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SU‐E‐J‐93: Development of Pre‐Contoured Human Model Library in DICOM‐RT Format for the Epidemiological Study of the Radiotherapy Patients
Author(s) -
Pyakuryal A,
Lee C,
Pelletier C,
Jung J,
Lee C
Publication year - 2015
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4924180
Subject(s) - dicom , computer science , medical imaging , software , medical physics , computer graphics (images) , radiation treatment planning , matlab , nuclear medicine , radiation therapy , medicine , artificial intelligence , radiology , operating system
Purpose: Prior to 3D conformal radiation therapy planning, patient anatomy information was mostly limited to 2D beams‐eye‐view from the conventional simulator. To analyze the outcomes of such treatments for radiation late effects, 3D computational human models are often used in commercial treatment planning systems (TPSs). However, several underlying difficulties such as time‐consuming manual delineation procedures of a large number of structures in the model have always limited its applications. Primary objective of this work was to develop a human model library for the epidemiological study by converting 3D‐surface model organs to DICOM‐RT format (DICOM‐RT structure) using an in‐house built software. We converted the ICRP reference human models to DICOM‐RT models, which can be readily adopted for various dose calculations. Methods: MATLAB based code were utilized to convert the contour drawings extracted in text‐format from the 3D graphic‐tool, Rhinoceros into DICOM‐RT structure format for 50 different organs of each model using a 16GB dual‐core processor. The conversion periods were measured for each DICOM‐RT models, and the reconstructed structure volumes were validated against the original 3D‐surface models in the TPS. Ten reference hybrid whole‐body models (8‐pediatric and 2‐adults) were automatically processed to create DICOM‐RT computational human model library. Results: Mean contour conversion period was found to be 580 (N=2) and 394.5 (N=8) seconds for 50 organs in the adult and pediatric models respectively. A good agreement for large organs (NRMSD <1.0%) and small organs (NRMSD <7.7%) was also observed between the original volumes and corresponding DICOM‐RT structure volumes of the organs. Conclusion: The ICRP reference human models were converted into DICOM‐RT format to support the epidemiological study using a large cohort of conventional radiotherapy patients. Due to its DICOM‐compatibility, the library may be implemented to many other different applications. We also expect to develop the library by including additional models in future.