Evidence map›Paper›PMID 37796151›Full record

ArticleMagnetic resonance in medicine2024

Deuterium metabolic imaging for 3D mapping of glucose metabolism in humans with central nervous system lesions at 3T.

Philip M Adamson, Keshav Datta, Ron Watkins, Lawrence D Recht, Ralph E Hurd, Daniel M Spielman

Open access · bronzeAbstract 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 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
7.3field-weighted citation impact, top 2% 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

21 citing papers in PubMed, 32 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 1 institution in 1 country.

Philip M AdamsonDepartment of Electrical Engineering, Stanford University, Stanford, California, USA.ORCID 0000-0002-5028-0683
Keshav DattaDepartment of Radiology, Stanford University, Stanford, California, USA.ORCID 0000-0002-9985-8300
Ron WatkinsDepartment of Radiology, Stanford University, Stanford, California, USA.
Lawrence D RechtDepartment of Neurology, Stanford University, Stanford, California, USA.
Ralph E HurdDepartment of Radiology, Stanford University, Stanford, California, USA.ORCID 0000-0001-5761-3690
Daniel M SpielmanDepartment of Radiology, Stanford University, Stanford, California, USA.ORCID 0000-0003-0838-6967
Stanford University · US

Funding

Enhanced Deuterium Metabolic Imaging (DMI) of Metabolic Reprogramming in Brain TumorsR01CA277832 · NCI · STANFORD UNIVERSITY · PI Daniel M Spielman · 2023 to 2026
$2.4M
Imaging Biomarkers for Glioma Treatment ResponseR01CA245097 · NCI · STANFORD UNIVERSITY · PI RECHT, LAWRENCE D, SPIELMAN, DANIEL M · 2020 to 2022
$714k
NCI NIH HHS R01 CA245097NCI NIH HHS R01 CA277832
6 · The paper itself

Abstract

purposeTo explore the potential of 3T deuterium metabolic imaging (DMI) using a birdcage

methodsA modified gradient filter, home-built

resultsThe ability to quantify local glucose metabolism in correspondence to anatomical landmarks across patients with varying CNS lesions is demonstrated, and increased lactate is observed in one patient with the most active disease.

conclusionDMI offers the potential to examine metabolic activity in human subjects with CNS lesions with DMI at 3T, promising for the potential of the future clinical translation of this metabolic imaging technique.

Indexed as

BrainMagnetic Resonance ImagingDeuteriumGlucoseHumansSignal-To-Noise RatioDeuteriumGlucose3 Tesla (3T)brain energy metabolismcentral nervous system lesionsdeuterium metabolic imaging (DMI)glucose metabolismhuman brain

Identifiers

PMID37796151
PMCPMC10841984
OpenAlexW4387357135

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.