ReviewDer Radiologe2022
[Imaging of the lung using low-field magnetic resonance imaging].
Review in Der Radiologe, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed, 14 citations in OpenAlex.
- Article
- Application of artificial intelligence in lung cancer diagnosis, therapy, and prognosis.BMC medical genomics · 2026Review
- Accuracy of Ultra-Fast Low-Field MRI (0.55 T) for Lung Nodule Detection with Ultra-Short Echo Time Sequences.Tomography (Ann Arbor, Mich.) · 2025Article
- Ventilation and perfusion MRI at a 0.35 T MR-Linac: feasibility and reproducibility study.Radiation oncology (London, England) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLung magnetic resonance imaging (MRI) examinations are challenging and have not become established in the routine clinical setting. Recent developments in low-field MRI, combined with computer-assisted algorithms for acquisition and evaluation, promise new perspectives for imaging of pulmonary diseases.
objectivesThis review aims to inform about the physical advantages of low-field MRI for imaging the lungs, provide a review of the sparse literature, and present first results from a new low-field MRI scanner. MATERIALS AND
methodsThis article provides information on the physical principles, an review of the literature, and our first experiences in lung imaging on a modern 0.55 T MRI.
conclusionLow-field MRI (< 1 T) may have technical and economic advantages over higher field strength MRI in lung imaging. The physical preconditions of low-field MRI are advantageous for imaging the lungs due to reduced susceptibility effects, increased transversal relaxation times, and lower specific absorption rates. The lower investment and operating costs may enable increased availability and sustainability. Combining modern sequences and computer-based image processing may expand beyond morphological imaging by providing spatially and temporally resolved functional examinations of the lung parenchyma without ionizing radiation. In critical scenarios, like screening and short-term follow-up examinations, and patients at risk, low-field MRI may bridge the gap. These indications may include acute and chronic pulmonary diseases in pediatric patients and suspected pulmonary embolisms in pregnant women.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.