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@ARTICLE{Petersen:1032009,
      author       = {Petersen, Marvin and Coenen, Mirthe and DeCarli, Charles
                      and De Luca, Alberto and van der Lelij, Ewoud and Barkhof,
                      Frederik and Benke, Thomas and Chen, Christopher P L H and
                      Dal-Bianco, Peter and Dewenter, Anna and Duering, Marco and
                      Enzinger, Christian and Ewers, Michael and Exalto, Lieza G
                      and Fletcher, Evan M and Franzmeier, Nicolai and Hilal,
                      Saima and Hofer, Edith and Koek, Huiberdina L and Maier,
                      Andrea B and Maillard, Pauline M and McCreary, Cheryl R and
                      Papma, Janne M and Pijnenburg, Yolande A L and Schmidt,
                      Reinhold and Smith, Eric E and Steketee, Rebecca M E and van
                      den Berg, Esther and van der Flier, Wiesje M and
                      Venkatraghavan, Vikram and Venketasubramanian, Narayanaswamy
                      and Vernooij, Meike W and Wolters, Frank J and Xu, Xin and
                      Horn, Andreas and Patil, Kaustubh R and Eickhoff, Simon B
                      and Thomalla, Götz and Biesbroek, J Matthijs and Jan
                      Biessels, Geert and Cheng, Bastian},
      title        = {{E}nhancing cognitive performance prediction by white
                      matter hyperintensity connectivity assessment},
      journal      = {Brain},
      volume       = {147},
      number       = {12},
      issn         = {0006-8950},
      address      = {Oxford},
      publisher    = {Oxford Univ. Press},
      reportid     = {FZJ-2024-05925},
      pages        = {4265-4279},
      year         = {2024},
      abstract     = {White matter hyperintensities of presumed vascular origin
                      (WMH) are associated with cognitive impairment and are a key
                      imaging marker in evaluating brain health. However, WMH
                      volume alone does not fully account for the extent of
                      cognitive deficits and the mechanisms linking WMH to these
                      deficits remain unclear. Lesion network mapping (LNM)
                      enables to infer if brain networks are connected to lesions
                      and could be a promising technique for enhancing our
                      understanding of the role of WMH in cognitive disorders. Our
                      study employed LNM to test the following hypotheses: (1)
                      LNM-informed markers surpass WMH volumes in predicting
                      cognitive performance, and (2) WMH contributing to cognitive
                      impairment map to specific brain networks.We analyzed
                      cross-sectional data of 3,485 patients from 10 memory clinic
                      cohorts within the Meta VCI Map Consortium, using harmonized
                      test results in 4 cognitive domains and WMH segmentations.
                      WMH segmentations were registered to a standard space and
                      mapped onto existing normative structural and functional
                      brain connectome data. We employed LNM to quantify WMH
                      connectivity to 480 atlas-based gray and white matter
                      regions of interest (ROI), resulting in ROI-level structural
                      and functional LNM scores. We compared the capacity of total
                      and regional WMH volumes and LNM scores in predicting
                      cognitive function using ridge regression models in a nested
                      cross-validation. LNM scores predicted performance in three
                      cognitive domains (attention/executive function, information
                      processing speed, and verbal memory) significantly better
                      than WMH volumes. LNM scores did not improve prediction for
                      language functions. ROI-level analysis revealed that higher
                      LNM scores, representing greater connectivity to WMH, in
                      gray and white matter regions of the dorsal and ventral
                      attention networks were associated with lower cognitive
                      performance.Measures of WMH-related brain network
                      connectivity significantly improve the prediction of current
                      cognitive performance in memory clinic patients compared to
                      WMH volume as a traditional imaging marker of
                      cerebrovascular disease. This highlights the crucial role of
                      network integrity, particularly in attention-related brain
                      regions, improving our understanding of vascular
                      contributions to cognitive impairment. Moving forward,
                      refining WMH information with connectivity data could
                      contribute to patient-tailored therapeutic interventions and
                      facilitate the identification of subgroups at risk of
                      cognitive disorders.},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5251 - Multilevel Brain Organization and Variability
                      (POF4-525) / 5252 - Brain Dysfunction and Plasticity
                      (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5251 / G:(DE-HGF)POF4-5252},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {39400198},
      UT           = {WOS:001434577200001},
      doi          = {10.1093/brain/awae315},
      url          = {https://juser.fz-juelich.de/record/1032009},
}