Evidence map›Paper›PMID 37382801›Full record

ArticleRadiological physics and technology2023

Compressed sensing reconstruction shortens the acquisition time for myocardial perfusion imaging: a simulation study.

Mitsuha Fukami, Norikazu Matsutomo, Takeyuki Hashimoto, Tomoaki Yamamoto, Masayuki Sasaki

Abstract read
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Article in Radiological physics and technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Mitsuha FukamiDepartment of Medical Radiological Technology, Faculty of Health Sciences, Kyorin University, 5-4-1 Shimorenjaku, Mitaka-shi, Tokyo, 181-8612, Japan. mitsuha-f@ks.kyorin-u.ac.jp.
Norikazu MatsutomoDepartment of Medical Radiological Technology, Faculty of Health Sciences, Kyorin University, 5-4-1 Shimorenjaku, Mitaka-shi, Tokyo, 181-8612, Japan.
Takeyuki HashimotoDepartment of Medical Radiological Technology, Faculty of Health Sciences, Kyorin University, 5-4-1 Shimorenjaku, Mitaka-shi, Tokyo, 181-8612, Japan.
Tomoaki YamamotoDepartment of Medical Radiological Technology, Faculty of Health Sciences, Kyorin University, 5-4-1 Shimorenjaku, Mitaka-shi, Tokyo, 181-8612, Japan.
Masayuki SasakiDepartment of Medical Quantum Science, Faculty of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka-shi, Fukuoka, 812-8582, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Compressed sensing (CS) has been used to improve image quality in single-photon emission tomography (SPECT) imaging. However, the effects of CS on image quality parameters in myocardial perfusion imaging (MPI) have not been investigated in detail. This preliminary study aimed to compare the performance of CS-iterative reconstruction (CS-IR) with filtered back-projection (FBP) and maximum likelihood expectation maximization (ML-EM) on their ability to reduce the acquisition time of MPI. A digital phantom that mimicked the left ventricular myocardium was created. Projection images with 120 and 30 directions (360°), and with 60 and 15 directions (180°) were generated. The SPECT images were reconstructed using FBP, ML-EM, and CS-IR. The coefficient of variation (CV) for the uniformity of myocardial accumulation, septal wall thickness, and contrast ratio (Contrast) of the defect/normal lateral wall were calculated for evaluation. The simulation was performed ten times. The CV of CS-IR was lower than that of FBP and ML-EM in both 360° and 180° acquisitions. The septal wall thickness of CS-IR at the 360° acquisition was inferior to that of ML-EM, with a difference of 2.5 mm. Contrast did not differ between ML-EM and CS-IR for the 360° and 180° acquisitions. The CV for the quarter-acquisition time in CS-IR was lower than that for the full-acquisition time in the other reconstruction methods. CS-IR has the potential to reduce the acquisition time of MPI.

Indexed as

Image Processing, Computer-AssistedMyocardial Perfusion ImagingAlgorithmsMyocardiumPerfusionPhantoms, ImagingTomography, Emission-Computed, Single-PhotonTomography, X-Ray ComputedAcquisition time reductionCompressed sensingMyocardial perfusion imageReconstruction methodsTotal variation

Identifiers

PMID37382801

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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.