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. 2023 Aug;18(8):1533-1541.
doi: 10.1007/s11548-023-02832-2. Epub 2023 Jan 31.

Automated image fusion during endovascular aneurysm repair: a feasibility and accuracy study

Stefan P M Smorenburg  1   2 , Rutger J Lely  3   4 , Iris Smit-Ockeloen  5 , Kak Khee Yeung  6   4 , Arjan W J Hoksbergen  6   4
Affiliations

Automated image fusion during endovascular aneurysm repair: a feasibility and accuracy study

Stefan P M Smorenburg et al. Int J Comput Assist Radiol Surg. 2023 Aug.

Abstract

Purpose: Image fusion merges preoperative computed tomography angiography (CTA) with live fluoroscopy during endovascular procedures to function as an overlay 3D roadmap. However, in most current systems, the registration between imaging modalities is performed manually by vertebral column matching which can be subjective, inaccurate and time consuming depending on experience. Our objective was to evaluate feasibility and accuracy of image-based automated 2D-3D image fusion between preoperative CTA and intraoperative fluoroscopy based on vertebral column matching.

Methods: A single-center study with offline procedure data was conducted in 10 consecutive patients which had endovascular aortic repair in which we evaluated unreleased automated fusion software provided by Philips (Best, the Netherlands). Fluoroscopy and digital subtraction angiography images were collected after the procedures and the vertebral column was fused fully automatically. Primary endpoints were feasibility and accuracy of bone alignment (mm). Secondary endpoint was vascular alignment (mm) between the lowest renal artery orifices. Clinical non-inferiority was defined at a mismatch of < 1 mm.

Results: In total, 87 automated measurements and 40 manual measurements were performed on vertebrae T12-L5 in all 10 patients. Manual correction was needed in 3 of the 10 patients due to incomplete visibility of the vertebral edges in the fluoroscopy image. Median difference between automated fusion and manual fusion was 0.1 mm for bone alignment (p = 0.94). The vascular alignment was 4.9 mm (0.7-17.5 mm) for manual and 5.5 mm (1.0-14.0 mm) for automated fusion. This did not improve, due to the presence of stiff wires and stent graft.

Conclusion: Automated image fusion was feasible when all vertebral edges were visible. Accuracy was non-inferior to manual image fusion regarding bone alignment. Future developments should focus on intraoperative image-based correction of vascular alignment.

Keywords: 2D-3D; 3D roadmap; Automated; EVAR; Fusion imaging; Image fusion; Navigation; Overlay.

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Figures

Fig. 1
Fig. 1
Diagram of the study protocol. First, CTA and fluoroscopy were acquired during an EVAR procedure. After the procedure, the images were retrieved and the vertebral column was fused automatically by the registration algorithm on an anteroposterior (AP) image. After this, regular manual image fusion was performed, 30° right anterior oblique (RAO) and left anterior oblique (LAO), in the identical patients to function as a control group. To correct for inter-observer variability, this was performed by two physicians. Fusion results were assessed on bone alignment measurements (mm) at the lateral edges of the vertebrae and vascular alignment measurements at the lowest renal artery orifice
Fig. 2
Fig. 2
Imaging used for automated fusion: first fluoroscopy image of the initial DSA (a) and preoperative CTA converted to a digital X-ray projection (b)
Fig. 3
Fig. 3
Automated registration evaluation (a) by measuring bone alignment in millimeters at the lateral side of each vertebral body (Db) and live guidance evaluation (b) by measuring vascular alignment orifice displacement of the lowest renal artery compared with the initial DSA (Dv). Note that for the bone alignment an average is calculated of the two lateral vertebra measurements
See this image and copyright information in PMC

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