Image-guided adaptive gating of lung cancer radiotherapy: a computer simulation study

被引:11
|
作者
Aristophanous, Michalis [1 ,2 ]
Rottmann, Joerg [1 ,2 ]
Park, Sang-June [1 ,2 ]
Nishioka, Seiko [3 ]
Shirato, Hiroki [4 ]
Berbeco, Ross I. [1 ,2 ]
机构
[1] Brigham & Womens Hosp, Dana Farber Canc Inst, Dept Radiat Oncol, Boston, MA 02115 USA
[2] Harvard Univ, Sch Med, Boston, MA USA
[3] NTT Hosp, Dept Radiol, Sapporo, Hokkaido, Japan
[4] Hokkaido Univ, Sch Med, Dept Radiat Med, Sapporo, Hokkaido 060, Japan
来源
PHYSICS IN MEDICINE AND BIOLOGY | 2010年 / 55卷 / 15期
关键词
GATED RADIOTHERAPY; TUMOR TRACKING; MOTION; INTRAFRACTION; DELIVERY; KV; VERIFICATION; FEASIBILITY; PATTERN; CT;
D O I
10.1088/0031-9155/55/15/009
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The purpose of this study is to investigate the effect that image-guided adaptation of the gating window during treatment could have on the residual tumor motion, by simulating different gated radiotherapy techniques. There are three separate components of this simulation: (1) the 'Hokkaido Data', which are previously measured 3D data of lung tumor motion tracks and the corresponding 1D respiratory signals obtained during the entire ungated radiotherapy treatments of eight patients, (2) the respiratory gating protocol at our institution and the imaging performed under that protocol and (3) the actual simulation in which the Hokkaido Data are used to select tumor position information that could have been collected based on the imaging performed under our gating protocol. We simulated treatments with a fixed gating window and a gating window that is updated during treatment. The patient data were divided into different fractions, each with continuous acquisitions longer than 2 min. In accordance to the imaging performed under our gating protocol, we assume that we have tumor position information for the first 15 s of treatment, obtained from kV fluoroscopy, and for the rest of the fractions the tumor position is only available during the beam-on time from MV imaging. The gating window was set according to the information obtained from the first 15 s such that the residual motion was less than 3 mm. For the fixed gating window technique the gate remained the same for the entire treatment, while for the adaptive technique the range of the tumor motion during beam-on time was measured and used to adapt the gating window to keep the residual motion below 3 mm. The algorithm used to adapt the gating window is described. The residual tumor motion inside the gating window was reduced on average by 24% for the patients with regular breathing patterns and the difference was statistically significant (p-value = 0.01). The magnitude of the residual tumor motion depended on the regularity of the breathing pattern suggesting that image-guided adaptive gating should be combined with breath coaching. The adaptive gating window technique was able to track the exhale position of the breathing cycle quite successfully. Out of a total of 53 fractions the duty cycle was greater than 20% for 42 fractions for the fixed gating window technique and for 39 fractions for the adaptive gating window technique. The results of this study suggest that real-time updating of the gating window can result in reliably low residual tumor motion and therefore can facilitate safe margin reduction.
引用
收藏
页码:4321 / 4333
页数:13
相关论文
共 50 条
  • [1] Image-guided adaptive radiotherapy in the treatment of lung cancer patients
    Tvilum, M.
    Knap, M. Marquard
    Hoffmann, L.
    Khalil, A. Ahmed
    Lutz, C. M.
    Moller, D. Sloth
    [J]. RADIOTHERAPY AND ONCOLOGY, 2019, 133 : S177 - S177
  • [2] Image-guided radiotherapy in lung cancer
    Aboudaram, A.
    Khalifa, J.
    Massabeau, C.
    Sirrion, L.
    Henni, A. Hadj
    Thureau, S.
    [J]. CANCER RADIOTHERAPIE, 2018, 22 (6-7): : 602 - 607
  • [3] Workflow optimization of image-guided adaptive radiotherapy in lung cancer patients
    Hattu, D.
    Mannens, J.
    Van Elmpt, W.
    De Ruysscher, D.
    Ollers, M.
    [J]. RADIOTHERAPY AND ONCOLOGY, 2018, 127 : S161 - S161
  • [4] Image-guided Adaptive Radiotherapy in Cervical Cancer
    Tan, Li Tee
    Tanderup, Kari
    Kirisits, Christian
    de Leeuw, Astrid
    Nout, Remi
    Duke, Simon
    Seppenwoolde, Yvette
    Nesvacil, Nicole
    Georg, Dietmar
    Kirchheiner, Kathrin
    Fokdal, Lars
    Sturdza, Alina
    Schmid, Maximilian
    Swamidas, Jamema
    van Limbergen, Erik
    Haie-Meder, Christine
    Mahantshetty, Umesh
    Jurgenliemk-Schulz, Ina
    Lindegaard, Jacob C.
    Poetter, Richard
    [J]. SEMINARS IN RADIATION ONCOLOGY, 2019, 29 (03) : 284 - 298
  • [5] Image-guided Adaptive Radiotherapy for Bladder Cancer
    Kong, V
    Hansen, V. N.
    Hafeez, S.
    [J]. CLINICAL ONCOLOGY, 2021, 33 (06) : 350 - 368
  • [6] Image-guided radiotherapy and hypofractionation in lung cancer
    Orecchia, Roberto
    [J]. JOURNAL OF THORACIC ONCOLOGY, 2007, 2 (05) : S42 - S44
  • [7] Image-guided and adaptive radiotherapy
    Louvel, G.
    Cazoulat, G.
    Chajon, E.
    Le Maitre, A.
    Simon, A.
    Henry, O.
    Bensadoun, R. J.
    de Crevoisier, R.
    [J]. CANCER RADIOTHERAPIE, 2012, 16 (5-6): : 423 - 429
  • [8] Clinical outcome of image-guided adaptive radiotherapy in the treatment of lung cancer patients
    Tvilum, Marie
    Khalil, Azza A.
    Moller, Ditte S.
    Hoffmann, Lone
    Knap, Marianne M.
    [J]. ACTA ONCOLOGICA, 2015, 54 (09) : 1430 - 1437
  • [9] Image-guided adaptive therapy for lung cancer
    Ramsey, C
    Mahan, S
    [J]. MEDICAL PHYSICS, 2005, 32 (06) : 2125 - 2125
  • [10] Image-guided radiotherapy and motion management in lung cancer
    Gram, V.
    [J]. RADIOTHERAPY AND ONCOLOGY, 2019, 133 : S177 - S177