Evidence map›Paper›PMID 33068288›Full record

ArticleAnnals of nuclear medicine2021

Development of a new Python-based cardiac phantom for myocardial SPECT imaging.

Osama S Hanafy, Magdy M Khalil, Ibrahim M Khater, Haitham S Mohammed

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Article in Annals of nuclear medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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4 authors.

Osama S HanafyDepartment of Biophysics, Faculty of Science, Cairo University, Cairo, Egypt.ORCID http://orcid.org/0000-0001-6539-0415
Magdy M KhalilDepartment of Physics, Faculty of Science, Helwan University, Cairo, Egypt. magdy_khalil@hotmail.com.ORCID http://orcid.org/0000-0003-2087-5229
Ibrahim M KhaterDepartment of Biophysics, Faculty of Science, Cairo University, Cairo, Egypt.
Haitham S MohammedDepartment of Biophysics, Faculty of Science, Cairo University, Cairo, Egypt.ORCID http://orcid.org/0000-0002-6055-9514

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aim of this work was to develop a digital dynamic cardiac phantom able to mimic gated myocardial perfusion single photon emission computed tomography (SPECT) images.

methodsA software code package was written to construct a cardiac digital phantom based on mathematical ellipsoidal model utilizing powerful numerical and mathematic libraries of python programing language. An ellipsoidal mathematical model was adopted to create the left ventricle geometrical volume including myocardial boundaries, left ventricular cavity, with incorporation of myocardial wall thickening and motion. Realistic myocardial count density from true patient studies was used to simulate statistical intensity variation during myocardial contraction. A combination of different levels of defect extent and severity were precisely modeled taking into consideration defect size variation during cardiac contraction. Wall thickening was also modeled taking into account the effect of partial volume.

resultsIt has been successful to build a python-based software code that is able to model gated myocardial perfusion SPECT images with variable left ventricular volumes and ejection fraction. The recent flexibility of python programming enabled us to manipulate the shape and control the functional parameters in addition to creating variable sized-defects, extents and severities in different locations. Furthermore, the phantom code also provides different levels of image filtration mimicking those filters used in image reconstruction and their influence on image quality. Defect extent and severity were found to impact functional parameter estimation in consistence to clinical examinations.

conclusionA python-based gated myocardial perfusion SPECT phantom has been successfully developed. The phantom proved to be reliable to assess cardiac software analysis tools in terms of perfusion and functional parameters. The software code is under further development and refinement so that more functionalities and features can be added.

Indexed as

HeartImage Processing, Computer-AssistedMyocardial Perfusion ImagingPhantoms, ImagingSoftwareHumansTomography, Emission-Computed, Single-PhotonCardiac SPECTLeft ventricleMathematical phantomsPythonSimulation

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.