Virtual phantom methodology for assessment of MRI distortion correction in high-precision stereotactic radiosurgery treatment planning

IntroductionThe accuracy of stereotactic treatment planning is primarily limited by the least accurate process in the whole chain of events, and is particularly important in cranial radiosurgery. Ameliorating this process can improve treatment targeting, providing additional reliability for these in...

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Main Authors: Tristan Belloeil-Marrane, Adrian Gutierrez, Marlies Boussaer, Cristina Teixeira, Thierry Gevaert, Mark De Ridder
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-05-01
Series:Frontiers in Oncology
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Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2025.1530332/full
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author Tristan Belloeil-Marrane
Adrian Gutierrez
Marlies Boussaer
Cristina Teixeira
Thierry Gevaert
Mark De Ridder
author_facet Tristan Belloeil-Marrane
Adrian Gutierrez
Marlies Boussaer
Cristina Teixeira
Thierry Gevaert
Mark De Ridder
author_sort Tristan Belloeil-Marrane
collection DOAJ
description IntroductionThe accuracy of stereotactic treatment planning is primarily limited by the least accurate process in the whole chain of events, and is particularly important in cranial radiosurgery. Ameliorating this process can improve treatment targeting, providing additional reliability for these indications. Quality assurance (QA) in radiotherapy is often performed on the dose delivery and planning section rather than the localization. Magnetic Resonance Images (MRI) are notably subject to distortions, due to the nonlinearity of gradient fields, potentially source of geometric errors. This study aimed to analyze the impact of a patient-specific algorithm, rather than manufacturer-specific, to correct spatial distortion in cranial MRI by using a novel software-only paradigm.Material and methodsAn unbiased simulated T1-Weighted MRI validated dataset is utilized to create a synthetic CT (sCT). By introducing controlled distortion in simulated datasets, we can evaluate the influence of noise and intensity non-uniformity (“RF”) ranging from 0 to 9% noise and 0 to 40% RF. These MRIs were corrected using the sCT as base modality for distortion correction. To evaluate the impact of the distortion correction, each corrected/non-corrected image set was compared to the unbiased MRI using Root-mean-square-error (RMSE) as a full-image reference comparison metric.ResultsThe distortion correction allows for an improvement based on the RMSE correlation between baseline and distorted MRIs. The amelioration of average RMSE in corrected versus non-corrected MRI is up to 42.22% for the most distorted datasets.ConclusionThe distortion correction results show a proportional improvement with increased noise and intensity non-uniformity. This provides additional robustness and reliability to the accuracy of SRS treatment planning using MR T1-W sequences as imaging reference for target definition and organ delineation, remaining consistent independently from the variability of the non-uniformity gradient values. This virtual phantom methodology primarily aims to provide a simple/robust evaluation metric in radiotherapy for MR distortion correction solutions, providing an additional/complement QA procedure to dedicated hardware phantoms, comparatively costly in time and resources. This approach is also designed to assist with an easily implementable secondary QA for validation during commissioning of distortion correction software, focusing on this feature, to better isolate and identify sources of geometric errors resulting from MR distortions.
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spelling doaj-art-cff22bb67d384ae6a922c229da41731c2025-08-20T03:47:45ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-05-011510.3389/fonc.2025.15303321530332Virtual phantom methodology for assessment of MRI distortion correction in high-precision stereotactic radiosurgery treatment planningTristan Belloeil-MarraneAdrian GutierrezMarlies BoussaerCristina TeixeiraThierry GevaertMark De RidderIntroductionThe accuracy of stereotactic treatment planning is primarily limited by the least accurate process in the whole chain of events, and is particularly important in cranial radiosurgery. Ameliorating this process can improve treatment targeting, providing additional reliability for these indications. Quality assurance (QA) in radiotherapy is often performed on the dose delivery and planning section rather than the localization. Magnetic Resonance Images (MRI) are notably subject to distortions, due to the nonlinearity of gradient fields, potentially source of geometric errors. This study aimed to analyze the impact of a patient-specific algorithm, rather than manufacturer-specific, to correct spatial distortion in cranial MRI by using a novel software-only paradigm.Material and methodsAn unbiased simulated T1-Weighted MRI validated dataset is utilized to create a synthetic CT (sCT). By introducing controlled distortion in simulated datasets, we can evaluate the influence of noise and intensity non-uniformity (“RF”) ranging from 0 to 9% noise and 0 to 40% RF. These MRIs were corrected using the sCT as base modality for distortion correction. To evaluate the impact of the distortion correction, each corrected/non-corrected image set was compared to the unbiased MRI using Root-mean-square-error (RMSE) as a full-image reference comparison metric.ResultsThe distortion correction allows for an improvement based on the RMSE correlation between baseline and distorted MRIs. The amelioration of average RMSE in corrected versus non-corrected MRI is up to 42.22% for the most distorted datasets.ConclusionThe distortion correction results show a proportional improvement with increased noise and intensity non-uniformity. This provides additional robustness and reliability to the accuracy of SRS treatment planning using MR T1-W sequences as imaging reference for target definition and organ delineation, remaining consistent independently from the variability of the non-uniformity gradient values. This virtual phantom methodology primarily aims to provide a simple/robust evaluation metric in radiotherapy for MR distortion correction solutions, providing an additional/complement QA procedure to dedicated hardware phantoms, comparatively costly in time and resources. This approach is also designed to assist with an easily implementable secondary QA for validation during commissioning of distortion correction software, focusing on this feature, to better isolate and identify sources of geometric errors resulting from MR distortions.https://www.frontiersin.org/articles/10.3389/fonc.2025.1530332/fullMRI distortion correctionstereotactic radiosurgery (SRS)cranial indicationstarget positioning accuracysynthetic CT (sCT)magnetic resonance imaging (MRI)
spellingShingle Tristan Belloeil-Marrane
Adrian Gutierrez
Marlies Boussaer
Cristina Teixeira
Thierry Gevaert
Mark De Ridder
Virtual phantom methodology for assessment of MRI distortion correction in high-precision stereotactic radiosurgery treatment planning
Frontiers in Oncology
MRI distortion correction
stereotactic radiosurgery (SRS)
cranial indications
target positioning accuracy
synthetic CT (sCT)
magnetic resonance imaging (MRI)
title Virtual phantom methodology for assessment of MRI distortion correction in high-precision stereotactic radiosurgery treatment planning
title_full Virtual phantom methodology for assessment of MRI distortion correction in high-precision stereotactic radiosurgery treatment planning
title_fullStr Virtual phantom methodology for assessment of MRI distortion correction in high-precision stereotactic radiosurgery treatment planning
title_full_unstemmed Virtual phantom methodology for assessment of MRI distortion correction in high-precision stereotactic radiosurgery treatment planning
title_short Virtual phantom methodology for assessment of MRI distortion correction in high-precision stereotactic radiosurgery treatment planning
title_sort virtual phantom methodology for assessment of mri distortion correction in high precision stereotactic radiosurgery treatment planning
topic MRI distortion correction
stereotactic radiosurgery (SRS)
cranial indications
target positioning accuracy
synthetic CT (sCT)
magnetic resonance imaging (MRI)
url https://www.frontiersin.org/articles/10.3389/fonc.2025.1530332/full
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