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Spatial and Temporal Control of Hyperthermia Using Real Time Ultrasonic Thermal Strain Imaging with Motion Compensation, Phantom Study.

ABSTRACT: Mild hyperthermia has been successfully employed to induce reversible physiological changes that can directly treat cancer and enhance local drug delivery. In this approach, temperature monitoring is essential to avoid undesirable biological effects that result from thermal damage. For thermal therapies, Magnetic Resonance Imaging (MRI) has been employed to control real-time Focused Ultrasound (FUS) therapies. However, combined ultrasound imaging and therapy systems offer the benefits of simple, low-cost devices that can be broadly applied. To facilitate such technology, ultrasound thermometry has potential to reliably monitor temperature. Control of mild hyperthermia was previously achieved using a proportional-integral-derivative (PID) controller based on thermocouple measurements. Despite accurate temporal control of heating, this method is limited by the single position at which the temperature is measured. Ultrasound thermometry techniques based on exploiting the thermal dependence of acoustic parameters (such as longitudinal velocity) can be extended to create thermal maps and allow an accurate monitoring of temperature with good spatial resolution. However, in vivo applications of this technique have not been fully developed due to the high sensitivity to tissue motion. Here, we propose a motion compensation method based on the acquisition of multiple reference frames prior to treatment. The technique was tested in the presence of 2-D and 3-D physiological-scale motion and was found to provide effective real-time temperature monitoring. PID control of mild hyperthermia in presence of motion was then tested with ultrasound thermometry as feedback and temperature was maintained within 0.3°C of the requested value.

SUBMITTER: Foiret J

PROVIDER: S-EPMC4526517 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PURPOSE:Robotic stabilization of a therapeutic radiation beam with respect to a dynamically moving tumor target can be accomplished either by moving the radiation source, the patient, or both. As the treatment beam is on during this process, the primary goal is to minimize exposure of normal tissue to radiation as much as possible when moving the target back to the desired position. Due to the complex mechanical structure of 6 degree-of-freedom (6DoF) robots, it is not intuitive as to what 6 dimensional (6D) correction trajectory is optimal in achieving such a goal. With proportional-integrative-derivative (PID) and other controls, the potential exists that the controller may generate a trajectory that is highly curved, slow, or suboptimal in that it leads to unnecessary exposure of healthy tissue to radiation. This work investigates a novel feedback planning method that takes into account a robot's mechanical joint structure, patient safety tolerances, and other system constraints, and performs real-time optimization to search the entire 6D trajectory space in each time cycle so it can respond with an optimal 6D correction trajectory. METHODS:Computer simulations were created for two 6DoF robotic patient support systems: a Stewart-Gough platform for moving a patient's head in frameless maskless stereotactic radiosurgery, and a linear accelerator treatment table for moving a patient in prostate cancer radiation therapy. Motion planning was formulated as an optimization problem and solved at real-time speeds using the L-BFGS algorithm. Three planning methods were investigated, moving the platform as fast as possible (platform-D), moving the target along a straight-line (target-S), and moving the target based on the fastest descent of position error (target-D). Both synthetic motion and prior recorded human motion were used as input data and output results were analyzed. RESULTS:For randomly generated 6D step-like and sinusoidal synthetic input motion, target-D planning demonstrated the smallest net trajectory error in all cases. On average, optimal planning was found to have a 45% smaller target trajectory error than platform-D control, and a 44% smaller target trajectory error than target-S planning. For patient head motion compensation, only target-D planning was able to maintain a ?0.5mm and ?0.5deg clinical tolerance objective for 100% of the treatment time. For prostate motion, both target-S planning and target-D planning outperformed platform-D control. CONCLUSIONS:A general 6D target trajectory optimization framework for robotic patient motion compensation systems was investigated. The method was found to be flexible as it allows control over various performance requirements such as mechanical limits, velocities, acceleration, or other system control objectives.

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Spatial and Temporal Control of Hyperthermia Using Real Time Ultrasonic Thermal Strain Imaging with Motion Compensation, Phantom Study.

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