AneuGuidederived metal coverage ratio and pore density in Pipeline embolization devices: validation against VasoCT and association with aneurysm occlusion

Introduction

Subarachnoid hemorrhage (SAH) is a form of hemorrhagic stroke that shows high mortality and low rates of full recovery, and its incidence has risen between 1990 and 2021 (1,2). Among its causes, rupture of intracranial aneurysms (IAs) is a major contributor, with an annual rate of 0.95% (3).

Flow diverters (FDs) are designed to reconstruct the parent artery and redirect blood flow away from the aneurysm sac, thereby promoting endothelialization and thrombus formation. This mechanism, achieving occlusion through flow diversion rather than dense coil packing, represents a paradigm shift from traditional endovascular techniques. Numerous clinical studies have demonstrated the safety and efficacy of FDs (4-10).

The pipeline embolization device (PED, Covidien, Irvine, California), a representative FD, was initially indicated for large and giant wide-neck IAs and has more recently been applied to small- and medium-sized aneurysms (4,5,11,12).

The PED is constructed from 48 cobalt-chromium and platinum-tungsten alloy wires in a ratio of 3:1 (4). The mesh size ranges from 0.02 to 0.05 mm², and the metal coverage ratio (MCR) is approximately 30–35% in the unstressed state. Pore density (PD) is another important parameter characterizing the pore distribution of FDs. Animal studies have shown that variations in MCR and PD influence intimal growth, which is closely associated with aneurysm occlusion (13-15). However, wire distribution may become heterogeneous due to deformation caused by device manipulation or complex parent artery morphology. The effects of curvature (16,17), oversizing (18,19), overlapping (18,20), and push-and-pull maneuvers (21) on MCR or PD have been widely investigated. This heterogeneity leads to local variations in MCR and PD, limiting the reliability of nominal values provided by manufacturers.

Two-dimensional projection-based methods (22) or reconstructed radiopaque wire models (23) have been used to estimate MCR and PD. However, projection-based approaches cannot eliminate interference from overlapping wires, potentially leading to overestimation, whereas reconstruction methods require high-resolution postoperative imaging and substantial manual effort. These limitations hinder the practical and accurate quantification of MCR and PD. The virtual stenting tool AneuGuide enables real-time simulation of FD deployment and provides device apposition contours as well as MCR and PD values. This study aimed to evaluate the accuracy of AneuGuide in calculating MCR and PD and to explore their association with aneurysm occlusion. We present this article in accordance with the STARD reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2026-0744/rc).

Methods

Study population

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Chinese PLA General Hospital (No. S2022-079-02), and the requirement for informed consent was waived due to the retrospective, anonymized nature of the study. All consecutive patients with IAs treated with PED in the Senior Department of Neurosurgery, Chinese PLA General Hospital, between June 2022 and April 2024 were retrospectively reviewed.

The exclusion criteria were as follows: (I) IAs treated with overlapping PEDs; (II) lack of cone-beam CT angiographic data; (III) insufficient VasoCT image quality for PED reconstruction; and (IV) absence of follow-up imaging.

Baseline demographic and clinical characteristics, including patient sex, age, aneurysm location, morphology, maximum aneurysm diameter, and PED size, were collected for all enrolled patients.

Image acquisition

All angiographic images, including pre-treatment three-dimensional digital subtraction angiography (3D-DSA) and post-deployment VasoCT images, were acquired using a flat-panel detector monoplane angiography system (Azurion 7 M20, Philips Healthcare, Best, The Netherlands).

Both 3D-DSA and VasoCT were obtained using rotational angiography, with the C-arm performing a 240° rotation at 30 frames per second. For 3D-DSA, image acquisition lasted 4 seconds and was initiated after a 2-second delay following intra-arterial injection of undiluted contrast medium at 3 mL/s for 6 seconds. VasoCT imaging was performed immediately after PED deployment. Projection images were acquired without pixel binning using a reduced detector format (22 cm × 22 cm), with a total acquisition time of 20 seconds. To enable simultaneous visualization of the vessel lumen and PED structure, 10% diluted iodinated contrast was injected intra-arterially at 3 mL/s for 22 seconds with a 2-second X-ray delay.

