Patient-Specific Implants in Musculoskeletal (Orthopedic) Surgery

Most of the treatments in medicine are patient specific, aren’t they? So why should we bother with individualizing implants if we adapt our therapy to patients anyway? Looking at the neighboring field of oncologic treatment, you would not question the fact that individualization of tumor therapy with personalized antibodies has led to the thriving of this field in terms of success in patient survival and positive responses to alternatives for conventional treatments. Regarding the latest cutting-edge developments in orthopedic surgery and biotechnology, including new imaging techniques and 3D-printing of bone substitutes as well as implants, we do have an armamentarium available to stimulate the race for innovation in medicine. This Special Issue of Journal of Personalized Medicine will gather all relevant new and developed techniques already in clinical practice. Examples include the developments in revision arthroplasty and tumor (pelvic replacement) surgery to recreate individual defects, individualized implants for primary arthroplasty to establish physiological joint kinematics, and personalized implants in fracture treatment, to name but a few

Craniofacial Growth Series Volume 56

https://deepblue.lib.umich.edu/bitstream/2027.42/153991/1/56th volume CF growth series FINAL 02262020.pdfDescription of 56th volume CF growth series FINAL 02262020.pdf : Proceedings of the 46th Annual Moyers Symposium and 44th Moyers Presymposiu

Advanced Applications of Rapid Prototyping Technology in Modern Engineering

Rapid prototyping (RP) technology has been widely known and appreciated due to its flexible and customized manufacturing capabilities. The widely studied RP techniques include stereolithography apparatus (SLA), selective laser sintering (SLS), three-dimensional printing (3DP), fused deposition modeling (FDM), 3D plotting, solid ground curing (SGC), multiphase jet solidification (MJS), laminated object manufacturing (LOM). Different techniques are associated with different materials and/or processing principles and thus are devoted to specific applications. RP technology has no longer been only for prototype building rather has been extended for real industrial manufacturing solutions. Today, the RP technology has contributed to almost all engineering areas that include mechanical, materials, industrial, aerospace, electrical and most recently biomedical engineering. This book aims to present the advanced development of RP technologies in various engineering areas as the solutions to the real world engineering problems

Smart actuation and sensing for meso-scale surgical robotic systems

This dissertation presents the development of meso-scale surgical robotics based on smart actuation and sensing for minimally invasive surgery (MIS). By replacing conventional straight tools by steerable surgical robots, surgical outcomes can potentially be improved due to more precise, stable, and flexible manipulation. Since bending and torsion are the two fundamental motion forms required by surgical tools to complete general surgical procedures, compact torsion and bending modules, both integrated with intrinsic sensors for motion feedback, have been developed based on shape memory alloy (SMA). The developed actuation and sensing techniques have been applied on a robot for neurosurgical intracerebral hemorrhage evacuation (NICHE) and a steerable catheter for atrial fibrillation (AFib) treatment. The NICHE robot consists of a straight stem, an SMA torsion module, and an SMA bending module as a distal bending tip. By synchronizing the motion of the stem, the bending module, and the torsion module, the robot is capable of tip articulation within the brain to remove hemorrhage effectively through suction and electrocauterization. In addition, a skull-mounted robotic headframe has been developed based on a Stewart platform to manipulate the NICHE robot. The robotic catheter is developed by integrating multiple SMA bending modules with flexible braid reinforced tubing. Polymer 3D-printing is used to fabricate all the structural components due to its relatively low cost, short fabrication period, and capability of fabricating complicated structures with high accuracy. The developed surgical robotic systems have been thoroughly evaluated using phantom or cadaver models under computed tomography (CT) and/or magnetic resonance imaging (MRI) guidance. The imaging-guided experimental studies showed that the developed robotic systems consisting of smart actuation and sensing were compatible with CT and MR imaging.Ph.D

