Comparison of treatment position with mask immobilization and standard diagnostic setup in intracranial MRI radiotherapy simulation

Mekiš, Vesna; Marciuš, Valerija Žager; Rogina, Dominika; Dolenc, Laura; Mekiš, Nejc

doi:10.1007/s00066-021-01776-3

Cited by 5 publications

(4 citation statements)

References 19 publications

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“…A hybrid 3-point thermoplastic mask was customized for immobilization for the CT-planning but not used for MR-planning, as the skull allows perfect CT-MR co-registration. This is supported by the literature as there is no difference in image quality or movement artifacts when comparing mask immobilization versus standard diagnostic setup [ 12 ]. All the images were kept isotropic in terms of resolution and acquired without angulation.…”

Section: Resultssupporting

confidence: 68%

Clinical implementation of magnetic resonance imaging simulation for radiation oncology planning: 5 year experience

Palhares

Lü

et al. 2023

Radiat Oncol

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Purpose Integrating magnetic resonance (MR) into radiotherapy planning has several advantages. This report details the clinical implementation of an MR simulation (MR-planning) program for external beam radiotherapy (EBRT) in one of North America's largest radiotherapy programs. Methods and materials An MR radiotherapy planning program was developed and implemented at Sunnybrook Health Sciences Center in 2016 with two dedicated wide-bore MR platforms (1.5 and 3.0 Tesla). Planning MR was sequentially implemented every 3 months for separate treatment sites, including the central nervous system (CNS), gynecologic (GYN), head and neck (HN), genitourinary (GU), gastrointestinal (GI), breast, and brachial plexus. Essential protocols and processes were detailed in this report, including clinical workflow, optimized MR-image acquisition protocols, MR-adapted patient setup, strategies to overcome risks and challenges, and an MR-planning quality assurance program. This study retrospectively reviewed simulation site data for all MR-planning sessions performed for EBRT over the past 5 years. Results From July 2016 to December 2021, 8798 MR-planning sessions were carried out, which corresponds to 25% of all computer tomography (CT) simulations (CT-planning) performed during the same period at our institution. There was a progressive rise from 80 MR-planning sessions in 2016 to 1126 in 2017, 1492 in 2018, 1824 in 2019, 2040 in 2020, and 2236 in 2021. As a result, the relative number of planning MR/CT increased from 3% of all planning sessions in 2016 to 36% in 2021. The most common site of MR-planning was CNS (49%), HN (13%), GYN (12%), GU (12%), and others (8%). Conclusion Detailed clinical processes and protocols of our MR-planning program were presented, which have been improved over more than 5 years of robust experience. Strategies to overcome risks and challenges in the implementation process are highlighted. Our work provides details that can be used by institutions interested in implementing an MR-planning program.

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Section: Resultssupporting

confidence: 68%

Clinical implementation of magnetic resonance imaging simulation for radiation oncology planning: 5 year experience

Palhares

Lü

et al. 2023

Radiat Oncol

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“…A previous study examined the automatic segmentation of brain metastases by generating synthetic CT from MRI, yet its integration into radiotherapy planning faces hurdles due to the discrepancies in patient positioning and support systems between MRI and CT scans ( 29 ). Variations in positioning devices such as RT flat tabletops, thermoplastic masks, and coil setups during MRI and CT procedures can introduce anatomical shifts, which may crucially effect brain radiotherapy in which millimeter accuracy is vital for targeting metastases and safeguarding vital structures ( 30 ). Additionally, the specialized MRI simulation equipment needed for consistent positioning is not universally accessible, particularly in resource-constrained environments, restricting synthetic CT’s widespread adoption.…”

Section: Discussionmentioning

confidence: 99%

Improved automatic segmentation of brain metastasis gross tumor volume in computed tomography images for radiotherapy: a position attention module for U-Net architecture

