Safety Constrained Sparse Radiation Therapy via Efficient Optimization Approach for Biomedical Phased Array Applications

 The development of interventional radiotherapy techniques has become one of the most important concerns for antenna designers worldwide. In this study, an efficient optimization approach based on a hybrid algorithm that exploits the quantitative concept and the theory of reinforcement convexity, called the quantitative-convex approach (QCA), is presented to produce a high-performance electromagnetic radiation pattern. The novelty of this study lies in shaping patterns that mimic the shape of the targeted human organ in radiotherapy by steering a flat main beam from a square antenna array, along with optimal control of the sidelobe level. The proposed approach works by identifying the diseased organ captured from medical imaging, converting it into a binary image (black and white colors), and then feeding it into the antenna system to form a radiation pattern that accurately mimics the diseased organ. To reduce the systemic and computational complexity of the therapeutic antenna system, a sparsity technique was added to the hybrid algorithm. The computer simulation results showed high efficiency in generating robust patterns with sharp boundary profiles, such as those used for isolating diseased and undiseased tissues and measuring the tissue-specific absorption rate (TSAR), making it suitable for use in radiotherapy.