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Record W2781392573 · doi:10.1115/1.4038791

Optimization of Electrode Configuration and Pulse Strength in Irreversible Electroporation for Large Ablation Volumes Without Thermal Damage

2017· article· en· W2781392573 on OpenAlexaff
Yongji Yang, Mike Moser, Edwin Zhang, Wenjun Zhang, Bing Zhang

Bibliographic record

VenueJournal of Engineering and Science in Medical Diagnostics and Therapy · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsUniversity of TorontoUniversity of Saskatchewan
Fundersnot available
KeywordsAblationVolume (thermodynamics)ElectrodeMaximum temperatureMaterials scienceIrreversible electroporationAnalytical Chemistry (journal)ElectroporationBiomedical engineeringComposite materialChemistryMedicineChromatographyThermodynamicsCardiologyPhysics

Abstract

fetched live from OpenAlex

The aim of this study was to analyze five factors that are responsible for the ablation volume and maximum temperature during the procedure of irreversible electroporation (IRE). The five factors used in this study were the pulse strength (U), the electrode diameter (B), the distance between the electrode and the center (D), the electrode length (L), and the number of electrodes (N). A validated finite element model (FEM) of IRE was built to collect the data of the ablation volume and maximum temperature generated in a liver tissue. Twenty-five experiments were performed, in which the ablation volume and maximum temperature were taken as response variables. The five factors with ranges were analyzed to investigate their impacts on the ablation volume and maximum temperature, respectively, using analysis of variance. Response surface method (RSM) was used to optimize the five factors for the maximum ablation volume without thermal damage (the maximum temperature ≤ 50 °C for 90 s). U and L were found with significant impacts on the ablation volume (P < 0.001, and P = 0.009, respectively) while the same conclusion was not found for B, D and N (P = 0.886, P = 0.075 and P = 0.279, respectively). Furthermore, U, D, and N had the significant impacts on the maximum temperature with P < 0.001, P < 0.001, and P = 0.003, respectively, while same conclusion was not found for B and L (P = 0.720 and P = 0.051, respectively). The maximum ablation volume of 2952.9960 mm3 without thermal damage can be obtained by using the following set of factors: U = 2362.2384 V, B = 1.4889 mm, D = 7 mm, L = 4.5659 mm, and N = 3. The study concludes that both B and N have insignificant impacts (P = 0.886, and P = 0.279, respectively) on the ablation volume; U has the most significant impact (P < 0.001) on the ablation volume; electrode configuration and pulse strength in IRE can be optimized for the maximum ablation volume without thermal damage using RSM.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.297
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2017
Admission routes1
Has abstractyes

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