Abstract
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.
Purpose: Morphometry techniques were applied to quantify the normal tissue therapy response in patients receiving whole-brain radiation for intracranial malignancies.
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.
Original language | English (US) |
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Pages (from-to) | 393-401 |
Number of pages | 9 |
Journal | International Journal of Computer Assisted Radiology and Surgery |
Volume | 10 |
Issue number | 4 |
DOIs | |
State | Published - Apr 1 2015 |
Externally published | Yes |
Keywords
- Computational anatomy
- Diffeomorphism
- Image registration
- Morphometry
- Radiation therapy response
ASJC Scopus subject areas
- Surgery
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging
- Computer Vision and Pattern Recognition
- Computer Science Applications
- Health Informatics
- Computer Graphics and Computer-Aided Design