Real-time respiration monitoring using the radiotherapy treatment beam and four-dimensional computed tomography (4DCT)—a conceptual study

• Published in: Physics in medicine & biology 2006-09, Vol.51 (18), p.4469-4495
• Main Authors: Lu, Weiguo, Ruchala, Kenneth J, Chen, Ming-Li, Chen, Quan, Olivera, Gustavo H
• Format: Article
• Language: English
• Subjects: Algorithms; Computer Simulation; Humans; Lung Neoplasms - diagnostic imaging; Lung Neoplasms - radiotherapy; Radiographic Image Enhancement - methods; Radiographic Image Interpretation, Computer-Assisted - methods; Radiotherapy Dosage; Radiotherapy Planning, Computer-Assisted - methods; Respiration; Respiratory Mechanics
• ISSN: 0031-9155; 1361-6560
• DOI: 10.1088/0031-9155/51/18/003

Real-time knowledge of intra-fraction motion, such as respiration, is essential for four-dimensional (4D) radiotherapy. Surrogate-based and internal-fiducial-based methods may suffer from one or many drawbacks such as false correlation, being invasive, delivering extra patient radiation, and requiring complicated hardware and software development and implementation. In this paper we develop a simple non-surrogate, non-invasive method to monitor respiratory motion during radiotherapy treatments in real time. This method directly utilizes the treatment beam and thus imposes no additional radiation to the patient. The method requires a pre-treatment 4DCT and a real-time detector system. The method combines off-line processes with on-line processes. The off-line processes include 4DCT imaging and pre-calculating detector signals at each phase of the 4DCT based on the planned fluence map and the detector response function. The on-line processes include measuring detector signal from the treatment beam, and correlating the measured detector signal with the pre-calculated signals. The respiration phase is determined as the position of peak correlation. We tested our method with extensive simulations based on a TomoTherapy machine and a 4DCT of a lung cancer patient. Three types of simulations were implemented to mimic the clinical situations. Each type of simulation used three different TomoTherapy delivery sinograms, each with 800 to 1000 projections, as input fluences. Three arbitrary breathing patterns were simulated and two dose levels, 2 Gy/fraction and 2 cGy/fraction, were used for simulations to study the robustness of this method against detector quantum noise. The algorithm was used to determine the breathing phases and this result was compared with the simulated breathing patterns. For the 2 Gy/fraction simulations, the respiration phases were accurately determined within one phase error in real time for most projections of the treatment, except for a few projections at the start and end of the treatment in which beam intensities were extremely low. At 2 cGy/fraction dose level, the method can still determine the respiration phase very well with less than 10% of projections having more than two phases (approximately 1 s) error. This technique can also be applied in other delivery systems such as orthogonal x-ray systems, although in those cases it would entail the delivery of additional non-treatment radiation.