Orthopedic surgeons can play an essential role in healthcare innovation. But in order to truly benefit patients, innovations must first undergo stringent testing through randomised controlled trials.
Minimally invasive surgery utilises smaller incisions, specialized instruments, and advanced imaging technologies for reduced tissue disruption and faster recovery time. This technique includes arthroscopic procedures as well as minimally invasive spine surgeries.
Robotics
Orthopedic robots are becoming an essential tool in surgical practice. Their precision can assist surgeons in cutting and shaping bone, an integral step of orthopedic replacement surgeries.
Due to robotic systems’ precision, surgeons need less healthy bone tissue removed for procedures resulting in less stiffness and discomfort for patients after surgeries.
Robotic technology also has the additional benefit of allowing surgeons to utilize smaller tools, which reduces the risk of damaging nearby tissue while speeding recovery times for patients.
Skeptics of orthopedic robotics raise concerns over long-term effects and lack of data, yet researchers continue to work toward expanding this technology. According to a bibliometric analysis, global publications on robotic orthopedic surgery have increased since 2000 with the US being the primary contributor. Stryker has taken steps to collaborate with other organizations and make its robotic platform more adaptable so as to reach more surgical centers while expanding its potential uses across various orthopedic procedures.
Navigation
Technology and orthopaedics have recently come together in ways that are revolutionizing precision, customization and data collection in patient care. Innovations like navigation, augmented reality and smart sensors allow surgeons to increase accuracy during surgeries while providing better patient outcomes.
Surgical navigation allows surgeons to precisely locate instruments within the body, reducing complications and risk. It can also be used to guide procedures through needle-size incisions for more efficient procedures that reduce blood loss.
AR is providing orthopedic surgeons with a technology for more accurate surgery pre-planning using 3D holographic models. AR helps surgeons prepare for knee replacement surgeries and other operations with the aim of minimizing complications and speeding recovery times.
Minimally Invasive Techniques
Minimally invasive techniques refer to surgeries conducted through smaller incisions rather than large cuts, which enables surgeons to reach problem areas more safely while causing less trauma to surrounding tissues and organs. Minimally invasive surgeries have been linked with faster healing times and reduced post-procedure pain for patients.
Minimally invasive procedures can shorten recovery time from orthopedic issues like carpal tunnel syndrome, shoulder resurfacing surgery, spinal fusion and herniated discs by lessening damage to muscle tissue that requires the patient’s body to repair after invasive surgeries such as carpal tunnel surgery or shoulder resurfacing surgery. This is due to minimally invasive approaches being less likely to create scar tissue which requires further healing process from within their bodies.
Arthroscopy is one of the most frequently performed minimally invasive orthopedic procedures. It allows physicians to identify and treat tears, lesions, inflammation, bone spurs and other joint damage through small incisions with tubular retractor insertion that creates tunnel-like passageways from openings into problematic joint areas, pushing muscles out of their way and limiting muscle damage during surgery.
Artificial Intelligence
AI has gained ground in orthopedics, providing novel diagnostic tools and surgical approaches. AI is currently being utilized for image-based diagnosis of knee injuries, fractures, ligament and cartilage injuries, spinal disease, tumor assessment and bone age assessment among other orthopedic diseases.
One of the primary applications for artificial intelligence (AI) in orthopedics has been joint reconstruction, where robot-assisted surgery has proven integral in increasing implant success and clinical outcomes. MAKO utilizes CT scans to generate patient-specific 3D models which guide surgeons during procedures ensuring precise bone preparation and accurate placement of implants, as well as providing haptic feedback that prevents excessive bone resection and retains surgeon control of operations.
Other machine learning applications include forecasting injury risk patterns and aiding decision-making processes. A recent research project from NYU Langone Hospital used machine learning to standardize medical records with machine learning and train a model to detect certain biomarkers that allow doctors to predict which patients have increased post-operative complications risks.