Microwave thermal ablation is a cancer treatment that exploits local heating caused by a microwave electromagnetic field to induce coagulative necrosis of tumor cells. Recently, such a technique has significantly progressed in the clinical practice. However, its effectiveness would dramatically improve if paired with a noninvasive system for the real-time monitoring of the evolving dimension and shape of the thermally ablated area. In this respect, microwave imaging can be a potential candidate to monitor the overall treatment evolution in a noninvasive way, as it takes direct advantage from the dependence of the electromagnetic properties of biological tissues from temperature. This paper explores such a possibility by presenting a proof of concept validation based on accurate simulated imaging experiments, run with respect to a scenario that mimics an ex vivo experimental setup. In particular, two model-based inversion algorithms are exploited to tackle the imaging task. These methods provide independent results in real-time and their integration improves the quality of the overall tracking of the variations occurring in the target and surrounding regions. © 2017 Rosa Scapaticci et al.

Exploiting Microwave Imaging Methods for Real-Time Monitoring of Thermal Ablation

Lopresto, V.
2017

Abstract

Microwave thermal ablation is a cancer treatment that exploits local heating caused by a microwave electromagnetic field to induce coagulative necrosis of tumor cells. Recently, such a technique has significantly progressed in the clinical practice. However, its effectiveness would dramatically improve if paired with a noninvasive system for the real-time monitoring of the evolving dimension and shape of the thermally ablated area. In this respect, microwave imaging can be a potential candidate to monitor the overall treatment evolution in a noninvasive way, as it takes direct advantage from the dependence of the electromagnetic properties of biological tissues from temperature. This paper explores such a possibility by presenting a proof of concept validation based on accurate simulated imaging experiments, run with respect to a scenario that mimics an ex vivo experimental setup. In particular, two model-based inversion algorithms are exploited to tackle the imaging task. These methods provide independent results in real-time and their integration improves the quality of the overall tracking of the variations occurring in the target and surrounding regions. © 2017 Rosa Scapaticci et al.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12079/1977
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