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dc.contributor.authorSmyczynski, Mark S.
dc.contributor.authorGifford, Howard C.
dc.contributor.authorLehovich, Andre
dc.contributor.authorMcNamara, Joseph E.
dc.contributor.authorSegars, W. Paul
dc.contributor.authorHoffman, Eric A.
dc.contributor.authorTsui, Benjamin M. W.
dc.contributor.authorKing, Michael A.
dc.date2022-08-11T08:10:46.000
dc.date.accessioned2022-08-23T17:19:25Z
dc.date.available2022-08-23T17:19:25Z
dc.date.issued2016-02-01
dc.date.submitted2016-07-12
dc.identifier.citationIEEE Trans Nucl Sci. 2016 Feb;63(1):117-129. Epub 2016 Feb 15. <a href="http://dx.doi.org/10.1109/TNS.2015.2512840">Link to article on publisher's site</a>
dc.identifier.issn0018-9499 (Linking)
dc.identifier.doi10.1109/TNS.2015.2512840
dc.identifier.pmid27182079
dc.identifier.urihttp://hdl.handle.net/20.500.14038/48070
dc.description.abstractThe 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.
dc.language.isoen_US
dc.relation<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=27182079&dopt=Abstract">Link to Article in PubMed</a>
dc.relation.urlhttp://dx.doi.org/10.1109/TNS.2015.2512840
dc.subjectSPECT data quantification and correction methods
dc.subjectimage generation
dc.subjectimage quality assessment
dc.subjectsimulation
dc.subjectDiagnosis
dc.subjectMedical Biophysics
dc.subjectNuclear
dc.subjectRadiology
dc.titleModeling the respiratory motion of solitary pulmonary nodules and determining the impact of respiratory motion on their detection in SPECT imaging
dc.typeJournal Article
dc.source.journaltitleIEEE transactions on nuclear science
dc.source.volume63
dc.source.issue1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/radiology_pubs/175
dc.identifier.contextkey8826542
html.description.abstract<p>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.</p>
dc.identifier.submissionpathradiology_pubs/175
dc.contributor.departmentDepartment of Radiology
dc.source.pages117-129


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