Evaluation of the ability of the Brainlab Elements Cranial Distortion Correction algorithm to correct clinically relevant MRI distortions for cranial SRT.

Purpose: Cranial stereotactic radiotherapy (SRT) requires highly accurate lesion delineation. However, MRI can have significant inherent geometric distortions. We investigated how well the Elements Cranial Distortion Correction algorithm of Brainlab (Munich, Germany) corrects the distortions in MR i...

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Published in:Strahlentherapie und Onkologie Vol. 198; no. 10; pp. 907 - 919
Main Authors: Retif, Paul, Djibo Sidikou, Abdourahamane, Mathis, Christian, Letellier, Romain, Verrecchia-Ramos, Emilie, Dupres, Rémi, Michel, Xavier
Format: Journal Article
Published: Springer Nature Oct2022
Online Access:View this record in EBSCOhost
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      dt: Oct2022
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s00066-022-01988-1
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        atl: Evaluation of the ability of the Brainlab Elements Cranial Distortion Correction algorithm to correct clinically relevant MRI distortions for cranial SRT.
      aug:
        au:
          Retif, Paul
          Djibo Sidikou, Abdourahamane
          Mathis, Christian
          Letellier, Romain
          Verrecchia-Ramos, Emilie
          Dupres, Rémi
          Michel, Xavier
        affil: Medical Physics Unit, CHR Metz-Thionville, Metz, France
      sug:
        subj:
          Magnetic Resonance Imaging Methods
          Algorithms
          Phantoms, Imaging
          Imaging, Three-Dimensional Methods
          Tomography, X-Ray Computed
      ab: Purpose: Cranial stereotactic radiotherapy (SRT) requires highly accurate lesion delineation. However, MRI can have significant inherent geometric distortions. We investigated how well the Elements Cranial Distortion Correction algorithm of Brainlab (Munich, Germany) corrects the distortions in MR image-sets of a phantom and patients.Methods: A non-distorted reference computed tomography image-set of a CIRS Model 603-GS (CIRS, Norfolk, VA, USA) phantom was acquired. Three-dimensional T1-weighted images were acquired with five MRI scanners and reconstructed with vendor-derived distortion correction. Some were reconstructed without correction to generate heavily distorted image-sets. All MR image-sets were corrected with the Brainlab algorithm relative to the computed tomography acquisition. CIRS Distortion Check software measured the distortion in each image-set. For all uncorrected and corrected image-sets, the control points that exceeded the 0.5-mm clinically relevant distortion threshold and the distortion maximum, mean, and standard deviation were recorded. Empirical cumulative distribution functions (eCDF) were plotted. Intraclass correlation coefficient (ICC) was calculated. The algorithm was evaluated with 10 brain metastases using Dice similarity coefficients (DSC).Results: The algorithm significantly reduced mean and standard deviation distortion in all image-sets. It reduced the maximum distortion in the heavily distorted image-sets from 2.072 to 1.059 mm and the control points with > 0.5-mm distortion fell from 50.2% to 4.0%. Before and especially after correction, the eCDFs of the four repeats were visually similar. ICC was 0.812 (excellent-good agreement). The algorithm increased the DSCs for all patients and image-sets.Conclusion: The Brainlab algorithm significantly and reproducibly ameliorated MRI distortion, even with heavily distorted images. Thus, it increases the accuracy of cranial SRT lesion delineation. After further testing, this tool may be suitable for SRT of small lesions.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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