Korean J Med Phys.
2010 Jun;21(2):153-164.
Development of the Multi-Parametric Mapping Software Based on Functional Maps to Determine the Clinical Target Volumes
- Affiliations
-
- 1Department of Biomedical Engineering, The Catholic University of Korea, Seoul, Korea. suhsanta@catholic.ac.kr
- 2Research Institute of Biomedical Engineering, The Catholic University of Korea, Seoul, Korea.
- 3Department of the Radiation Oncology, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Korea.
- 4Department of Radiology, Seoul St. Mary's Hospital, The Catholic University of Korea, Seoul, Korea.
- 5Department of Psychiatry, University of Ulsan, Asan Medical Center, Seoul, Korea.
Abstract
- To determine the clinical target volumes considering vascularity and cellularity of tumors, the software was developed for mapping of the analyzed biological clinical target volumes on anatomical images using regional cerebral blood volume (rCBV) maps and apparent diffusion coefficient (ADC) maps. The program provides the functions for integrated registrations using mutual information, affine transform and non-rigid registration. The registration accuracy is evaluated by the calculation of the overlapped ratio of segmented bone regions and average distance difference of contours between reference and registered images. The performance of the developed software was tested using multimodal images of a patient who has the residual tumor of high grade gliomas. Registration accuracy of about 74% and average 2.3 mm distance difference were calculated by the evaluation method of bone segmentation and contour extraction. The registration accuracy can be improved as higher as 4% by the manual adjustment functions. Advanced MR images are analyzed using color maps for rCBV maps and quantitative calculation based on region of interest (ROI) for ADC maps. Then, multi-parameters on the same voxels are plotted on plane and constitute the multi-functional parametric maps of which x and y axis representing rCBV and ADC values. According to the distributions of functional parameters, tumor regions showing the higher vascularity and cellularity are categorized according to the criteria corresponding malignant gliomas. Determined volumes reflecting pathological and physiological characteristics of tumors are marked on anatomical images. By applying the multi-functional images, errors arising from using one type of image would be reduced and local regions representing higher probability as tumor cells would be determined for radiation treatment plan. Biological tumor characteristics can be expressed using image registration and multi-functional parametric maps in the developed software. The software can be considered to delineate clinical target volumes using advanced MR images with anatomical images.
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