On the analysis of functional PET (fPET)-FDG: baseline mischaracterization can introduce artifactual metabolic (de)activations Article Swipe
Sean E. Coursey
,
Joseph B. Mandeville
,
Murray Bruce Reed
,
Grant Hartung
,
Arun Garimella
,
Hasan Sari
,
Rupert Lanzenberger
,
Julie C. Price
,
Jon̈athan R. Polimeni
,
Douglas N. Greve
,
Andreas Hahn
,
Jingyuan E. Chen
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.10.17.618550
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.10.17.618550
Functional Positron Emission Tomography (fPET) with (bolus plus) constant infusion of [18F]-fluorodeoxyglucose FDG), known as fPET-FDG, is a recently introduced technique in human neuroimaging, enabling the detection of dynamic glucose metabolism changes within a single scan. However, the statistical analysis of fPET-FDG data remains challenging because its signal and noise characteristics differ from both classic bolus-administration FDG PET and from functional Magnetic Resonance Imaging (fMRI), which together compose the primary sources of inspiration for analytical methods used by fPET-FDG researchers. In this study, we present an investigate of how inaccuracies in modeling baseline FDG uptake can introduce artifactual patterns to detrended TAC residuals, potentially introducing spurious (de)activations to general linear model (GLM) analyses. By combining simulations and empirical data from both constant infusion and bolus-plus-constant infusion protocols, we evaluate the effects of various baseline modeling methods, including polynomial detrending, regression against the global mean time-activity curve, and two analytical methods based on tissue compartment model kinetics. Our findings indicate that improper baseline removal can introduce statistically significant artifactual effects, although these effects characterized in this study (~2-8%) are generally smaller than those reported by previous literature employing robust sensory stimulation (~10-30%). We discuss potential strategies to mitigate this issue, including informed baseline modeling, optimized tracer administration protocols, and careful experimental design. These insights aim to enhance the reliability of fPET-FDG in capturing true metabolic dynamics in neuroimaging research.
Related Topics
Concepts
Positron emission tomography
Neuroimaging
Functional magnetic resonance imaging
Computer science
Spurious relationship
Functional imaging
Magnetic resonance imaging
Nuclear medicine
Baseline (sea)
Artificial intelligence
Medicine
Machine learning
Radiology
Psychology
Neuroscience
Oceanography
Geology
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2024.10.17.618550
- https://www.biorxiv.org/content/biorxiv/early/2024/10/21/2024.10.17.618550.full.pdf
- OA Status
- green
- References
- 32
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403592660
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4403592660Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/2024.10.17.618550Digital Object Identifier
- Title
-
On the analysis of functional PET (fPET)-FDG: baseline mischaracterization can introduce artifactual metabolic (de)activationsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-10-21Full publication date if available
- Authors
-
Sean E. Coursey, Joseph B. Mandeville, Murray Bruce Reed, Grant Hartung, Arun Garimella, Hasan Sari, Rupert Lanzenberger, Julie C. Price, Jon̈athan R. Polimeni, Douglas N. Greve, Andreas Hahn, Jingyuan E. ChenList of authors in order
- Landing page
-
https://doi.org/10.1101/2024.10.17.618550Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2024/10/21/2024.10.17.618550.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.biorxiv.org/content/biorxiv/early/2024/10/21/2024.10.17.618550.full.pdfDirect OA link when available
- Concepts
-
Positron emission tomography, Neuroimaging, Functional magnetic resonance imaging, Computer science, Spurious relationship, Functional imaging, Magnetic resonance imaging, Nuclear medicine, Baseline (sea), Artificial intelligence, Medicine, Machine learning, Radiology, Psychology, Neuroscience, Oceanography, GeologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
32Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.By | 113 |
| abstract_inverted_index.In | 80 |
| abstract_inverted_index.We | 191 |
| abstract_inverted_index.an | 85 |
| abstract_inverted_index.as | 14 |
| abstract_inverted_index.by | 77, 183 |
| abstract_inverted_index.in | 21, 90, 173, 220, 225 |
| abstract_inverted_index.is | 16 |
| abstract_inverted_index.of | 10, 27, 40, 71, 87, 131, 218 |
| abstract_inverted_index.on | 151 |
| abstract_inverted_index.to | 99, 107, 195, 214 |
| abstract_inverted_index.we | 83, 127 |
| abstract_inverted_index.FDG | 56, 93 |
| abstract_inverted_index.Our | 156 |
| abstract_inverted_index.PET | 57 |
| abstract_inverted_index.TAC | 101 |
| abstract_inverted_index.aim | 213 |
| abstract_inverted_index.and | 48, 58, 116, 123, 146, 207 |
| abstract_inverted_index.are | 177 |
| abstract_inverted_index.can | 95, 163 |
| abstract_inverted_index.for | 73 |
| abstract_inverted_index.how | 88 |
| abstract_inverted_index.its | 46 |
| abstract_inverted_index.the | 25, 37, 68, 129, 141, 216 |
| abstract_inverted_index.two | 147 |
| abstract_inverted_index.both | 53, 120 |
| abstract_inverted_index.data | 42, 118 |
| abstract_inverted_index.from | 52, 59, 119 |
| abstract_inverted_index.mean | 143 |
| abstract_inverted_index.than | 180 |
| abstract_inverted_index.that | 159 |
| abstract_inverted_index.this | 81, 174, 197 |
| abstract_inverted_index.true | 222 |
| abstract_inverted_index.used | 76 |
| abstract_inverted_index.with | 5 |
| abstract_inverted_index.(GLM) | 111 |
| abstract_inverted_index.FDG), | 12 |
| abstract_inverted_index.These | 211 |
| abstract_inverted_index.based | 150 |
| abstract_inverted_index.human | 22 |
| abstract_inverted_index.known | 13 |
| abstract_inverted_index.model | 110, 154 |
| abstract_inverted_index.noise | 49 |
| abstract_inverted_index.plus) | 7 |
| abstract_inverted_index.scan. | 35 |
| abstract_inverted_index.study | 175 |
| abstract_inverted_index.these | 170 |
| abstract_inverted_index.those | 181 |
| abstract_inverted_index.which | 65 |
| abstract_inverted_index.(bolus | 6 |
| abstract_inverted_index.(fPET) | 4 |
| abstract_inverted_index.curve, | 145 |
| abstract_inverted_index.differ | 51 |
| abstract_inverted_index.global | 142 |
| abstract_inverted_index.issue, | 198 |
| abstract_inverted_index.linear | 109 |
| abstract_inverted_index.robust | 187 |
| abstract_inverted_index.signal | 47 |
| abstract_inverted_index.single | 34 |
| abstract_inverted_index.study, | 82 |
| abstract_inverted_index.tissue | 152 |
| abstract_inverted_index.tracer | 204 |
| abstract_inverted_index.uptake | 94 |
| abstract_inverted_index.within | 32 |
| abstract_inverted_index.(fMRI), | 64 |
| abstract_inverted_index.(~2-8%) | 176 |
| abstract_inverted_index.Imaging | 63 |
| abstract_inverted_index.against | 140 |
| abstract_inverted_index.because | 45 |
| abstract_inverted_index.careful | 208 |
| abstract_inverted_index.changes | 31 |
| abstract_inverted_index.classic | 54 |
| abstract_inverted_index.compose | 67 |
| abstract_inverted_index.design. | 210 |
| abstract_inverted_index.discuss | 192 |
| abstract_inverted_index.dynamic | 28 |
| abstract_inverted_index.effects | 130, 171 |
| abstract_inverted_index.enhance | 215 |
| abstract_inverted_index.general | 108 |
| abstract_inverted_index.glucose | 29 |
| abstract_inverted_index.methods | 75, 149 |
| abstract_inverted_index.present | 84 |
| abstract_inverted_index.primary | 69 |
| abstract_inverted_index.remains | 43 |
| abstract_inverted_index.removal | 162 |
| abstract_inverted_index.sensory | 188 |
| abstract_inverted_index.smaller | 179 |
| abstract_inverted_index.sources | 70 |
| abstract_inverted_index.various | 132 |
| abstract_inverted_index.Emission | 2 |
| abstract_inverted_index.However, | 36 |
| abstract_inverted_index.Magnetic | 61 |
| abstract_inverted_index.Positron | 1 |
| abstract_inverted_index.although | 169 |
| abstract_inverted_index.analysis | 39 |
