Minimally invasive or laparoscopic surgery has completely changed the focus of surgery becoming an alternative to various types of open surgery. Minimally invasive surgery avoids invasive open surgery as the operation is performed through one or more small incisions in the abdomen and using a small camera called laparoscope. Through these incisions, surgeons insert specialized surgical instruments to perform the operation resulting in less postoperative pain, shorter hospital stay, and faster recovery. However, the main problems during minimally-invasive surgery are the limited space for operating instruments and the reduced visibility and range of motion inside the patient’s body. During minimally-invasive surgery, one of the most difficult and time consuming surgical procedures is suturing and knot tying. This procedure significantly increases the operation time as it requires advanced techniques and extensive experience by surgeons.The main goal of this research is to investigate, design, and develop a new suturing instrument to facilitate suturing procedures during minimally invasive surgery.Qualitative research data was collected through interviews with a surgeon and six indepth observations of minimally invasive surgeries at Tampa General Hospital. Different design concepts and mechanisms were created using SolidWorks CAD software, and tested using SimulationXpress in order to identify dimensions, materials and expected performance of the design and its components. The prototypes of the device were made using a Dimension SST 768 FDM machine and tested by the surgeon to ensure that the final design meets the specified needs and criteria. This new device will eliminate the use of many different devices during the operation and allow the use of any type of suture. The proposed suturing device aims to benefit both patients and surgeons. For surgeons, the new device aims to decrease the number of steps for laparoscopic suturing through an intuitive and ergonomic design. For patients, the proposed device will reduce time during surgery and under general anesthesia leading towards improved health care.

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<p>Intra-Arterial Chemotherapy (IAC) is a preferred treatment for the primary liver cancer, despite its adverse side-effects. During IAC, a mixture of chemotherapeutic drugs, e.g. Doxorubicin, is injected into an artery supplying the tumor. A fraction of Doxorubicin is absorbed by the tumor, but the remaining drug passes into systemic circulation, causing irreversible heart failure. The efficiency and safety of the IAC can be improved by chemical filtration of the excessive drugs with a catheter-based Chemofilter device, as proposed by a team of neuroradilogists. </p> <p>The objective of my work was to optimize the hemodynamic and drug binding performance of the Chemofilter device, using Computational Fluid Dynamics (CFD) modeling. For this, I investigated the performance of two distinct Chemofilter configurations: 1) a porous “Chemofilter basket” formed by a lattice of micro-cells and 2) a non-porous “honeycomb Chemofilter” consisting of parallel hexagonal channels. A multiscale modeling approach was developed to resolve the flow through a representative section of the porous membrane and subsequently characterize the overall performance of the device. A heat and mass transfer analogy was utilized to facilitate the comparison of alternative honeycomb configurations. </p> A multiphysics approach was developed for modeling the electrochemical binding of Doxorubicin to the anionic surface of the Chemofilter. An effective diffusion coefficient was derived based on dilute and concentrated solution theory, to account for the induced migration of ions. Computational predictions were supported by results of <i>in-vivo</i> studies performed by collaborators. CFD models showed that the honeycomb Chemofilter is the most advantageous configuration with 66.8% drug elimination and 2.9 mm-Hg pressure drop across the device. Another facet of the Chemofilter project was its surface design with shark-skin inspired texturing, which improves the binding performance by up to 3.5%. Computational modeling enables optimization of the chemofiltration device, thus allowing the increase of drug dose while reducing systemic toxicity of IAC.