Evidence map›Paper›PMID 35980455›Full record

ArticleStrahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]2022

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

Paul Retif, Abdourahamane Djibo Sidikou, Christian Mathis, Romain Letellier, Emilie Verrecchia-Ramos, Rémi Dupres, Xavier Michel

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Article in Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al], 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  4. [Spherical measurement-based analysis of gradient nonlinearity in magnetic resonance imaging].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Paul RetifMedical Physics Unit, CHR Metz-Thionville, Metz, France. p.retif@chr-metz-thionville.fr.ORCID http://orcid.org/0000-0003-4997-2620
Abdourahamane Djibo SidikouMedical Physics Unit, CHR Metz-Thionville, Metz, France.
Christian MathisMedical Imaging Department, CHR Metz-Thionville, Metz, France.
Romain LetellierMedical Physics Unit, CHR Metz-Thionville, Metz, France.
Emilie Verrecchia-RamosMedical Physics Unit, CHR Metz-Thionville, Metz, France.
Rémi DupresMedical Imaging Department, CHR Metz-Thionville, Metz, France.
Xavier MichelRadiation Therapy Department, CHR Metz-Thionville, Metz, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeCranial 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.

methodsA 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).

resultsThe 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.

conclusionThe 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.

Indexed as

AlgorithmsMagnetic Resonance ImagingHumansImaging, Three-DimensionalPhantoms, ImagingTomography, X-Ray ComputedCranial SRTImage registrationIntracranial metastasesMRI distortionRadiotherapy

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.