Multimodal Noncontact Tracking of Surgical Instruments

For many procedures, open surgery is being replaced with minimally invasive surgical (MIS) techniques. The advantages of MIS include reduced operative trauma and fewer complications leading to faster patient recovery, better cosmetic results and shorter hospital stays. As the demand for MIS procedures increases, effective surgical training tools must be developed to improve procedure efficiency and patient safety. Motion tracking of laparoscopic instruments can provide objective skills assessment for novices and experienced users. The most common approaches to noncontact motion capture are optical and electromagnetic (EM) tracking systems, though each approach has operational limitations. Optical trackers are prone to occlusion and the performance of EM trackers degrades in the presence of magnetic and ferromagnetic material. The cost of these systems also limits their availability for surgical training and clinical environments. This thesis describes the development and validation of a novel, noncontact laparoscopic tracking system as an inexpensive alternative to current technology. This system is based on the fusion of inertial, magnetic and distance sensing to generate real-time, 6-DOF pose data. Orientation is estimated using a Kalman-filtered attitude-heading reference system (AHRS) and restricted motion at the trocar provides a datum from which position information can be recovered. The Inertial and Range-Enhanced Surgical (IRES) Tracker was prototyped, then validated using a MIS training box and by comparison to an EM tracking system. Results of IRES tracker testing showed similar performance to an EM tracker with position error as low as 1.25 mm RMS and orientation error \u3c0.58 degrees RMS along each axis. The IRES tracker also displayed greater precision and superior magnetic interference rejection capabilities. At a fraction of the cost of current laparoscopic tracking methods, the IRES tracking system would provide an excellent alternative for use in surgical training and skills assessment

On Sensor-Controlled Robotized One-off Manufacturing

A semi-automatic task oriented system structure has been developed and tested on an arc welding application. In normal industrial robot programming, the path is created and the process is based upon the decided path. Here a process-oriented method is proposed instead. It is natural to focus on the process, since the path is in reality a result of process needs. Another benefit of choosing process focus, is that it automatically leads us into task oriented thoughts, which in turn can be split in sub-tasks, one for each part of the process with similar process-characteristics. By carefully choosing and encapsulating the information needed to execute a sub-task, this component can be re-used whenever the actual subtask occurs. By using virtual sensors and generic interfaces to robots and sensors, applications built upon the system design do not change between simulation and actual shop floor runs. The system allows a mix of real- and simulated components during simulation and run-time

NASA Tech Briefs, February 1996

Topics covered include: Materials; Computer Programs; Mechanics; Machinery/Automation; Manufacturing/Fabrication; Mathematics and Information Sciences; Life Sciences; Books and Reports

AN AUTOMATED, DEEP LEARNING APPROACH TO SYSTEMATICALLY & SEQUENTIALLY DERIVE THREE-DIMENSIONAL KNEE KINEMATICS DIRECTLY FROM TWO-DIMENSIONAL FLUOROSCOPIC VIDEO

Total knee arthroplasty (TKA), also known as total knee replacement, is a surgical procedure to replace damaged parts of the knee joint with artificial components. It aims to relieve pain and improve knee function. TKA can improve knee kinematics and reduce pain, but it may also cause altered joint mechanics and complications. Proper patient selection, implant design, and surgical technique are important for successful outcomes. Kinematics analysis plays a vital role in TKA by evaluating knee joint movement and mechanics. It helps assess surgery success, guides implant and technique selection, informs implant design improvements, detects problems early, and improves patient outcomes. However, evaluating the kinematics of patients using conventional approaches presents significant challenges. The reliance on 3D CAD models limits applicability, as not all patients have access to such models. Moreover, the manual and time-consuming nature of the process makes it impractical for timely evaluations. Furthermore, the evaluation is confined to laboratory settings, limiting its feasibility in various locations. This study aims to address these limitations by introducing a new methodology for analyzing in vivo 3D kinematics using an automated deep learning approach. The proposed methodology involves several steps, starting with image segmentation of the femur and tibia using a robust deep learning approach. Subsequently, 3D reconstruction of the implants is performed, followed by automated registration. Finally, efficient knee kinematics modeling is conducted. The final kinematics results showed potential for reducing workload and increasing efficiency. The algorithms demonstrated high speed and accuracy, which could enable real-time TKA kinematics analysis in the operating room or clinical settings. Unlike previous studies that relied on sponsorships and limited patient samples, this algorithm allows the analysis of any patient, anywhere, and at any time, accommodating larger subject populations and complete fluoroscopic sequences. Although further improvements can be made, the study showcases the potential of machine learning to expand access to TKA analysis tools and advance biomedical engineering applications