Quiescent frame, contrast-enhanced coronary magnetic resonance angiography reconstructed using limited number of physiologic frames from 5D free-running acquisitions.

5D whole-heart MRI Coronary MRA Free-running

Journal

Magnetic resonance imaging
ISSN: 1873-5894
Titre abrégé: Magn Reson Imaging
Pays: Netherlands
ID NLM: 8214883

Informations de publication

Date de publication:
04 Jul 2024
Historique:
received: 25 04 2024
revised: 12 06 2024
accepted: 03 07 2024
medline: 8 7 2024
pubmed: 8 7 2024
entrez: 7 7 2024
Statut: aheadofprint

Résumé

5D, free-running imaging resolves sets of 3D whole-heart images in both cardiac and respiratory dimensions. In an application such as coronary imaging when a single, static image is of interest, computationally expensive offline iterative reconstruction is still needed to compute the multiple 3D datasets. Evaluate how the number of physiologic bins included in the reconstruction affects the computational cost and resulting image quality of a single, static volume reconstruction. Retrospective. 15 pediatric patients following Ferumoxytol infusion (4 mg/kg). 1.5 T/Ungated 5D free-running GRE sequence. The raw data of each subject were binned and reconstructed into a 5D (x-y-z-cardiac-respiratory) images. 1, 3, 5, 7, and 9 bins adjacent to both sides of the retrospectively determined cardiac resting phase and 1, 3 bins adjacent to the end-expiration phase are used for limited frame reconstructions. The static volume within each limited reconstruction was compared with the corresponding full 5D reconstruction using the structural similarity index measure (SSIM). A non-linear regression model was used to fit SSIM with the percentage of data used compared to full reconstruction (% data). A linear regression model was used to fit computation time with % raw data used. Coronary artery sharpness is measured on each limited reconstructed images to determine the minimal number of cardiac and respiratory bins needed to preserve image quality. The coefficient of determination (R The % of data used in the reconstruction was linearly related to the computational time (R Reconstruction using only a limited number of acquired physiological states can linearly reduce the computational cost while preserving similarity to the full reconstruction image. It is suggested to use no less than 5 cardiac and all respiratory phases in the limited reconstruction to best preserve the original quality seen on the full reconstructed images.

Sections du résumé

BACKGROUND BACKGROUND
5D, free-running imaging resolves sets of 3D whole-heart images in both cardiac and respiratory dimensions. In an application such as coronary imaging when a single, static image is of interest, computationally expensive offline iterative reconstruction is still needed to compute the multiple 3D datasets.
PURPOSE OBJECTIVE
Evaluate how the number of physiologic bins included in the reconstruction affects the computational cost and resulting image quality of a single, static volume reconstruction.
STUDY TYPE METHODS
Retrospective.
SUBJECTS METHODS
15 pediatric patients following Ferumoxytol infusion (4 mg/kg).
FIELD STRENGTH/SEQUENCE UNASSIGNED
1.5 T/Ungated 5D free-running GRE sequence.
ASSESSMENT RESULTS
The raw data of each subject were binned and reconstructed into a 5D (x-y-z-cardiac-respiratory) images. 1, 3, 5, 7, and 9 bins adjacent to both sides of the retrospectively determined cardiac resting phase and 1, 3 bins adjacent to the end-expiration phase are used for limited frame reconstructions. The static volume within each limited reconstruction was compared with the corresponding full 5D reconstruction using the structural similarity index measure (SSIM). A non-linear regression model was used to fit SSIM with the percentage of data used compared to full reconstruction (% data). A linear regression model was used to fit computation time with % raw data used. Coronary artery sharpness is measured on each limited reconstructed images to determine the minimal number of cardiac and respiratory bins needed to preserve image quality.
STATISTICAL TESTS METHODS
The coefficient of determination (R
RESULTS RESULTS
The % of data used in the reconstruction was linearly related to the computational time (R
DATA CONCLUSION CONCLUSIONS
Reconstruction using only a limited number of acquired physiological states can linearly reduce the computational cost while preserving similarity to the full reconstruction image. It is suggested to use no less than 5 cardiac and all respiratory phases in the limited reconstruction to best preserve the original quality seen on the full reconstructed images.

Identifiants

pubmed: 38972471
pii: S0730-725X(24)00184-X
doi: 10.1016/j.mri.2024.07.008
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Auteurs

Yitong Yang (Y)

Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States.

Jackson Hair (J)

Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States.

Jérôme Yerly (J)

Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland; Center for Biomedical Imaging, Lausanne, Switzerland.

Davide Piccini (D)

Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland.

Lorenzo Di Sopra (L)

Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland; Center for Biomedical Imaging, Lausanne, Switzerland.

Aurelien Bustin (A)

Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland; Center for Biomedical Imaging, Lausanne, Switzerland.

Milan Prsa (M)

Department of Interventional Cardiology, Lausanne University Hospital, Lausanne, Switzerland.

Salim Si-Mohamed (S)

Department of Radiology, University of Claude Bernard Lyon 1., Lyon, France.

Matthias Stuber (M)

Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland; Center for Biomedical Imaging, Lausanne, Switzerland.

John N Oshinski (JN)

Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States; Department of Radiology, Emory University School of Medicine, Atlanta, GA, United States. Electronic address: jnoshin@emory.edu.

Classifications MeSH