Evidence map›Paper›PMID 37078045›Full record

ArticleBiomedical optics express2023

Photobiomodulation for knee osteoarthritis: a model-based dosimetry study.

Zefeng Feng, Peipei Wang, Yang Song, Haiyang Wang, Zhiliang Jin, Daxi Xiong

Abstract read
In one paragraph

Article in Biomedical optics express, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
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

6 authors.

Zefeng FengSchool of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China.
Peipei WangSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.ORCID https://orcid.org/0000-0003-4482-6149
Yang SongSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.
Haiyang WangSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.ORCID https://orcid.org/0000-0001-7379-4794
Zhiliang JinSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.
Daxi XiongSchool of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

LED-based photobiomodulation (LED-PBM) for the treatment of knee osteoarthritis (KOA) is a promising technology. However, the light dose at the targeted tissue, which dominates the phototherapy effectiveness, is difficult to measure. This paper studied the dosimetric issues in the phototherapy of KOA by developing an optical model of the knee and performing Monte Carlo (MC) simulation. The model was validated by the tissue phantom and knee experiments. In the study, we investigated the effect of luminous characteristics of the light source, such as divergence angle, wavelength and irradiation position, on the treatment doses for PBM. The result showed that the divergence angle and the wavelength of the light source have a significant impact on the treatment doses. The optimal irradiation location was on both sides of the patella, where the largest dose could reach the articular cartilage. This optical model can be used to determine the key parameters in phototherapy and help the phototherapy of KOA patients.

Identifiers

PMID37078045
PMCPMC10110300

What Socratic 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 Socratic graph.