Analysis of 31P chemical-shift signatures of high-energy phosphates in glioma patients measured at 7 Tesla

Motivation: The detailed characterization of tumor micro-environment can be supported by 31P MRSI enabling the non-invasive determination of pH and magnesium ion content (Mg). Goal(s): The aim of this study was to investigate whether a discrimination between different glioma micro-environments might be possible based on the differences in 31P chemical-shift signatures. Approach: For this purpose, 31P MRSI datasets from 12 patients with glioma acquired at 7T were analyzed and used to estimate the underlying pH and Mg values. Results: For the analyzed cohort, different trends in 31P chemical-shift signatures, as well as in pH and Mg values were observed for different tumor subtypes. Impact: The analysis of 31P chemical-shift signatures in glioma patients could potentially be used for stratifying tumor subtypes, and might help in the characterization of tumor microenvironments, e.g. by determining potential biomarkers such as pH and the magnesium ion content.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/5082
Primary Topic
Medical Imaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of 31P chemical-shift signatures of high-energy phosphates in glioma patients measured at 7 Tesla

Heinz‐Peter Schlemmer, Mark E. Ladd, Vanessa L. Franke, Nina Weckesser et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Medical Imaging Techniques and Applications
article

Analysis of 31P chemical-shift signatures of high-energy phosphates in glioma patients measured at 7 Tesla

Heinz‐Peter Schlemmer, Mark E. Ladd, Vanessa L. Franke, Nina Weckesser, Peter Bachert, Andreas Korzowski, Daniel Paech, Justyna Platek, Bela Seng
article en

Abstract

Motivation: The detailed characterization of tumor micro-environment can be supported by 31P MRSI enabling the non-invasive determination of pH and magnesium ion content (Mg). Goal(s): The aim of this study was to investigate whether a discrimination between different glioma micro-environments might be possible based on the differences in 31P chemical-shift signatures. Approach: For this purpose, 31P MRSI datasets from 12 patients with glioma acquired at 7T were analyzed and used to estimate the underlying pH and Mg values. Results: For the analyzed cohort, different trends in 31P chemical-shift signatures, as well as in pH and Mg values were observed for different tumor subtypes. Impact: The analysis of 31P chemical-shift signatures in glioma patients could potentially be used for stratifying tumor subtypes, and might help in the characterization of tumor microenvironments, e.g. by determining potential biomarkers such as pH and the magnesium ion content.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Peace, Justice and strong institutions
Openalex Percentile: Top 64%
Medical Imaging Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.