Evidence map›Paper›PMID 37799087›Full record

ArticleMagnetic resonance in medicine2024

HyperSLICE: HyperBand optimized spiral for low-latency interactive cardiac examination.

Olivier Jaubert, Javier Montalt-Tordera, Daniel Knight, Simon Arridge, Jennifer Steeden, Vivek Muthurangu

Open access · hybridAbstract read
In one paragraph

Article in Magnetic resonance in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

6 citing papers in PubMed, 9 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

6 authors at 3 institutions in 1 country.

Olivier JaubertUCL Center for Translational Cardiovascular Imaging, University College London, London, UK.ORCID 0000-0002-7854-4150
Javier Montalt-TorderaUCL Center for Translational Cardiovascular Imaging, University College London, London, UK.
Daniel KnightUCL Center for Translational Cardiovascular Imaging, University College London, London, UK.
Simon ArridgeDepartment of Computer Science, University College London, London, UK.
Jennifer SteedenUCL Center for Translational Cardiovascular Imaging, University College London, London, UK.ORCID 0000-0002-9792-2022
Vivek MuthuranguUCL Center for Translational Cardiovascular Imaging, University College London, London, UK.
The London College · GBRoyal Free London NHS Foundation Trust · GBUniversity College London · GB

Funding

British Heart Foundation NH/18/1/33511British Heart Foundation PG/17/6/32797Medical Research Council MR/S032290/1
6 · The paper itself

Abstract

purposeInteractive cardiac MRI is used for fast scan planning and MR-guided interventions. However, the requirement for real-time acquisition and near-real-time visualization constrains the achievable spatio-temporal resolution. This study aims to improve interactive imaging resolution through optimization of undersampled spiral sampling and leveraging of deep learning for low-latency reconstruction (deep artifact suppression).

methodsA variable density spiral trajectory was parametrized and optimized via HyperBand to provide the best candidate trajectory for rapid deep artifact suppression. Training data consisted of 692 breath-held CINEs. The developed interactive sequence was tested in simulations and prospectively in 13 subjects (10 for image evaluation, 2 during catheterization, 1 during exercise). In the prospective study, the optimized framework-HyperSLICE- was compared with conventional Cartesian real-time and breath-hold CINE imaging in terms quantitative and qualitative image metrics. Statistical differences were tested using Friedman chi-squared tests with post hoc Nemenyi test (p < 0.05).

resultsIn simulations the normalized RMS error, peak SNR, structural similarity, and Laplacian energy were all statistically significantly higher using optimized spiral compared to radial and uniform spiral sampling, particularly after scan plan changes (structural similarity: 0.71 vs. 0.45 and 0.43). Prospectively, HyperSLICE enabled a higher spatial and temporal resolution than conventional Cartesian real-time imaging. The pipeline was demonstrated in patients during catheter pull back, showing sufficiently fast reconstruction for interactive imaging.

conclusionHyperSLICE enables high spatial and temporal resolution interactive imaging. Optimizing the spiral sampling enabled better overall image quality and superior handling of image transitions compared with radial and uniform spiral trajectories.

Indexed as

Image Processing, Computer-AssistedMagnetic Resonance Imaging, CineBreath HoldingHumansMagnetic Resonance ImagingProspective Studiescardiac MRIdeep learningimage reconstructioninterventionalreal-time

Identifiers

PMID37799087
PMCPMC10953456
OpenAlexW4387392658

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Registered trials

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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.