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Development of a dedicated 3D printed myocardial perfusion phantom: proof-of-concept in dynamic SPECT.

Authors :
Kamphuis ME
de Vries GJ
Kuipers H
Saaltink M
Verschoor J
Greuter MJW
Slart RHJA
Slump CH
Source :
Medical & biological engineering & computing [Med Biol Eng Comput] 2022 Jun; Vol. 60 (6), pp. 1541-1550. Date of Electronic Publication: 2022 Jan 19.
Publication Year :
2022

Abstract

We aim to facilitate phantom-based (ground truth) evaluation of dynamic, quantitative myocardial perfusion imaging (MPI) applications. Current MPI phantoms are static representations or lack clinical hard- and software evaluation capabilities. This proof-of-concept study demonstrates the design, realisation and testing of a dedicated cardiac flow phantom. The 3D printed phantom mimics flow through a left ventricular cavity (LVC) and three myocardial segments. In the accompanying fluid circuit, tap water is pumped through the LVC and thereafter partially directed to the segments using adjustable resistances. Regulation hereof mimics perfusion deficit, whereby flow sensors serve as reference standard. Seven phantom measurements were performed while varying injected activity of <superscript>99m</superscript> Tc-tetrofosmin (330-550 MBq), cardiac output (1.5-3.0 L/min) and myocardial segmental flows (50-150 mL/min). Image data from dynamic single photon emission computed tomography was analysed with clinical software. Derived time activity curves were reproducible, showing logical trends regarding selected input variables. A promising correlation was found between software computed myocardial flows and its reference ([Formula: see text]=ā€‰-ā€‰0.98; pā€‰=ā€‰0.003). This proof-of-concept paper demonstrates we have successfully measured first-pass LV flow and myocardial perfusion in SPECT-MPI using a novel, dedicated, myocardial perfusion phantom. This proof-of-concept study focuses on the development of a novel, dedicated myocardial perfusion phantom, ultimately aiming to contribute to the evaluation of quantitative myocardial perfusion imaging applications.<br /> (© 2022. The Author(s).)

Details

Language :
English
ISSN :
1741-0444
Volume :
60
Issue :
6
Database :
MEDLINE
Journal :
Medical & biological engineering & computing
Publication Type :
Academic Journal
Accession number :
35048275
Full Text :
https://doi.org/10.1007/s11517-021-02490-z