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Image Registration to Compensate for EPI Distortion in Patients with Brain Tumors : An Evaluation of Tract-Specific Effects

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2018

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Meola, Antonio
Zhang, Fan
Kahali, Pegah
Rigolo, Laura
Tax, Chantal M. W.
Ciris, Pelin Aksit
Essayed, Walid I.
Unadkat, Prashin
O'Donnell, Lauren J.
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Journal of neuroimaging : official journal of the American Society of Neuroimaging. Wiley. 2018, 28(2), pp. 173-182. ISSN 1051-2284. eISSN 1552-6569. Available under: doi: 10.1111/jon.12485

Zusammenfassung

BACKGROUND AND PURPOSE
Diffusion magnetic resonance imaging (dMRI) provides preoperative maps of neurosurgical patients’ white matter tracts, but these maps suffer from echo‐planar imaging (EPI) distortions caused by magnetic field inhomogeneities. In clinical neurosurgical planning, these distortions are generally not corrected and thus contribute to the uncertainty of fiber tracking. Multiple image processing pipelines have been proposed for image‐registration‐based EPI distortion correction in healthy subjects. In this article, we perform the first comparison of such pipelines in neurosurgical patient data.

METHODS
Five pipelines were tested in a retrospective clinical dMRI dataset of 9 patients with brain tumors. Pipelines differed in the choice of fixed and moving images and the similarity metric for image registration. Distortions were measured in two important tracts for neurosurgery, the arcuate fasciculus and corticospinal tracts.

RESULTS
Significant differences in distortion estimates were found across processing pipelines. The most successful pipeline used dMRI baseline and T2‐weighted images as inputs for distortion correction. This pipeline gave the most consistent distortion estimates across image resolutions and brain hemispheres.

CONCLUSIONS
Quantitative results of mean tract distortions on the order of 1–2 mm are in line with other recent studies, supporting the potential need for distortion correction in neurosurgical planning. Novel results include significantly higher distortion estimates in the tumor hemisphere and greater effect of image resolution choice on results in the tumor hemisphere. Overall, this study demonstrates possible pitfalls and indicates that care should be taken when implementing EPI distortion correction in clinical settings.

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Fachgebiet (DDC)
570 Biowissenschaften, Biologie

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Diffusion tensor imaging, EPI distortion correction, image registration, neurosurgical planning, tractography

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ISO 690ALBI, Angela, Antonio MEOLA, Fan ZHANG, Pegah KAHALI, Laura RIGOLO, Chantal M. W. TAX, Pelin Aksit CIRIS, Walid I. ESSAYED, Prashin UNADKAT, Lauren J. O'DONNELL, 2018. Image Registration to Compensate for EPI Distortion in Patients with Brain Tumors : An Evaluation of Tract-Specific Effects. In: Journal of neuroimaging : official journal of the American Society of Neuroimaging. Wiley. 2018, 28(2), pp. 173-182. ISSN 1051-2284. eISSN 1552-6569. Available under: doi: 10.1111/jon.12485
BibTex
@article{Albi2018Image-49981,
  year={2018},
  doi={10.1111/jon.12485},
  title={Image Registration to Compensate for EPI Distortion in Patients with Brain Tumors : An Evaluation of Tract-Specific Effects},
  number={2},
  volume={28},
  issn={1051-2284},
  journal={Journal of neuroimaging : official journal of the American Society of Neuroimaging},
  pages={173--182},
  author={Albi, Angela and Meola, Antonio and Zhang, Fan and Kahali, Pegah and Rigolo, Laura and Tax, Chantal M. W. and Ciris, Pelin Aksit and Essayed, Walid I. and Unadkat, Prashin and O'Donnell, Lauren J.}
}
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    <dcterms:abstract xml:lang="eng">BACKGROUND AND PURPOSE&lt;br /&gt;Diffusion magnetic resonance imaging (dMRI) provides preoperative maps of neurosurgical patients’ white matter tracts, but these maps suffer from echo‐planar imaging (EPI) distortions caused by magnetic field inhomogeneities. In clinical neurosurgical planning, these distortions are generally not corrected and thus contribute to the uncertainty of fiber tracking. Multiple image processing pipelines have been proposed for image‐registration‐based EPI distortion correction in healthy subjects. In this article, we perform the first comparison of such pipelines in neurosurgical patient data.&lt;br /&gt;&lt;br /&gt;METHODS&lt;br /&gt;Five pipelines were tested in a retrospective clinical dMRI dataset of 9 patients with brain tumors. Pipelines differed in the choice of fixed and moving images and the similarity metric for image registration. Distortions were measured in two important tracts for neurosurgery, the arcuate fasciculus and corticospinal tracts.&lt;br /&gt;&lt;br /&gt;RESULTS&lt;br /&gt;Significant differences in distortion estimates were found across processing pipelines. The most successful pipeline used dMRI baseline and T2‐weighted images as inputs for distortion correction. This pipeline gave the most consistent distortion estimates across image resolutions and brain hemispheres.&lt;br /&gt;&lt;br /&gt;CONCLUSIONS&lt;br /&gt;Quantitative results of mean tract distortions on the order of 1–2 mm are in line with other recent studies, supporting the potential need for distortion correction in neurosurgical planning. Novel results include significantly higher distortion estimates in the tumor hemisphere and greater effect of image resolution choice on results in the tumor hemisphere. Overall, this study demonstrates possible pitfalls and indicates that care should be taken when implementing EPI distortion correction in clinical settings.</dcterms:abstract>
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