Accurate and precise head refixation in fractionated stereotactic radiotherapy has been achieved through alignment of real-time 3D-surface images with a reference surface image. The reference surface image is either a 3D optical surface image taken at simulation with the desired treatment position, or a CT/MRI-surface rendering in the treatment plan with corrections for patient motion during CT/MRI scans and partial volume effects. The real-time 3D surface images are rapidly captured by using a 3D video camera mounted on the ceiling of the treatment vault. Any facial expression such as mouth opening that affects surface shape and location can be avoided using a new facial monitoring technique. The image artifacts on the real-time surface can generally be removed by setting a threshold of jumps at the neighboring points while preserving detailed features of the surface of interest. Such a real-time surface image, registered in the treatment machine coordinate system, provides a reliable representation of the patient head position during the treatment. A fast automatic alignment between the real-time surface and the reference surface using a modified iterative-closest-point method leads to an efficient and robust surface-guided target refixation. Experimental and clinical results demonstrate the excellent efficacy of <2 min set-up time, the desired accuracy and precision of <1 mm in isocenter shifts, and <1 degree in rotation.
Purpose: Three‐dimensional (3D) static CT images of structures in the thorax and abdomen constantly suffer from artifacts caused by periodic respiratory motion. This study presents a novel method to correct respiratory motion for 3D CT images by correlating CT images with dynamic body surface models in which physiologic motion of body surface is recorded with the aid of a 3D video imaging system. Method and Materials: We introduce a new dynamic CT imaging technique that utilizes a commercially available high‐speed 3D camera system to gather magnitude and frequency information of respiration cycle by acquiring the motion of body surface. A dynamic body surface model is built to record 3D surface geometry and texture information at different phases of respiration cycle. Retrospective gating technique is then adopted to correlate or register CT images with the dynamic body surface model. Multiple skin markers shown on CT and video surface images are used for verification of the dynamic model. Results: In this study, motion artifacts were remarkable reduced and accurate 4D CT datasets were generated for the further use by planning systems. Conclusion: Quantifying internal anatomy motion as a function of respiration cycle is important in conformal radiotherapy, especially for lung and breast tumors. Compared to conventional 3D CT, four‐dimensional CT (4D CT) techniques present overwhelming advantage on imaging objects undergoing periodic motion. The feasibility of 4D CT techniques based on a 3D video imaging system has been demonstrated in this work. Correlating these images with the dynamic body surface models reduced respiratory motion artifacts for 3D CT images. Conflict of Interest: Partially supported by the camera company.
Purpose: to develop an accurate and precise surface‐guided target refixation through optimally mapping real‐time surface images with planning volume images. Method and Materials: An algorithm of merging the real‐time surface images captured by a video camera and the simulation‐planning volume images obtained through a CT or MR scanner is presented. The first concern is the systematic difference between CT/MRI skin contours and optic surface. The surface image artifacts are removed at the surface reconstruction by setting a limit on jumps at the neighboring facets. The partial‐volume effect and table‐patient movement in CT/MR images are corrected through comparison of the skin contours with an instant surface image without motion and partial‐volume effect. The second concern is that the skin surface is not rigid and it changes with the facial expression such as opening and closing of the mouth. To capture the consistent surface images, we have added a function of continuous monitoring of facial movement. A template‐based image registration and automatic surface alignment using a modified ICP algorithm have characterized the surface shape and landmarks' information and organize them into a reliable representation of the patient head position, which has lead to improve efficiency and robustness in surface‐guided target localization and radiation dose delivery. Results: Accuracy and precision of < 1 mm and efficacy of < 1 minute have been obtained in phantom experiments and on patients in a clinical trial. Conclusion: By using this refixation system, one can directly transform the surface images into the planned treatment position, quickly visualize the anatomical information relative to the treatment machine, and accurately detect the target positioning error in all six degrees of freedom. Conflict of Interest: Authors are either consultant or employees of the camera company.
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