Abstract
Background
Endovascular treatment (EVT) of intracranial aneurysms (IAs) has improved significantly with the integration of virtual simulation software (VSS) in surgical planning and device selection. Despite promising outcomes, discrepancies remain between physician and VSS recommendations. This review synthesizes evidence on (1) comparisons between VSS-chosen and physician-chosen dimensions; (2) VSS-chosen and postoperative measured dimensions; and (3) the success rate of VSS-guided device deployment.
Methods
A systematic search adhering to PRISMA guidelines was conducted in Medline, Embase, Web of Science, and Cochrane databases up to January 2024. Eligible studies included case series, cohort studies, and randomized trials assessing VSS for stent selection in IAs treatment. Mean difference (MD) and single-arm meta-analysis with 95% confidence intervals (CIs) under a random-effects model were performed for continuous and binary outcomes. Subanalyses were conducted for Sim&Size and PreSize software.
Results
Ten studies comprising 658 IAs were included. Pipeline Embolization Device was most commonly used. Findings demonstrated (1) high accuracy of VSS when comparing simulated and postoperative lengths (MD −1.7 mm; 95% CI −4.37 to 0.98 mm); (2) physician-chosen lengths overestimated compared to VSS (MD −2.11 mm; −3.43 to −0.79 mm); (3) no significant difference in physician- versus VSS-chosen diameters (MD −0.04 mm; −0.13 to 0.06 mm); and (4) high VSS-guided deployment success (96%; 93–99%) with low complications (4%). Subanalyses showed 95% and 92% deployment success rates for Sim&Size and PreSize, respectively.
Conclusion
VSS effectively estimates device length and achieves high deployment success, with low complication rates, supporting its utility in EVT planning.
Keywords: Flow-diverter, simulation, flow-diverter sizing
Introduction
Simulation Software has become an integral component of surgical planning and training in the field of endovascular treatment (EVT) for intracranial aneurysms (IAs). 1 Leveraging technological advancements, simulation software solutions offer precise simulations of critical aspects of procedures, such as stent positioning, sizing recommendations, and assessment of wall apposition. Given the individualized nature of aneurysm treatment, where each case presents distinct challenges and the critical need for precise planning, the adoption of simulation tools holds promise in improving procedural outcomes and device utilization.
Specifically, virtual simulation software (VSS) utilizes 3D rotational angiography (3D-RA) to accurately model stent behavior and ensure optimal wall apposition based on the unique characteristics of a patient's angioarchitecture and a chosen stent. This technology can guide stent size selection, ultimately improving procedural accuracy, efficiency, and safety. 2 Moreover, VSS has shown significant benefits, including reduced need for corrective interventions, minimized radiation exposure, and shorter procedural durations.2,3
Improper stent sizing can have significant implications: undersized stents risk poor wall apposition and endoleak formation, while oversized flow diverters (FDs) increase metal coverage in the artery, potentially elongating and covering branches unnecessarily. Optimal wall apposition is essential for stent endothelialization and successful aneurysm occlusion. 4 VSS supports precise stent sizing, enhancing procedural outcomes in EVT and improving the likelihood of favorable long-term results. Furthermore, the use of an improperly chosen stent device increases the risk of complications.5,6
Given the burgeoning interest in VSS tools, we conducted a meta-analysis to assess the effectiveness of leading platforms such as Sim&Size® (Sim&Cure, Grabels, France) and PreSize PreSize® (Oxford Heartbeat, UK), alongside other relevant software solutions, in aiding stent and flow-diversion stent placement. We aim to synthesize available evidence regarding the comparison between VSS-chosen dimensions and physician-chosen dimensions, VSS-chosen dimension, and postoperative measured dimension, and the rate of successful deployment of VSS-chosen devices, seeking to provide insights into the current application of VSS for device dimensions selection in neurovascular interventions.
Methods
This systematic review and single-arm meta-analysis was performed following the Cochrane Collaboration Handbook for Systematic Review of Interventions 7 and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement guidelines. 8
Eligibility criteria
Included studies fulfilled all the following criteria: (1) case series, retrospective or prospective cohorts, and randomized studies; (2) evaluating the use of VSS for stent selection in the treatment of IAs; (3) reporting at least one outcome of interest. Case reports, conference abstracts, letters, reviews, editorials, and comments were excluded from the initial assessment.
