Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 169

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Nanoparticles for cancer imaging: The good, the bad, and the promise

Open access
Chapman, Sandra, Dobrovolskaia, Marina, Farahani, Keyvan, Goodwin, Andrew, Joshi, Amit, Lee, Hakho, Meade, Thomas, Pomper, Martin, Ptak, Krzysztof, Rao, Jianghong, Singh, Ravi, Sridhar, Srinivas, Stern, Stephan, Wang, Andrew, Weaver, John B., Woloschak, Gayle, Yang, Lily·2013·Nano Today

Abstract

Summary Recent advances in molecular imaging and nanotechnology are providing new opportunities for biomedical imaging with great promise for the development of novel imaging agents. The unique optical, magnetic, and chemical properties of materials at the scale of nanometers allow the creation of imaging probes with better contrast enhancement, increased sensitivity, controlled biodistribution, better spatial and temporal information, multi-functionality and multi-modal imaging across MRI, PET, SPECT, and ultrasound. These features could ultimately translate to clinical advantages such as earlier detection, real time assessment of disease progression and personalized medicine. However, several years of investigation into the application of these materials to cancer research has revealed challenges that have delayed the successful application of these agents to the field of biomedical imaging. Understanding these challenges is critical to take full advantage of the benefits offered by nano-sized imaging agents. Therefore, this article presents the lessons learned and challenges encountered by a group of leading researchers in this field, and suggests ways forward to develop nanoparticle probes for cancer imaging. Published by Elsevier Ltd.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.nantod.2013.06.001

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Cited by

See all 169

Metadata

Authors
Chapman, S., Dobrovolskaia, M., Farahani, K., Goodwin, A., Joshi, A., Lee, H., Meade, T., Pomper, M., Ptak, K., Rao, J., Singh, R., Sridhar, S., Stern, S., Wang, A., Weaver, J. B., Woloschak, G., & Yang, L.
Venue
Nano Today
Publisher
Elsevier BV
Published
2013-10
Volume
8
Issue
5
Pages
454-460
ISSN
1748-0132 (ISSN-L)
OpenAlex
W2017669739
Cited by
169
References
2
FWCI
7.62
Type
journal article
Language
en
Open access
green

About these checks

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.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Nanoparticles for cancer imaging: The good, the bad, and the promise. https://app.cochat.ai/papers/10.1016/j.nantod.2013.06.001
The paper
Chapman, S., Dobrovolskaia, M., Farahani, K., Goodwin, A., Joshi, A., Lee, H., Meade, T., Pomper, M., Ptak, K., Rao, J., Singh, R., Sridhar, S., Stern, S., Wang, A., Weaver, J. B., Woloschak, G., & Yang, L. (2013). Nanoparticles for cancer imaging: The good, the bad, and the promise. Nano Today. https://doi.org/10.1016/j.nantod.2013.06.001

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.