Evidence map›Paper›PMID 38683704›Full record

ArticleIEEE transactions on bio-medical engineering2024

Treatment of Spontaneous Tumors With Algorithmically Controlled Electroporation.

Christopher C Fesmire, Ross A Petrella, Robert H Williamson, Kobi Derks, Jennifer Ruff, Thomas McParland, Erin O'Neil, Callie Fogle, Timo Prange, Michael B Sano

Abstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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

10 authors.

Christopher C Fesmire
Ross A Petrella
Robert H Williamson
Kobi Derks
Jennifer Ruff
Thomas McParland
Erin O'Neil
Callie Fogle
Timo Prange
Michael B Sano

Funding

Academic-Industrial Partnership to Develop Clinical Tools for Algorithmic Irreversible Electroporation of Inoperable TumorsR01CA272550 · NCI · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI SANO, MICHAEL BENJAMIN · 2022 to 2025
$2.8M
Development of an INSPIRE System for the Treatment of Inoperable Liver TumorsR01CA276232 · NCI · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI Michael Benjamin Sano · 2023 to 2026
$2.3M
NCI NIH HHS R01 CA272550NCI NIH HHS R01 CA276232
6 · The paper itself

Abstract

objectiveTo study the safety and efficacy of algorithmically controlled electroporation (ACE) against spontaneous equine melanoma.

methodsA custom temperature sensing coaxial electrode was paired with a high voltage pulse generation system with integrated temperature feedback controls. Computational modeling and ex vivo studies were conducted to evaluate the system's ability to achieve and maintain target temperatures. Twenty-five equine melanoma tumors were treated with a 2000 V protocol consisting of a 2-5-2 waveform, 45 °C temperature set point, and integrated energized times of 0.005 s, 0.01 s, or 0.02 s (2500x, 5000x, and 10000x 2 μs pulses, respectively). Patients returned 20-50 days post treatment to determine the efficacy of the treatment.

resultsACE temperature control algorithms successfully achieved and maintained target temperatures in a diverse population of spontaneous tumors with significant variation in tissue impedance. All treatments were completed successfully without and without adverse events. Complete response rates greater than 93% were achieved in all treatment groups.

conclusionACE is a safe and effective treatment for spontaneous equine melanoma. The temperature control algorithm enabled rapid delivery of electroporation treatments without prior knowledge of tissue electrical or thermal properties and could adjust to real time changes in tissue properties. SIGNIFICANCE: Real time temperature control in electroporation procedures enables treatments near critical structures where thermal damage is contraindicated. Unlike standard approaches, ACE protocols do not require extensive pretreatment planning or knowledge of tissue properties to determine an optimal energy delivery rate and they can account for changes in tissue state (e.g., perfusion) in real time to simultaneously minimize treatment time and potential for thermal damage.

Indexed as

AlgorithmsMelanomaAnimalsElectrochemotherapyElectroporationHorse DiseasesHorses

Identifiers

PMID38683704
PMCPMC11447859

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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.