Development of an automated region of interest selection method for 3D surface monitoring of head motion

The Remove-the-Mask Open-Source head and neck Surface-Guided radiation therapy system

Background and Purpose

Surface Guided Radiotherapy (SGRT) for head and neck radiotherapy is challenging as obstructions are common and non-rigid facial motion can compromise surface accuracy. The purpose of this work was to develop and benchmark the Remove the Mask (RtM) SGRT system, an open-source system especially designed to address the challenges faced in radiotherapy of head and neck cancer.

Materials and Methods

The accuracy of the RtM SGRT system was benchmarked using a head phantom positioned on a robotic motion platform capable of sub-millimetre accuracy which was used to induce unidirectional shifts and to reproduce three real head motion traces. We also assessed the accuracy of the system in ten humans volunteers. The ground truth motion of the volunteers was obtained using a commercial motion capture system with an accuracy < 0.3 mm.

Results

The mean tracking error of the RtM SGRT system for the ten volunteers was of -0.1 ± 0.4 mm -0.6 ± 0.6 mm and 0.3 ± 0.2 mm, and 0.0 ± 0.2° 0.0 ± 0.1° and 0.0 ± 0.2° for translations and rotations along the left-right, superior-inferior and anterior-posterior axes respectively and we also found similar results in measurements with the head phantom. Forced facial motion was associated with lower tracking accuracy. The RtM SGRT system achieved submillimetre accuracy.

Conclusion

The RtM SGRT system is a low-cost, easy to build and open-source SGRT system that can achieve an accuracy that meets international commissioning guidelines. Its open-source and modular design allows for the development and easy translation of novel surface tracking techniques.

AAPM task group report 302: Surface guided radiotherapy

The clinical use of surface imaging has increased dramatically with demonstrated utility for initial patient positioning, real-time motion monitoring, and beam gating in a variety of anatomical sites. The Therapy Physics Subcommittee and the Imaging for Treatment Verification Working Group of the American Association of Physicists in Medicine commissioned Task Group 302 to review the current clinical uses of surface imaging and emerging clinical applications. The specific charge of this task group was to provide technical guidelines for clinical indications of use for general positioning, breast deep-inspiration breath-hold (DIBH) treatment, and frameless stereotactic radiosurgery (SRS). Additionally, the task group was charged with providing commissioning and on-going quality assurance (QA) requirements for surface guided radiation therapy (SGRT) as part of a comprehensive QA program including risk assessment. Workflow considerations for other anatomic sites and for computed tomography (CT) simulation, including motion management are also discussed. Finally, developing clinical applications such as stereotactic body radiotherapy (SBRT) or proton radiotherapy are presented. The recommendations made in this report, which are summarized at the end of the report, are applicable to all video-based SGRT systems available at the time of writing. Review current use of non-ionizing surface imaging functionality and commercially available systems. Summarize commissioning and on-going quality assurance (QA) requirements of surface image-guided systems, including implementation of risk or hazard assessment of surface guided radiotherapy as a part of a total quality management program (e.g., TG-100). Provide clinically relevant technical guidelines that include recommendations for the use of SGRT for general patient positioning, breast DIBH, and frameless brain SRS, including potential pitfalls to avoid when implementing this technology. Discuss emerging clinical applications of SGRT and associated QA implications based on evaluation of technology and risk assessment. This article is protected by copyright. All rights reserved.

Proposed patient motion monitoring system using feature point tracking with a web camera

Patient motion monitoring systems play an important role in providing accurate treatment dose delivery. We propose a system that utilizes a web camera (frame rate up to 30 fps, maximum resolution of 640 × 480 pixels) and an in-house image processing software (developed using Microsoft Visual C++ and OpenCV). This system is simple to use and convenient to set up. The pyramidal Lucas-Kanade method was applied to calculate motions for each feature point by analysing two consecutive frames. The image processing software employs a color scheme where the defined feature points are blue under stable (no movement) conditions and turn red along with a warning message and an audio signal (beeping alarm) for large patient movements. The initial position of the marker was used by the program to determine the marker positions in all the frames. The software generates a text file that contains the calculated motion for each frame and saves it as a compressed audio video interleave (AVI) file. We proposed a patient motion monitoring system using a web camera, which is simple and convenient to set up, to increase the safety of treatment delivery.

Feasibility of differential geometry-based features in detection of anatomical feature points on patient surfaces in range image-guided radiation therapy

PURPOSE

To investigate the feasibility of differential geometry features in the detection of anatomical feature points on a patient surface in infrared-ray-based range images in image-guided radiation therapy.

