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Detecting tumor response to treatment using hyperpolarized 13C magnetic resonance imaging and spectroscopy
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Cited by
Kurhanewicz, J., Vigneron, D. B., Brindle, K., Chekmenev, E. Y., Comment, A., Cunningham, C. H., DeBerardinis, R. J., Green, G. G., Leach, M. O., Rajan, S. S., et al. (2011) · Neoplasia · doi:10.1593/neo.101102 · Cited by 681
Self-citationGallagher, F. A., Kettunen, M. I., Hu, D.-E., Jensen, P. R., Zandt, R. I. ‘., Karlsson, M., Gisselsson, A., Nelson, S. K., Witney, T. H., Bohndiek, S. E., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0911447106 · Cited by 301
Self-citationNMR-based metabolomics in human disease diagnosis: applications, limitations, and recommendations
Emwas, A.-H. M., Salek, R. M., Griffin, J. L., & Merzaban, J. (2013) · Metabolomics · doi:10.1007/s11306-013-0524-y · Cited by 296
Hu, S., Balakrishnan, A., Bok, R. A., Anderton, B., Larson, P. E. Z., Nelson, S. J., Kurhanewicz, J., Vigneron, D. B., & Goga, A. (2011) · Cell Metabolism · doi:10.1016/j.cmet.2011.04.012 · Cited by 245
Targeting Cancer Metabolism: Dietary and Pharmacologic Interventions
Vernieri, C., Casola, S., Foiani, M., Pietrantonio, F., de Braud, F., & Longo, V. (2016) · Cancer Discovery · doi:10.1158/2159-8290.cd-16-0615 · Cited by 202
Rajeshkumar, N. V., Dutta, P., Yabuuchi, S., de Wilde, R. F., Martinez, G. V., Le, A., Kamphorst, J. J., Rabinowitz, J. D., Jain, S. K., Hidalgo, M., et al. (2015) · Cancer Research · doi:10.1158/0008-5472.can-15-0108 · Cited by 158
“The recently discovered hyperpolarized MRI using DNP (dynamic nuclear polarization) technology has the potential of providing real-time images of metabolic processes in tumors at unprecedented levels of sensitivity for monitoring therapy responses (40-43).”
Granlund, K. L., Tee, S.-S., Vargas, H. A., Lyashchenko, S. K., Reznik, E., Fine, S., Laudone, V., Eastham, J. A., Touijer, K. A., Reuter, V. E., et al. (2020) · Cell Metabolism · doi:10.1016/j.cmet.2019.08.024 · Cited by 138
Deuterium metabolic imaging reports on tert expression and early response to therapy in cancer
Batsios, G., Taglang, C., Tran, M., Stevers, N., Barger, C., Gillespie, A. M., Ronen, S. M., Costello, J. F., & Viswanath, P. (2022) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-21-4418 · Cited by 40
Imaging cancer metabolism using magnetic resonance
Brindle, K. M. (2024) · npj Imaging · doi:10.1038/s44303-023-00004-0 · Cited by 22
Self-citationHall, H., Cuellar-Baena, S., Dahlberg, C., in’t Zandt, R., Denisov, V., & Kirik, D. (2011) · Current Topics in Behavioral Neurosciences · doi:10.1007/7854_2011_166 · Cited by 17
Metadata
- Authors
- Day, S. E., Kettunen, M. I., Gallagher, F. A., Hu, D.-E., Lerche, M., Wolber, J., Golman, K., Ardenkjaer-Larsen, J. H., & Brindle, K. M.
- Venue
- Nature Medicine
- Published
- 2007-10-28
- Volume
- 13
- Issue
- 11
- Pages
- 1382-1387
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W2142136953
- Cited by
- 883
- References
- 0
- FWCI
- 14.96
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Data sources
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.