A total of 122 projection images for 3D-DSA and 622 for VasoCT were reconstructed on an XtraVision workstation. The voxel size for 3D-DSA was 0.32 mm. VasoCT images were reconstructed into a 512×512×512 matrix centered on the stent, corresponding to a field-of-view of 17.8–34.5 mm and an isotropic resolution of 0.04 mm.

Image analysis and calculations

Pre-operative 3D-DSA images were used to reconstruct patientspecific vessel-aneurysm models for subsequent MCR and PD calculation (24).

The PED consists of 48 braided wires, including 36 cobalt-chromium and 12 platinum wires for radiopacity. The radiopaque platinum wires were reconstructed from VasoCT images and exported as STL files. Figure 1 illustrates the overall workflow for MCR and PD calculation. Centerlines were initially generated automatically from the reconstructed stent model and subsequently reviewed and manually corrected when necessary to account for reconstruction artifacts. Then, each centerline was swept into a three-dimensional structure with a diameter of 0.03 mm. Finally, the region of interest (ROI) corresponding to the aneurysm neck coverage was manually delineated, and all subsequent calculations were performed within this region. Figure 1A-1C illustrates a representative reconstruction and ROI selection.

Figure 1 Workflow for MCR and PD calculation using VasoCT-based reconstruction and AneuGuide simulation. (A) PED visualized on VasoCT. (B) Reconstructed PED model exported as an STL file. (C) Swept stent structure generated from centerlines. (D) Metal coverage visualization provided by AneuGuide. (E) Simulated PED with the value at each intersection calculated by AneuGuide. (F) Selection of corresponding regions within the VasoCT-based and AneuGuide-derived models to ensure assessment of the same aneurysm neck coverage area. MCR, metal coverage ratio; PD, pore density; PED, pipeline embolization device.

MCR was defined as the ratio of metal-covered area to the total aneurysm neck area. Direct calculation of this quantity on the three-dimensional stent surface is challenging due to the complex braided geometry. Therefore, two geometric approximations were introduced to simplify the computation. First, for each local stent cell formed by four intersecting wires, the curved 3D surface was approximated by its projection onto a two-dimensional plane. Under this local planar approximation, MCR was calculated as the projected area ratio within the aneurysm neck region. Second, each projected cell was further approximated as a rhombus defined by two pairs of intersecting wires. Based on this geometric representation, MCR for each cell was derived analytically as follows:

MCR=SmetalareaSneckarea[1]

Smetalarea=Sneckarea−Smetalfreearea[2]

MCRCT=(1−(1−dL×sin2α)2)×4[3]

where L and d denote the characteristic cell length and wire diameter, respectively, and α represents the angle between the two crossing wires along the axial direction of the PED. The factor ‘×4’ accounts for the three non-visible wires between adjacent platinum wires in the reconstructed model. As shown in Figure 2, the rhombus defined by four red lines represents the minimum repeating unit of the stent structure. MCR values were calculated for all cells within the ROI at the aneurysm neck, and the mean value was taken as the representative MCR for each case.

Figure 2 The minimum cell of reconstructed structures and actual PED. Red rhombus is the minimum cell of reconstructed stent with a length L. The enlarging rhombus (right) is the minimum cell of actual PED with a length l and braiding angle α. d represents the diameter of braiding wires. PED, pipeline embolization device.

PD was defined as the number of pores per unit area, or equivalently, the reciprocal of the pore area. In this study, the PD was also calculated based on the swept stent models. Due to the models only presenting 12 platinum wires, each reconstructed cell corresponds to 16 pores in the actual PED structure. PD_CT for each cell was calculated as:

PDCT=16L2sin2α[4]

Virtual stenting and calculation based on AneuGuide

AneuGuide is a virtual stenting tool designed to assist FD sizing and deployment simulation using 3D-DSA images or reconstructed STL models.

