Evidence map›Paper›PMID 37892940›Full record

ArticleBioengineering (Basel, Switzerland)2023

Model-Optimizing Radiofrequency Parameters of 3D Finite Element Analysis for Ablation of Benign Thyroid Nodules.

Fabiano Bini, Andrada Pica, Franco Marinozzi, Alessandro Giusti, Andrea Leoncini, Pierpaolo Trimboli

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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.

Fabiano BiniDepartment of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy.ORCID 0000-0002-5641-1189
Andrada PicaDepartment of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy.ORCID 0000-0002-6877-4120
Franco MarinozziDepartment of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy.
Alessandro GiustiDalle Mole Institute for Artificial Intelligence (IDSIA), Università della Svizzera Italiana (USI), The University of Applied Sciences and Arts of Southern Switzerland (SUPSI), 6900 Lugano, Switzerland.
Andrea LeonciniServizio di Radiologia e Radiologia Interventistica, Istituto di Imaging della Svizzera Italiana (IIMSI), Ente Ospedaliero Cantonale (EOC), 6900 Lugano, Switzerland.ORCID 0000-0002-6466-7221
Pierpaolo TrimboliClinic of Endocrinology and Diabetology, Lugano Regional Hospital, Ente Ospedaliero Cantonale (EOC), 6500 Bellinzona, Switzerland.ORCID 0000-0002-2125-4937

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiofrequency (RF) ablation represents an efficient strategy to reduce the volume of thyroid nodules. In this study, a finite element model was developed with the aim of optimizing RF parameters, e.g., input power and treatment duration, in order to achieve the target volume reduction rate (VRR) for a thyroid nodule. RF ablation is modelled as a coupled electro-thermal problem wherein the electric field is applied to induce tissue heating. The electric problem is solved with the Laplace equation, the temperature distribution is estimated with the Pennes bioheat equation, and the thermal damage is evaluated using the Arrhenius equation. The optimization model is applied to RF electrode with different active tip lengths in the interval from 5 mm to 40 mm at the 5 mm step. For each case, we also explored the influence of tumour blood perfusion rate on RF ablation outcomes. The model highlights that longer active tips are more efficient as they require lesser power and shorter treatment time to reach the target VRR. Moreover, this condition is characterized by a reduced transversal ablation zone. In addition, a higher blood perfusion increases the heat dispersion, requiring a different combination of RF power and time treatment to achieve the target VRR. The model may contribute to an improvement in patient-specific RF ablation treatment.

Indexed as

finite element methodoptimization modelradiofrequency ablationthyroid benign nodulestreatment planning

Identifiers

PMID37892940
PMCPMC10604455

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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.