Time dependence of intrafraction patient motion assessed by repeat stereoscopic imaging.

PURPOSE To quantify intrafraction patient motion and its time dependence in immobilized intracranial and extracranial patients. The data can be used to optimize the intrafraction imaging frequency and consequent patient setup correction with an image guidance and tracking system, and to establish the required safety margins in the absence of such a system. METHOD AND MATERIALS The intrafraction motion of 32 intracranial patients, immobilized with a thermoplastic mask, and 11 supine- and 14 prone-treated extracranial spine patients, immobilized with a vacuum bag, were analyzed. The motion was recorded by an X-ray, stereoscopic, image-guidance system. For each group, we calculated separately the systematic (overall mean and SD) and the random displacement as a function of elapsed intrafraction time. RESULTS The SD of the systematic intrafraction displacements increased linearly over time for all three patient groups. For intracranial-, supine-, and prone-treated patients, the SD increased to 0.8, 1.2, and 2.2 mm, respectively, in a period of 15 min. The random displacements for the prone-treated patients were significantly higher than for the other groups, namely 1.6 mm (1 SD), probably caused by respiratory motion. CONCLUSIONS Despite the applied immobilization devices, patients drift away from their initial position during a treatment fraction. These drifts are in general small if compared with conventional treatment margins, but will significantly contribute to the margin for high-precision radiation treatments with treatment times of 15 min or longer.

[1]  D A Jaffray,et al.  A radiographic and tomographic imaging system integrated into a medical linear accelerator for localization of bone and soft-tissue targets. , 1999, International journal of radiation oncology, biology, physics.

[2]  M. V. van Herk,et al.  The probability of correct target dosage: dose-population histograms for deriving treatment margins in radiotherapy. , 2000, International journal of radiation oncology, biology, physics.

[3]  J C Stroom,et al.  Inclusion of geometrical uncertainties in radiotherapy treatment planning by means of coverage probability. , 1999, International journal of radiation oncology, biology, physics.

[4]  Jean-Claude Latombe,et al.  Image-Guided Robotic Radiosurgery , 1994, Modelling and Planning for Sensor Based Intelligent Robot Systems.

[5]  Jake Van Dyk,et al.  The impact of geometric uncertainty on hypofractionated external beam radiation therapy of prostate cancer. , 2003, International journal of radiation oncology, biology, physics.

[6]  Quynh-Thu Le,et al.  Patterns of patient movement during frameless image-guided radiosurgery. , 2003, International journal of radiation oncology, biology, physics.

[7]  Mark Oldham,et al.  Cone-beam-CT guided radiation therapy: A model for on-line application. , 2005, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[8]  D. Verellen,et al.  Six dimensional analysis with daily stereoscopic x-ray imaging of intrafraction patient motion in head and neck treatments using five points fixation masks. , 2006, Medical physics.

[9]  Hilke Vorwerk,et al.  Interfractional and intrafractional accuracy during radiotherapy of gynecologic carcinomas: a comprehensive evaluation using the ExacTrac system. , 2003, International journal of radiation oncology, biology, physics.

[10]  Steven D Chang,et al.  An Analysis of the Accuracy of the CyberKnife: A Robotic Frameless Stereotactic Radiosurgical System , 2003, Neurosurgery.

[11]  Jatinder R Palta,et al.  Evaluation of intrafraction patient movement for CNS and head & neck IMRT. , 2004, Medical physics.

[12]  Joos V Lebesque,et al.  Biologic and physical fractionation effects of random geometric errors. , 2003, International journal of radiation oncology, biology, physics.

[13]  Stanley J. Rosenthal,et al.  Intra- and interfractional patient motion for a variety of immobilization devices. , 2005, Medical physics.

[14]  J. Adler,et al.  An Anthropomorphic Phantom Study of the Accuracy of CyberKnife Spinal Radiosurgery , 2004, Neurosurgery.

[15]  B. Heijmen,et al.  Analysis and reduction of 3D systematic and random setup errors during the simulation and treatment of lung cancer patients with CT-based external beam radiotherapy dose planning. , 2001, International journal of radiation oncology, biology, physics.

[16]  Joos V Lebesque,et al.  Inclusion of geometric uncertainties in treatment plan evaluation. , 2002, International journal of radiation oncology, biology, physics.