This paper provides sufficient conditions for the finite time stability of linear time invariant discrete descriptor time delay systems, mathematically described as Ex(k+1) = A0x(k) + A1x(t-h). A novel method was used to derive new delay dependent conditions. Stability of the system was analyzed using both the Lyapunov-like approach and the Jensen's inequality, including convolution of delayed states. The established conditions were applied to analysis of the system stability. In this case, the aggregation functional does not have to be positive in the state space domain and does not need to have the negative derivatives along the system trajectories. The system stability conditions were applicable to investigation of the finite time stability using the novel conditions proposed in this paper. This mathematical formulation guaranteed that the states of the systems do not exceed the predefined boundaries over a finite time interval.

In medical procedures, needle insertion is a challenging task highly dependent on the surgeon's manual skills. Implanted needles are used for drug delivery, biopsy, delivery of radiation sources, etc. In the named clinical procedures, the accuracy of the needle placement is crucial for patient treatment outcomes. Therefore, we have proposed an automated medical device for needle implantation to eliminate uncertainties of the standard procedures and to increase the accuracy of the needle placement. In this article, the mathematical model of such a device has been developed. The mathematical model takes into account the needle deflection; therefore, with the adequate development of the control strategy, the deflection could be minimized using predictive or adaptive controllers.

In external beam radiotherapy (EBRT), one of the major challenges is to compensate for target motion induced by patient's respiration and organ motion. The accurate delivery of radiation to the moving targets (tumors) requires new innovative technologies and methods to avoid excessive irradiation of healthy tissue. Recently, we developed a tracking method for target motion compensations, which includes the real-time motion of the robotic treatment couch and a prediction algorithm to correct the motion trajectory for the latency of the mechanical components of the system. The purpose of this study was to evaluate the tracking system efficacy, using different tumor motion trajectories collected from real patients diagnosed with lung cancer.

Modular software design is a technique that increase reusability and portability of software composed from separate parts, called modules. We have designed and developed a reusable integrated software solution for robotic prostate brachytherapy procedure. The application is capable of concurrent handling of all aspects of the image-guided brachytherapy procedure: ultrasound image acquisition, anatomic delineation, target modeling, dosimetry planning and analysis, seed delivery, and visualization of all surgerical steps involved in the procedure. Based on force feedback and visual feedback, the control module of the application is capable of controlling the robotic system (i.e. motions of the ultrasound probe and the needles), supervising the flow of the procedure via built-in strategies for emergency handling and recovery, collision avoidance, manual takeover (if necessary), needle tracking and real-time dose updates. The implementation of the developed software solution to the two brachytherapy robotic systems has been presented.

Respiratory and cardiac motions induce displacement and deformation of the tumor-volume in various internal organs. To accommodate this undesired movement and other errors, physicians incorporate a large margin around the tumor to delineate Planning Target Volume (PTV), so that the Clinical Target Volume (CTV) receives the prescribed radiation dose under any scenario. Consequently, a large volume of healthy tissue is irradiated and sometimes it is difficult to spare critical organs adjacent to the tumor. In this study we have proposed a novel approach to 4D Active Tracking and Dynamic Delivery (ATDD) together with tumor motion prediction. Proposed algorithm can predict tumor position and the robotic system can continuously track the tumor during radiation dose delivery, so that a precise dose is given to a moving target while reducing dose to nearby critical organs for improved patient treatment outcome. The efficacy of the proposed method has been investigated by extensive computer simulation. The results have been presented in this article.

Prediction of tumor motion is one of the important steps in active tracking of tumor and dynamic delivery of radiation dose to tumor. In this paper, we have presented a novel adaptive acceleration-enhanced normalized least mean squares (AE-nLMS) prediction filter based on the adaptive normalized least mean squares (nLMS) filter with predicted acceleration and ratio between the real and predicted acceleration taken into account. We have compared the performances of nLMS, artificial neural network (ANN), and AE-nLMS filter for predicting the respiration motion during normal and irregular respiration. The results revealed that the ANN filter has the best performance in the prediction of normal respiration motion, whereas the AE-nLMS filter outperformed other filters in the prediction of irregular respiration motion.

In low-dose-rate (LDR) brachytherapy, precise placement of needle and accurate delivery of radioactive seeds are very important and challenging. Therefore, development of robotic systems for performing brachytherapy is gaining significant momentum. In this paper, we present a multichannel robotic system developed for image-guided brachytherapy (IGBT), especially radioactive seed implantation in prostate gland. The developed multichannel robotic system is capable of inserting a large number of needles concurrently and depositing seeds automatically. Numerous techniques perfected by a variety of experiments have been implemented in the system design and development. Thus, this system possesses potential several advantages such as reduction of target displacement, edema, and operating time as compared to single needle insertion technique. Feasibility and efficacy of this robot has been demonstrated with experimental results. Seeds can be delivered with about within 0.2 mm accuracy.

Tumors in thorax region incur significant amount of motion and deformation due to respiratory and cardiac cycles. To accommodate this undesired movement, physicians incorporate a large standard margin around the tumor to delineate a Planning Target Volume (PTV), so that the Clinical Target Volume (CTV) receives the prescribed dose under any scenario. Consequently, a large volume of healthy tissue might be irradiated and sometimes it is difficult to spare critical organs adjacent to the tumor. For compensating this tumor motion, techniques such as breath-hold, gating, and Active Tracking and Dynamic Delivery (ATDD) are used. Although, ATDD is the most effective technique, it is the most challenging one. The ATDD can be accomplished in three different ways: adjusting the Multi-Leaf Collimator (MLC), adjusting the couch, and adjusting the MLC and couch simultaneously. The first two techniques have been explored and/or implemented in practice. However, the third approach has not been investigated extensively. In this study, we have proposed a novel approach for ATDD that exploits the advantages of both the MLC (or MLC-bank) and the HexaPOD™ robotic couch. In our proposed new approach, we have decomposed and allocated the tumor motion trajectory to the subsystems (MLC or MLC-bank and HexaPOD™ robotic couch) based on their natural frequency domains using wavelet technique. The efficacy of the proposed method has been investigated by extensive computer simulation and the results are presented in this paper.

As a technique for compensating for tumor motion induced by respiratory and cardiac motions, various dynamic approaches are being investigated and implemented in radiation therapy. This paper presents a novel system that can continuously track the tumor during radiation dose delivery so that a precise dose is given to a moving target while reducing dose to nearby critical organs for improved patient treatment outcome. The efficacy of the proposed methodology has been investigated by extensive computer simulation using a Proportional, Integral and Derivative (PID) controller. System design and simulation results are presented in this paper.