| abstract_inverted_index.baseline | 92, 133, 161, 201 |
| abstract_inverted_index.constant | 8, 121 |
| abstract_inverted_index.dynamics | 224 |
| abstract_inverted_index.effects, | 168 |
| abstract_inverted_index.enabling | 24 |
| abstract_inverted_index.evaluate | 128 |
| abstract_inverted_index.fPET-FDG | 41, 78, 219 |
| abstract_inverted_index.findings | 157 |
| abstract_inverted_index.improper | 160 |
| abstract_inverted_index.indicate | 158 |
| abstract_inverted_index.informed | 200 |
| abstract_inverted_index.infusion | 9, 122, 125 |
| abstract_inverted_index.insights | 212 |
| abstract_inverted_index.methods, | 135 |
| abstract_inverted_index.mitigate | 196 |
| abstract_inverted_index.modeling | 91, 134 |
| abstract_inverted_index.patterns | 98 |
| abstract_inverted_index.previous | 184 |
| abstract_inverted_index.recently | 18 |
| abstract_inverted_index.reported | 182 |
| abstract_inverted_index.spurious | 105 |
| abstract_inverted_index.together | 66 |
| abstract_inverted_index.Resonance | 62 |
| abstract_inverted_index.analyses. | 112 |
| abstract_inverted_index.capturing | 221 |
| abstract_inverted_index.combining | 114 |
| abstract_inverted_index.detection | 26 |
| abstract_inverted_index.detrended | 100 |
| abstract_inverted_index.empirical | 117 |
| abstract_inverted_index.employing | 186 |
| abstract_inverted_index.fPET-FDG, | 15 |
| abstract_inverted_index.generally | 178 |
| abstract_inverted_index.including | 136, 199 |
| abstract_inverted_index.introduce | 96, 164 |
| abstract_inverted_index.kinetics. | 155 |
| abstract_inverted_index.metabolic | 223 |
| abstract_inverted_index.modeling, | 202 |
| abstract_inverted_index.optimized | 203 |
| abstract_inverted_index.potential | 193 |
| abstract_inverted_index.research. | 227 |
| abstract_inverted_index.technique | 20 |
| abstract_inverted_index.(~10-30%). | 190 |
| abstract_inverted_index.Functional | 0 |
| abstract_inverted_index.Tomography | 3 |
| abstract_inverted_index.analytical | 74, 148 |
| abstract_inverted_index.functional | 60 |
| abstract_inverted_index.introduced | 19 |
| abstract_inverted_index.literature | 185 |
| abstract_inverted_index.metabolism | 30 |
| abstract_inverted_index.polynomial | 137 |
| abstract_inverted_index.protocols, | 126, 206 |
| abstract_inverted_index.regression | 139 |
| abstract_inverted_index.residuals, | 102 |
| abstract_inverted_index.strategies | 194 |
| abstract_inverted_index.artifactual | 97, 167 |
| abstract_inverted_index.challenging | 44 |
| abstract_inverted_index.compartment | 153 |
| abstract_inverted_index.detrending, | 138 |
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| abstract_inverted_index.introducing | 104 |
| abstract_inverted_index.investigate | 86 |
| abstract_inverted_index.potentially | 103 |
| abstract_inverted_index.reliability | 217 |
| abstract_inverted_index.significant | 166 |
| abstract_inverted_index.simulations | 115 |
| abstract_inverted_index.statistical | 38 |
| abstract_inverted_index.stimulation | 189 |
| abstract_inverted_index.experimental | 209 |
| abstract_inverted_index.inaccuracies | 89 |
| abstract_inverted_index.neuroimaging | 226 |
| abstract_inverted_index.researchers. | 79 |
| abstract_inverted_index.characterized | 172 |
| abstract_inverted_index.neuroimaging, | 23 |
| abstract_inverted_index.statistically | 165 |
| abstract_inverted_index.time-activity | 144 |
| abstract_inverted_index.administration | 205 |
| abstract_inverted_index.(de)activations | 106 |
| abstract_inverted_index.characteristics | 50 |
| abstract_inverted_index.bolus-plus-constant | 124 |
| abstract_inverted_index.bolus-administration | 55 |
| abstract_inverted_index.[18F]-fluorodeoxyglucose | 11 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5013153317 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 12 |
| corresponding_institution_ids | https://openalex.org/I136199984, https://openalex.org/I4210087915, https://openalex.org/I4210127055 |
| citation_normalized_percentile.value | 0.34124862 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |