title: Parametric color coding of digital subtraction angiography in the evaluation of carotid cavernous fistulas.
abstract: OBJECTIVE
  Angiographic assessment of carotid cavernous fistulas (CCFs) can be complex. Our purpose was to examine whether the use of parametric color coding in the postprocessing of DSA series is advantageous in the evaluation of CCFs.
  
  
  METHODS
  We enrolled 16 patients with angiographically proven CCFs. Endovascular treatment was performed in 14 cases. For postprocessing of digital subtraction angiography (DSA) series, a newly implemented algorithm of parametric color coding was used, turning sequential images of two-dimensional (2D)-DSA series into a single color-coded image. Angiographic data of initial, interventional, and postinterventional 2D-DSA series were compared with color-coded images. Whether parametric color coding could facilitate evaluation of fistula architecture and provide a more precise estimation of fistula venous drainage patterns as well as whether flow analysis could reveal objective changes during and after treatment were investigated.
  
  
  RESULTS
  In 56 % of the cases, parametric color coding was observed to facilitate visualization of fistula angioarchitecture. Estimation of fistula drainage flow patterns was considered to be improved in 31 % of the cases. For assessment of hemodynamic changes during and after treatment, parametric color coding was assumed to be helpful in 21 % of the cases, especially because revealing flow changes that were not visible on 2D-DSA series were now visible.
  
  
  CONCLUSIONS
  Parametric color coding is a fast application tool that might provide additional support in the angiographic evaluation of CCFs. Visualization of complex fistula architecture could be facilitated, and flow analysis might improve assessment of venous drainage patterns, thereby increasing overall diagnostic confidence. During and after treatment, hemodynamic changes that were not visible on 2D-DSA series could now be depicted.
authors.affiliation: Department of Neuroradiology, University of Erlangen-Nuremberg, Schwabachanlage 6, 91052, Erlangen, Germany. philipp.goelitz@uk-erlangen.de
authors.forename: P
authors.initials: P
authors.lastname: Gölitz
authors.forename: T
authors.initials: T
authors.lastname: Struffert
authors.forename: H
authors.initials: H
authors.lastname: Lücking
authors.forename: J
authors.initials: J
authors.lastname: Rösch
authors.forename: F
authors.initials: F
authors.lastname: Knossalla
authors.forename: O
authors.initials: O
authors.lastname: Ganslandt
authors.forename: Y
authors.initials: Y
authors.lastname: Deuerling-Zheng
authors.forename: A
authors.initials: A
authors.lastname: Doerfler
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D015901:Angiography, Digital Subtraction / Q000379:methods*; D020216:Carotid-Cavernous Sinus Fistula / Q000000981:diagnostic imaging*; D003116:Color; D003196:Computer Graphics; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014584:User-Computer Interface