Analysis of Intrafractional Mass Variabilities Using Deformable Image Registration Program

영상변조 프로그램을 이용한 호흡 위상 간 종양의 움직임 특성 분석

  • Cho, Jeong-Hee (Dept. of radiologic science, College of health science, Eulji University) ;
  • Kim, Joo-Hoo (Dept. of Radiation Oncology, Yonsei Cancer Center, Yonsei University Health System) ;
  • Seo, Sun-Youl (Dept. of Health Science, Eulji University Hospital) ;
  • Han, Dong-Kyoon (Dept. of radiologic science, College of health science, Eulji University)
  • 조정희 (을지대학교 보건과학대학 방사선학과) ;
  • 김주호 (연세의료원 암센터 방사선종양학과) ;
  • 서선열 (을지대학병원 영상의학과) ;
  • 한동균 (을지대학교 보건과학대학 방사선학과)
  • Received : 2012.05.09
  • Accepted : 2012.06.15
  • Published : 2012.06.30

Abstract

The aim of this study is to compare the geometric characteristics of the lung tumor, such as tumor centroid, HU change relative to breath phase, depending on tumor location and adhesion using 4DCT and deformable image registration program (MIMVista). The Y axis change was most significant and the mean Y axis centroid fluctuation was $7.32{\pm}6.88mm$ in lower lung tumor. The mean HU variation in lower lung mass has changed more than other locations, and its mean HU variation was $7.7{\pm}4.97%$ and non-adhered mass was more changed. Correlation for the mass volume between 3DCT and MIP was very high and its coefficient was 0.998. The effect of tumor location, adhesion and diaphragm excursion to geometric uncertainties was analyzed by linear regression model, it was influenced to mass deformation and geometrical variation so much except diaphragm excursion. but intra-fractional and inter-patient's uncertainties were great, so it couldn't find any exact deformation trend.

본 연구의 목적은 호흡 위상을 고려한 4DCT 자료를 토대로 자동영상변조등록 프로그램인 MIMVista에서 계산한 최대강도투영 영상에서 폐종양의 발생위치와 유착여부에 따른 종양의 움직임 특성을 분석하고 3DCT 결과 값과 비교하였으며 호흡 위상 간 종양의 도심변화 등 기하학적 변형 특성를 분석했다. 분석결과 폐하부에 위치한 종양에서 Y축으로의 평균 도심 변화가 $7.32{\pm}6.88mm$로 가장 크게 나타났으며 HU값의 차이를 분석한 결과에서도 평균 $7.7{\pm}4.97%$로 가장 큰 차이를 보였다. 유착성 종양보다는 비유착성 종양에서 호흡 간 변화가 크게 나타났다. 3DCT 영상과 MIP 영상간에 종양 용적의 연관성을 분석한 결과 상관계수가 0.998로 매우 높게 나타났다. 종양의 기하학적 변화에 영향을 미치는 요인분석결과 종양의 위치와 유착여부가 큰 영향을 미치는 것으로 분석되었으나 횡격막의 움직임 정도에 따른 차이는 없었으며 환자 간 호흡 위상에 따른 편차가 매우 크기 때문에 종양의 움직임과 관련한 특정 경향성을 파악할 수는 없었다.

Keywords

References

  1. Shimizu S, Shirato H, Ogura S, et al.: Detection of lung tumor movement in real-time tumor- tracking radiotherapy, Int J Radiat Oncol Biol Phys 51, 304-310, 2001
  2. Paul Keall; 4-Dimensional Computed Tomography Imaging and Treatment Planning, Seminars in Radiation Oncology, 14(1), 81-90, 2004 https://doi.org/10.1053/j.semradonc.2003.10.006
  3. Ackerly T, Andrews J, Ball D, et al.: Discrepancies in volume calculations between different radiotherapy treatment planning systems, Australas Phys Eng Sci Med, 26, 91-93, 2003
  4. ICRU Report 62: Prescribing, recording, and reporting photon beam therapy, Bethesda, 1999
  5. Altonen P, Brahme A, Lax I, et al.: Specification of dose delivery in radiation therapy, Recommendation by the Nordic Association of Clinical Physics (NACP), Acta Oncol, 36(Suppl 10), 132, 1997
  6. ICRU Report 50: Prescribing, recording, and reporting photon beam therapy, Bethesda, 1993
  7. I.Martel, P.Clavere, J.Labat et al.: Radiation therapy Quality Control in a Frech Multicentric Randomised Phase II Trial, Int. J. Radiation Oncology Biol. Phys., 66(3), S149, 2006
  8. R. Speight, J. Sykes, R. Lindsay et al.: The evaluation of a deformable image registration segmentation technique for semi-automating internal target volume (ITV) production from 4DCT images of lung stereotactic body radiotherapy (SBRT) patients, Radiotherapy and Oncology 98, 277-283, 2011 https://doi.org/10.1016/j.radonc.2010.12.007
  9. E. WEISS, K. WIJESOORIYA, S. V.DILL: Tumor And Normal Tissue Motion In The Thorax During Respiration: Analysis Of Volumetric And Positional Variations Using 4D Ct, Int. J. Radiation Oncology Biol. Phys., 67(1), 296-307, 2007 https://doi.org/10.1016/j.ijrobp.2006.09.009
  10. K.J.Redmond, D.Y.Song, J.L.Fox et al.: Respiratory Motion Changes Of Lung Tumors Over The Course Of Radiation Therapy Based On Respiration-Correlated Fourdimensional Computed Tomography Scans, Int. J. Radiation Oncology Biol. Phys., 75(5), 1605-1612, 2009 https://doi.org/10.1016/j.ijrobp.2009.05.024
  11. Stevens CW, Munden RF, Forster KM et al.: Respiratory driven lung tumor motion is independent of tumor size, tumor location, and pulmonary function. Int J Radiat Oncol Biol Phys., 51, 62-68, 2001
  12. Liu HH, Balter P, Tutt T, et al.: Assessing respiration- induced tumor motion and internal target volume using four-dimensional computed tomography for radiotherapy of lung cancer, Int J Radiat Oncol Biol Phys., 68, 531-540, 2007 https://doi.org/10.1016/j.ijrobp.2006.12.066
  13. GS. MAGERAS, A. PEVSNER, ED. Yorke: Measurement Of Lung Tumor Motion Using Respiration-Correlated Ct, Int. J. Radiation Oncology Biol. Phys., 60(3), 933-941, 2004 https://doi.org/10.1016/j.ijrobp.2004.06.021
  14. Mead J, Loring SH: Analysis of volume displacement and length changes of the diaphragm during breathing. J Appl Physiol., 53, 750-755, 1982 https://doi.org/10.1152/jappl.1982.53.3.750
  15. S. Gaede, G. Carnes, E. Yu et al.: The use of CT density changes at internal tissue interfaces to correlate internal organ motion with an external surrogate Phys. Med. Biol., 54, 259-273, 2009 https://doi.org/10.1088/0031-9155/54/2/006