Overview of Research Projects

Engineering research in surgical technologies is a thriving field. At Duke, many surgical technologies are being developed in research labs, some of which are already deployed for testing in the operating room. Notably, current research efforts at Duke include automated laser scalpel systems for neurosurgery (Codd) and dermatology (Burton); advanced imaging technologies with micrometer resolution including photo-acoustic microscopy (Yao) and advanced optical coherence tomography (OCT); and techniques for measuring and analyzing surgeon performance on robotic surgical systems (Mann), among others. Many of these researchers are participants in this proposal and will serve as Faculty advisors, mentors, and lecturers for the TAST trainees. Trainees will be exposed to these research topics and more through the following research groups.

Surgical Data Science (Zani and Mann)

The ever-increasing complexity of surgery, made possible by advances in surgical techniques and technologies, has put a strain on traditional techniques for evaluating surgical interventions. Existing approaches for evaluating surgical interventions rely on subjective reviews, the integration of which into day-to-day activities, although insightful, would be cost-prohibitive, prone to bias, and time-consuming. The modern, data-rich surgical environment has established a new field of research that uses techniques in data science to objectively describe and evaluate the proficiency of surgeons and their efficacy within the operating room. This work will be spearheaded by Duke Research in Engineering and Surgical Technologies (REST). The main focus of Duke REST is to develop novel and robust computational approaches to the analysis of the surgical workflow, providing insight in to the efficacy of surgical staff and surgical technique, as well as identifying surgical errors. The overarching goal of this research is to streamline surgical interventions, optimize the education of surgical staff and maximize patient safety.

Intelligent Surgical Tools (Codd)

Surgeons are provided with a plethora of information about the patient’s vital signs and state of the surgical site, both pre-and intraoperatively, from a variety of imaging modalities including MRI, CT, Ultrasound, OCT, and direct view of the surgery with microscopes and the like. All the while, they are tasked with reviewing and considering this information whilst performing the surgery itself, oftentimes with mechanical tooling. Tumorous tissue is mechanically separated and aspirated away from adjacent structures, imparting potentially damaging forces on the otherwise healthy surrounding tissue. More recently, the adoption of laser scalpels has grown, though they are frequently invisible to the human eye and therefore difficult to precisely control. Needless to say, surgeons are already operating at the peak of their abilities given the tools available. As advanced technologies for imaging and surgical action are developed, limitations arise from the workload and precision limits of the human surgeon. So, intelligent surgical tools capable of synthesizing multiple modalities of imaging and performing precision guidance of surgical tooling will be a necessary next step in enabling future advanced surgical technologies. This requires research at the intersection of control theory, intraoperative medical image processing, surgical path planning, and precision guidance of surgical tools with the development of new surgical tools and characterizing their effects on tissues for modeling purposes. The Brain Tool Laboratory, headed by PI Patrick Codd, develops intelligent imaging and surgical systems for various applications ranging from tattoo removal to neurosurgery.

Additive Manufacturing for Surgical Technologies (Gall)

A fundamental understanding of the relationship between the processing, structure, and mechanical properties of materials is critical for biomaterials and their application in the biomedical field. Research in Prof. Ken Gall’s lab spans three major classes of materials: metals, polymers, and ceramics. Their interactions, architectures, and processing techniques are investigated for their efficacy for future clinical applications. Specifically, 3D printing is used to create implantable devices with improved mechanical behavior for translational research applications in regenerative medicine, tissue engineering, and other clinical applications. The main expertise of the group lies in the creation, modification, understanding, and commercialization of synthetic biomaterials. The use of novel implantable materials will allow for the advancement of surgical techniques by expanding the array of surgical skills and procedures.

Robotic Systems for Acute Medical Care (Buckland)

The Duke Acute Care Technology Lab (DACTL) works at the interface of robotics, autonomy, and human users in safety-critical systems, particularly in autonomous robotics for procedures in acute medical care. Utilizing Dr. Buckland’s unique dual role as a practicing clinician in the Duke University Hospital Emergency Department and as research faculty in the Department of Mechanical Engineering and Materials Science, the DACTL group trains both engineers and clinicians to work both independently and collaboratively on engineering solutions to clinical needs. TAST trainees will develop fundamental technologies that utilize computer vision and autonomous systems to image and access diverse tissue types in-vivo. The initial focus of the technology is on venous access, a critical bottleneck in the delivery or operation of most laboratory testing and medications. Automated venous access technology could allow nurses and healthcare providers to focus on difficult-access patients and the multitude of other tasks that are needed.

