nach oben

Annals of Nuclear Medicine

Erschienen in:

17.10.2020 | Original Article

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

verfasst von: Osama S. Hanafy, Magdy M. Khalil, Ibrahim M. Khater, Haitham S. Mohammed

Erschienen in: Annals of Nuclear Medicine | Ausgabe 1/2021

Einloggen, um Zugang zu erhalten

Abstract

Purpose

The 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.

Methods

A 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.

Results

It 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.

Conclusion

A 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.

Nur mit Berechtigung zugänglich

Xu XG. An exponential growth of computational phantom research in radiation protection, imaging, and radiotherapy: a review of the fifty-year history. Phys Med Biol. 2014;59(18):R233–302.PubMedPubMedCentralCrossRef

Zaidi H, Xu XG. Computational anthropomorphic models of the human anatomy: the path to realistic Monte Carlo modeling in radiological sciences. Annu Rev Biomed Eng. 2007;9:471–500.PubMedCrossRef

Pretorius PH, King MA, Tsui BM, LaCroix KJ, Xia WA. Mathematical model of motion of the heart for use in generating source and attenuation maps for simulating emission imaging. Med Phys. 1999;26(11):2323–32.PubMedCrossRef

Könik A, Connolly CM, Johnson KL, Dasari P, Segars PW, et al. Digital anthropomorphic phantoms of non-rigid human respiratory and voluntary body motion for investigating motion correction in emission imaging. Phys Med Biol. 2014;59(14):3669–822.PubMedPubMedCentralCrossRef

Furhang EE, Chui CS, Sgouros GA. Monte Carlo approach to patient-specific dosimetry. Med Phys. 1996;23(9):1523–9.PubMedCrossRef

Bouchet LG, Bolch WE. Five pediatric head and brain mathematical models for use in internal dosimetry. J Nucl Med. 1999;40(8):1327–36.PubMed

Smith T, Petoussi-Henss N, Zankl M. Comparison of internal radiation doses estimated by MIRD and voxel techniques for a “family” of phantoms. Eur J Nucl Med. 2000;27(9):1387–98.PubMedCrossRef

Segars WP. Development and Application of the New Dynamic NURBS based Cardiac-Torso (NCAT) Phantom PhD Dissertation. Carolina: The University of North Carolina; 2001.

De Bondt P, Nichols K, Vandenberghe S, Segers P, De Winter O, et al. Validation of gated blood-pool SPECT cardiac measurements tested using a biventricular dynamic physical phantom. J Nucl Med. 2003;44(6):967–72.PubMed

10.

Khalil MM. Basic Sciences of Nuclear Medicine. London: Springer Science and Business Media; 2010.

11.

Germano G, Kiat H, Kavanagh PB, Moriel M, Mazzanti M, et al. Automatic quantification of ejection fraction from gated myocardial perfusion SPECT. J Nucl Med. 1995;36(11):2138–47.PubMed

12.

Lum DP, Coel MN. Comparison of automatic quantification software for the measurement of ventricular volume and ejection fraction in gated myocardial perfusion SPECT. Nucl Med Commun. 2003;24(3):259–66.PubMedCrossRef

13.

Segars WP, Veress AI, Sturgeon GM, Samei E. Incorporation of the living heart model into the 4D XCAT phantom for cardiac imaging research. IEEE Trans Radiat Plasma Med Sci. 2019;3(1):54–60.PubMedCrossRef

14.

Khalil MM, Attia A, Ali M, Ziada G, Omar A, Elgazzar A. Echocardiographic validation of the layer of maximum count method in the estimation of the left ventricular EF using gated myocardial perfusion SPECT: correlation with QGS, ECTb, and LVGTF. Nucl Med Commun. 2009;30(8):622–8.PubMedCrossRef

15.

Khalil MM, Elgazzar A, Khalil W, Omar A, Ziada G. Assessment of left ventricular ejection fraction by four different methods using 99mTc tetrofosmin gated SPECT in patients with small hearts: correlation with gated blood pool. Nucl Med Commun. 2005;26(10):885–93.PubMedCrossRef

16.

Severance C. Python for informatics: Exploring information. Create Space 2013.

17.

www.python.org. Accessed on 29 Dec 2019.

18.

Wentworth P, Elkner J, Downey AB, Meyers C. How to think like a computer scientist: learning with Python 3. 2012. http://openbookproject.net/thinkcs/python/english3e/. Accessed 29 Dec 2019.

19.

www.python.org. Accessed 1 Dec 2019.

20.

Van den Broek JHJM, Van den Broek MHLM. Application of an ellipsoidal heart model in studying left ventricular contractions. J Biomech. 1980;13(6):493–503.

21.

Domingues JS, Vale MD, Martinez CB. New mathematical model for the surface area of the left ventricle by the truncated prolate spheroid. Sci World J. 2017;1

22.

Khalil MM, Elgazzar A, Khalil W. Evaluation of left ventricular ejection fraction by the quantitative algorithms QGS, ECTb, LMC and LVGTF using gated myocardial perfusion SPECT: investigation of relative accuracy. Nucl Med Commun. 2006;27(4):321–32.PubMedCrossRef

23.

Gonzalez RC, Woods RE. Digital image processing. USA: Prentice Hall; 2002.

24.

