Description:
Background and objectives: Recently, there have been calls for RFA to be implemented in the bipolar mode for cancer treatment due to the benefits it offers over the monopolar mode. These include the ability to prevent skin burns at the grounding pad and to avoid tumour track seeding. The usage of bipolar RFA in clinical practice remains uncommon however, as not many research studies have been carried out on bipolar RFA. As such, there is still uncertainty in understanding the effects of the different RF probe configurations on the treatment outcome of RFA. This paper demonstrates that the electrode lengths have a strong influence on the mechanics of bipolar RFA. The information obtained here may lead to further optimization of the system for subsequent uses in the hospitals. Methods: A 2D model in the axisymmetric coordinates was developed to simulate the electro-thermophysiological responses of the tissue during a single probe bipolar RFA. Two different probe configurations were considered, namely the configuration where the active electrode is longer than the ground and the configuration where the ground electrode is longer than the active. The mathematical model was first verified with an existing experimental study found in the literature. Results: Results from the simulations showed that heating is confined only to the region around the shorter electrode, regardless of whether the shorter electrode is the active or the ground. Consequently, thermal coagulation also occurs in the region surrounding the shorter electrode. This opened up the possibility for a better customized treatment through the development of RF probes with adjustable electrode lengths. Conclusions: The electrode length was found to play a significant role on the outcome of single probe bipolar RFA. In particular, the length of the shorter electrode becomes the limiting factor that influences the mechanics of single probe bipolar RFA. Results from this study can be used to further develop and optimize bipolar RFA as an effective and reliable cancer treatment technique. (C) 2019 Elsevier B.V. All rights reserved.
Description:
Because of the high dimensionality of the microarray data sets, feature selection (FS) has become an important challenge in molecular classification. Using the degree of differential prioritization (DDP) between relevance and antiredundancy, our proposed DDP-based FS technique is capable of achieving better accuracies than those previously reported, using a smaller predictor set. However, previously, we have neither devised nor used any method for determining the value of the DDP to be used for the data set of interest before the FS process. In this article, we propose a system for predicting the optimal value of the DDP, which costs less computationally than conventional tuning while maintaining the independence of the FS technique from the type of underlying classifier used