Soft Robotics, Control, and AI for Teleoperation (Bridgeman) 

Society is presently undergoing a revolution in automation. Machine learning and nearly ubiquitous connectivity are expanding the capabilities and use of robotics. However, strong safety and reliability guarantees are required to unleash the full potential for surgical robots to function with the autonomy society envisions. PI Bridgeman studies robust and optimal control, developing techniques to ensure systems function despite changing environments, noisy forces, inputs, and sensor measurements, uncertain system parameters, and variable configurations. Specifically, PI Bridgeman’s research into a time delay and sparse control will enable reliable teleoperation of surgical robots over long distances and unreliable networks.  Her research into the control of constrained, switched systems will enable collaborative robotics, and her research into passivity and conic-sector-based techniques will enable enhanced control of flexible robotics that can interact safely with humans.

Machine Learning for Surgical Technologies (Carlson)

Machine learning tools have the power to help build novel support systems for many surgical techniques by extracting information from complex sources (sensors, videos, etc.). However, there is often skepticism from practitioners over the introduction of new techniques: when should they really be trusted? Towards that end, Carlson’s research group focuses on building explainable machine learning techniques so that the decision path can be interpreted and communicated to end users. By also properly assessing confidence (e.g., the algorithm knows when it doesn’t know), we can begin building more trustworthy algorithms that can make their way into practice. In conjunction with the NRT Trainees, we will build and evaluate these novel algorithmic techniques. Notably, Prof. Carlson’s faculty appointment is split across the engineering school and the medical school, and the Ph.D. students in his research group go through programs on both sides.  This uncommon setup allows us to both build and transition technologies in a highly interdisciplinary environment—exactly the type of environment necessary for success in such a highly interdisciplinary program.

Non-Invasive Surgical Techniques and Technologies (Zhong)

Surgical procedures have evolved significantly in the past decades from open surgery to minimally invasive and non-invasive surgery. This critical transformation in surgical techniques and technologies has been driven by the desire to improve the quality of surgery outcomes, reduce collateral injury, and shorten patient recovery time. A primary example is image-guided surgery using high-intensity focused ultrasound (HIFU) for tumor ablation or tissue fractionation and focused shock waves (known as shock wave lithotripsy) for non-invasive disintegration of kidney stones in patients. Although widely used in clinics, the lithotripsy procedure is largely empirical, and the mechanism of action has yet to be fully understood. Therefore, fundamental research is needed to gain physical and biological insights into the interaction of focused shock waves with biological tissues (including concretions) to improve the performance and safety of existing devices and for advancing lithotripsy technologies. This requires close collaborations between engineers and urologic surgeons to carry out research from in vitro phantom tests, and computational modeling, to in vivo animal experiments and clinical trials. The Lithotripsy and Therapeutic Ultrasound Laboratory, headed by PI Pei Zhong, focuses on fundamental and translational research ranging from shock wave and laser lithotripsy, to HIFU-boosted cancer immunotherapy and ultrasound neuromodulation.

Imaging tools for Intrasurgical Guidance (Wax)

The BIOS laboratory (Adam Wax, PI) develops optical techniques for assessing the structural and functional features of cells and tissues using light scattering and interferometry. Among the compelling applications of this approach is the ability to diagnose disease and pathology based on measuring cellular morphology in vivo without the need for exogenous contrast agents. We have brought six different imaging technologies through clinical trials. These include endoscopic depth-resolved imaging of the esophageal endothelium, endoscopic early cancer detection in the esophagus using light scattering, imaging the pharmacokinetics of topically applied drugs to the vaginal epithelium, early cancer detection in the cervix using light scattering, and most recently a combined imaging platform for visualizing the transformation zone of the cervical epithelium with detection of dysplastic lesions using light scattering. A significant advance from our laboratory in our lab in recent years is the introduction of the first low-cost Optical Coherence Tomography (OCT) device. OCT has been established as the gold standard for the early detection of retinal disease but its cost of $35-100k limits access to this technology. We introduced an OCT scanner with a cost of $5,000 which will allow greater use for retinal screening, particularly in low-resource settings such as the developing world, and the development of novel applications of OCT, such as intrasurgical use, where the high cost of instrumentation has been a barrier to developing effective tools. TAST trainees will develop skills in the design and implementation of novel optical tools and instruments as well as participating in translational efforts that bring these technologies to bear on human health care.