Evidence map›Paper›PMID 36497210›Full record

ArticleCancers2022

Multiscale Modelling of Nanoparticle Distribution in a Realistic Tumour Geometry Following Local Injection.

George Caddy, Justin Stebbing, Gareth Wakefield, Megan Adair, Xiao Yun Xu

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

5 authors at 1 institution in 1 country.

George CaddyDepartment of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
Justin StebbingDepartment of Surgery and Cancer, Imperial College London, London SW7 2AZ, UK.
Gareth WakefieldXerion Healthcare Ltd., Cherwell Innovation Centre, 77 Heyford Park, Oxfordshire OX25 5HD, UK.
Megan AdairXerion Healthcare Ltd., Cherwell Innovation Centre, 77 Heyford Park, Oxfordshire OX25 5HD, UK.
Xiao Yun XuDepartment of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.ORCID 0000-0002-8267-621X
Imperial College London · GB

Funding

Engineering and Physical Sciences Research Council EP/R513052/1
6 · The paper itself

Abstract

Radiosensitizers have proven to be an effective method of improving radiotherapy outcomes, with the distribution of particles being a crucial element to delivering optimal treatment outcomes due to the short range of effect of these particles. Here we present a computational model for the transport of nanoparticles within the tumour, whereby the fluid velocity and particle deposition are obtained and used as input into the convection-diffusion equation to calculate the spatio-temporal concentration of the nanoparticles. The effect of particle surface charge and injection locations on the distribution of nanoparticle concentration within the interstitial fluid and deposited onto cell surfaces is assessed. The computational results demonstrate that negatively charged particles can achieve a more uniform distribution throughout the tumour as compared to uncharged or positively charged particles, with particle volume within the fluid being 100% of tumour volume and deposited particle volume 44.5%. In addition, varying the injection location from the end to the middle of the tumour caused a reduction in particle volume of almost 20% for negatively charged particles. In conclusion, radiosensitizing particles should be negatively charged to maximise their spread and penetration within the tumour. Choosing an appropriate injection location can further improve the distribution of these particles.

Indexed as

mathematical modellingparticle transportradiotherapytumour

Identifiers

PMID36497210
PMCPMC9736186
OpenAlexW4309689812

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.