's disease (PD)-related alterations in individual metabolic connectivity, in comparison to inter-subject measures and hemodynamic connectivity. Fifteen PD patients and 14 healthy controls with comparable cognition underwent sequential resting-state dynamic PET with constant infusion and functional MRI. Intrinsic networks were identified by independent component analysis and interregional connectivity calculated for summed static PET images, PET time series and functional MRI.METHODSIn the current study, this technique was employed to explore Parkinson's disease (PD)-related alterations in individual metabolic connectivity, in comparison to inter-subject measures and hemodynamic connectivity. Fifteen PD patients and 14 healthy controls with comparable cognition underwent sequential resting-state dynamic PET with constant infusion and functional MRI. Intrinsic networks were identified by independent component analysis and interregional connectivity calculated for summed static PET images, PET time series and functional MRI.Our findings revealed an intrinsic sensorimotor network in PD patients that has not been previously observed to this extent. In PD, a significantly higher number of connections in cortical motor areas was observed compared to elderly control subjects, as indicated by both static PET and functional MRI (pBonferroni-Holm = 0.027), as well as constant infusion PET and functional MRI connectomes (pBonferroni-Holm = 0.012). This intensified coupling was associated with disease severity (ρ = 0.56, p = 0.036).RESULTSOur findings revealed an intrinsic sensorimotor network in PD patients that has not been previously observed to this extent. In PD, a significantly higher number of connections in cortical motor areas was observed compared to elderly control subjects, as indicated by both static PET and functional MRI (pBonferroni-Holm = 0.027), as well as constant infusion PET and functional MRI connectomes (pBonferroni-Holm = 0.012). This intensified coupling was associated with disease severity (ρ = 0.56, p = 0.036).Metabolic connectivity, as revealed by both static and dynamic PET, provides unique information on metabolic network activity. Subject-level metabolic connectivity based on constant infusion PET may serve as a potential marker for the metabolic network signature in neurodegeneration.CONCLUSIONMetabolic connectivity, as revealed by both static and dynamic PET, provides unique information on metabolic network activity. Subject-level metabolic connectivity based on constant infusion PET may serve as a potential marker for the metabolic network signature in neurodegeneration. |
Author | Steidel, Kenan Müller, Hans-Helge Timmermann, Lars Luster, Markus Ruppert-Junck, Marina C. Heinecke, Vanessa Eggers, Carsten Librizzi, Damiano Verburg, Frederik A. Pedrosa, David Beckersjürgen, Maya Schurrat, Tino |
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Keywords | F]-Fluorodeoxyglucose-PET Dynamic Network degeneration Metabolic connectivity Imaging biomarker Multimodal connectome Glucose Dynamics Dynamic [18F]-Fluorodeoxyglucose-PET |
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While fMRI provides information on the temporal changes in blood oxygenation, 2- [18F]fluoro-2-deoxy-D-glucose ([
18
F]FDG)-PET has traditionally... While fMRI provides information on the temporal changes in blood oxygenation, 2- [18F]fluoro-2-deoxy-D-glucose ([ F]FDG)-PET has traditionally offered a static... PurposeWhile fMRI provides information on the temporal changes in blood oxygenation, 2- [18F]fluoro-2-deoxy-D-glucose ([18F]FDG)-PET has traditionally offered... While fMRI provides information on the temporal changes in blood oxygenation, 2- [18F]fluoro-2-deoxy-D-glucose ([18F]FDG)-PET has traditionally offered a... |
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SubjectTerms | Aged Biomarkers Blood levels Brain Cardiology Case-Control Studies Cognition Coupling Female Fluorine isotopes Fluorodeoxyglucose F18 Functional magnetic resonance imaging Glucose Glucose - metabolism Hemodynamics Humans Imaging Independent component analysis Magnetic Resonance Imaging Male Medicine Medicine & Public Health Metabolic networks Metabolism Middle Aged Motor task performance Movement disorders Nerve Net - diagnostic imaging Nerve Net - physiopathology Neural networks Neurodegeneration Neurodegenerative diseases Nuclear Medicine Oncology Original Original Article Orthopedics Oxygenation Parkinson Disease - diagnostic imaging Parkinson Disease - metabolism Parkinson Disease - physiopathology Parkinson's disease Positron emission Positron emission tomography Radiology Sensorimotor system |
Title | Connectivity based on glucose dynamics reveals exaggerated sensorimotor network coupling on subject-level in Parkinson’s disease |
URI | https://link.springer.com/article/10.1007/s00259-024-06796-6 https://www.ncbi.nlm.nih.gov/pubmed/38884774 https://www.proquest.com/docview/3111719753 https://www.proquest.com/docview/3069175632 https://pubmed.ncbi.nlm.nih.gov/PMC11445336 |
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