Search strategy and data extraction
A systematic search was conducted in Medline, Embase, Cochrane, and Web of Science databases, from inception to January 2024, with the following research strategy: (stent* OR “flow diver*” OR coil*) AND (“Sim&Size” OR “Aneuguide” OR “AneuShape” OR “PreSize” OR “Customized Simulation Software” OR “Simulation Software” OR “Software-based simulation” OR Sizing OR Shaping OR “Virtual Simulation” OR “Preoperative Simulation” OR “Computational Modeling”) AND (“Intracranial Aneurysm” OR “Brain Aneurysm” OR “Cerebral aneurysm” OR “intracerebral aneurysm”). Two authors (MYF and HGM) independently extracted the data following predefined search criteria. Any conflicts were resolved by a third author (CF).
Endpoints, definitions, and subanalysis
Endpoints included: (1) difference of means between VSS length and standard length measurements; (2) dimension matching between VSS-chosen device and physician-chosen device; and (3) successful deployment of the chosen device after simulation. Prespecified subanalyses were performed restricted to (1) Sim&Size software; and (2) PreSize software. Successful deployment was accounted for in cases when the device sized and selected by VSS was successfully deployed. The postoperative length measurements considered were those obtained after deployment through postprocessed volume acquisition images.
Statistical analysis
Mean difference (MD) with 95% confidence intervals under a random effects model was used to compare the data for continuous endpoints. Single proportion analysis with 95% confidence intervals under a random effects model was utilized to pool the data for binary endpoints. Heterogeneity was assessed using I² statistics, where I² > 40% was considered significant. Leave-one-out sensitivity analysis was conducted in analyses with moderate or high heterogeneity. The statistical analysis was performed using R 4.3.0 (R Core Team, 2023) with the meta package, 9 employing the inverse variance and the restricted maximum likelihood methods.
Results
Study selection
A total of 629 studies were initially identified. After eliminating duplicate entries and excluding 591 articles through title and abstract screening, 38 articles were thoroughly reviewed. Thirty additional manuscripts were excluded after review of the full report. Reasons for exclusion included: other uses for VSS other than optimal choice of the stent (13 papers), insufficient information for the assessment of outcomes of interest (n = 7), “Wrong intervention” (n = 9), and risk of overlap (n = 1). At last, 10 studies were included in this meta-analysis.1,2,8–18 The study selection process is illustrated in Figure 1.
Figure 1.
PRISMA flow diagram.
Included studies were nine retrospective and one prospective, comprising 657 patients and 658 IAs. The integrity of the aneurysm was reported in five studies, corresponding to a total of 11 ruptured in 321 aneurysms. Softwares utilized for VSS were Sim&Size® in three studies (Sim&Cure, Grabels, France), PreSize® (Oxford Heartbeat, UK), in two, Syngo 3D Aneurysm Guidance Neuro software (Siemens Healthcare GmbH, Erlangen, Germany) in one, VSP (Pentas Inc.) in one, UKNOW in one, and Proprietary Software described in Bouillot et al., 10 and AneuGuide ™ AneuGuideTM (ArteryFlow Technology, Hangzhou, China). Study-specific information can be found in Table 1.
Table 1.
Characteristics of the included studies.
| Study | Type | N patients/N aneurysm | Mean age, in years ± SD (range) | Ruptured/ unruptured | Device (n) | Software |
|---|---|---|---|---|---|---|
| Bouillot et al. 10 | R | 20/20 | N/A | N/A | FD (unspecified) | Proprietary Software |
| Briganti et al. 11 | R | 27/27 | 58.3 ± 7,6 | 0/27 | P64 (15), P48 (6), PED (3), LVIS jr (3) | Syngo 3D Aneurysm Guidance Neuro |
| Kan et al. 12 | P | 33/33 | 53.6 ± N/A (N/A) | 0/33 | PENTAS 16 (7) PENTAS 24 (26) | VSP (Virtual Stent Position) |
| Lv et al. 13 | R | 98/98 | 52.3 ± 12.2 (25–76) | 0/98 | PED (98) | AneuGuide ™ |
| Mantilla et al. 14 | R | 56/56 | 64 ± N/A (50.00–73.00) | N/A | PED (56) | Sim&Size® |
| Ngo et al. 15 | R | 88/88 | N/A | N/A | DERIVO (88) | PreSize® |
| Ospel et al. 16 | R | 74/74 | 58.6 ± 13.3 (30–83) | 5/69 | PED: 53/74 Coil + PED: 11/74 Multi PED: 7/74 | Sim&Size® |
| Patankar et al. 17 | R | 138/138 | N/A | N/A | PED (138) | PreSize® |
| Piergallini et al. 2 | R | 94/94 | 59.0 ± N/A (48–66) a | 6/94 | PED (94) | Sim&Size® |
| Wang et al. 18 | R | 29/30 | 55.8 ± 7.9 (40–70) | N/A | PED (21) Coil Assisted + PED (9) | UKNOW |
FD: flow diverter stent; N: number; P: prospective; PED: pipeline embolization device; R: retrospective; SD: standard deviation.
