Article Figures & Data
Figures
- FIG 1.
Key aspects of the chosen network architecture. In addition to the in- and output of the network, kernel sizes, dilation rates, number of filters, and activation function (ie, rectified linear unit [ReLu]) are shown. Conv3D indicates 3D convolutional neural network.
- FIG 2.
Sample measurement of the vascular dimensions of an ICA (C4 segment) in a 3D-DSA data set. The maximum vessel diameters have been assessed for both 3D-DSA and 3DA in 2 projections each (VD1 and VD2) using multiplanar reconstructions. A, Sagittal orientation of the C4 segment. B, Coronary orientation of the C4 segment. C, Finally, both vessel diameters allow the calculation of the VGI (VGI = VD1/VD2).
- FIG 3.
Illustrative case 1. Sample visualization of a right-sided AVM with 3D-DSA (A) and the AI-based 3DA (B) using VRT. 3DA (B) shows both feeding arteries originating from the MCA and the nidus and drainage via superficial veins, equivalent to 3D-DSA. Not only the flow-associated aneurysm of the MCA bifurcation (red arrow) but also the venous ectasia adjacent to the nidus is comparably visualized without loss of information using 3DA.
- FIG 4.
Illustrative case 2. Sample visualization of a left-sided dAVF with 3D-DSA (A) and the AI–based 3DA (B) using VRT. 3DA (B) offers comparable visualization of the influx of the fistula via the dilated middle meningeal artery and the drainage of the fistula via an ectatic cerebral vein compared with 3D-DSA (A).
- FIG 5.
Illustrative case 3. Sample 3D visualization of an irregular aneurysm of the anterior communicating artery in VRT reconstructions using 3D-DSA (A) and 3DA (B). Despite differences concerning the reconstruction algorithm, AI-based 3DA (B) provides all relevant information on the aneurysmal configuration equivalent to 3D-DSA.
Tables
Grade Characteristics 4 Excellent (high contrast, no artifacts) 3 Good (high contrast; minimal artifacts, eg, due to movement or implants) 2 Compromised (eg, noticeable movement artifacts and/or reduced homogeneity of the vessel contrast) 1 Heavily compromised (low contrast and/or strong movement artifacts) 0 Not diagnostic (vasculature is not differentiable due to heavy artifacts and/or missing contrast) Parameter 3DA (Mean) 3D-DSA (Mean) r P VD1AVM 3.82 (SD, 0.47) mm 3.81 (SD, 0.55) mm 0.988 <.001 VD2AVM 3.97 (SD, 0.60) mm 3.94 (SD, 0.59) mm 0.984 <.001 VGIAVM 0.96 (SD, 0.04) mm 0.97 (SD, 0.03) mm 0.835 .003 VD1CA 4.39 (SD, 0.84) mm 4.34 (SD, 0.87) mm 0.998 <.001 VD2CA 4.61 (SD, 0.81) mm 4.54 (SD, 0.85) mm 0.996 <.001 VGICA 0.95 (SD, 0.04) mm 0.95 (SD, 0.03) mm 0.955 <.001 VD1dAVF 4.24 (SD, 0.72) mm 4.22 (SD, 0.77) mm 0.993 <.001 VD2dAVF 4.44 (SD, 0.780) mm 4.43 (SD, 0.81) mm 0.992 <.001 VGIdAVF 0.95 (SD, 0.02) mm 0.95 (SD, 0.02) mm 0.824 .003
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