OBJECTIVES: After deployment of flow-diverting stents (FDS), complete aneurysm occlusion is not predictable. This study investigated whether parametric colour coding (PCC) could allow in vivo visualization of flow alterations induced by FDS and identify favourable or adverse flow modulations. METHODS: Thirty-six patients treated by FDS were analyzed. Preinterventional and postinterventional DSA-series were postprocessed by PCC and time-density curves (TDCs) were calculated. The parameters aneurysmal inflow, outflow, and relative time-to-peak (rTTP) were calculated. Preinterventional and postinterventional values were compared and related to occlusion rate. RESULTS: Postinterventional inflow showed a mean reduction of 37%, outflow of 51%, and rTTP a prolongation of 82%. Saccular aneurysm occlusion occurred if a reduction of at least 15% was achieved for inflow and 35% for outflow (sensitivity: 89%, specificity: 82%). Unchanged outflow and a slightly prolonged rTTP were associated with growth in one fusiform aneurysm. CONCLUSIONS: PCC allows visualization of flow alterations after FDS treatment, illustrating "flow diverting effects" by the TDC shape and indicating mainly aneurysmal outflow and lesser inflow changes. Quantifiable parameters (inflow, outflow, rTTP) can be obtained, thresholds for predicting aneurysm occlusion determined, and adverse flow modulations assumed. As a rapid intraprocedural tool, PCC might support the decision to implant more than one FDS. KEY POINTS: • After deployment of a flow-diverting stent, complete aneurysm occlusion is unpredictable. • Parametric colour coding offers new options for visualizing in vivo flow alterations non-invasively. • Quantifiable parameters, i.e., aneurysmal inflow/outflow can be obtained allowing prognostic stratification. • Rapid, intraprocedural application allows treatment monitoring, potentially contributing to patient safety.
OBJECTIVES: After deployment of flow-diverting stents (FDS), complete aneurysm occlusion is not predictable. This study investigated whether parametric colour coding (PCC) could allow in vivo visualization of flow alterations induced by FDS and identify favourable or adverse flow modulations. METHODS: Thirty-six patients treated by FDS were analyzed. Preinterventional and postinterventional DSA-series were postprocessed by PCC and time-density curves (TDCs) were calculated. The parameters aneurysmal inflow, outflow, and relative time-to-peak (rTTP) were calculated. Preinterventional and postinterventional values were compared and related to occlusion rate. RESULTS: Postinterventional inflow showed a mean reduction of 37%, outflow of 51%, and rTTP a prolongation of 82%. Saccular aneurysm occlusion occurred if a reduction of at least 15% was achieved for inflow and 35% for outflow (sensitivity: 89%, specificity: 82%). Unchanged outflow and a slightly prolonged rTTP were associated with growth in one fusiform aneurysm. CONCLUSIONS: PCC allows visualization of flow alterations after FDS treatment, illustrating "flow diverting effects" by the TDC shape and indicating mainly aneurysmal outflow and lesser inflow changes. Quantifiable parameters (inflow, outflow, rTTP) can be obtained, thresholds for predicting aneurysm occlusion determined, and adverse flow modulations assumed. As a rapid intraprocedural tool, PCC might support the decision to implant more than one FDS. KEY POINTS: • After deployment of a flow-diverting stent, complete aneurysm occlusion is unpredictable. • Parametric colour coding offers new options for visualizing in vivo flow alterations non-invasively. • Quantifiable parameters, i.e., aneurysmal inflow/outflow can be obtained allowing prognostic stratification. • Rapid, intraprocedural application allows treatment monitoring, potentially contributing to patient safety.
Authors: Z Kulcsár; E Houdart; A Bonafé; G Parker; J Millar; A J P Goddard; S Renowden; G Gál; B Turowski; K Mitchell; F Gray; M Rodriguez; R van den Berg; A Gruber; H Desal; I Wanke; D A Rüfenacht Journal: AJNR Am J Neuroradiol Date: 2010-11-11 Impact factor: 3.825
Authors: M de Barros Faria; R Nella Castro; J Lundquist; E Scrivano; R Ceratto; A Ferrario; P Lylyk Journal: AJNR Am J Neuroradiol Date: 2011-09-01 Impact factor: 3.825
Authors: I Szikora; Z Berentei; Z Kulcsar; M Marosfoi; Z S Vajda; W Lee; A Berez; P K Nelson Journal: AJNR Am J Neuroradiol Date: 2010-02-11 Impact factor: 3.825
Authors: Hector Fernandez; Juan M Macho; Jordi Blasco; Luis San Roman; Werner Mailaender; Luis Serra; Ignacio Larrabide Journal: Int J Comput Assist Radiol Surg Date: 2015-06-11 Impact factor: 2.924
Authors: Ronak J Dholakia; Ari D Kappel; Andrew Pagano; Henry H Woo; Baruch B Lieber; David J Fiorella; Chander Sadasivan Journal: Interv Neuroradiol Date: 2017-12-14 Impact factor: 1.610