Evidence map›Paper›PMID 40459830›Full record

ArticleJournal of neuro-oncology2025

Super-resolution sodium MRI of human gliomas at 3T using physics-based generative artificial intelligence.

Catalina Raymond, Jingwen Yao, Alfredo L Lopez Kolkovsky, Thorsten Feiweier, Bryan Clifford, Heiko Meyer, Xiaodong Zhong, Fei Han, Nicholas S Cho, Francesco Sanvito and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of neuro-oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Multinuclear Interleaving ofNMR in biomedicine · 2025
    Article
  3. Review
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

17 authors.

Catalina RaymondUCLA Brain Tumor Imaging Laboratory (BTIL), Departments of Radiological Sciences, Psychiatry, and Neurosurgery, David Geffen School of Medicine, Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.
Jingwen YaoUCLA Brain Tumor Imaging Laboratory (BTIL), Departments of Radiological Sciences, Psychiatry, and Neurosurgery, David Geffen School of Medicine, Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.
Alfredo L Lopez KolkovskyUCLA Brain Tumor Imaging Laboratory (BTIL), Departments of Radiological Sciences, Psychiatry, and Neurosurgery, David Geffen School of Medicine, Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.
Thorsten FeiweierResearch and Clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany.
Bryan CliffordSiemens Medical Solutions USA, Inc., Boston, MA, USA.
Heiko MeyerResearch and Clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany.
Xiaodong ZhongDepartment of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Fei HanSiemens Medical Solutions USA, Inc., Boston, MA, USA.
Nicholas S ChoUCLA Brain Tumor Imaging Laboratory (BTIL), Departments of Radiological Sciences, Psychiatry, and Neurosurgery, David Geffen School of Medicine, Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.
Francesco SanvitoUCLA Brain Tumor Imaging Laboratory (BTIL), Departments of Radiological Sciences, Psychiatry, and Neurosurgery, David Geffen School of Medicine, Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.
Sonoko OshimaUCLA Brain Tumor Imaging Laboratory (BTIL), Departments of Radiological Sciences, Psychiatry, and Neurosurgery, David Geffen School of Medicine, Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.
Noriko SalamonDepartment of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Linda M LiauDepartment of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Kunal S PatelDepartment of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Richard G EversonDepartment of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Timothy F CloughesyDepartment of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Benjamin M EllingsonUCLA Brain Tumor Imaging Laboratory (BTIL), Departments of Radiological Sciences, Psychiatry, and Neurosurgery, David Geffen School of Medicine, Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA. bellingson@mednet.ucla.edu.

Funding

UCLA-Caltech Medical Scientist Training ProgramT32GM008042 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI AJIJOLA, OLUJIMI A, DAWSON, DAVID WAYNE · 1985 to 2023
$29.9M
UCLA SPORE in Brain CancerP50CA211015 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GANG LI · 2017 to 2026
$25.2M
UCLA-Caltech Medical Scientist Training ProgramT32GM152342 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Olujimi A Ajijola, David Wayne Dawson · 2024 to 2026
$5.3M
Role of decorin and diffusion MRI in anti-VEGF efficacy for recurrent glioblastomaR01CA270027 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI TIMOTHY CLOUGHESY, Benjamin M. Ellingson · 2022 to 2026
$3.0M
Quantitative molecular MR-PET imaging of glycolysis in glioblastomaR01CA279984 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Benjamin M. Ellingson, David A. Nathanson · 2023 to 2026
$2.4M
Molecular MR-PET to characterize malignant transformation and identify therapeutic vulnerabilities in human IDH-mutant gliomasF30CA284809 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CHO, NICHOLAS S. · 2023 to 2025
$136k
Congressionally Directed Medical Research Programs CA220732NCI NIH HHS F30 CA284809NCI NIH HHS F30CA284809, R01CA270027, R01CA279984, P50CA211015NCI NIH HHS P50 CA211015NCI NIH HHS R01 CA270027NCI NIH HHS R01 CA279984NIGMS NIH HHS T32 GM008042NIGMS NIH HHS T32GM008042, T32GM152342NIGMS NIH HHS T32 GM152342
6 · The paper itself

Abstract

purposeSodium neuroimaging provides unique insights into the cellular and metabolic properties of brain tumors. However, at 3T, sodium neuroimaging MRI's low signal-to-noise ratio (SNR) and resolution discourages routine clinical use. We evaluated the recently developed Anatomically constrained GAN using physics-based synthetic MRI artifacts" (ATHENA) for high-resolution sodium neuroimaging of brain tumors at 3T. We hypothesized the model would improve the image quality while preserving the inherent sodium information.

methods4,573 proton MRI scans from 1,390 suspected brain tumor patients were used for training. Sodium and proton MRI datasets from Twenty glioma patients were collected for validation. Twenty-four image-guided biopsies from seven patients were available for sodium-proton exchanger (NHE1) expression evaluation on immunohistochemistry. High-resolution synthetic sodium images were generated using the ATHENA model, then compared to native sodium MRI and NHE1 protein expression from image-guided biopsy samples.

resultsThe ATHENA produced synthetic-sodium MR with significantly improved SNR (native SNR 18.20 ± 7.04; synthetic SNR 23.83 ± 9.33, P = 0.0079). The synthetic-sodium values were consistent with the native measurements (P = 0.2058), with a strong linear correlation within contrast-enhancing areas of the tumor (R

conclusionATHENA generates high-resolution synthetic-sodium MRI at 3T, enabling clinically attainable multinuclear imaging for brain tumors that retain the inherent information from the native sodium. The resulting synthetic sodium significantly correlates with tissue expression, potentially supporting its utility as a non-invasive marker of underlying sodium homeostasis in brain tumors.

Indexed as

Artificial IntelligenceBrain NeoplasmsGliomaMagnetic Resonance ImagingNeuroimagingSodiumAdultAgedFemaleGenerative Artificial IntelligenceHumansMaleMiddle AgedSignal-To-Noise RatioSodium-Hydrogen Exchanger 1SLC9A1 protein, humanSodiumSodium-Hydrogen Exchanger 1Brain tumorsGenerative adversarial networkGliomaImage reconstructionSodium MRI

Identifiers

PMID40459830
PMCPMC12263758

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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.