@article{RN350,
   author = {de Jong, J. J. A. and Jansen, J. F. A. and Vergoossen, L. W. M. and Schram, M. T. and Stehouwer, C. D. A. and Wildberger, J. E. and Linden, D. E. J. and Backes, W. H.},
   title = {Effect of Magnetic Resonance Image Quality on Structural and Functional Brain Connectivity: The Maastricht Study},
   journal = {Brain Sci},
   volume = {14},
   number = {1},
   note = {de Jong, Joost J A
Jansen, Jacobus F A
Vergoossen, Laura W M
Schram, Miranda T
Stehouwer, Coen D A
Wildberger, Joachim E
Linden, David E J
Backes, Walter H
eng
grant 31O.041/European Regional Development Fund via OP-Zuid, The Province of Limburg, the Dutch Ministry of Economic Affairs/
Switzerland
Brain Sci. 2024 Jan 8;14(1):62. doi: 10.3390/brainsci14010062.},
   abstract = {In population-based cohort studies, magnetic resonance imaging (MRI) is vital for examining brain structure and function. Advanced MRI techniques, such as diffusion-weighted MRI (dMRI) and resting-state functional MRI (rs-fMRI), provide insights into brain connectivity. However, biases in MRI data acquisition and processing can impact brain connectivity measures and their associations with demographic and clinical variables. This study, conducted with 5110 participants from The Maastricht Study, explored the relationship between brain connectivity and various image quality metrics (e.g., signal-to-noise ratio, head motion, and atlas-template mismatches) that were obtained from dMRI and rs-fMRI scans. Results revealed that in particular increased head motion (R(2) up to 0.169, p < 0.001) and reduced signal-to-noise ratio (R(2) up to 0.013, p < 0.001) negatively impacted structural and functional brain connectivity, respectively. These image quality metrics significantly affected associations of overall brain connectivity with age (up to -59%), sex (up to -25%), and body mass index (BMI) (up to +14%). Associations with diabetes status, educational level, history of cardiovascular disease, and white matter hyperintensities were generally less affected. This emphasizes the potential confounding effects of image quality in large population-based neuroimaging studies on brain connectivity and underscores the importance of accounting for it.},
   keywords = {brain connectivity
image quality
magnetic resonance imaging
neuroimaging
population-cohort study},
   ISSN = {2076-3425 (Print)
2076-3425 (Linking)},
   DOI = {10.3390/brainsci14010062},
   url = {https://www.ncbi.nlm.nih.gov/pubmed/38248277},
   year = {2024},
   type = {Journal Article}
}

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H."],"bibdata":{"bibtype":"article","type":"Journal Article","author":[{"propositions":["de"],"lastnames":["Jong"],"firstnames":["J.","J.","A."],"suffixes":[]},{"propositions":[],"lastnames":["Jansen"],"firstnames":["J.","F.","A."],"suffixes":[]},{"propositions":[],"lastnames":["Vergoossen"],"firstnames":["L.","W.","M."],"suffixes":[]},{"propositions":[],"lastnames":["Schram"],"firstnames":["M.","T."],"suffixes":[]},{"propositions":[],"lastnames":["Stehouwer"],"firstnames":["C.","D.","A."],"suffixes":[]},{"propositions":[],"lastnames":["Wildberger"],"firstnames":["J.","E."],"suffixes":[]},{"propositions":[],"lastnames":["Linden"],"firstnames":["D.","E.","J."],"suffixes":[]},{"propositions":[],"lastnames":["Backes"],"firstnames":["W.","H."],"suffixes":[]}],"title":"Effect of Magnetic Resonance Image Quality on Structural and Functional Brain Connectivity: The Maastricht Study","journal":"Brain Sci","volume":"14","number":"1","note":"de Jong, Joost J A Jansen, Jacobus F A Vergoossen, Laura W M Schram, Miranda T Stehouwer, Coen D A Wildberger, Joachim E Linden, David E J Backes, Walter H eng grant 31O.041/European Regional Development Fund via OP-Zuid, The Province of Limburg, the Dutch Ministry of Economic Affairs/ Switzerland Brain Sci. 2024 Jan 8;14(1):62. doi: 