Multilayered non-invasive temperature estimation from backscattered ultrasound

Roughly one in four breast cancer survivors report some degree of arm oedema. Lymphoedema is a build-up of excess lymph fluids in the tissues. Persistent lymphoedema leads to pain, diminished limb function, increased risk of infection, soft tissue fibrosis, and severe cases can be grossly disfiguring. From a mechanics perspective, the lymphoedemous tissue may be thought of as a two phase composite, consisting of both fluid and solid phases. Here we discuss the use of composites mixture theory to model the mechanics of lymphoedemous tissues. By treating the tissue as a fluid-solid composite, rules-of-mixtures may be used to estimate the effective moduli in terms of the properties of the individual components and their respective volume fractions in these two states.

Open source data sensing software for ultrasonic non-invasive temperature estimation

In this paper, an open source solution for measurement of temperature and ultrasonic signals (RF-lines) is proposed. This software is an alternative to the expensive commercial data acquisition software, enabling the user to tune applications to particular acquisition architectures. The collected ultrasonic and temperature signals were used for non-invasive temperature estimation using neural networks. The existence of precise temperature estimators is an essential point aiming at the secure and effective applica tion of thermal therapies in humans. If such estimators exist then effective controllers could be developed for the therapeutic instrumentation. In previous works the time-shift between RF-lines echoes were extracted, and used for creation of neural networks estimators. The obtained estimators successfully represent the temperature in the time-space domain, achieving a maximum absolute error inferior to the threshold value defined for hyperthermia/diathermia applications.

A soft-computing approach for non-invasive temperature estimation

The domain of thermal therapies applications can be improved with the development of accurate non-invasive timespatial temperature models. These models should represent the non-linear tissue thermal behaviour and be capable of tracking temperature at both time-instant and spatial position. If such estimators exist then efficient controllers for the therapeutic instrumentation could be developed, and the desired safety and effectiveness reached.

On the assessment of time-shift variations from backscattered ultrasound for large temperature changes in biological phantoms

This work reports the assessment of time-shifts (TS) from backscattered ultrasound (BSU) signals when large temperature variations (up to 15 degrees C) were induced in a gel-based phantom. The results showed that during cooling temperature is linear with TS at a rate of approximately 74 ns/degrees C. However during a complete heating/cooling cycle, the relation is highly non-linear. This can be explained by the fact that during cooling the temperature distribution is more uniform. Another problem to report is that TS is very sensitive to external movements.