Results reported as median and interquartile range.
Seven studies reported aneurysm location and the most common was in the internal carotid artery (ICA) (n = 277 cases) followed by the vertebral artery (VA) (n = 33). Six studies disclosed mean aneurysm diameter, with an overall range from 6.0 to 8.8 mm in the means. A total of 26 complications were reported across the 10 included studies, comprising 4% of complications in the included population. This information, as well as the follow-up periods outlined by the study, can be found in Table 2.
Table 2.
Aneurysm location and mean diameter, complications, and mean follow-up of the included studies.
| Study | Aneurysm location | Aneurysm mean diameter ± SD (mm) | Complications (n) | Mean follow-up ± SD (range) (months) |
|---|---|---|---|---|
| Bouillot et al. 10 | ICA (20) | NR | None reported | NR |
| Briganti et al. 11 | ICA (21) BAS (3) ACA (3) | NR | None reported | NR ± NR (6–12) |
| Kan et al. 12 | ICA (20) VA (13) | 7.1 ± NR | Minor stroke (1) Major stroke (1) | 31.3 ± NR (14–44) |
| Lv et al. 13 | ICA (85) VA (13) | 6.7 ± 4.7 | None reported | NR |
| Mantilla et al. 14 | ICA (70) ACA (2) MCA (1) | 6.0 ± NR | Intracranial hemorrhage (3) Vascular access hemorrhage (4) Monocular hemianopsia (1) Decreased visual acuity (1) Stroke occlusion (1) | 0,5 ± NR (12–25) |
| Ngo et al. 15 | NR | NR | None reported | NR |
| Ospel et al. 16 | ACA(4) BAS(3) ICA(61) MCA(6) | 8.8 ± NR | PED deployment failure (5) Ischemia (4) Intracranial hemorrhage (2) | 1 year ± NR (NR) |
| Patankar et al. 17 | NR | NR | None reported | NR |
| Piergallini et al. 2 | NR | 6.0 ± NR | Embolic partial occlusion (1) Minor stroke (1) Asymptomatic carotid Dissection (1) | NR |
| Wang et al. 2022 18 | ICA (22) MCA (1) VA (7) | 6.3 ± 2.4 | None reported | NR |
ACA: anterior cerebral artery; BAS: basilar artery; ICA: internal carotid artery; MCA: middle cerebral artery; mm: millimeters; N/A: not available.
Difference in mean length between VSS simulation and postoperatively measurement
The length analysis included five studies and 315 simulations. The pooled analysis revealed an MD of −1.7 mm (95% CI −4.37 to 0.98 mm; I² = 86%; P > .05; Figure 2). This nonsignificant mean difference indicates a precise simulation when comparing the simulated length with the postoperative length obtained after deployment through postprocessed volume acquisition images.
Figure 2.
Forest plot showing a comparison in mean length between virtual simulation software (VSS) simulation and postoperatively measurement, demonstrating a nonsignificant mean difference (MD) in five studies, comprising 315 simulations, and indicating a precise simulation when comparing the simulated length with the postoperative length.
Dimension matching by the physician-chosen dimension and the VSS-chosen device dimension
Dimension matching analysis, both length and diameter analysis, included four studies and 293 simulations. The pooled analysis of length matching revealed an MD of −2.11 mm (95% CI −3.43 to −0.79 mm; I² = 73%; P < .01; Figure 3), while the pooled analysis of diameter matching revealed an MD of −0.04 mm (95% CI −0.13 to 0.06 mm; I² = 0%; P > .05; Figure 4). Those findings indicate a significant mismatch between physician-chosen length and VSS-chosen length, with physician-chosen length tended to be longer when compared with VSS-chosen length, and a nonsignificant difference between physician-chosen diameter and VSS-chosen diameter.
Figure 3.
Forest plot showing a comparison in virtual simulation software (VSS) mean length and physician-chosen mean length, demonstrating a significant mean difference (MD) in four studies, comprising 293 simulations, and indicating a significant mismatch between physician-chosen length and VSS-chosen length.
Figure 4.
Forest plot showing a comparison in virtual simulation software (VSS) mean diameter and physician-chosen mean diameter, demonstrating a significant mean difference (MD) in four studies, comprising 293 simulations, and indicating a nonsignificant difference between physician-chosen diameter and VSS-chosen diameter.
