High variability in physician estimations of flow-diverting stent deployment versus PreSize Neurovascular software simulation: a comparison study Article Swipe
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· 2023
· Open Access
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· DOI: https://doi.org/10.1136/jnis-2023-020527
Background Physician variablity in preoperative planning of endovascular implant deployment and associated inaccuracies have not been documented. This study aimed to quantify the variability in accuracy of physician flow diverter (FD) planning and directly compares it with PreSize Neurovascular (Oxford Heartbeat Ltd) software simulations. Methods Eight experienced neurointerventionalists (NIs), blinded to procedural details, were provided with preoperative 3D rotational angiography (3D-RA) volumetric data along with images annotated with the distal landing location of a deployed Surpass Evolve (Stryker Neurovascular) FD from 51 patient cases. NIs were asked to perform a planning routine reflecting their normal practice and estimate the stent’s proximal landing using volumetric data and the labeled dimensions of the FD used. Equivalent deployed length estimation was performed using PreSize software. NI- and software-estimated lengths were compared with postprocedural observed deployed stent length (control) using Bland–Altman plots. NI assessment agreement was assessed with the intraclass correlation coefficient (ICC). Results The mean accuracy of NI-estimated deployed FD length was 81% (±15%) versus PreSize’s accuracy of 95% (±4%), demonstrating significantly higher accuracy for the software (p<0.001). The mean absolute error between estimated and control lengths was 4 mm (±3.5 mm, range 0.03–30.2 mm) for NIs and 1 mm (±0.9 mm, range 0.01–3.9 mm) for PreSize. No discernable trends in accuracy among NIs or across vasculature and aneurysm morphology (size, vessel diameter, tortuousity) were found. Conclusions The study quantified experienced physicians’ significant variablity in predicting an FD deployment with current planning approaches. In comparison, PreSize-simulated FD deployment was consistently more accurate and reliable, demonstrating its potential to improve standard of practice.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1136/jnis-2023-020527
- https://jnis.bmj.com/content/neurintsurg/early/2023/06/22/jnis-2023-020527.full.pdf
- OA Status
- hybrid
- Cited By
- 5
- References
- 19
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4381884642
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4381884642Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1136/jnis-2023-020527Digital Object Identifier
- Title
-
High variability in physician estimations of flow-diverting stent deployment versus PreSize Neurovascular software simulation: a comparison studyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-06-24Full publication date if available
- Authors
-
Ansaar Rai, SoHyun Boo, Jonathan Downer, Johannes DuPlessis, Riitta Rautio, Matias Sinisalo, Johanna Pekkola, Vinicius Carraro do Nascimento, Curtis A. Given, Tufail PatankarList of authors in order
- Landing page
-
https://doi.org/10.1136/jnis-2023-020527Publisher landing page
- PDF URL
-
https://jnis.bmj.com/content/neurintsurg/early/2023/06/22/jnis-2023-020527.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
- OA URL
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https://jnis.bmj.com/content/neurintsurg/early/2023/06/22/jnis-2023-020527.full.pdfDirect OA link when available
- Concepts
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Neurovascular bundle, Medicine, Intraclass correlation, Nuclear medicine, Radiology, Stent, Surgery, Clinical psychology, PsychometricsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 2, 2023: 2Per-year citation counts (last 5 years)
- References (count)
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19Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 91 |
| corresponding_author_ids | https://openalex.org/A5064304760 |
| countries_distinct_count | 4 |
| institutions_distinct_count | 10 |
| corresponding_institution_ids | https://openalex.org/I12097938, https://openalex.org/I4210089362 |
| citation_normalized_percentile.value | 0.7975663 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |