Evidence map›Paper›PMID 36999225›Full record

ArticleNMR in biomedicine2023

Single-heartbeat cardiac cine imaging via jointly regularized nonrigid motion-corrected reconstruction.

Gastao Cruz, Kerstin Hammernik, Thomas Kuestner, Carlos Velasco, Alina Hua, Tevfik Fehmi Ismail, Daniel Rueckert, Rene Michael Botnar, Claudia Prieto

Open access · hybridAbstract read
In one paragraph

Article in NMR in biomedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 3 countries.

Gastao CruzSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.ORCID https://orcid.org/0000-0002-7397-9104
Kerstin HammernikDepartment of Computing, Imperial College London, London, UK.
Thomas KuestnerSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Carlos VelascoSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Alina HuaSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Tevfik Fehmi IsmailSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Daniel RueckertDepartment of Computing, Imperial College London, London, UK.
Rene Michael BotnarSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Claudia PrietoSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
King's College London · GBPontificia Universidad Católica de Chile · CLTUM Klinikum · DE

Funding

British Heart Foundation RG/20/1/34802Wellcome Trust
6 · The paper itself

Abstract

The aim of the current study was to develop a novel approach for 2D breath-hold cardiac cine imaging from a single heartbeat, by combining cardiac motion-corrected reconstructions and nonrigidly aligned patch-based regularization. Conventional cardiac cine imaging is obtained via motion-resolved reconstructions of data acquired over multiple heartbeats. Here, we achieve single-heartbeat cine imaging by incorporating nonrigid cardiac motion correction into the reconstruction of each cardiac phase, in conjunction with a motion-aligned patch-based regularization. The proposed Motion-Corrected CINE (MC-CINE) incorporates all acquired data into the reconstruction of each (motion-corrected) cardiac phase, resulting in a better posed problem than motion-resolved approaches. MC-CINE was compared with iterative sensitivity encoding (itSENSE) and Extra-Dimensional Golden Angle Radial Sparse Parallel (XD-GRASP) in 14 healthy subjects in terms of image sharpness, reader scoring (range: 1-5) and reader ranking (range: 1-9) of image quality, and single-slice left ventricular assessment. MC-CINE was significantly superior to both itSENSE and XD-GRASP using 20 heartbeats, two heartbeats, and one heartbeat. Iterative SENSE, XD-GRASP, and MC-CINE achieved a sharpness of 74%, 74%, and 82% using 20 heartbeats, and 53%, 66%, and 82% with one heartbeat, respectively. The corresponding results for reader scoring were 4.0, 4.7, and 4.9 with 20 heartbeats, and 1.1, 3.0, and 3.9 with one heartbeat. The corresponding results for reader ranking were 5.3, 7.3, and 8.6 with 20 heartbeats, and 1.0, 3.2, and 5.4 with one heartbeat. MC-CINE using a single heartbeat presented nonsignificant differences in image quality to itSENSE with 20 heartbeats. MC-CINE and XD-GRASP at one heartbeat both presented a nonsignificant negative bias of less than 2% in ejection fraction relative to the reference itSENSE. It was concluded that the proposed MC-CINE significantly improves image quality relative to itSENSE and XD-GRASP, enabling 2D cine from a single heartbeat.

Indexed as

cardiac MRCINEcompressed sensingmotion correctionsingle-heartbeat

Identifiers

PMID36999225
PMCPMC10909414
OpenAlexW4362458419

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.