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@ARTICLE{Rosen:845832,
      author       = {Rosen, Allyson C. and Soman, Salil and Bhat, Jyoti and
                      Laird, Angela R. and Stephens, Jeffrey and Eickhoff, Simon
                      and Fox, P. Mickle and Long, Becky and Dinishak, David and
                      Ortega, Mario and Lane, Barton and Wintermark, Max and
                      Hitchner, Elizabeth and Zhou, Wei},
      title        = {{C}onvergence {A}nalysis of {M}icro-{L}esions ({CAML}):
                      {A}n approach to mapping of diffuse lesions from carotid
                      revascularization},
      journal      = {NeuroImage: Clinical},
      volume       = {18},
      issn         = {2213-1582},
      address      = {[Amsterdam u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2018-03039},
      pages        = {553 - 559},
      year         = {2018},
      note         = {ACR was supported by a K award NIH NIA (K01AG025157) and
                      the Mental Illness Research Education and Clinical Center
                      (MIRECC). JTS was supported by the MIRECC. ARL, SBE, PMF
                      were supported by the NIMH (R01-MH074457). Other grant
                      support includes the American Heart Association (CRP2610312)
                      and NIH NINDS (R01NS070308). JB was supported by NIH NINDS
                      (R21NS081416) and Palo Alto Veterans Institute for Research
                      (PAVIR).},
      abstract     = {Carotid revascularization (endarterectomy, stenting)
                      prevents stroke; however, procedure-related embolization is
                      common and results in small brain lesions easily identified
                      by diffusion weighted magnetic resonance imaging (DWI). A
                      crucial barrier to understanding the clinical significance
                      of these lesions has been the lack of a statistical approach
                      to identify vulnerable brain areas. The problem is that the
                      lesions are small, numerous, and non-overlapping. Here we
                      address this problem with a new method, the Convergence
                      Analysis of Micro-Lesions (CAML) technique, an extension of
                      the Anatomic Likelihood Analysis (ALE). The method combines
                      manual lesion tracing, constraints based on known lesion
                      patterns, and convergence analysis to represent regions
                      vulnerable to lesions as probabilistic brain atlases. Two
                      studies were conducted over the course of 12 years in an
                      active, vascular surgery clinic. An analysis in an initial
                      group of 126 patients at 1.5 T MRI was cross-validated in a
                      second group of 80 patients at 3T MRI. In CAML, lesions were
                      manually defined and center points identified. Brains were
                      aligned according to side of surgery since this factor
                      powerfully determines lesion distribution. A convergence
                      based analysis, was performed on each of these groups.
                      Results indicated the most consistent region of
                      vulnerability was in motor and premotor cortex regions.
                      Smaller regions common to both groups included the
                      dorsolateral prefrontal cortex and medial parietal regions.
                      Vulnerability of motor cortex is consistent with previous
                      work showing changes in hand dexterity associated with these
                      procedures. The consistency of CAML also demonstrates the
                      feasibility of this new approach to characterize small,
                      diffuse, non-overlapping lesions in patients with multifocal
                      pathologies.},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {572 - (Dys-)function and Plasticity (POF3-572)},
      pid          = {G:(DE-HGF)POF3-572},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:29868451},
      UT           = {WOS:000433169000057},
      doi          = {10.1016/j.nicl.2018.01.020},
      url          = {https://juser.fz-juelich.de/record/845832},
}