In this study, each reconstructed vessel-aneurysm model was imported into AneuGuide to simulate PED deployment. The workflow, including centerline extraction, discretization, stent deployment, and visualization, has been described previously (25). The reliability of AneuGuide for PED sizing has also been validated (25,26).

In addition to providing optimal device dimensions, AneuGuide calculates MCR and PD at each wire intersection based on three-dimensional coordinates. The formulation of MCR is consistent with the VasoCT-based method, except that the cell is defined by four adjacent wires from the full 48-wire structure. The corresponding equation is:

MCRAG=1−(1−dl×sin2α)2[5]

where l represents the minimum cell length of the actual PED structure. PD was defined as the reciprocal of the pore area:

PDAG=1l2sin2α[6]

To ensure anatomical correspondence between the virtual stent model and the VasoCT-based reconstruction, the actual implanted PED size and deployed landing zones identified on postoperative imaging were used as references for virtual deployment. This step was performed solely to ensure that MCR and PD were calculated within equivalent aneurysm neck coverage regions and was not intended to optimize simulation performance or improve deployment prediction. The deployed PED structure with MCR and PD values at each intersection was exported from AneuGuide in VTP format. Then, both the virtual stent and VasoCT-based model were imported into ParaView 5.13 (Kitware Inc., New York, USA) to spatially match corresponding intersections. The mean MCR or PD was obtained by averaging all selected intersections. Figure 1D-1F illustrates this process.

Statistical analysis

Continuous variables are presented as mean ± standard deviation (SD), and categorical variables as counts (percentages). MCR and PD were derived from CT-based reconstructions (MCR_CT, PD_CT) and AneuGuide simulations (MCR_AG, PD_AG), respectively. Agreement and correlation were assessed using Bland-Altman analysis and Pearson correlation coefficients. Differences were evaluated using the Wilcoxon signed-rank test. Discriminatory performance was assessed using the area under the receiver operating characteristic curve (AUC), and optimal cutoff values were determined using Youden’s J statistic. A two-sided P value <0.05 was considered statistically significant. All analyses were performed using GraphPad Prism 9.5.0 (GraphPad Software, Boston, MA, USA).

Results

Patient characteristics

Between June 2022 and April 2024, 87 patients (95 aneurysms) underwent PED treatment at our center. Patients were excluded if they were treated with overlapping PEDs (n=5) or PED-assisted coiling (n=14). Among the remaining patients, 23 were further excluded: 13 patients lacked follow-up imaging, and 10 patients had suboptimal VasoCT image quality that precluded reconstruction of the stent mesh at the aneurysm neck. Ultimately, 45 patients (48 aneurysms) were included in the final analysis (Figure 3). The mean age of the cohort was 55.75 years (range, 33–78 years), and 73.33% (33/45) of patients were female. The mean follow-up duration was 6.77 months (range, 4–9 months). Baseline characteristics are summarized in Table 1.

Figure 3 Flowchart of patient selection process for the study. MCR, metal coverage ratio; PD, pore density; PED, pipeline embolization device.

Agreement and correlation of MCR and PD

Figure 4 illustrates the agreement and correlation analyses between VasoCT and AneuGuide. Figure 4A,4C present Bland-Altman plots comparing MCR and PD measurements between VasoCT and AneuGuide, demonstrating good agreement between the two methods. Pearson correlation analysis, illustrated by scatter plots in Figure 4B,4D, showed moderate correlations for MCR (r=0.65, P<0.001) and PD (r=0.79, P<0.001). AneuGuide showed slightly higher values for MCR (mean difference, 1.247) and PD (mean difference, 0.859 pores/mm²); however, these differences were not statistically significant (MCR, P=0.157; PD, P=0.286).

Figure 4 Agreement and correlation analysis. (A) Agreement between MCR_CT and MCR_AG. (B) Correlation between MCR_CT and MCR_AG. (C) Agreement between PD_CT and PD_AG. (D) Correlation between PD_CT and PD_AG. AG, AneuGuide; CT, VasoCT; MCR, metal coverage ratio; PD, pore density; SD, standard deviation.

Correlation between MCR and PD

Because MCR and PD represent related geometric descriptors of FD architecture, an additional correlation analysis was performed. A strong positive correlation was observed between AneuGuide-derived MCR and PD (r=0.868, P<0.001; Figure 5), indicating substantial geometric coupling between these two parameters.

Figure 5 Correlation between AneuGuide-derived MCR and PD, demonstrating the geometric relationship between the two parameters. AG, AneuGuide; MCR, metal coverage ratio; PD, pore density.

Predictive performance of MCR and PD for aneurysm occlusion

Follow-up imaging revealed persistent aneurysm patency in 6 aneurysms (12.5%), all presenting with residual aneurysm filling. AneuGuide simulations showed that, compared with occluded aneurysms, non-occluded lesions had lower MCR (22.05%±3.02% vs. 27.14%±7.65%, P=0.034) and PD (13.53±3.85 vs. 17.50±6.28 pores/mm², P=0.058). Figure 6A,6B show the receiver operating characteristic (ROC) curves for MCR and PD, respectively. MCR demonstrated discriminative ability for predicting aneurysm occlusion, with an AUC of 0.770 (95% CI: 0.561–0.979; P=0.034) and an optimal cutoff of 22.01 (sensitivity, 83.3%; specificity, 66.7%). PD showed an AUC of 0.742 (95% CI: 0.516–0.968; P=0.057), with an optimal cutoff of 13.27 pores/mm² (sensitivity, 78.6%; specificity, 66.7%).

Figure 6 Receiver operating characteristic curves evaluating the association of AneuGuide-derived parameters with aneurysm occlusion after PED treatment. (A) MCR and (B) PD. AUC, area under the receiver operating characteristic curve; MCR, metal coverage ratio; PD, pore density; PED, pipeline embolization device.

Discussion

This study demonstrated that MCR and PD derived from AneuGuide showed good agreement with those calculated from VasoCT-based reconstructions, supporting the accuracy of this virtual stenting approach. Although the mean values of MCR and PD obtained from AneuGuide were slightly higher than those from VasoCT, the differences remained within acceptable limits. Such minor deviations may be attributable to differences in geometric assumptions and reconstruction resolution, which are unlikely to substantially affect the overall interpretation of the results. These findings suggest that AneuGuide can provide reliable geometric estimates of deployed PEDs and may serve as a practical tool for device assessment and treatment-related decision support.

The accurate estimation of MCR and PD is challenging because FDs are braided, deformable structures whose wire distribution varies according to vessel anatomy and deployment technique. Nominal device specifications therefore may not accurately reflect local metal coverage at the aneurysm neck. In this study, we reconstructed the 12 radiopaque platinum wires from postoperative VasoCT images to establish a clinically applicable reference model for wire distribution at the aneurysm neck. This approach enabled us to balance geometric fidelity and computational feasibility, while minimizing the bias introduced by imaging resolution constraints. However, it should be recognized that neither the VasoCT-based reconstruction nor the AneuGuide-derived calculation represents a physical ground truth. Both approaches rely on geometric simplifications of the braided stent architecture. In particular, local three-dimensional stent surfaces were approximated using planar projections and rhombus-shaped cells to facilitate MCR and PD calculation. These assumptions may influence the absolute values of MCR and PD and introduce systematic deviations from the true device geometry. Therefore, the primary objective of the present study was to evaluate the consistency between two clinically applicable estimation methods rather than to determine exact physical values. Importantly, postoperative imaging information was used only to establish anatomical correspondence between the virtual and reconstructed models and to ensure equivalent neck coverage regions for comparison, rather than to optimize or retrospectively improve simulation performance.