Wang,

Hu,

Chen

et al. 2024

Quant Imaging Med Surg

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Background Brain metastases present significant challenges in radiotherapy due to the need for precise tumor delineation. Traditional methods often lack the efficiency and accuracy required for optimal treatment planning. This paper proposes an improved U-Net model that uses a position attention module (PAM) for automated segmentation of gross tumor volumes (GTVs) in computed tomography (CT) simulation images of patients with brain metastases to improve the efficiency and accuracy of radiotherapy planning and segmentation. Methods We retrospectively collected CT simulation imaging datasets of patients with brain metastases from two centers, which were designated as the training and external validation datasets. The U-Net architecture was enhanced by incorporating a PAM into the transition layer, which improved the automated segmentation capability of the U-Net model. With cross-entropy loss employed as the loss function, the samples from the training dataset underwent training. The model’s segmentation performance on the external validation dataset was assessed using metrics including the Dice similarity coefficient (DSC), intersection over union (IoU), accuracy, sensitivity, specificity, Matthews correlation coefficient (MCC), and Hausdorff distance (HD). Results The proposed automated segmentation model demonstrated promising performance on the external validation dataset, achieving a DSC of 0.753±0.172. In terms of evaluation metrics (including the DSC, IoU, accuracy, sensitivity, MCC, and HD), the model outperformed the standard U-Net, which had a DSC of 0.691±0.142. The proposed model produced segmentation results that were closer to the ground truth and could reveal more detailed features of brain metastases. Conclusions The PAM-improved U-Net model offers considerable advantages in the automated segmentation of the GTV in CT simulation images for patients with brain metastases. Its superior performance in comparison with the standard U-Net model supports its potential for streamlining and improving the accuracy of radiotherapy. With its ability to produce segmentation results consistent with the ground truth, the proposed model holds promise for clinical adoption and provides a reference for radiation oncologists to make more informed GTV segmentation decisions.

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“…While magnetic resonance imaging (MRI) for target delineation in brain tumors was introduced many decades ago [16,[38][39][40], the signi cance of pretreatment MR imaging for treatment outcomes is recently becoming recognized more widely [41][42][43][44][45][46]. In 2015, Seymour et al were the rst to demonstrate the prognostic signi cance of the time interval between planning MRI and SRS for subsequent local control.…”

Section: Discussionmentioning

confidence: 99%

MRI distortion correction is associated with improved local control in stereotactic radiotherapy for brain metastases

Höfler,

Grigo,

Siavosch

et al. 2024

Preprint

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Distortions in brain MRI caused by gradient nonlinearities may reach several millimeters, thus distortion correction is strongly recommended for radiotherapy treatment planning. However, the significance of MRI distortion correction on actual clinical outcomes has not been described yet. Therefore we investigated the impact of planning MRI distortion correction on subsequent local control in an historic series of 419 brain metastases in 189 patients treated with stereotactic radiotherapy between 01/2003–04/2015. Local control was evaluated using a volumetric extension of the RANO-BM criteria. The prognostic significance of distortion correction was assessed using competing risk analysis. In this cohort, 2D distortion-corrected MRIs had been used for treatment planning in 52.5% (220/419) of lesions, while uncorrected MRIs had been employed in 47.5% (199/419) of metastases. 2D distortion correction was associated with improved local control (Cumulative incidence of local progression at 12 months: 14.3% vs. 21.2% and at 24 months: 18.7% vs. 28.6%, p = 0.038). In multivariate analysis, adjusting for histology, baseline tumor volume, interval between MRI and treatment delivery, year of planning MRI, biologically effective dose and adjuvant Whole-brain radiotherapy, use of distortion correction remained significantly associated with improved local control (HR 0.55, p = 0.020). This is the first study to clinically evaluate the impact of MRI gradient nonlinearity distortion correction on local control in stereotactic radiotherapy for brain metastases. In this historic series, we found significantly higher local control when using 2D corrected vs. uncorrected MRI studies for treatment planning. These results stress the importance of assuring that MR images used for radiotherapy treatment planning are properly distortion-corrected.

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Comparison of treatment position with mask immobilization and standard diagnostic setup in intracranial MRI radiotherapy simulation

Cited by 5 publications

References 19 publications

Clinical implementation of magnetic resonance imaging simulation for radiation oncology planning: 5 year experience

Clinical implementation of magnetic resonance imaging simulation for radiation oncology planning: 5 year experience

Improved automatic segmentation of brain metastasis gross tumor volume in computed tomography images for radiotherapy: a position attention module for U-Net architecture

MRI distortion correction is associated with improved local control in stereotactic radiotherapy for brain metastases

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