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A Review of Basic to Clinical Studies of Irreversible Electroporation Therapy
Abstract
The use of irreversible electroporation (IRE) for cancer treatment has increased sharply over the past decade. As a nonthermal therapy, IRE offers several potential benefits over other focal therapies, which include 1) short treatment delivery time, 2) reduced collateral thermal injury, and 3) the ability to treat tumors adjacent to major blood vessels. These advantages have stimulated widespread interest in basic through clinical studies of IRE. For instance, many in vitro and in vivo studies now identify treatment planning protocols (IRE threshold, pulse parameters, etc.), electrode delivery (electrode design, placement, intraoperative imaging methods, etc.), injury evaluation (methods and timing), and treatment efficacy in different cancer models. Therefore, this study reviews the in vitro, translational, and clinical studies of IRE cancer therapy based on major experimental studies particularly within the past decade. Further, this study provides organized data and facts to assist further research, optimization, and clinical applications of IRE.
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Metadata
- Authors
- Jiang, C., Davalos, R. V., & Bischof, J. C.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2015-01
- Volume
- 62
- Issue
- 1
- Pages
- 4-20
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2032132376
- Cited by
- 332
- References
- 117
- FWCI
- 27.54
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.