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18F-FDG-PET/MR imaging to monitor disease activity in large vessel vasculitis
by
Czopek, Alicja
, Grayson, Peter C.
, Tan, Sovira
, Basu, Neil
, Pugh, Dan
, Bruce, Lorraine
, Macnaught, Gillian
, Gallacher, Peter J.
, Ahlman, Mark
, Dhaun, Neeraj
, Donachie, James
, Patel, Dilip
in
59/57
/ 59/78
/ 631/250/256/2516
/ 692/308/575
/ 692/4023/1670/595
/ Fluorine isotopes
/ Functional magnetic resonance imaging
/ High definition
/ Humanities and Social Sciences
/ Magnetic resonance imaging
/ Medical imaging
/ Monitoring
/ multidisciplinary
/ Positron emission
/ Positron emission tomography
/ Radiation effects
/ Science
/ Science (multidisciplinary)
/ Structure-function relationships
/ Telemedicine
/ Vasculitis
2024
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18F-FDG-PET/MR imaging to monitor disease activity in large vessel vasculitis
by
Czopek, Alicja
, Grayson, Peter C.
, Tan, Sovira
, Basu, Neil
, Pugh, Dan
, Bruce, Lorraine
, Macnaught, Gillian
, Gallacher, Peter J.
, Ahlman, Mark
, Dhaun, Neeraj
, Donachie, James
, Patel, Dilip
in
59/57
/ 59/78
/ 631/250/256/2516
/ 692/308/575
/ 692/4023/1670/595
/ Fluorine isotopes
/ Functional magnetic resonance imaging
/ High definition
/ Humanities and Social Sciences
/ Magnetic resonance imaging
/ Medical imaging
/ Monitoring
/ multidisciplinary
/ Positron emission
/ Positron emission tomography
/ Radiation effects
/ Science
/ Science (multidisciplinary)
/ Structure-function relationships
/ Telemedicine
/ Vasculitis
2024
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18F-FDG-PET/MR imaging to monitor disease activity in large vessel vasculitis
by
Czopek, Alicja
, Grayson, Peter C.
, Tan, Sovira
, Basu, Neil
, Pugh, Dan
, Bruce, Lorraine
, Macnaught, Gillian
, Gallacher, Peter J.
, Ahlman, Mark
, Dhaun, Neeraj
, Donachie, James
, Patel, Dilip
in
59/57
/ 59/78
/ 631/250/256/2516
/ 692/308/575
/ 692/4023/1670/595
/ Fluorine isotopes
/ Functional magnetic resonance imaging
/ High definition
/ Humanities and Social Sciences
/ Magnetic resonance imaging
/ Medical imaging
/ Monitoring
/ multidisciplinary
/ Positron emission
/ Positron emission tomography
/ Radiation effects
/ Science
/ Science (multidisciplinary)
/ Structure-function relationships
/ Telemedicine
/ Vasculitis
2024
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18F-FDG-PET/MR imaging to monitor disease activity in large vessel vasculitis
Journal Article
18F-FDG-PET/MR imaging to monitor disease activity in large vessel vasculitis
2024
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Overview
Disease-monitoring in large vessel vasculitis (LVV) is challenging. Simultaneous
18
F-fluorodeoxyglucose positron emission tomography with magnetic resonance imaging (PET/MRI) provides functional assessment of vascular inflammation alongside high-definition structural imaging with a relatively low burden of radiation exposure. Here, we investigate the ability of PET/MRI to monitor LVV disease activity longitudinally in a prospective cohort of patients with active LVV. We demonstrate that both the PET and MRI components of the scan can distinguish active from inactive disease using established quantification methods. Using logistic-regression modelling of PET/MRI metrics, we devise a novel PET/MRI-specific
V
asculitis
A
ctivity using
M
R
P
ET (
VAMP
) score which is able to distinguish active from inactive disease with more accuracy than established methods and detects changes in disease activity longitudinally. These findings are evaluated in an independent validation cohort. Finally, PET/MRI improves clinicians’ assessment of LVV disease activity and confidence in disease management, as assessed via clinician survey. In summary, PET/MRI may be useful in tracking disease activity and assessing treatment-response in LVV. Based on our findings, larger, prospective studies assessing PET/MRI in LVV are now warranted.
Disease-monitoring in large vessel vasculitis is challenging, often leading to a mismatch between disease activity and treatment intensity. Here, the authors show that PET/MRI scanning can distinguish active from inactive large vessel vasculitis and track disease longitudinally, potentially allowing more stratified treatment for patients.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
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