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SNIS 20th annual meeting electronic poster abstracts
E-142 A new graphical interface to capture quantitative venous outflow metrics
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  1. G Adusumilli1,
  2. S Christensen2,
  3. T Faizy3,
  4. G Albers2,
  5. M Lansberg2,
  6. J Heit4
  1. 1Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
  2. 2Stanford Stroke Center, Stanford University, Palo Alto, CA, USA
  3. 3Department of Neuroradiology, University of Hamburg-Eppendorf, Hamburg, Germany
  4. 4Department of Neuroradiology and Neurointervention, Stanford University, Palo Alto, CA, USA

Abstract

Background Robust venous outflow (VOF) profiles are strongly correlated with favorable reperfusion and functional outcomes in patients with acute ischemic stroke due to large vessel occlusion treated by endovascular thrombectomy. VOF is measured by the degree of venous opacification on pre-thrombectomy CTA studies, but these measurements are laborious and require neuroimaging expertise. We aimed to develop an automated method to measure VOF using CTA and CT perfusion imaging studies.

Methods We developed a Python-based graphical interface that links Computed Tomography Angiography (CTA) vessel isosurface renderings with axial Computed Tomography Perfusion (CTP) slices for each patient. The interface was implemented in The Visualization Toolkit, and co-registration from CTA to CTP was performed with SimpleITK v 1.1. Concentration curves representing arterial input function (AIF) and VOF were set to automatically generate upon selection of voxels on CTP.

Results Within the interface, the user is able to expeditiously select 5-10 voxels on CTP for each AIF and VOF location with co-registration to the vascular anatomy on CTA (figure 1). The average curve at each location is then fitted to a gamma variate function and parameterized by its initial upslope, time to peak (TTP), and first moment. Outcome variables such as VOF TTP, Time between AIF and VOF Peak, or VOF Curve Width can be readily calculated.

Conclusions Our newly developed graphical interface allows users to output quantitative metrics that may represent AIF and VOF. These metrics should be checked against existing scales for association and performance.

Abstract E-142 Figure 1
Abstract E-142 Figure 1

Disclosures G. Adusumilli: None. S. Christensen: 2; C; iSchemaView. 4; C; iSchemaView. T. Faizy: None. G. Albers: 2; C; iSchemaView, Genentech. 4; C; iSchemaView. M. Lansberg: None. J. Heit: 2; C; Medtronic, MicroVention. 6; C; iSchemaView.

https://doi.org/10.1136/jnis-2023-SNIS.242

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