Goos P, Meintrup D. Statistics with JMP: Hypothesis Tests. John Wiley and Sons, Newyork: ANOVA and Regression; 2016.

25.

Chua T, Yin LC, Thiang TH, Choo TB, Ping DZ, Leng LY. Accuracy of the automated assessment of left ventricular function with gated perfusion SPECT in the presence of perfusion defects and left ventricular dysfunction: correlation with equilibrium radionuclide ventriculography and echocardiography. J Nucl Cardiol. 2000;7(4):301–11.PubMedCrossRef

26.

Akincioglu C, Berman DS, Nishina H, Kavanagh PB, et al. Assessment of diastolic function using 16 frame 99mTc-sestamibi gated myocardial perfusion SPECT: normal values. J Nucl Med. 2005;46(7):1102–8.PubMed

27.

Yoshino T, Nakae I, Matsumoto T, Mitsunami K, Horie M. Relationship between exercise capacity and cardiac diastolic function assessed by time–volume curve from 16-frame gated myocardial perfusion SPECT. Ann Nucl Med. 2010;24(6):469–76.PubMedCrossRef

28.

Higuchi T, Taki J, Nakajima K, et al. Left ventricular ejection and filling rate measurement based on the automatic edge detection method of ECG-gated blood pool single-photon emission tomography. Ann Nucl Med. 2004;18(6):507–11.PubMedCrossRef

29.

Nakae I, Matsuo S, Tsutamoto T, Matsumoto T, Mitsunami K, Horie M. Assessment of cardiac function in patients with heart disease by quantitative gated myocardial perfusion SPECT. Ann Nucl Med. 2007;21(6):315–23.PubMedCrossRef

30.

Kenichi N, et al. Normal values and standardization of parameters in nuclear cardiology: Japanese Society of Nuclear Medicine working group database. Ann Nuclear Med. 2016;30(3):188–99.CrossRef

31.

Véra P, Manrique A, Pontvianne V, Hitzel A, Koning R, Cribier A. Thallium-gated SPECT in patients with major myocardial infarction: effect of filtering and zooming in comparison with equilibrium radionuclide imaging and left ventriculography. J Nucl Med. 1999;40(4):513–21.PubMed

32.

Hambye AS, Vervaet A, Dobbeleir A. Variability of left ventricular ejection fraction and volumes with quantitative gated SPECT: influence of algorithm, pixel size and reconstruction parameters in small and normal-sized hearts. Eur J Nucl Med Mol Imaging. 2004;31(12):1606–13.PubMedCrossRef

33.

Dorbala S, Ananthasubramaniam K, Armstrong IS, Chareonthaitawee P, DePuey EG, et al. Single photon emission computed tomography (SPECT) myocardial perfusion imaging guidelines: instrumentation, acquisition, processing, and interpretation. J Nucl Cardiol. 2018;25(5):1784–846.PubMedCrossRef

34.

Piccinelli M, Garcia EV. Advances in software for faster procedure and lower radiotracer dose myocardial perfusion imaging. Prog Cardiovasc Dis. 2015;57(6):579–87.PubMedCrossRef

35.

Slomka PJ, Patton JA, Berman DS, Germano G. Advances in technical aspects of myocardial perfusion SPECT imaging. J Nucl Cardiol. 2009;16(2):255–76.PubMedCrossRef

36.

Fung GS, Lee TS, Higuchi T, Tsui BM, Segars WP, Veress AI, Gullberg GT. Realistic simulation of regional myocardial perfusion defects for cardiac SPECT studies. IEEE Nucl Sci Symp Conf Rec. 1997;1997(2010):3061–4.

37.

Rastgou F, Shojaeifard M, Amin A, et al. Assessment of left ventricular mechanical dyssynchrony by phase analysis of gated-SPECT myocardial perfusion imaging and tissue Doppler imaging: comparison between QGS and ECTb software packages. J Nucl Cardiol. 2014;21(6):1062–71.PubMedCrossRef

Titel: Development of a new Python-based cardiac phantom for myocardial SPECT imaging
verfasst von: Osama S. Hanafy
Magdy M. Khalil
Ibrahim M. Khater
Haitham S. Mohammed
Publikationsdatum: 17.10.2020
Verlag: Springer Singapore
Erschienen in: Annals of Nuclear Medicine / Ausgabe 1/2021
Print ISSN: 0914-7187
Elektronische ISSN: 1864-6433
DOI: https://doi.org/10.1007/s12149-020-01534-y

Springer Medizin

Abstract

Purpose

Methods

Results

Conclusion

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Ausgabe 1/2021

Performance assessment of the ALBIRA II pre-clinical SPECT S102 system for 99mTc imaging

131I-MIBG negative progressive symptomatic metastatic paraganglioma: response and outcome with 177Lu-DOTATATE peptide receptor radionuclide therapy

Immune microenvironment of the gene signature reflecting the standardised uptake value on 18F-fluorodeoxyglucose positron emission tomography/computed tomography in head and neck squamous cell carcinoma

Quantitative Monte Carlo-based brain dopamine transporter SPECT imaging

Indirectly radioiodinated exendin-4 as an analytical tool for in vivo detection of glucagon-like peptide-1 receptor in a disease setting

Absorbed dose simulation of meta-211At-astato-benzylguanidine using pharmacokinetics of 131I-MIBG and a novel dose conversion method, RAP