Dataset Information

Characterizing geometrical accuracy in clinically optimised 7T and 3T magnetic resonance images for high-precision radiation treatment of brain tumours.

ABSTRACT:

Background and purpose

In neuro-oncology, high spatial accuracy is needed for clinically acceptable high-precision radiation treatment planning (RTP). In this study, the clinical applicability of anatomically optimised 7-Tesla (7T) MR images for reliable RTP is assessed with respect to standard clinical imaging modalities.

Materials and methods

System- and phantom-related geometrical distortion (GD) were quantified on clinically-relevant MR sequences at 7T and 3T, and on CT images using a dedicated anthropomorphic head phantom incorporating a 3D grid-structure, creating 436 points-of-interest. Global GD was assessed by mean absolute deviation (MAD_Global). Local GD relative to the magnetic isocentre was assessed by MAD_Local. Using 3D displacement vectors of individual points-of-interest, GD maps were created. For clinically acceptable radiotherapy, 7T images need to meet the criteria for accurate dose delivery (GD < 1 mm) and present comparable GD as tolerated in clinically standard 3T MR/CT-based RTP.

Results

MAD_Global in 7T and 3T images ranged from 0.3 to 2.2 mm and 0.2-0.8 mm, respectively. MAD_Local increased with increasing distance from the isocentre, showed an anisotropic distribution, and was significantly larger in 7T MR sequences (MAD_Local = 0.2-1.2 mm) than in 3T (MAD_Local = 0.1-0.7 mm) (p < 0.05). Significant differences in GD were detected between 7T images (p < 0.001). However, maximum MAD_Local remained ≤1 mm within 68.7 mm diameter spherical volume. No significant differences in GD were found between 7T and 3T protocols near the isocentre.

Conclusions

System- and phantom-related GD remained ≤1 mm in central brain regions, suggesting that 7T MR images could be implemented in radiotherapy with clinically acceptable spatial accuracy and equally tolerated GD as in 3T MR/CT-based RTP. For peripheral regions, GD should be incorporated in safety margins for treatment uncertainties. Moreover, the effects of sequence-related factors on GD needs further investigation to obtain RTP-specific MR protocols.

SUBMITTER: Peerlings J

PROVIDER: S-EPMC7807620 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

Characterizing geometrical accuracy in clinically optimised 7T and 3T magnetic resonance images for high-precision radiation treatment of brain tumours.

Peerlings Jurgen J Compter Inge I Janssen Fiere F Wiggins Christopher J CJ Postma Alida A AA Mottaghy Felix M FM Lambin Philippe P Hoffmann Aswin L AL

Physics and imaging in radiation oncology 20190103

<h4>Background and purpose</h4>In neuro-oncology, high spatial accuracy is needed for clinically acceptable high-precision radiation treatment planning (RTP). In this study, the clinical applicability of anatomically optimised 7-Tesla (7T) MR images for reliable RTP is assessed with respect to standard clinical imaging modalities.<h4>Materials and methods</h4>System- and phantom-related geometrical distortion (GD) were quantified on clinically-relevant MR sequences at 7T and 3T, and on CT images ...[more]

PMID: 33458423

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Project description:In the recent MRI scanning, ultra-high-field (7T) MR imaging provides higher resolution and better tissue contrast compared to routine 3T MRI, which may help in more accurate and early brain diseases diagnosis. However, currently, 7T MRI scanners are more expensive and less available at clinical and research centers. These motivate us to propose a method for the reconstruction of images close to the quality of 7T MRI, called 7T-like images, from 3T MRI, to improve the quality in terms of resolution and contrast. By doing so, the post-processing tasks, such as tissue segmentation, can be done more accurately and brain tissues details can be seen with higher resolution and contrast. To do this, we have acquired a unique dataset which includes paired 3T and 7T images scanned from same subjects, and then propose a hierarchical reconstruction based on group sparsity in a novel multi-level Canonical Correlation Analysis (CCA) space, to improve the quality of 3T MR image to be 7T-like MRI. First, overlapping patches are extracted from the input 3T MR image. Then, by extracting the most similar patches from all the aligned 3T and 7T images in the training set, the paired 3T and 7T dictionaries are constructed for each patch. It is worth noting that, for the training, we use pairs of 3T and 7T MR images from each training subject. Then, we propose multi-level CCA to map the paired 3T and 7T patch sets to a common space to increase their correlations. In such space, each input 3T MRI patch is sparsely represented by the 3T dictionary and then the obtained sparse coefficients are used together with the corresponding 7T dictionary to reconstruct the 7T-like patch. Also, to have the structural consistency between adjacent patches, the group sparsity is employed. This reconstruction is performed with changing patch sizes in a hierarchical framework. Experiments have been done using 13 subjects with both 3T and 7T MR images. The results show that our method outperforms previous methods and is able to recover better structural details. Also, to place our proposed method in a medical application context, we evaluated the influence of post-processing methods such as brain tissue segmentation on the reconstructed 7T-like MR images. Results show that our 7T-like images lead to higher accuracy in segmentation of white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), and skull, compared to segmentation of 3T MR images.

Project description:BackgroundIn MRI, the signal-to-noise ratio (SNR) theoretically increases with B0 field strength. However, because of attenuation of the radiofrequency (RF) fields at 7T, it is not certain if this SNR gain can be realized for prostate imaging.Purpose/hypothesisTo investigate the SNR gain in prostate imaging at 7T as compared with 3T. It is expected that SNR will improve for prostate imaging at 7T compared with 3T.Study typeProspective.SubjectsFour healthy volunteers and one prostate cancer patient.Field strength/sequenceAll subjects were scanned at 3T and at 7T using optimal coil setups for both field strengths. For all volunteers, proton density-weighted images were acquired for SNR analysis and actual flip angle imaging (AFI) B 1 + | maps were acquired for correction of measured SNR values. In the patient, a T2 -weighted (T2 w) image was acquired at 3T and at 7T.AssessmentSNR was calculated in the prostate region for all volunteers. SNR was normalized for flip angle, receiver bandwidth, and voxel volume. SNR was also calculated for different sensitivity encoding (SENSE) acceleration factors.Statistical testingSNR values are represented as the arithmetic mean of SNR values in the prostate. Estimated SNR in the T2 w image is calculated as the arithmetic mean of the signal intensity (SI) divided by the standard deviation of the SI in a specified zone. Tumor-to-tissue contrast is calculated as (SItumor +SIzone )/( SItumor -SIzone ).ResultsAn increase in SNR ranging from 1.7-fold to 2.8-fold was measured in the prostate at 7T in comparison to 3T for four volunteers. At 7T, it is possible to achieve a 4-fold SENSE acceleration in the left-right direction with similar SNR to a nonaccelerated 3T image. T2 w imaging was done at 3T and 7T in one patient, where improved tumor-to-tissue contrast was demonstrated at 7T.Data conclusionSNR improves for prostate imaging at 7T as compared with 3T.Level of evidence2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:1446-1455.

Dataset Information

Characterizing geometrical accuracy in clinically optimised 7T and 3T magnetic resonance images for high-precision radiation treatment of brain tumours.

Background and purpose

Materials and methods

Results

Conclusions

Publications

Characterizing geometrical accuracy in clinically optimised 7T and 3T magnetic resonance images for high-precision radiation treatment of brain tumours.

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