METHODS

The key technology was to reconstruct the patient surface in the range image, i.e., point distribution with three-dimensional coordinates, and characterize the geometrical shape at every point based on curvature features. The region of interest on the range image was extracted by using a template matching technique, and the range image was processed for reducing temporal and spatial noise. Next, a mathematical smooth surface of the patient was reconstructed from the range image by using a non-uniform rational B-splines model. The feature points were detected based on curvature features computed on the reconstructed surface. The framework was tested on range images acquired by a time-of-flight (TOF) camera and a Kinect sensor for two surface (texture) types of head phantoms A and B that had different anatomical geometries. The detection accuracy was evaluated by measuring the residual error, i.e., the mean of minimum Euclidean distances (MMED) between reference (ground truth) and detected feature points on convex and concave regions.

RESULTS

The MMEDs obtained using convex feature points for range images of the translated and rotated phantom A were [Formula: see text] and [Formula: see text], respectively, using the TOF camera. For the phantom B, the MMEDs of the convex and concave feature points were [Formula: see text] and [Formula: see text] mm, respectively, using the Kinect sensor. There was a statistically significant difference in the decreased MMED for convex feature points compared with concave feature points [Formula: see text].

CONCLUSIONS

The proposed framework has demonstrated the feasibility of differential geometry features for the detection of anatomical feature points on a patient surface in range image-guided radiation therapy.

Spatial and temporal performance of 3D optical surface imaging for real-time head position tracking

PURPOSE

The spatial and temporal tracking performance of a commercially available 3D optical surface imaging system is evaluated for its potential use in frameless stereotactic radiosurgery head tracking applications.

METHODS

Both 3D surface and infrared (IR) marker tracking were performed simultaneously on a head phantom mounted on an xyz motion stage and on four human subjects. To allow spatial and temporal comparison on human subjects, three points were simultaneously monitored, including the upper facial region (3D surface), a dental plate (IR markers), and upper forehead (IR markers).

RESULTS

For both static and dynamic phantom studies, the 3D surface tracker was found to have a root mean squared error (RMSE) of approximately 0.30 mm for region-of-interest (ROI) surface sizes greater than 1000 vertex points. Although, the processing period (1/fps) of the 3D surface system was found to linearly increase as a function of the number of ROI vertex points, the tracking accuracy was found to be independent of ROI size provided that the ROI was sufficiently large and contained features for registration. For human subjects, the RMSE between 3D surface tracking and IR marker tracking modalities was 0.22 mm left-right (x-axis), 0.44 mm superior-inferior (y-axis), 0.27 mm anterior-posterior (z-axis), 0.29° pitch (around x-axis), 0.18° roll (around y-axis), and 0.15° yaw (around z-axis).

CONCLUSIONS

3D surface imaging has the potential to provide submillimeter level head motion tracking. This is provided that a highly accurate camera-to-LINAC frame of reference calibration can be performed and that the reference ROI is of sufficient size and contains suitable surface features for registration.

Three-dimensional surface scanning for accurate patient positioning and monitoring during breast cancer radiotherapy

PURPOSE

Clinical evaluation of an optical three-dimensional surface scanning (3D-SS) system for patient positioning and monitoring during radiotherapy (RT) for breast cancer.

MATERIALS AND METHODS

A ceiling-mounted scanner was developed to acquire multiple 3D body surface images and tested in 14 conservatively operated breast cancer patients. A reference skin surface was derived from the planning computed tomography (CT) scan as basis for rigid registration with the surface scans. In addition to electronic portal images (EPIs), optical scans were acquired at three defined time points before and during daily RT. Patient setup was guided by laser alignments and corrected according to EPI findings. The accuracy of the 3D-SS system was validated by comparison of the optical scans to EPIs generated in parallel. Interfraction shifts were investigated by comparison of the first 3D-SS image with the reference body outline. Intrafractional motions were analysed by comparing the three daily surface scans with the first EPI.

RESULTS

Comparison of EPIs and 3D-SS images revealed good accordance (- 0.05±0.94 mm). Analysis of daily patient positions revealed average deviations of 0.4±2.4 mm laterally, 0.3±1.9 mm longitudinally and 0.2±3.3 mm vertically. After 2 weeks, a systematic interfraction shift in patient positioning was noted, particularly in the vertical direction (4.9±0.56 mm), which was attributed to patients progressively relaxing. 3D-SS images showed intrafractional shifts of 1.2±0.7 mm over a time course of 2 min.

CONCLUSION

Optical surface scanning is a simple, fast and reproducible method for breast cancer patient alignment. Particularly for more sophisticated irradiation techniques, it helps to improve accuracy in patient positioning during radiotherapy without the exposure to additional ionizing radiation.