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Cited by 660

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Studies of human tumors by MRS: A review

Negendank, William·1992·NMR in Biomedicine

Abstract

The literature describing 31 P, 1 H, 13 C, 23 Na and 19 F MRS in vivo in human cancers is reviewed. Cancers have typical metabolic characteristics in 31 P and 1 H MRS including high levels of phospholipid metabolites and a cellular pH more alkaline than normal. These alone are not specific for cancer but are diagnostic in appropriate clinical settings. Some metabolic characteristics appear to be prognostic indices and correlation with treatment response is emerging as an important potentially cost‐effective use of MRS in oncology. 19 F MRS examines pharmacokinetics of 5‐fluorouracil and by demonstrating its retention predicts response of a cancer to treatment. Current needs include improvement of diagnostic specificity by use of techniques like multivoxel MRS, proton decoupling of 31 P, short echo time and fat‐suppressed 1 H MRS, 13 C MRS direct or via 1 H‐observe, and statistical analysis of multiple spectral features. Trials in large populations in well defined clinical settings are needed to determine if MRS can provide independent prognostic indices useful in cancer management.

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Metadata

Authors
Negendank, W.
Venue
NMR in Biomedicine
Publisher
Wiley
Published
1992-09
Volume
5
Issue
5
Pages
303-324
ISSN
  • 0952-3480 (ISSN-L)
  • 1099-1492
OpenAlex
W2104807697
Cited by
660
References
1
FWCI
18.00
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Studies of human tumors by MRS: A review. https://app.cochat.ai/papers/10.1002/nbm.1940050518
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Negendank, W. (1992). Studies of human tumors by MRS: A review. NMR in Biomedicine. https://doi.org/10.1002/nbm.1940050518

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.