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    Modeling the respiratory motion of solitary pulmonary nodules and determining the impact of respiratory motion on their detection in SPECT imaging

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    Authors
    Smyczynski, Mark S.
    Gifford, Howard C.
    Lehovich, Andre
    McNamara, Joseph E.
    Segars, W. Paul
    Hoffman, Eric A.
    Tsui, Benjamin M. W.
    King, Michael A.
    UMass Chan Affiliations
    Department of Radiology
    Document Type
    Journal Article
    Publication Date
    2016-02-01
    Keywords
    SPECT data quantification and correction methods
    image generation
    image quality assessment
    simulation
    Diagnosis
    Medical Biophysics
    Nuclear
    Radiology
    
    Metadata
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    Link to Full Text
    http://dx.doi.org/10.1109/TNS.2015.2512840
    Abstract
    The objectives of this investigation were to model the respiratory motion of solitary pulmonary nodules (SPN) and then use this model to determine the impact of respiratory motion on the localization and detection of small SPN in SPECT imaging for four reconstruction strategies. The respiratory motion of SPN was based on that of normal anatomic structures in the lungs determined from breath-held CT images of a volunteer acquired at two different stages of respiration. End-expiration (EE) and time-averaged (Frame Av) non-uniform-B-spline cardiac torso (NCAT) digital-anthropomorphic phantoms were created using this information for respiratory motion within the lungs. SPN were represented as 1 cm diameter spheres which underwent linear motion during respiration between the EE and end-inspiration (EI) time points. The SIMIND Monte Carlo program was used to produce SPECT projection data simulating Tc-99m depreotide (NeoTect) imaging. The projections were reconstructed using 1) no correction (NC), 2) attenuation correction (AC), 3) resolution compensation (RC), and 4) attenuation correction, scatter correction, and resolution compensation (AC_SC_RC). A human-observer localization receiver operating characteristics (LROC) study was then performed to determine the difference in localization and detection accuracy with and without the presence of respiratory motion. The LROC comparison determined that respiratory motion degrades tumor detection for all four reconstruction strategies, thus correction for SPN motion would be expected to improve detection accuracy. The inclusion of RC in reconstruction improved detection accuracy for both EE and Frame Av over NC and AC. Also the magnitude of the impact of motion was least for AC_SC_RC.
    Source
    IEEE Trans Nucl Sci. 2016 Feb;63(1):117-129. Epub 2016 Feb 15. Link to article on publisher's site
    DOI
    10.1109/TNS.2015.2512840
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/48070
    PubMed ID
    27182079
    Related Resources
    Link to Article in PubMed
    ae974a485f413a2113503eed53cd6c53
    10.1109/TNS.2015.2512840
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