Computer-assisted surgery: Evolution and basic concepts

As the field of robotics evolves, so too does our willingness to welcome technology into traditionally human-dominated realms. Computer-assisted surgery (CAS) is available for the modern operating room and is constantly being refined to enhance functionality, precision, and cost-effectiveness. Part 1 chronicles some of the evolution of CAS, looking at terminology and basic concepts.

Through the ages, humans have been fascinated with the idea of automated devices that serve our needs. Consider Hephaestus’ mechanical servants in Greek mythology [1]. We have been entranced by the potential of machines for millennia [2,3]. Now, our capabilities are catching up to our imaginings: take a look at robotics lab Boston Dynamics’ newest commercial robot, Spot® [4].

Advancements in technology, combined with interdisciplinary team collaboration, is propelling the integration of innovations in materials, computing, and medicine to bring a technological revolution to the operating room (OR) across all surgical disciplines.


What is computer-assisted surgery?

Computer-assisted surgery (CAS) is a umbrella term that encompasses different kinds of technologies that are used to [1]: perform surgical procedures, in part or in their entirety [2]; guide or navigate during surgery [3]; plan surgeries [4]; train less experienced surgeons [5]; and create patient-specific instruments (PSI) [5–7]. It is sometimes referred to as computer-aided surgery, computer-assisted intervention, surgical robots, image-guided surgery, or surgical navigation, depending on what the technology does [5, 7, 8].

CAS helps orthopedic surgeons perform surgery with increased precision and reproducibility, which is believed to have a positive impact on clinical and functional outcomes. There are two categories of CAS: robotic-assisted surgery, where a motor moves the technology, and general CAS (usually navigation systems), where the surgeon physically moves the technology [9].


Ahmed Magan

BM BSc (Hons) MRCS (Eng) FRCS (Eng), Trauma & Orth. University College London Hospital NHS Foundation Trust, Trauma and Orthopaedics Department, UK

Ahmed Magan, Trauma and Orthopedic Surgeon with University College London Hospital NHS Foundation Trust, UK, notes that robotic surgery in particular “has revolutionized surgical practice—from planning through to the execution of the operation. It is easy to learn and the results are reproducible.”


It all started with the brain

The pioneering work of CAS was in the field of neurosurgery in the early 1900s. Two British academics working at University College London Hospital, Sir Victory Horsley (professor of neurosurgery and a neuroscientist) and British physiologist, Robert Clarke, collaborated on the development of a stereotactic apparatus for locating lesions in the brain in 1908.

It essentially involved attaching the cranium to the “Horsley-Clarke Apparatus” and inserting a probe into an area of interest with some degree of accuracy. Their work was based on three-dimensional (3D) Cartesian geometry of a monkey brain [10]. It is no wonder that their invention lacked precision and required further work.


Applications of CAS

Over time, CAS systems have been developed for use in a wide range of surgical disciplines. An indicator of the growth of the field is that in 1999, only 14 articles indexed in PubMed included “computer-assisted surgery” or “robotic surgery” in their titles or abstracts, while by 2019, 1,027 articles were published.

Neurosurgery was the first field to employ CAS [8, 11, 12], and the technology has expanded to support myriad surgical interventions. Here are a few examples:

  • Total hip arthroplasty (THA): Robotic THA was found to improve acetabular implant positioning and reduce dislocations compared to manual THA [13, 14].
  • Partial and total knee arthroplasty (TKA): Using navigation in TKA was associated with higher clinical accuracy in implant placement [15] and robot-assisted TKAs also improved implant positioning [16].
  • Osteotomies: Using 3D-planned patient-specific instrumentation (PSI) and navigation in high tibial open wedge valgus-producing osteotomies resulted in accurately corrected mechanical leg axis [17].
  • Tumors: Minimally invasive robotic hepatectomy for liver tumors has been shown to be “safe and feasible” [18]. Intraoperative computer-assisted navigation and 3D PSI printing facilitated a successful surgical resection of metastatic acetabular osteosarcoma, ultimately preserving the patient’s hip stability and providing better quality of life for two palliative years [19].
  • Neurosurgery: Robot-assisted drainage of thalamic hemorrhages improved patients’ prognoses and was associated with reduced cases of pneumonia and renal dysfunction [20].
  • Spine surgery: A study of 18 patients that received navigation-assisted surgery for a primary spine tumor indicated that it was beneficial in the resection of tumors due to more accurate screw placement and fewer complications [21].
  • Dental implants: Compared with a novice freehand implant placement group, novices using navigation were able to achieve implant placement in mandible models with an accuracy similar to that of experienced professionals [22].

