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MRI BrainAGE demons...
MRI BrainAGE demonstrates increased brain aging in systemic lupus erythematosus patients
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- Kuchcinski, Grégory (author)
- Lund University,Lunds universitet,Diagnostisk radiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Diagnostic Radiology, (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Skåne University Hospital
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- Rumetshofer, Theodor (author)
- Lund University,Lunds universitet,Logopedi, foniatri och audiologi,Sektion IV,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Diagnostisk radiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Logopedics, Phoniatrics and Audiology,Section IV,Department of Clinical Sciences, Lund,Faculty of Medicine,Diagnostic Radiology, (Lund),Section V,Department of Clinical Sciences, Lund,Skåne University Hospital
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- Zervides, Kristoffer A. (author)
- Lund University,Lunds universitet,Reumatologi och molekylär skelettbiologi,Sektion III,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Lund SLE Research Group,Forskargrupper vid Lunds universitet,Rheumatology,Section III,Department of Clinical Sciences, Lund,Faculty of Medicine,Lund University Research Groups,Skåne University Hospital
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- Lopes, Renaud (author)
- University of Lille
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- Gautherot, Morgan (author)
- University of Lille
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- Pruvo, Jean Pierre (author)
- University of Lille
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- Bengtsson, Anders A. (author)
- Lund University,Lunds universitet,Reumatologi och molekylär skelettbiologi,Sektion III,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Lund SLE Research Group,Forskargrupper vid Lunds universitet,Rheumatology,Section III,Department of Clinical Sciences, Lund,Faculty of Medicine,Lund University Research Groups,Skåne University Hospital
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- Hansson, Oskar (author)
- Lund University,Lunds universitet,Klinisk minnesforskning,Forskargrupper vid Lunds universitet,LU profilområde: Proaktivt åldrande,Lunds universitets profilområden,Clinical Memory Research,Lund University Research Groups,LU Profile Area: Proactive Ageing,Lund University Profile areas,Skåne University Hospital
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- Jönsen, Andreas (author)
- Lund University,Lunds universitet,Reumatologi och molekylär skelettbiologi,Sektion III,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Lund SLE Research Group,Forskargrupper vid Lunds universitet,Rheumatology,Section III,Department of Clinical Sciences, Lund,Faculty of Medicine,Lund University Research Groups,Skåne University Hospital
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- Sundgren, Pia C.Maly (author)
- Lund University,Lunds universitet,Diagnostisk radiologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Lund University Bioimaging Center,Diagnostic Radiology, (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Skåne University Hospital
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(creator_code:org_t)
- 2023
- 2023
- English.
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In: Frontiers in Aging Neuroscience. - 1663-4365. ; 15
- Related links:
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http://dx.doi.org/10... (free)
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https://lup.lub.lu.s...
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https://doi.org/10.3...
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Abstract
Subject headings
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- Introduction: Systemic lupus erythematosus (SLE) is an autoimmune connective tissue disease affecting multiple organs in the human body, including the central nervous system. Recently, an artificial intelligence method called BrainAGE (Brain Age Gap Estimation), defined as predicted age minus chronological age, has been developed to measure the deviation of brain aging from a healthy population using MRI. Our aim was to evaluate brain aging in SLE patients using a deep-learning BrainAGE model. Methods: Seventy female patients with a clinical diagnosis of SLE and 24 healthy age-matched control females, were included in this post-hoc analysis of prospectively acquired data. All subjects had previously undergone a 3 T MRI acquisition, a neuropsychological evaluation and a measurement of neurofilament light protein in plasma (NfL). A BrainAGE model with a 3D convolutional neural network architecture, pre-trained on the 3D-T1 images of 1,295 healthy female subjects to predict their chronological age, was applied on the images of SLE patients and controls in order to compute the BrainAGE. SLE patients were divided into 2 groups according to the BrainAGE distribution (high vs. low BrainAGE). Results: BrainAGE z-score was significantly higher in SLE patients than in controls (+0.6 [±1.1] vs. 0 [±1.0], p = 0.02). In SLE patients, high BrainAGE was associated with longer reaction times (p = 0.02), lower psychomotor speed (p = 0.001) and cognitive flexibility (p = 0.04), as well as with higher NfL after adjusting for age (p = 0.001). Conclusion: Using a deep-learning BrainAGE model, we provide evidence of increased brain aging in SLE patients, which reflected neuronal damage and cognitive impairment.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Neurologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Neurology (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Reumatologi och inflammation (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Rheumatology and Autoimmunity (hsv//eng)
Keyword
- aging
- brain
- deep learning
- magnetic resonance imaging
- systemic lupus erythematosus
Publication and Content Type
- art (subject category)
- ref (subject category)
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Kuchcinski, Grég ...
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Rumetshofer, The ...
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Zervides, Kristo ...
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Lopes, Renaud
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Gautherot, Morga ...
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Pruvo, Jean Pier ...
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Bengtsson, Ander ...
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Hansson, Oskar
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Jönsen, Andreas
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Sundgren, Pia C. ...
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- MEDICAL AND HEALTH SCIENCES
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and Neurology
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MEDICAL AND HEAL ...
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Frontiers in Agi ...
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Lund University