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Population of 4D Computational Phantoms for CT Imaging Research and Dosimetry CARL E RAVIN ADVANCED I M A G I N G LABORATORIES W. Paul Segars, PhD Carl E. Ravin Advanced Imaging Labs Duke University Medical Imaging Simulation Computer model of SPECT scanner Emission Computed Tomography (ECT) Myocardial SPECT Digital phantom Images reconstructed from projections Transmission Computed Tomography (TCT) Computer model of X-ray CT scanner X-ray CT Images reconstructed from projections Medical Imaging Simulation • Advantages: – Exact anatomy of the computer phantom is known providing a gold standard to evaluate and improve devices and techniques – Computer phantoms can be altered easily to model different anatomies and medical situations providing a large population of subjects from which to perform research – No need to worry about overexposing the phantom to radiation or being sued by the phantom (IRB approval not needed) 4D eXtended CArdiac-Torso (XCAT) Phantoms Segars el al, 4D XCAT phantom for multimodality imaging research, Medical Physics, vol. 37 (9), 2010 4 4D XCAT Phantom Anatomy Detailed Brain Model based on MRI 5 4D XCAT Phantom Anatomy Detail in the hands and feet Adding nervous and lymphatic systems 6 Cardiac and Respiratory Models Cardiac Model Based on 4D Tagged MRI and CT Respiratory Model Based on 4D CT 7 Imaging Simulations using the Computerized XCAT Phantoms 8 Population of 4D XCAT Phantoms • Create a population of hundreds of detailed phantoms to represent the public at large from infancy to adulthood – Optimize CT clinical applications, image quality vs. dose • Each model is based on patient CT data from Duke Database • Include cardiac and respiratory motions for 4D simulations • First library of 4D phantoms Segars el al, Population of anatomically variable 4D XCAT adult phantoms for imaging research and optimization, Medical Physics, vol. 40 (4), 2013 9 Phantom Construction • Segment CT data to define initial base anatomy for the patient • Map template to patient models using the segmented framework as a guide • Morph the template to define unsegmented structures in the target patients (blood vessels, muscles, tendons, ligaments, etc) • Check morphed phantom for anatomical accuracy 10 LDDMM Method to Map the XCAT to the Patient 11 Application of LDDMM to Create Patient-Specific Phantom 12 New XCAT Phantoms 13 58 Adult Phantoms 14 Adult Phantoms 15 42 Pediatric Phantoms 16 Pediatric Phantoms 17 Simulation of Male CT Data BMI: 21.9 BMI: 22.7 BMI: 28.5 BMI: 36.1 18 Simulation of Female CT Data BMI: 18.2 BMI: 22.3 BMI: 28.6 BMI: 35.5 19 Simulation of 4D CT Data Cardiac Model End-systole End-diastole Respiratory Model End-expiration End-inspiration 20 Accurate Dose Estimation from CT Protocols Chest Scan Abdomen Scan 21 Ultimate Goal • Create hundreds of models representing both genders with varying ages, heights, and weights encompassing the full range from pediatric to adult patients • Optimize CT clinical applications in terms of image quality versus radiation dose • Distribute the phantoms for research 22 Conclusions • The phantoms developed in this work will have a widespread use in CT imaging research to quantitatively evaluate and improve imaging devices and techniques and to investigate the effects of anatomy and motion • They can also be used to investigate patient and population-based dose correlations in CT and to enable prospective estimation of CT dose and radiation risk 23