The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Molecular imaging for personalized cancer care
Open accessAbstract
Molecular imaging is rapidly gaining recognition as a tool with the capacity to improve every facet of cancer care. Molecular imaging in oncology can be defined as in vivo characterization and measurement of the key biomolecules and molecularly based events that are fundamental to the malignant state. This article outlines the basic principles of molecular imaging as applied in oncology with both established and emerging techniques. It provides examples of the advantages that current molecular imaging techniques offer for improving clinical cancer care as well as drug development. It also discusses the importance of molecular imaging for the emerging field of theranostics and offers a vision of how molecular imaging may one day be integrated with other diagnostic techniques to dramatically increase the efficiency and effectiveness of cancer care.
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Majumder, P. K., Febbo, P. G., Bikoff, R., Berger, R., Xue, Q., McMahon, L. M., Manola, J., Brugarolas, J., McDonnell, T. J., Golub, T. R., et al. (2004) · Nature Medicine · doi:10.1038/nm1052 · Cited by 964
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
Raman's “Effect” on Molecular Imaging
Zavaleta, C. L., Kircher, M. F., & Gambhir, S. S. (2011) · Journal of Nuclear Medicine · doi:10.2967/jnumed.111.087775 · Cited by 88
Self-citation
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Molecular imaging for cancer diagnosis and surgery
Hussain, T., & Nguyen, Q. T. (2014) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2013.09.007 · Cited by 337
Surface-enhanced resonance Raman scattering nanostars for high-precision cancer imaging
Harmsen, S., Huang, R., Wall, M. A., Karabeber, H., Samii, J. M., Spaliviero, M., White, J. R., Monette, S., O’Connor, R., Pitter, K. L., et al. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.3010633 · Cited by 296
Self-citationDeveloping biomarker-specific end points in lung cancer clinical trials
Neal, J. W., Gainor, J. F., & Shaw, A. T. (2015) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2014.222 · Cited by 51
Computational Approaches in Theranostics: Mining and Predicting Cancer Data
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Metadata
- Authors
- Kircher, M. F., Hricak, H., & Larson, S. M.
- Venue
- Molecular Oncology
- Publisher
- Wiley
- Published
- 2012-03-10
- Volume
- 6
- Issue
- 2
- Pages
- 182-195
- ISSN
- 1574-7891 (ISSN-L)
- 1878-0261
- OpenAlex
- W1995979320
- Cited by
- 193
- References
- 3
- FWCI
- 11.35
- Type
- journal article
- Language
- en
- Open access
- bronze
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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.
