Patient motion is an ever-present potential cause of artifacts that can limit the accuracy of diagnostic imaging. The problem is especially significant for imaging modalities such as SPECT and PET, which require the patient to remain motionless for protracted periods of time. Compensation strategies for motion that rely exclusively on the emission data itself, although commercially available, are inadequate for robust clinical usage. The goal of the proposed investigations is to determine if information from a visual-tracking-system will provide a robust compensation for patient motion as part of iterative reconstruction. By visual-trackingsystem it is meant a computational system that processes stereo-images taken by optical cameras thereby providing a source of motion information that is independent of the SPECT system. Motion of the chest and abdomen will be determined by tracking the locations of a pattern that is part of a stretchy garment wrapped about these portions of the patient. The types of patient motion for which compensation will be investigated with the visual-tracking-system are rigid-body motion, non-rigid-body motion, respiratory motion, upward-creep of the heart, and motion between sequential emission and transmission, CT or MRI imaging. The ultimate test of the success of the visual-tracking-system based compensation will be physician-observer ROC studies comparing the detection accuracy of coronary artery disease with and without motion compensation for patients undergoing SPECT perfusion imaging. The first specific aim is to perfect the visual-tracking-system and determine its accuracy for tracking rigid-body motion. The second specific aim is to modify the visual-tracking-system to include compensation for respiratory motion, and upward-creep of the heart. The third specific aim is to investigate the need for non-rigid-body motion, and whether the motion of the locations in the pattern on the garment can predict the internal motion of structures when coupled with knowledge of the individual patient's anatomy from multi-modality imaging on the same imaging bed. The fourth specific aim is to develop a motion-compensation algorithm that employs the information from the visual-tracking-system to compensate for the above motions as part of list-mode iterative reconstruction. The fifth specific aim is to determine whether the visual-tracking-system and motioncompensation algorithm are able to improve the diagnostic accuracy of cardiac-perfusion SPECT imaging as determined by human-observer ROC studies with clinical images.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB001457-05
Application #
7231336
Study Section
Diagnostic Imaging Study Section (DMG)
Program Officer
Haller, John W
Project Start
2003-06-01
Project End
2009-05-31
Budget Start
2007-06-01
Budget End
2009-05-31
Support Year
5
Fiscal Year
2007
Total Cost
$596,557
Indirect Cost
Name
University of Massachusetts Medical School Worcester
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
603847393
City
Worcester
State
MA
Country
United States
Zip Code
01655
Dasari, Paul K R; Könik, Arda; Pretorius, P Hendrik et al. (2017) Correction of hysteretic respiratory motion in SPECT myocardial perfusion imaging: Simulation and patient studies. Med Phys 44:437-450
Smyczynski, Mark S; Gifford, Howard C; Dey, Joyoni et al. (2016) LROC Investigation of Three Strategies for Reducing the Impact of Respiratory Motion on the Detection of Solitary Pulmonary Nodules in SPECT. IEEE Trans Nucl Sci 63:130-139
Smyczynski, Mark S; Gifford, Howard C; Lehovich, Andre et al. (2016) Modeling the respiratory motion of solitary pulmonary nodules and determining the impact of respiratory motion on their detection in SPECT imaging. IEEE Trans Nucl Sci 63:117-129
Pretorius, P Hendrik; Johnson, Karen L; King, Michael A (2016) Evaluation of Rigid-Body Motion Compensation in Cardiac Perfusion SPECT Employing Polar-Map Quantification. IEEE Trans Nucl Sci 63:1419-1425
Mukherjee, J M; Lindsay, C; Mukherjee, A et al. (2016) Improved frame-based estimation of head motion in PET brain imaging. Med Phys 43:2443
Dey, Joyoni; Segars, W Paul; Pretorius, P Hendrik et al. (2015) Effect of Non-Alignment/Alignment of Attenuation Map Without/With Emission Motion Correction in Cardiac SPECT/CT. IEEE Trans Nucl Sci 62:1813-1824
Dasari, Paul K R; Shazeeb, Mohammed Salman; Könik, Arda et al. (2014) Adaptation of the modified Bouc-Wen model to compensate for hysteresis in respiratory motion for the list-mode binning of cardiac SPECT and PET acquisitions: testing using MRI. Med Phys 41:112508
Könik, Arda; Connolly, Caitlin M; Johnson, Karen L et al. (2014) Digital anthropomorphic phantoms of non-rigid human respiratory and voluntary body motion for investigating motion correction in emission imaging. Phys Med Biol 59:3669-82
Dasari, Paul; Johnson, Karen; Dey, Joyoni et al. (2014) MRI Investigation of the Linkage Between Respiratory Motion of the Heart and Markers on Patient's Abdomen and Chest: Implications for Respiratory Amplitude Binning List-Mode PET and SPECT Studies. IEEE Trans Nucl Sci 61:192-201
King, Michael A; Dey, Joyoni; Johnson, Karen et al. (2013) Use of MRI to assess the prediction of heart motion with gross body motion in myocardial perfusion imaging by stereotracking of markers on the body surface. Med Phys 40:112504

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