ReviewBioengineering (Basel, Switzerland)2022
Computational Modeling of Microwave Tumor Ablation.
Review in Bioengineering (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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.
Who cites it
8 citing papers in PubMed.
- Ultrasound-guided microwave ablation for breast tumors: current status and future perspectives.Diagnostic and interventional radiology (Ankara, Turkey) · 2026Review
- Efficacy and safety of ultrasound-guided microwave ablation for primary hyperparathyroidism: a dual-centre study.Scientific reports · 2026Article
- Roadmap towards personalized approaches and safety considerations in non-ionizing radiation: from dosimetry to therapeutic and diagnostic applications.Physics in medicine and biology · 2026Review
- In vivo percutaneous microwave ablation with ECO system in swine kidney and liver: comparison of ablation-zone size to manufacturer predictions and assessment of new antenna design.Research in diagnostic and interventional imaging · 2025Article
- Review
- Safety and Effectiveness of Triple-Antenna Hepatic Microwave Ablation.Bioengineering (Basel, Switzerland) · 2024Article
- Treatment Planning Strategies for Interstitial Ultrasound Ablation of Prostate Cancer.IEEE open journal of engineering in medicine and biology · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Microwave ablation is recognized as a minimally invasive, fast-recovery treatment for destroying cancer cells using the heat generated by microwave energy. Despite the unquestionable benefits of microwave ablation, the interaction of the microwave applicator with the tissue may result in localized heating and damage to the surrounding tissue. The majority of the tissue damage can be removed by clarifying the conditions for their development. In addition to experimental methods, computer modeling has proven to be an effective tool for optimizing the performance of microwave ablation. Furthermore, because the thermal spread in biological tissue is difficult to measure, developing a predictive model from procedural planning to execution may have a substantial influence on patient care. The comprehension of heat transport in biological tissues plays a significant role in gaining insight into the mechanisms underlying microwave ablation. Numerical methods that enable ablation size control are required to guarantee tumor destruction and minimize damage to healthy tissues. Various values of input power and ablation time correspond to different tumor shapes ensuring the preservation of healthy tissues. The optimal conditions can be estimated by performing full three-dimensional simulations. This topical review recapitulates numerous computational studies on microwave tumor ablation. Novel areas emerging in treatment planning that exploit the advantages of numerical methods are also discussed. As an illustration, the results of the three-dimensional simulations of real liver tumors in the 3D-IRCADb-01 database are presented and analyzed. The simulation results confirm that numerical methods are very useful tools for modeling microwave tumor ablation with minimal invasiveness and collateral damage.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.