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Morphometry-based measurements of the structural response to whole-brain radiation

  • D. Fuentes
  • J. Contreras
  • J. Yu
  • R. He
  • E. Castillo
  • R. Castillo
  • T. Guerrero
Original Article

Abstract

Purpose

Morphometry techniques were applied to quantify the normal tissue therapy response in patients receiving whole-brain radiation for intracranial malignancies.

Methods

Pre- and Post-irradiation magnetic resonance imaging (MRI) data sets were retrospectively analyzed in N = 15 patients. Volume changes with respect to pre-irradiation were quantitatively measured in the cerebrum and ventricles. Measurements were correlated with the time interval from irradiation. Criteria for inclusion included craniospinal irradiation, pre-irradiation MRI, at least one follow-up MRI, and no disease progression. The brain on each image was segmented to remove the skull and registered to the initial pre-treatment scan. Average volume changes were measured using morphometry analysis of the deformation Jacobian and direct template registration-based segmentation of brain structures.

Results

An average cerebral volume atrophy of \(-\)0.2 and \(-\)3 % was measured for the deformation morphometry and direct segmentation methods, respectively. An average ventricle volume dilation of 21 and 20 % was measured for the deformation morphometry and direct segmentation methods, respectively.

Conclusion

The presented study has developed an image processing pipeline for morphometric monitoring of brain tissue volume changes as a response to radiation therapy. Results indicate that quantitative morphometric monitoring is feasible and may provide additional information in assessing response.

Keywords

Image registration Radiation therapy response Morphometry Diffeomorphism Computational anatomy 

Notes

Acknowledgments

This work is supported in part by the O’Donnell Foundation and NIH DP2OD007044, NIH DP2OD007044-01S1, and CPRIT RP101502 funding mechanisms. The authors would also like to thank the open source communities ITK, ANTs [4], itk-SNAP [37], and FSL [19] for providing enabling software for image processing and visualization.

Conflict of interest

The authors have no conflicts of interest to report.

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Copyright information

© CARS 2014

Authors and Affiliations

  • D. Fuentes
    • 1
  • J. Contreras
    • 2
  • J. Yu
    • 2
  • R. He
    • 1
  • E. Castillo
    • 3
  • R. Castillo
    • 3
  • T. Guerrero
    • 2
  1. 1.Department of Imaging PhysicsThe University of Texas M.D. Anderson Cancer CenterHoustonUSA
  2. 2.Department of Radiation OncologyThe University of Texas M.D. Anderson Cancer CenterHoustonUSA
  3. 3.Department of Radiation PhysicsThe University of Texas M.D. Anderson Cancer CenterHoustonUSA

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