Evidence map›Paper›PMID 39802351›Full record

ArticleJournal of biomedical optics2025

Photosensitizer spatial heterogeneity and its impact on personalized interstitial photodynamic therapy treatment planning.

Tina Saeidi, Shuran Wang, Hector A Contreras, Michael J Daly, Vaughn Betz, Lothar Lilge

Abstract read
In one paragraph

Article in Journal of biomedical optics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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.

Tina SaeidiUniversity of Toronto, University Health Network, Princess Margaret Cancer Centre, Department of Medical Biophysics, Toronto, Ontario, Canada.
Shuran WangUniversity of Toronto, Edward S. Rogers Sr. Department of Electrical and Computer Engineering, Toronto, Ontario, Canada.ORCID 0000-0003-4345-7628
Hector A ContrerasUniversity of Toronto, University Health Network, Princess Margaret Cancer Centre, Department of Medical Biophysics, Toronto, Ontario, Canada.
Michael J DalyUniversity Health Network, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.ORCID 0000-0002-2217-4146
Vaughn BetzUniversity of Toronto, Edward S. Rogers Sr. Department of Electrical and Computer Engineering, Toronto, Ontario, Canada.ORCID 0000-0003-0528-6493
Lothar LilgeUniversity of Toronto, University Health Network, Princess Margaret Cancer Centre, Department of Medical Biophysics, Toronto, Ontario, Canada.ORCID 0000-0001-5533-0005

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Significance: Personalized photodynamic therapy (PDT) treatment planning requires knowledge of the spatial and temporal co-localization of photons, photosensitizers (PSs), and oxygen. The inter- and intra-subject variability in the photosensitizer concentration can lead to suboptimal outcomes using standard treatment plans. Aim: We aim to quantify the PS spatial variation in tumors and its effect on PDT treatment planning solutions. Approach: The spatial variability of two PSs is imaged at various spatial resolutions for an orthotopic rat glioma model and applied Results: The Conclusions: Assuming homogeneous photosensitizer distribution results in suboptimal therapeutic outcomes, we highlight the need to predict the photosensitizer distribution before source placement for effective treatment plans.

Indexed as

PhotochemotherapyPhotosensitizing AgentsPrecision MedicineAnimalsBrain NeoplasmsCell Line, TumorGlioblastomaGliomaHumansRatsPhotosensitizing Agentsinterstitial photodynamic therapyPDT-SPACEphotosensitizer heterogeneitypre-treatment planning

Identifiers

PMID39802351
PMCPMC11724368

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.