Respiratory motion has significant effects on abdominal and lung tumor position, and incorporation of this uncertainty
increases volumes for focal cancer treatments. Respiratory correlated CT, obtained by oversampling images throughout
the respiratory cycle based on an external surrogate, is increasingly being used for radiation therapy planning.
Respiratory correlated CT is dependant on a fixed relationship between the external surrogate and the tumor, which may
change based on weight loss, breathing pattern changes or non-respiratory motion. Moreover, the process decouples
localization of the tumor (which is the goal of tumor directed therapy) with respiratory motion management. Recently,
implantable passive transponders (Calypso Medical Technologies) have been developed which can be tracked via an
external electromagnetic array in real-time and without ionizing radiation. We aimed to integrate wireless
electromagnetic tracking with multislice CT, and create volumetric datasets that are correlated to tumor position, as
opposed to an external surrogate. We call this process 'tumor correlated CT' (TCCT). Use of these images for
treatment planning will allow localization of the tumor to predict the position of other organs during treatment delivery.
We show the preliminary work in the integration of electromagnetic tracking and CT imaging.
It is well established that respiratory motion has significant effects on lung tumor position, and incorporation of this
uncertainty increases the normal lung tissue irradiated. Respiratory correlated CT, which provides three
dimensional image sets for different phases of the breathing cycle, is increasingly being used for radiation therapy
planning. Cone beam CT is being used to obtain cross sectional imaging at the time of therapy for accurate patient
set-up. However, it is not possible to obtain cross sectional respiratory correlated imaging throughout the course of
radiation, leaving residual uncertainties. Recently, implantable passive transponders (Calypso Medical
Technologies) have been developed which are currently FDA-cleared for prostate use only and can be tracked via an
external electromagnetic array in real-time, without the use of ionizing radiation. A visualization system needs to be
developed to quickly and efficiently utilize both the dynamic real-time point measurements with the previously
acquired volumetric data. We have created such a visualization system by incorporating the respiratory correlated
imaging and the individual transponder locations into the Image Guided Surgery Toolkit (IGSTK.org). The tool
already allows quick, qualitative verification of the differences between the measured transponder position and the
imaged position at planning and will support quantitative measurements displaying uncertainty in positioning.
Three-dimensional volumetric imaging correlated with respiration (4DCT) typically utilizes external breathing
surrogates and phase-based models to determine lung tissue motion. However, 4DCT requires time consuming post-processing
and the relationship between external breathing surrogates and lung tissue motion is not clearly defined. This
study compares algorithms using external respiratory motion surrogates as predictors of internal lung motion tracked in
real-time by electromagnetic transponders (Calypso® Medical Technologies) implanted in a canine model.
Simultaneous spirometry, bellows, and transponder positions measurements were acquired during free breathing and
variable ventilation respiratory patterns. Functions of phase, amplitude, tidal volume, and airflow were examined by
least-squares regression analysis to determine which algorithm provided the best estimate of internal motion. The cosine
phase model performed the worst of all models analyzed (R2 = 31.6%, free breathing, and R2 = 14.9%, variable
ventilation). All algorithms performed better during free breathing than during variable ventilation measurements. The
5D model of tidal volume and airflow predicted transponder location better than amplitude or either of the two phasebased
models analyzed, with correlation coefficients of 66.1% and 64.4% for free breathing and variable ventilation
respectively. Real-time implanted transponder based measurements provide a direct method for determining lung tissue
location. Current phase-based or amplitude-based respiratory motion algorithms cannot as accurately predict lung tissue
motion in an irregularly breathing subject as a model including tidal volume and airflow. Further work is necessary to
quantify the long term stability of prediction capabilities using amplitude and phase based algorithms for multiple lung
tumor positions over time.
In many patients respiratory motion causes motion artifacts in CT images, thereby inhibiting precise treatment planning and lowering the ability to target radiation to tumors. The 4D Phantom, which includes a 3D stage and a 1D stage that each are capable of arbitrary motion and timing, was developed to serve as an end-to-end radiation therapy QA device that could be used throughout CT imaging, radiation therapy treatment planning, and radiation therapy delivery. The dynamic accuracy of the system was measured with a camera system. The positional error was found to be equally likely to occur in the positive and negative directions for each axis, and the stage was within 0.1 mm of the desired position 85% of the time. In an experiment designed to use the 4D Phantom's encoders to measure trial-to-trial precision of the system, the 4D Phantom reproduced the motion during variable bag ventilation of a transponder that had been bronchoscopically implanted in a canine lung. In this case, the encoder readout indicated that the stage was within 10 microns of the sent position 94% of the time and that the RMS error was 7 microns. Motion artifacts were clearly visible in 3D and respiratory-correlated (4D) CT scans of phantoms reproducing tissue motion. In 4D CT scans, apparent volume was found to be directly correlated to instantaneous velocity. The system is capable of reproducing individual patient-specific tissue trajectories with a high degree of accuracy and precision and will be useful for end-to-end radiation therapy QA.
Respiratory motion is a significant source of error in conformal radiation therapy for the thorax and upper abdomen. Four-dimensional computed tomography (4D CT) has been proposed to reduce the uncertainty caused by internal respiratory organ motion. A 4D CT dataset is retrospectively reconstructed at various stages of a respiratory cycle. An important tool for 4D treatment planning is deformable image registration. An inverse consistent image registration is used to model lung motion from one respiratory stage to another during a breathing cycle. This diffeomorphic registration jointly estimates the forward and reverse transformations providing more accurate correspondence between two images. Registration results and modeled motions in the lung are shown for three example respiratory stages. The results demonstrate that the consistent image registration satisfactorily models the large motions in the lung, providing a useful tool for 4D planning and delivering.
Issam El Naqa, Daniel Low, Gary Christensen, Parag Parikh, Joo Hyun Song, Michelle Nystrom, Wei Lu, Joseph Deasy, James Hubenschmidt, Sasha Wahab, Sasa Mutic, Anurag Singh, Jeffrey Bradley
We are developing 4D-CT to provide breathing motion information (trajectories) for radiation therapy treatment planning of lung cancer. Potential applications include optimization of intensity-modulated beams in the presence of breathing motion and intra-fraction target volume margin determination for conformal therapy. The images are acquired using a multi-slice CT scanner while the patient undergoes simultaneous quantitative spirometry. At each couch position, the CT scanner is operated in ciné mode and acquires up to 15 scans of 12 slices each. Each CT scan is associated with the measured tidal volume for retrospective reconstruction of 3D CT scans at arbitrary tidal volumes. The specific tasks of this project involves the development of automated registration of internal organ motion (trajectories) during breathing. A modified least-squares based optical flow algorithm tracks specific features of interest by modifying the eigenvalues of gradient matrix (gradient structural tensor). Good correlations between the measured motion and spirometry-based tidal volume are observed and evidence of internal hysteresis is also detected.
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