Sliding window reduced FOV reconstruction for real-time cardiac imaging.


Journal

Zeitschrift fur medizinische Physik
ISSN: 1876-4436
Titre abrégé: Z Med Phys
Pays: Germany
ID NLM: 100886455

Informations de publication

Date de publication:
Aug 2020
Historique:
received: 16 10 2019
revised: 11 12 2019
accepted: 07 01 2020
pubmed: 19 2 2020
medline: 21 9 2021
entrez: 19 2 2020
Statut: ppublish

Résumé

Current functional cardiovascular imaging protocols mostly rely on electrocardiogram (ECG) gating and breathholding. The resulting image quality can substantially suffer from insufficient patient cooperation or severe arrhythmia. Real-time imaging can mitigate these effects but requires highly accelerated techniques, usually relying on non-cartesian trajectories and Compressed Sensing (CS). We investigate a sliding window reduced field of view (FOV) Echo Planar Imaging (EPI) technique for real-time cardiac MRI. Segmented EPI has been combined with a subtraction technique for reducing the FOV in cardiac applications to the region of the beating heart. Residual respiratory motion, potentially impairing the image quality, has been addressed by continuous update of the static image fraction, which is derived from a low-temporal resolution sliding window reconstruction. For further acceleration, the proposed technique was combined with parallel imaging. The sliding window reduced FOV technique was proven feasible to reconstruct images of diagnostic image quality at a temporal resolution of 36.5ms per image. Semi-quantitative evaluation of image quality showed significant improvement over the existing rFOV method (p=0.039). Derived functional parameters show comparable results as with the BH-CINE reference. However, a trend to a slight underestimation of the largest and smallest in-plane volumes is observed. The proposed technique is feasible of providing real-time cardiac MRI with a temporal resolution better than 40ms without the need of computably complex reconstruction techniques.

Sections du résumé

BACKGROUND BACKGROUND
Current functional cardiovascular imaging protocols mostly rely on electrocardiogram (ECG) gating and breathholding. The resulting image quality can substantially suffer from insufficient patient cooperation or severe arrhythmia. Real-time imaging can mitigate these effects but requires highly accelerated techniques, usually relying on non-cartesian trajectories and Compressed Sensing (CS).
METHODS METHODS
We investigate a sliding window reduced field of view (FOV) Echo Planar Imaging (EPI) technique for real-time cardiac MRI. Segmented EPI has been combined with a subtraction technique for reducing the FOV in cardiac applications to the region of the beating heart. Residual respiratory motion, potentially impairing the image quality, has been addressed by continuous update of the static image fraction, which is derived from a low-temporal resolution sliding window reconstruction. For further acceleration, the proposed technique was combined with parallel imaging.
RESULTS RESULTS
The sliding window reduced FOV technique was proven feasible to reconstruct images of diagnostic image quality at a temporal resolution of 36.5ms per image. Semi-quantitative evaluation of image quality showed significant improvement over the existing rFOV method (p=0.039). Derived functional parameters show comparable results as with the BH-CINE reference. However, a trend to a slight underestimation of the largest and smallest in-plane volumes is observed.
CONCLUSION CONCLUSIONS
The proposed technique is feasible of providing real-time cardiac MRI with a temporal resolution better than 40ms without the need of computably complex reconstruction techniques.

Identifiants

pubmed: 32067862
pii: S0939-3889(20)30001-5
doi: 10.1016/j.zemedi.2020.01.001
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

236-244

Informations de copyright

Copyright © 2020. Published by Elsevier GmbH.

Auteurs

Patrick Metze (P)

Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany. Electronic address: patrick.metze@uni-ulm.de.

Hao Li (H)

Core Facility Small Animal Imaging (CF-SANI), Ulm University, Ulm, Germany. Electronic address: hao.li@uni-ulm.de.

Tobias Speidel (T)

Core Facility Small Animal Imaging (CF-SANI), Ulm University, Ulm, Germany. Electronic address: tobias.speidel@uni-ulm.de.

Dominik Buckert (D)

Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany. Electronic address: dominik.buckert@uniklinik-ulm.de.

Wolfgang Rottbauer (W)

Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany. Electronic address: wolfgang.rottbauer@uniklinik-ulm.de.

Volker Rasche (V)

Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany; Core Facility Small Animal Imaging (CF-SANI), Ulm University, Ulm, Germany. Electronic address: volker.rasche@uniklinik-ulm.de.

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