Purpose: To develop and validate an automatic algorithm for the detection and functional assessment of lung tumors on three-dimensional respiratory gated PET/CT images. Method and Materials: First the algorithm will automatically segment lung regions in CT images, then identify and localize focal increases of activity in lung regions of PET images at each gated bin. Once the tumor voxels have been determined, an integration algorithm will include all the tumor counts collected at different bins within the respiratory cycle into one reference bin. Then the total activity (Bq), concentration (Bq/ml), functional volume (ml) and standard uptake values (SUV) are calculated for each tumor on PET images. Validation of the automatic algorithm was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System at Baptist Hospital of Miami. Tumor variables to be controlled were: volume, total number of counts (activity), maximum and average number of counts. These values were the gold standard to which the results of the algorithm were compared. The tumor's motion was also controlled with different respiratory periods and amplitudes. Results: Validation, feasibility and robustness of the algorithm were demonstrated. With the algorithm, the best compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become faster and more precise.
Motion artifacts have always been a non-desired effect in the field of Medical Imaging. Thus new technologies are
being investigated to ameliorate the damaging effects of image blurring caused by motion. The development of these
new technologies requires the use of phantoms as a means of precise, repeatable and controllable source of motion for
testing initial algorithms and prototypes. The objective of this project was to design a dynamic lung tumor phantom
coupled with chest motion. The phantom consists of a pair of linear actuators. The complete design, excluding the
actuators was built in house out of acrylic materials with low attenuation factors, making it ideal for PET studies. The
linear actuator is a stepper motor coupled to a lead screw which translates rotational motion into linear displacement at a
rate of 0.0254 mm/step. The system is driven by a PIC microcontroller that allows the user to select different tumor
motion parameters, and is capable of performing 3D motion. The phantom is capable of providing lung tumor and chest
position with an accuracy of 1.3 μm in the axis of motion, with a displacement of up to 52 mm and maximum velocity
of 21.59 mm/second. The design has proven to be suitable for simulating lung tumor motion in PET studies, as well as
testing motion tracking algorithms. However it can also be used in studies dealing with gated radiotherapy.
Lung cancer is the cause of more than 150,000 deaths annually in the United States. Early and accurate detection of lung
tumors with Positron Emission Tomography has enhanced lung tumor diagnosis. However, respiratory motion during the
imaging period of PET results in the reduction of accuracy of detection due to blurring of the images. Chest motion can
serve as a surrogate for tracking the motion of the tumor. For tracking chest motion, an optical laser system was designed
which tracks the motion of a patterned card placed on the chest by illuminating the pattern with two structured light
sources, generating 8 positional markers. The position of markers is used to determine the vertical, translational, and
rotational motion of the card. Information from the markers is used to decide whether the patient's breath is abnormal
compared to their normal breathing pattern. The system is developed with an inexpensive web-camera and two low-cost
laser pointers. The experiments were carried out using a dynamic phantom developed in-house, to simulate chest
movement with different amplitudes and breathing periods. Motion of the phantom was tracked by the system developed
and also by a pressure transducer for comparison. The studies showed a correlation of 96.6% between the respiratory
tracking waveforms by the two systems, demonstrating the capability of the system. Unlike the pressure transducer
method, the new system tracks motion in 3 dimensions. The developed system also demonstrates the ability to track a
sliding motion of the patient in the direction parallel to the bed and provides the potential to stop the PET scan in case of
such motion.
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