Evidence map›Paper›PMID 26740961›Full record

ReviewNeurophotonics2016

Review on photoacoustic imaging of the brain using nanoprobes.

Depeng Wang, Yun Wu, Jun Xia

Open access · bronzeAbstract readReview
In one paragraph

Review in Neurophotonics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
8.2field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 96 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Review
  16. Article
  17. Review
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Depeng WangState University of New York , University at Buffalo, Department of Biomedical Engineering, 208 Bonner Hall, Buffalo, New York 14260, United States.
Yun WuState University of New York , University at Buffalo, Department of Biomedical Engineering, 208 Bonner Hall, Buffalo, New York 14260, United States.
Jun XiaState University of New York , University at Buffalo, Department of Biomedical Engineering, 208 Bonner Hall, Buffalo, New York 14260, United States.
University at Buffalo, State University of New York · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Photoacoustic (PA) tomography (PAT) is a hybrid imaging modality that integrates rich optical contrasts with a high-ultrasonic spatial resolution in deep tissue. Among various imaging applications, PA neuroimaging is becoming increasingly important as it nicely complements the limitations of conventional neuroimaging modalities, such as the low-temporal resolution in magnetic resonance imaging and the low depth-to-resolution ratio in optical microscopy/tomography. In addition, the intrinsic hemoglobin contrast PA neuroimaging has also been greatly improved by recent developments in nanoparticles (NPs). For instance, near-infrared absorbing NPs greatly enhanced the vascular contrast in deep-brain PAT; tumor-targeting NPs allowed highly sensitive and highly specific delineation of brain tumors; and multifunctional NPs enabled comprehensive examination of the brain through multimodal imaging. We aim to give an overview of NPs used in PA neuroimaging. Classifications of various NPs used in PAT will be introduced at the beginning, followed by an overview of PA neuroimaging systems, and finally we will discuss major applications of NPs in PA neuroimaging and highlight representative studies.

Indexed as

nanoparticleneuroimagingphotoacoustic tomography

Identifiers

PMID26740961
PMCPMC4699324
OpenAlexW2225218646

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.