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Original Article

Korean Journal of Medical Physics 2010; 21(2): 153-164

Published online June 25, 2010

Copyright © Korean Society of Medical Physics.

Development of the Multi-Parametric Mapping Software Based on Functional Maps to Determine the Clinical Target Volumes

임상표적체적 결정을 위한 기능 영상 기반 생물학적 인자 맵핑 소프트웨어 개발

Ji-Yeon Park*, Won-Gyun Jung*, Jeong-Woo Lee, Kyoung-Nam Lee*, Kook-Jin Ahn§, Semie Hong, Rahyeong Juh, Bo-Young Choe*, Tae-Suk Suh*

박지연*ㆍ정원균*ㆍ이정우ㆍ이경남*ㆍ안국진§ㆍ홍세미ㆍ주라형ㆍ최보영*ㆍ서태석*

*Department of Biomedical Engineering, Research Institute of Biomedical Engineering, The Catholic University of Korea, Department of the Radiation Oncology, Konkuk University Medical Center, Konkuk University School of Medicine,§Department of Radiology, Seoul St. Mary's Hospital, The Catholic University of Korea,Department of Psychiatry, University of Ulsan, Asan Medical Center, Seoul, Korea

*가톨릭대학교 의과대학 의공학교실, 가톨릭대학교 의과대학 생체의공학연구소, 건국대학교 의학전문대학원 건국대학교병원 방사선종양학교실, §가톨릭대학교 서울성모병원 영상의학과, 울산대학교 서울아산병원 정신과

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.

KeywordsRegional cerebral blood volume (rCBV) maps, Apparent diffusion coefficient (ADC) maps, Multi-functional parametric mapping, Image registration

Korean Society of Medical Physics

Vol.35 No.2
June 2024

pISSN 2508-4445
eISSN 2508-4453
Formerly ISSN 1226-5829

Frequency: Quarterly

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