Evidence map›Paper›PMID 35565293›Full record

ArticleCancers2022

7T HR FID-MRSI Compared to Amino Acid PET: Glutamine and Glycine as Promising Biomarkers in Brain Tumors.

Gilbert Hangel, Philipp Lazen, Sukrit Sharma, Barbara Hristoska, Cornelius Cadrien, Julia Furtner, Ivo Rausch, Alexandra Lipka, Eva Niess, Lukas Hingerl and 12 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
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  5. Ultrahigh-field MRI: where it really makes a difference.Radiologie (Heidelberg, Germany) · 2024
    Review
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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

22 authors at 3 institutions in 1 country.

Gilbert HangelHigh-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0002-3986-3159
Philipp LazenHigh-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0002-9952-3084
Sukrit SharmaHigh-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Barbara HristoskaHigh-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Cornelius CadrienHigh-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Julia FurtnerDivision of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Ivo RauschCenter for Medical Physics and Biomedical Engineering, Medical University of Vienna, 1090 Vienna, Austria.
Alexandra LipkaHigh-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0002-1624-7994
Eva NiessHigh-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0001-9956-1470
Lukas HingerlHigh-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Stanislav MotykaHigh-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Stephan GruberHigh-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Bernhard StrasserHigh-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Barbara KieselDepartment of Neurosurgery, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0003-0939-9831
Matthias PreusserDivision of Oncology, Department of Internal Medicine I, Medical University of Vienna, 1090 Vienna, Austria.
Thomas Roetzer-PejrimovskyDivision of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0001-8875-7304
Adelheid WöhrerDivision of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0001-8435-8189
Wolfgang BognerHigh-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Georg WidhalmDepartment of Neurosurgery, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0001-6014-0273
Karl RösslerDepartment of Neurosurgery, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0002-9249-8082
Tatjana Traub-WeidingerDivision of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0003-1118-926X
Siegfried TrattnigHigh-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria.
Medical University of Vienna · ATChristian Doppler Research Association · ATHochschule Campus Wien · AT

Funding

Austrian Science Fund FWF KLI 646Austrian Science Fund FWF P 30701Austrian Science Fund FWF P 34198the Austrian Science Fund (FWF) KLI 646, P 30701, and P 34198
6 · The paper itself

Abstract

(1) Background: Recent developments in 7T magnetic resonance spectroscopic imaging (MRSI) made the acquisition of high-resolution metabolic images in clinically feasible measurement times possible. The amino acids glutamine (Gln) and glycine (Gly) were identified as potential neuro-oncological markers of importance. For the first time, we compared 7T MRSI to amino acid PET in a cohort of glioma patients. (2) Methods: In 24 patients, we co-registered 7T MRSI and routine PET and compared hotspot volumes of interest (VOI). We evaluated dice similarity coefficients (DSC), volume, center of intensity distance (CoI), median and threshold values for VOIs of PET and ratios of total choline (tCho), Gln, Gly, myo-inositol (Ins) to total N-acetylaspartate (tNAA) or total creatine (tCr). (3) Results: We found that Gln and Gly ratios generally resulted in a higher correspondence to PET than tCho. Using cutoffs of 1.6-times median values of a control region, DSCs to PET were 0.53 ± 0.36 for tCho/tNAA, 0.66 ± 0.40 for Gln/tNAA, 0.57 ± 0.36 for Gly/tNAA, and 0.38 ± 0.31 for Ins/tNAA. (4) Conclusions: Our 7T MRSI data corresponded better to PET than previous studies at lower fields. Our results for Gln and Gly highlight the importance of future research (e.g., using Gln PET tracers) into the role of both amino acids.

Indexed as

7TcholinegliomasglutamineglycineMRSIMR spectroscopyPET

Identifiers

PMID35565293
PMCPMC9101868
OpenAlexW4224996112

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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.