Evidence map›Paper›PMID 40500422›Full record

ArticleLasers in medical science2025

In silico design of blue laser soft tissue vaporization with optimized optical power efficiency and mitigated thermal side effects.

Takahiro Nishimura, Yusuke Watanabe, Yu Shimojo, Toshiyuki Ozawa, Daisuke Tsuruta

Abstract read
In one paragraph

Article in Lasers in medical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Takahiro NishimuraOsaka Metropolitan University, Osaka, Japan. nishimura-t@see.eng.osaka-u.ac.jp.
Yusuke WatanabeThe University of Osaka, Osaka, Japan.
Yu ShimojoOsaka Metropolitan University, Osaka, Japan.
Toshiyuki OzawaOsaka Metropolitan University, Osaka, Japan.
Daisuke TsurutaOsaka Metropolitan University, Osaka, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Blue diode laser irradiation has significant potential for realization of high vaporization efficiency with minimal thermal damage because of the strong blue light absorption of hemoglobin and the resulting shallow tissue penetration. This study presents an in silico framework for designing laser parameters, specifically pulse duration and power, for efficient vaporization under low-power irradiation conditions while minimizing thermal tissue damage. Computational simulations of laser-tissue interactions using the Monte Carlo light transport with dynamic optical properties model were conducted to evaluate vaporization and coagulation performance under various irradiation conditions. In addition to vaporization volume, the fraction of coagulated tissue was also calculated as a measure of thermal tissue damage. The in silico designs were validated experimentally through irradiation experiments performed on porcine liver tissue. Computational simulations revealed a non-monotonic relationship between pulse duration and vaporization volume at constant energy, as well as distinct trends for vaporization and coagulation. The experimental results confirmed the effectiveness of the simulation-derived parameters, and supported the practical utility of the proposed in silico design approach. The proposed in silico design approach enables quantitative analysis of vaporization and coagulation responses and can guide the development of safe and effective laser treatment protocols.

Indexed as

Laser CoagulationLasers, SemiconductorLiverLow-Level Light TherapyAnimalsComputer SimulationEquipment DesignMonte Carlo MethodSwineBlue laserCoagulationIn silico evaluationTissue vaporization

Identifiers

PMID40500422
PMCPMC12159099

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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.