10.3390/brainsci14010062.","abstract":"In population-based cohort studies, magnetic resonance imaging (MRI) is vital for examining brain structure and function. Advanced MRI techniques, such as diffusion-weighted MRI (dMRI) and resting-state functional MRI (rs-fMRI), provide insights into brain connectivity. However, biases in MRI data acquisition and processing can impact brain connectivity measures and their associations with demographic and clinical variables. This study, conducted with 5110 participants from The Maastricht Study, explored the relationship between brain connectivity and various image quality metrics (e.g., signal-to-noise ratio, head motion, and atlas-template mismatches) that were obtained from dMRI and rs-fMRI scans. Results revealed that in particular increased head motion (R(2) up to 0.169, p < 0.001) and reduced signal-to-noise ratio (R(2) up to 0.013, p < 0.001) negatively impacted structural and functional brain connectivity, respectively. These image quality metrics significantly affected associations of overall brain connectivity with age (up to -59%), sex (up to -25%), and body mass index (BMI) (up to +14%). Associations with diabetes status, educational level, history of cardiovascular disease, and white matter hyperintensities were generally less affected. This emphasizes the potential confounding effects of image quality in large population-based neuroimaging studies on brain connectivity and underscores the importance of accounting for it.","keywords":"brain connectivity image quality magnetic resonance imaging neuroimaging population-cohort study","issn":"2076-3425 (Print) 2076-3425 (Linking)","doi":"10.3390/brainsci14010062","url":"https://www.ncbi.nlm.nih.gov/pubmed/38248277","year":"2024","bibtex":"@article{RN350,\n author = {de Jong, J. J. A. and Jansen, J. F. A. and Vergoossen, L. W. M. and Schram, M. T. and Stehouwer, C. D. A. and Wildberger, J. E. and Linden, D. E. J. and Backes, W. H.},\n title = {Effect of Magnetic Resonance Image Quality on Structural and Functional Brain Connectivity: The Maastricht Study},\n journal = {Brain Sci},\n volume = {14},\n number = {1},\n note = {de Jong, Joost J A\nJansen, Jacobus F A\nVergoossen, Laura W M\nSchram, Miranda T\nStehouwer, Coen D A\nWildberger, Joachim E\nLinden, David E J\nBackes, Walter H\neng\ngrant 31O.041/European Regional Development Fund via OP-Zuid, The Province of Limburg, the Dutch Ministry of Economic Affairs/\nSwitzerland\nBrain Sci. 2024 Jan 8;14(1):62. doi: 10.3390/brainsci14010062.},\n abstract = {In population-based cohort studies, magnetic resonance imaging (MRI) is vital for examining brain structure and function. Advanced MRI techniques, such as diffusion-weighted MRI (dMRI) and resting-state functional MRI (rs-fMRI), provide insights into brain connectivity. However, biases in MRI data acquisition and processing can impact brain connectivity measures and their associations with demographic and clinical variables. This study, conducted with 5110 participants from The Maastricht Study, explored the relationship between brain connectivity and various image quality metrics (e.g., signal-to-noise ratio, head motion, and atlas-template mismatches) that were obtained from dMRI and rs-fMRI scans. Results revealed that in particular increased head motion (R(2) up to 0.169, p < 0.001) and reduced signal-to-noise ratio (R(2) up to 0.013, p < 0.001) negatively impacted structural and functional brain connectivity, respectively. These image quality metrics significantly affected associations of overall brain connectivity with age (up to -59%), sex (up to -25%), and body mass index (BMI) (up to +14%). Associations with diabetes status, educational level, history of cardiovascular disease, and white matter hyperintensities were generally less affected. 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