Simulation-guided photothermal therapy using MRI-traceable iron oxide-gold nanoparticle.
Clicks: 433
ID: 71931
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Emerging Content
30.0
/100
433 views
93 readers
AI Quality Assessment
Not analyzed
Readership in this journal
EmergingRanked #10 of 150 articles by views in journal of photochemistry and photobiology b, biology
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 150 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Despite the immense benefits of nanoparticle-assisted photothermal therapy (NPTT) in cancer treatment, the limited method and device for detecting temperature during heat operation significantly hinder its overall progress. Development of a pre-treatment planning tool for prediction of temperature distribution would greatly improve the accuracy and safety of heat delivery during NPTT. Reliable simulation of NPTT highly relies on accurate geometrical model description of tumor and determining the spatial location of nanoparticles within the tissue. The aim of this study is to develop a computational modeling method for simulation of NPTT by exploiting the theranostic potential of iron oxide‑gold hybrid nanoparticles (IO@Au) that enable NPTT under magnetic resonance imaging (MRI) guidance. To this end, CT26 colon tumor-bearing mice were injected with IO@Au nanohybrid and underwent MR imaging. The geometrical model description of tumor and nanoparticle distribution map were obtained from MR image of the tumor and involved in finite element simulation of heat transfer process. The experimental measurement of tumor temperature confirmed the validity of the model to predict temperature distribution. The constructed model can help to predict temperature distribution during NPTT and then allows to optimize the heating protocol by adjusting the treatment parameters prior to the actual treatment operation.
| Reference Key |
beik2019simulationguidedjournal
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Beik, Jaber;Asadi, Mohamadreza;Khoei, Samideh;Laurent, Sophie;Abed, Ziaeddin;Mirrahimi, Mehri;Farashahi, Ali;Hashemian, Reza;Ghaznavi, Habib;Shakeri-Zadeh, Ali; |
| Journal | journal of photochemistry and photobiology b, biology |
| Year | 2019 |
| DOI |
S1011-1344(19)30256-8
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.