Abstract
The potential of thermal therapy’s applications improve with the development of accurate non-invasive time-spatial temperature models. These models should represent the non-linear tissue thermal behaviour and be capable of tracking temperature at both time-instant and spatial point. An in-vitro experiment was developed based on a gel phantom, heated by a therapeutic ultrasound (TUS) device emitting continuously. The heating process was monitored by an imaging ultrasound (IUS) transducer working in pulse-echo mode, placed perpendicularly to the TUS transducer. The IUS RF-lines and temperature values were collected 60 mm distant from the TUS transducer face. Three thermocouples were aligned along the IUS transducer axial direction and across the TUS transducer radial direction (1 cm spaced). Three different TUS intensities were applied. The non-invasive time-spatial evolutionary temperature models were created making use of radial basis functions neural networks (RBFNN). The neural network input information was: the propagation time-delay between RF-line echoes and the past temperature lags from three different medium locations and three different TUS intensities. A total of nine different operating situations were studied. The best RBFNN structures were automatically determined by a multiobjective genetic algorithm, due to the enormous number of possible structures. The RBFNN temperature models were evaluated with data never used in the models, neither at the training or structural selection phases. In order to precisely evaluate the model generalisation performance these data included the nine possible operating situations. The best model presents a maximum absolute error less than 0.5 degrees Celsius (gold-standard value for hyperthermia/diathermia applications). To be mentioned also that the best model presents low computational complexity enabling future real-time implementations. Concluding, a maximum absolute error below the gold-standard value pointed for hyperthermia/diathermia applications was attained. In addition, this methodology does not require a-priori determination of physical constants and mathematical simplifications required for analytical methodologies.
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References
Paulsen K D, Moskowitz M J, Ryan T P et al. (1996) Initial in vivo experience with EIT as a thermal estimator during hyperthermia. Int J Hyperthermia 12:573–591
Meaney PM, Paulsen KD (1996) Microwave imaging for tissue assessment: initial evolution in multitarget tissue-equivalent phantoms. IEEE Trans Biomed Eng 43:878–890
Hynynen K, Chung A, Fjield T et al. (1996), Feasibility of using ultrasound phased arrays for MRI monitored noninvasive surgery. IEEE Trans Ultrason Ferroelectr Freq Control 43:1043–1052
Arthur R M, Straube W L, Trobaugh J W, Moros E G (2005) Noninvasive temperature estimation of hyperthermia temperatures with ultrasound. Int J Hyperthermia 21:589–600
Simon C, VanBaren P, Ebbini E S (1998) Two-dimensional temperature estimation using diagnostic ultrasound. IEEE Trans Ultrason Ferroelectr Freq Control 45:1088–1099
Amini A N, Ebbini E S, Georgiou T T (2005) Noninvasive estimation of tissue temperature via high-resolution spectral analysis techniques. IEEE Trans Biomed Eng 52:221–228
Ueno S, Hashimoto M, Fukukita H, Yano T (1990) Ultrasound thermometry in hyperthermia, IEEE Ultrasonic Symposium Proc. vol. 3, Honolulu, Hawaii, USA, 1990, pp. 1645–1652
Teixeira C A, Ruano A E, Graça Ruano M et al. (2006) Non-invasive temperature prediction of in vitro therapeutic ultrasound signals using neural networks. Med Biol Eng Comput 44:111–116
Viola F, Walker W F (2005) A spline-based algorithm for continuous time-delay estimation using sampled data. IEEE Trans Ultrason Ferroelectr Freq Control 52:80–93
Fonseca C M, Fleming P J (1993) Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization, 5th International Conference on Genetic Algorithms Proc., Illinois, USA, 1993, pp.416–423
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© 2007 International Federation for Medical and Biological Engineering
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Teixeira, C.A., Graça Ruano, M., Ruano, A.E., Pereira, W.C.A. (2007). Non-invasive tissue temperature evaluation during application of therapeutic ultrasound: precise time-spatial non-linear modelling. In: Magjarevic, R., Nagel, J.H. (eds) World Congress on Medical Physics and Biomedical Engineering 2006. IFMBE Proceedings, vol 14. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36841-0_25
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DOI: https://doi.org/10.1007/978-3-540-36841-0_25
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