Evidence map›Paper›PMID 34168905›Full record

ArticleBiomedical optics express2021

Quasi-distributed fiber optic sensor-based control system for interstitial laser ablation of tissue: theoretical and experimental investigations.

Leonardo Bianchi, Sanzhar Korganbayev, Annalisa Orrico, Martina De Landro, Paola Saccomandi

Abstract read
In one paragraph

Article in Biomedical optics express, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. A Thermo-Fluid-Solid Model Thermal Damage Prediction in Laser Ablation Therapy.The international journal of medical robotics + computer assisted surgery : MRCAS · 2026
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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

5 authors.

Leonardo BianchiDepartment of Mechanical Engineering, Politecnico di Milano, Milan, Italy.ORCID https://orcid.org/0000-0001-6100-0862
Sanzhar KorganbayevDepartment of Mechanical Engineering, Politecnico di Milano, Milan, Italy.ORCID https://orcid.org/0000-0002-6299-6048
Annalisa OrricoDepartment of Mechanical Engineering, Politecnico di Milano, Milan, Italy.ORCID https://orcid.org/0000-0001-7427-5590
Martina De LandroDepartment of Mechanical Engineering, Politecnico di Milano, Milan, Italy.ORCID https://orcid.org/0000-0002-1778-8928
Paola SaccomandiDepartment of Mechanical Engineering, Politecnico di Milano, Milan, Italy.ORCID https://orcid.org/0000-0003-4236-8033

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work proposes the quasi-distributed real-time monitoring and control of laser ablation (LA) of liver tissue. To confine the thermal damage, a pre-planning stage of the control strategy based on numerical simulations of the bioheat-transfer was developed to design the control parameters, then experimentally assessed. Fiber Bragg grating (FBG) sensors were employed to design the automatic thermometry system used for temperature feedback control for interstitial LA. The tissue temperature was maintained at a pre-set value, and the influence of different sensor locations (on the direction of the beam propagation and backward) on the thermal outcome was evaluated in comparison with the uncontrolled case. Results show that the implemented computational model was able to properly describe the temperature evolution of the irradiated tissue. Furthermore, the realized control strategy allowed for the accurate confinement of the laser-induced temperature increase, especially when the temperature control was actuated by sensors located in the direction of the beam propagation, as confirmed by the calculated fractions of necrotic tissues (e.g., 23 mm

Identifiers

PMID34168905
PMCPMC8194627

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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.