Clinicians' confidence in synthetic neuroimaging: a survey from the EANS emerging Technologies and Innovations in Neurosurgery (ETIN) taskforce.
10 affiliations
- 1Department of Neurosurgery, Park Medical Center, Rotterdam, the Netherlands.
- 2Machine Intelligence in Clinical Neuroscience & Microsurgical Neuroanatomy (MICN) Laboratory, Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland.
- 3Capio Spine Center Stockholm, Löwenströmska Hospital, Upplands-Väsby, Sweden.
- 4Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
- 5European Association of Neurosurgical Societies (EANS) Emerging Technologies and Innovations (ETIN) Taskforce, Brussels, Belgium.
- 6Department of Neurosurgery, University Hospital Münster, Münster, Germany.
- 7Macquarie Medical School, Macquarie University, Sydney, Australia.
- 8Department of Neurosurgery, Daejeon Eulji University Hospital, Eulji University Medical School, Daejeon, South Korea.
- 9Department of Neurosurgery, Macquarie University Hospital, Sydney, Australia.
- 10Department of Neurosurgery, La Paz University Hospital, Madrid, Spain.
Abstract
Introduction
Neurosurgery relies heavily on imaging for diagnostic, planning, intra-operative decision-making, and image-guided interventions. Machine learning (ML) enables synthetic imaging, such as synthetic CT (sCT) generated from MRI or biplanar X-rays, potentially reducing radiation exposure and improving imaging access. However, clinicians' confidence in synthetic imaging remains poorly understood.Research question
This study assessed respondents attitudes towards synthetic neuroimaging.Material and methods
An international cross-sectional survey was distributed via the European Association of Neurosurgical Societies (EANS) and a global neurosurgeon database. Nineteen questions covered demographics, general attitudes, and two algorithms: MRI-based sCT, and biplanar X-ray-based sCT. Confidence was reported using a 5-point Likert scale (1 = not confident, 5 = completely confident). Responses were summarized using medians, interquartile ranges (IQR), counts, and percentages.Results
Seventy-two respondents completed the survey; 61% were board-certified neurosurgeons, and 76% worked in academic hospitals. Confidence varied across the two clinical scenarios. Confidence for MRI-based spinal decision-making was moderate (median 3, IQR 3-4), whereas confidence in X-ray-based sCT for cranial applications was lower (median 2, IQR 2-3). Clinical and external validation were frequently selected as factors supporting confidence, whereas hallucinations and lack of validation limited confidence.Discussion and conclusion
Confidence in synthetic neuroimaging varied across clinical scenarios. Differences may reflect clinical context, perceived consequences of error, input modality, and information provided in each scenario. While synthetic imaging may improve access, reduce radiation exposure, and support decision-making, adoption requires robust, application-specific validation. These findings guide future implementation of synthetic imaging in neurosurgery.
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BibTeX
@article{poelman2026clinicians,
title = {{Clinicians' confidence in synthetic neuroimaging: a survey from the EANS emerging Technologies and Innovations in Neurosurgery (ETIN) taskforce.}},
author = {Michelle D Poelman and Massimo Bottini and Olivier Zanier and Istiak Khan and Daniel De Wilde and Stefanos Voglis and Adrian Elmi-Terander and Victor Gabriel El-Hajj and Nikolay Gabrovsky and Alessandro Boaro and Stefan Motov and Eric Suero Molina and Seung-Jun Ryu and Antonio Di Ieva and Marisa Gandia González and Luca Regli and Carlo Serra and Marc L Schröder and Victor E Staartjes},
journal = {Brain \& spine},
year = {2026},
month = oct,
doi = {10.1016/j.bas.2026.107488},
url = {https://europepmc.org/article/MED/42960159},
note = {CC BY},
}
RIS
TY - JOUR
TI - Clinicians' confidence in synthetic neuroimaging: a survey from the EANS emerging Technologies and Innovations in Neurosurgery (ETIN) taskforce.
AU - Michelle D Poelman
AU - Massimo Bottini
AU - Olivier Zanier
AU - Istiak Khan
AU - Daniel De Wilde
AU - Stefanos Voglis
AU - Adrian Elmi-Terander
AU - Victor Gabriel El-Hajj
AU - Nikolay Gabrovsky
AU - Alessandro Boaro
AU - Stefan Motov
AU - Eric Suero Molina
AU - Seung-Jun Ryu
AU - Antonio Di Ieva
AU - Marisa Gandia González
AU - Luca Regli
AU - Carlo Serra
AU - Marc L Schröder
AU - Victor E Staartjes
PY - 2026
DA - 2026/10/22
JO - Brain & spine
DO - 10.1016/j.bas.2026.107488
UR - https://europepmc.org/article/MED/42960159
AB - Introduction Neurosurgery relies heavily on imaging for diagnostic, planning, intra-operative decision-making, and image-guided interventions. Machine learning (ML) enables synthetic imaging, such as synthetic CT (sCT) generated from MRI or biplanar X-rays, potentially reducing radiation exposure and improving imaging access. However, clinicians' confidence in synthetic imaging remains poorly understood.Research question This study assessed respondents attitudes towards synthetic neuroimaging.Material and methods An international cross-sectional survey was distributed via the European Association of Neurosurgical Societies (EANS) and a global neurosurgeon database. Nineteen questions covered demographics, general attitudes, and two algorithms: MRI-based sCT, and biplanar X-ray-based sCT. Confidence was reported using a 5-point Likert scale (1 = not confident, 5 = completely confident). Responses were summarized using medians, interquartile ranges (IQR), counts, and percentages.Results Seventy-two respondents completed the survey; 61% were board-certified neurosurgeons, and 76% worked in academic hospitals. Confidence varied across the two clinical scenarios. Confidence for MRI-based spinal decision-making was moderate (median 3, IQR 3-4), whereas confidence in X-ray-based sCT for cranial applications was lower (median 2, IQR 2-3). Clinical and external validation were frequently selected as factors supporting confidence, whereas hallucinations and lack of validation limited confidence.Discussion and conclusion Confidence in synthetic neuroimaging varied across clinical scenarios. Differences may reflect clinical context, perceived consequences of error, input modality, and information provided in each scenario. While synthetic imaging may improve access, reduce radiation exposure, and support decision-making, adoption requires robust, application-specific validation. These findings guide future implementation of synthetic imaging in neurosurgery.
SN - 2772-5294
ER -