MCR and PD are important geometric descriptors of FD configuration and have been associated with endothelialization, flow modification, and aneurysm occlusion in previous experimental and clinical studies (14,27-29). In the present study, MCR was significantly higher in occluded aneurysms, whereas PD showed a similar trend without reaching statistical significance. Additional analysis demonstrated a strong correlation between MCR and PD (r=0.868, P<0.001), indicating substantial geometric coupling between these parameters. This finding suggests that both metrics largely reflect the same underlying characteristics of the deployed device, despite describing different aspects of stent architecture. Although several previous studies have suggested that PD may be a stronger determinant of aneurysm occlusion than MCR (13,22,30), the present results did not demonstrate a clear advantage of either parameter. This discrepancy may be related to the strong correlation between MCR and PD, the limited number of non-occluded aneurysms, and measurement variability associated with local geometric heterogeneity. Taken together, these findings suggest that MCR and PD should be regarded as complementary descriptors of deployed FD geometry rather than competing predictors.

To explore the potential clinical relevance of these validated geometric parameters, ROC analysis was performed. Both MCR and PD demonstrated moderate discriminatory ability (AUCs of 0.770 and 0.742, respectively). However, aneurysm occlusion after FD is a multifactorial process influenced not only by device-related geometric parameters but also by aneurysm morphology, neck configuration, parent vessel geometry, vascular curvature, and patient-specific hemodynamic conditions. These factors may interact with local metal coverage and pore distribution to affect endothelialization and flow remodeling. Since only six aneurysms remained non-occluded during follow-up, the observed associations should be interpreted cautiously and are best regarded as exploratory and hypothesis-generating rather than definitive evidence of predictive performance.

Limitations

Several limitations should be acknowledged. First, only six aneurysms remained non-occluded during follow-up, limiting the statistical power of the occlusion analysis and the stability of ROC estimates. Therefore, the observed associations between MCR, PD, and aneurysm occlusion should be considered exploratory and hypothesis-generating rather than definitive evidence of predictive performance. Second, postoperative imaging information was used to establish anatomical correspondence between the virtual deployment model and the VasoCT-based reconstruction. Although this step was performed solely for region matching rather than deployment optimization, a degree of validation bias cannot be completely excluded. In addition, manual correction of generated centerlines and manual ROI selection may introduce a limited degree of observer-dependent variability. Third, only PED devices were included, which may limit the generalizability of the findings to other FD systems with different structural characteristics or more complex treatment configurations. Fourth, the mean follow-up duration was 6.77 months, which is relatively short for evaluating aneurysm occlusion after FD treatment, and longer-term outcomes remain to be determined. Finally, aneurysm morphology, parent vessel geometry, and patient-specific hemodynamic factors were not incorporated into the present analysis. Future prospective, multicenter studies with longer follow-up, broader device representation, and integration of geometric, anatomical, and hemodynamic information are warranted to further validate and extend these findings.

Conclusions

This study validated the accuracy of AneuGuide in calculating MCR and PD, exhibiting good agreement with VasoCT-reconstructions. Higher MCR and PD were associated with aneurysm occlusion at short-term follow-up, although these findings should be interpreted cautiously because of the limited number of non-occluded aneurysms. These findings suggest that AneuGuide may provide useful geometric information to support assessment of FD deployment and treatment-related evaluation.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2026-0744/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2026-0744/dss

Funding: This work was supported by Zhejiang Provincial Key Research and Development Plan (No. 2024C03095).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2026-0744/coif). R.Z., Y.S., J.Z., and J.X. report that this work was supported by Zhejiang Provincial Key Research and Development Plan (No. 2024C03095). They are also employees of ArteryFlow Technology Co., Ltd. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Chinese PLA General Hospital (No. S2022-079-02), and the requirement for informed consent was waived due to the retrospective, anonymized nature of the study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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