Successful deployment single proportion meta-analysis included 8 studies covering 542 cases. The analysis revealed an estimated rate of 96% (95% CI, 93%–99%, I² = 70%, Figure 5). In the sensitivity analysis, omitting one study at a time (Figure 6), findings showed a sustained high heterogeneity in all scenarios, along with overall rates ranging from 95% to 97%.
Figure 5.
Forest plot showing a high rate of Successful deployment in 542 virtual simulation software (VSS)-chosen deployed devices.
Figure 6.
Sensitivity analysis for successful deployment analysis.
Subanalysis for successful deployment, focusing on Sim&Size, aggregates data from three studies with a total of 224 cases. An overall rate of 95% (95% CI, 90%–100%; random-effects model, I² = 81%, Figure 7) was identified. PreSize subanalysis includes data from two studies with 236 cases, showing an overall rate of 92% (95% CI, 87%–96%; random-effects model, I² = 34%, Figure 8).
Figure 7.
Forest plot showing a subanalysis for Sim&Size software. A high rate of successful deployment in 224 Sim&Size-chosen deployed devices.
Figure 8.
Forest plot showing a subanalysis for PreSize software. A high rate of successful deployment in 236 PreSize-chosen deployed devices.
Discussion
This study aimed to synthesize available evidence regarding the comparison between VSS-chosen dimensions and physician-chosen dimensions, VSS-chosen dimensions, and postoperative measured dimension, and the rate of successful deployment of VSS-chosen devices, seeking to provide insights into how VSS influences in determining the optimal device size for EVT of IAs. Our key findings were (1) a precise simulation when comparing the simulated length with the postoperative length; (2) a significant mismatch between physician-chosen device length and VSS-chosen length, with physician-chosen length significantly longer when compared with VSS-chosen length; (3) a nonsignificant difference between physician-chosen diameter and VSS-chosen diameter; and (4) successful deployment of the VSS-chosen device occurred at an exceptionally high rate, alongside with a 4% rate of complications. Those findings provide a fertile ground for discussion in several aspects.
Overall, the main objective of EVT of IAs is to provide a favorable hemodynamic environment that allows safe and efficient aneurysm thrombosis and vessel remodeling. To achieve a satisfying aneurysm occlusion, choosing the device's correct size plays a significant role in preventing complications and excluding the aneurysm from circulation. Undersized devices are more likely to migrate from their initial placement position, resulting in poor flow diversion, increased chance of endoleak, 19 and a need for additional treatment. Furthermore, oversized devices may fail to adequately divert flow from an aneurysm and also cover unnecessary branches. In such instances, the device's cells enlarge its size, permitting blood to flow back into the aneurysm. Consequently, this diminishes the likelihood of achieving rapid and efficient thrombosis. 20
Choosing the correct device size is essential but can be challenging, especially for less experienced neurointerventionalists, due to variations in vessel diameter and the technical specifics of each device. Typically, device sizing relies on 2D or 3D manual measurements that are operator-dependent and prone to error. In addition, a comprehensive understanding of patient anatomy, expertise in deployment techniques, and awareness of device size variations are crucial in the endovascular treatment of intracranial aneurysms. Our findings indicate that existing literature supports VSS as a valuable tool, offering precise simulations that closely match postoperative device length, thereby improving accuracy in device sizing.
One aspect that could directly influence the device selection process is the volume of cases conducted by a specific center, with the larger ones, theoretically, having more experience with a variety of devices and, consequently, more favorable results when compared to smaller and less experienced centers. 21 Previous studies have also shown that VSS tends to choose shorter devices when blinded from conventional 2D measurement, with this being attributed to the software's capabilities of anticipating the implanted length and accurate landing zones, therefore allowing the operators to select/choose the smallest possible device confidently.2,16 This can also be attributed to the fact that a precise wall apposition may reduce the risk of oversizing, consequently promoting a more efficient device functioning. 19 Usually, in a practical scenario, physicians tend to choose oversized stents, therefore mitigating the risk of device migration, and this trend was confirmed by our findings. However, as mentioned previously, using oversized devices can lead to inefficient aneurysm exclusion or excessive manipulation during deployment, thereby elevating the risk of complications such as stent torsion and unintended coverage of perforators or branches, potentially resulting in a stroke.
