Evidence map›Paper›PMID 40522990›Full record

ArticlePloS one2025

Shortening 7T MP2RAGE acquisition with compressed sensing: Evaluating quantitative accuracy and structural consistency.

Ikuhiro Kida

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. Article
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

1 author.

Ikuhiro KidaCenter for Information and Neural Networks, National Institute of Information and Communications Technology, and Osaka University, Suita, Osaka, Japan.ORCID 0000-0001-6592-3349

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to systematically evaluate the impact of compressed sensing (CS) on acquisition time, image quality, T1 mapping accuracy, and segmentation consistency in magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) at ultra-high fields (UHF). MP2RAGE sequences were acquired using the CS and parallel imaging (PI) technique, i.e., generalized autocalibrating partially parallel acquisitions (GRAPPA), with varying undersampling factors and samples per repetition time (TR). The acquisition time, quantitative accuracy of T1 mapping, and segmentation consistency across regions of interest (ROIs) were assessed. CS-MP2RAGE achieved a 61% reduction in acquisition time (< 3 min) compared with PI-MP2RAGE and maintained comparable image quality, segmentation accuracy, and T1-mapping fidelity. Higher undersampling factors effectively reduced scan duration but introduced segmentation volume mismatches of up to 20% and increased T1 values, despite the images appearing similar to PI-MP2RAGE. Reducing the number of samples per TR enhanced image quality, allowing for higher undersampling factors without a significant loss of fidelity, a finding consistent with previous studies. However, excessively low sampling densities destabilized reconstruction in complex ROIs. Our findings demonstrate that CS-MP2RAGE significantly reduces scan time while maintaining high image quality and quantitative accuracy, making it a viable alternative to GRAPPA in UHF applications. The interplay between undersampling factors and samples per TR is crucial for optimizing scan efficiency. Future studies should explore its application in clinical and research settings.

Indexed as

BrainData CompressionImage Processing, Computer-AssistedMagnetic Resonance ImagingAlgorithmsHumansPhantoms, Imaging

Identifiers

PMID40522990
PMCPMC12169513

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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.