Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing 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.
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
7 authors.
Abdullah S BdaiwiDivision of Pulmonary Medicine, Center for Pulmonary Imaging Research, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.ORCID 0000-0001-7835-7032
Matthew M WillmeringDivision of Pulmonary Medicine, Center for Pulmonary Imaging Research, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.ORCID 0000-0002-4356-9622
Riaz HussainDivision of Pulmonary Medicine, Center for Pulmonary Imaging Research, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.ORCID 0000-0003-4406-2345
Erik HysingerDivision of Pulmonary Medicine, Center for Pulmonary Imaging Research, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
Jason C WoodsDivision of Pulmonary Medicine, Center for Pulmonary Imaging Research, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
Laura L WalkupDivision of Pulmonary Medicine, Center for Pulmonary Imaging Research, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
Zackary I ClevelandDivision of Pulmonary Medicine, Center for Pulmonary Imaging Research, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.ORCID 0000-0001-6195-9061
Funding
TR&D3: Open-Source Tools for Processing Hyperpolarized MR DataP41EB013598 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Daniel B Vigneron · 2011 to 2026
$19.9M
UTE MRI to monitor CF lung disease and response to CFTR modulation in young childrenR01HL131012 · NHLBI · CINCINNATI CHILDRENS HOSP MED CTR · PI Raouf S. Amin, JASON C WOODS · 2016 to 2026
$6.8M
Using MRI To Visualize Regional Therapy Response In Idiopathic Pulmonary FibrosisR01HL126771 · NHLBI · DUKE UNIVERSITY · PI Bastiaan Driehuys · 2015 to 2026
$6.6M
Imaging and Molecular Phenotyping of Cystic Fibrosis Lung DiseaseR01HL151588 · NHLBI · CINCINNATI CHILDRENS HOSP MED CTR · PI CLEVELAND, ZACKARY I, ZIADY, ASSEM G · 2021 to 2025
$3.9M
Validating Quantitative Magnetic Resonance Imaging Biomarkers of Idiopathic Pulmonary FibrosisR01HL143011 · NHLBI · CINCINNATI CHILDRENS HOSP MED CTR · PI CLEVELAND, ZACKARY I · 2019 to 2023
$3.7M
A Phase III Trial to Validate HP 129Xe MRI as a Functional Pulmonary Biomarker in Pediatric Lung DiseaseR44HL123299 · NHLBI · POLAREAN, INC. · PI EMAMI, KIARASH · 2017 to 2019
$3.0M
Early detection of pulmonary complications of hematopoietic stem-cell transplantation in children using hyperpolarized xenon MRIR01HL166335 · NHLBI · CINCINNATI CHILDRENS HOSP MED CTR · PI Laura Lee Walkup · 2023 to 2026
$2.7M
Time-Resolved 129Xe Ventilation-Perfusion MRI in Models of Acute Lung InjuryR00HL111217 · NHLBI · CINCINNATI CHILDRENS HOSP MED CTR · PI CLEVELAND, ZACKARY I · 2015 to 2017
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.
Comparative evaluation of supervised and unsupervised deep learning strategies for denoising hyperpolarized · full record | OpenQuestion