Information regarding the safety of these tools seems to be in agreement in the literature. In an observational study, Briganti et al. 11 utilized software that estimates aneurysm and parental vessel size, therefore leading to an estimation of the more optimal device size. The author concludes that this technology is rapid, secure, and very useful when planning treatment. This is supported by a study led by Joshi et al. The authors measured the error discrepancy between the nominal length and simulated length when compared to the measure after deployment. The nominal difference between the nominal length and length after deployment presented a 22-mm mean squared deviation, which is the difference between the estimator and what is estimated, against only 6.14 mm in the simulated one. Additionally, Piergallini et al. 2 observed that software-performed device selection was associated with shorter operation durations. This reduction could decrease the risk of intraoperative ischemic events and lower radiation exposure, both of which are correlated with longer endovascular procedures. Our findings corroborate the safety of EVT using VSS-chosen devices, with a success rate of 96% and a low complication rate (4%, 26/658). Additionally, no device migration was reported in the 658 treated intracranial aneurysms.
The majority of included studies provide compelling evidence that virtual simulation device sizing is a valuable tool. However, these studies also raise concerns about the technology's limitations, which prompt reflection. Nonetheless, it is important to recognize that the human decision-making process, although complex, is well-established and supported by a strong body of scientific evidence, demonstrating its efficacy and low complication rate. Although VSS is increasingly utilized in specialized neuroradiology centers, there remains a significant need for more robust evidence before it can be deemed the gold standard in treatment planning. Methodological standards are still necessary to provide more trustful data on VSS efficacy through long-term follow-up studies.
The adoption of VSS is associated with several barriers that must be considered, including attributing cost savings to correct device selection, collating time savings from procedural mishaps, and optimizing workflow for simulation integration. Like any new technology being incorporated, it requires time and studies to optimize processes related to using this technology to be constructed, published, and widely adopted. Noteworthy, Mantilla et al. reported less surgical time in the simulation group when compared to the treatment without simulation. 14 New research on VSS should focus on these aspects, and evidence-based protocols would be useful to ensure these barriers do not prevent new departments from adopting the technology and exploiting its full potential, considering its limitations. Additionally, another aspect that should be the subject of upcoming studies and software development is addressing the issues involved in software, particularly their tendency to fail when the actual parameters exceed the boundary conditions of the model, precisely when the device is used in vessels that are either very stiff or very compliant.
To our knowledge, this is the first study to synthesize data regarding the applicability of VSS for device dimension estimating in EVTs of IAs. Our study corroborates empirical experience suggesting that physicians tend to choose an oversized device, and provides evidence that VSS is a helpful and feasible tool, despite still being in development. Further advancements in VSS, along with studies employing methodologies ensuring precise comparability, are necessary for the full potential of VSS in aiding device selection to be better understood. Intending to enhance patient care through complication-free procedures, this study is one more contribution to the exponential growth of neuro-interventional techniques in managing IAs.
Limitations
The present study has limitations. Included studies were observational, introducing inherent biases. Additionally, different VSS were included, and various methodologies were applied by studies to evaluate dimensions. A recognized limitation of the simulations is their tendency to fail when the actual parameters exceed the boundary conditions of the model, particularly when the device is used in vessels that are either very stiff or very compliant. Consequently, all interpretations of this study must consider this intrinsic limitation inherent in the original studies, affecting the meta-analyzed data. Also, most of the included studies reported on PED devices, and the interpretation of the data must consider that. High heterogeneity was identified in length analyses and successful deployment analysis. Despite attempts, it was not possible to analyze the VSS-chosen diameter versus the postoperatively measured diameter. Lastly, we aimed to assess long-term results; however, the included studies did not report long-term outcomes, leaving us with a gap in the interpretation of how VSS-chosen deployed devices behave in the long term after EVT of IAs.
Conclusion
This systematic review and meta-analysis identified that VSS is effective in estimating device length when comparing simulated length with postoperative measured length. Additionally, it was found that the physician-chosen length tends to be overestimated when compared with the VSS-chosen length, while the VSS-chosen diameter is similar to the physician-chosen diameter. Furthermore, successful deployment of the VSS-chosen device exhibits an exceptionally high rate, alongside a low rate of complications.
Acknowledgments
There were no contributors who did not meet the criteria for authorship.
Footnotes
Data availability: This systematic review used data from previously published studies; therefore, all data and study materials are in the public domain.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Ethical approval: Not applicable.
Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.
ORCID iDs: Ahmet Günkan https://orcid.org/0000-0002-6236-5633
Gean Carlo Müller https://orcid.org/0009-0009-1069-4206
Henrique Garcia Maia https://orcid.org/0009-0002-7719-5910
Ricardo A Hanel https://orcid.org/0000-0001-7195-5806
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