In relation to orthopedics, Ahmed Magan highlights that, “In terms of contributions, computer-assisted surgery has been a real game-changer in partial and TKA. With this procedure, the outcome is related to the alignment, balance, and soft tissue preservation and there is technology available to help surgeons achieve these factors in more reliable, repeatable ways.

“However, there are barriers to this technology being widely adopted and available in all ORs such as, added operative time, being limited to implants specific to the system, resistance to new technology training for theater staff and cost implications.”

[See Part 2 of this article series for more in-depth discussion of CAS in modern orthopedics and associated benefits and risks.]


Classification of CAS systems

As CAS technology has expanded, how these technologies are classified has also evolved. There is a wide range of applications for CAS and since the 1990s numerous classification schemes have been suggested, with some common unifying elements [23, 24].

What has emerged is a general classification by functionality and surgeon operation (active, semi-active, passive) with a secondary consideration within navigation systems of how the reference system and surgical plan is defined (image-based, imageless) [5, 23, 25] [See Table 1].

In 2000, Picard et al proposed broadly classifying computer-assisted surgical technologies as either robotic assistive systems, where patient-specific models are used and actual machine-controlled contact with a patient occurs (active), or surgical navigation systems, where surgeons use optical or magnetic markers to track their tools/anatomy and receive intraoperative guidance compared with their surgical plan (passive) [26]. As time has passed, some CAS technologies have been introduced that incorporate elements of both.


Table 1. Different types of computer-assisted surgical (CAS) systems


Active CAS systems execute preprogrammed tasks autonomously, such as drilling, while a surgeon oversees the procedure. They offer an interface between the surgeon and the patient, often with the intent to decrease human error [27, 28]. A motorized system moves the surgical tools and is capable of tirelessly performing preoperatively programmed, repetitive motions. This category aligns with what one would be most likely to label as a “robot”.

Semi-active/Haptic systems combine surgeon-controlled elements with preprogrammed elements in a complementary manner. Such a system might involve a robotic arm controlled by the surgeon that holds tools but will not move outside a predetermined milling path boundary [29].


What is haptic feedback?

Haptic feedback is the touch (force and tactile) information surgeons intuitively receive during their physical interaction with tissues and bone during surgery. Subconscious evaluation of this information allows them to adjust their movements in order to exert appropriate force to the tissues. Surgeons and engineers are working together to increase the haptic capabilities of surgical robots as the lack of effective feedback is a limitation for CAS [30].

Image: Used with permission under CC BY-SA 1.0 license. By: Shadow Robot Company

Another example of a semi-active CAS system is a teleoperated master-slave system [25]. In this case, a surgeon’s hand movements are translated into surgical actions performed by a robot with the surgeon at a distance, whether in the same room or further apart [31].


Passive CAS as a category is comprised of navigation systems, which is further broken down into image-based or imageless platforms, depending on if they use images and how those images are acquired [29, 37] [See Table 2]. They are used in preoperative planning as well as intraoperatively to monitor and compare a procedure to the plan in real-time; some systems combine these functions.

Navigation equipment can help: “1) to assess joint irregularities and joint biomechanics; 2) to make recommendations on how to continue with the procedure, when assessing ligament balancing, for instance; and 3) to monitor the accuracy of the bone cuts.” [38] Surgeons can override any recommendation made by these systems. The majority of CAS systems used in ORs today are tracking/navigation systems [27, 28, 39].



Navigation systems can be imagined as a global positioning system (GPS) for surgeons and are used in many surgical disciplines [40]. In orthopedics, navigation systems are used to plan optimized, patient-specific implant placements as well as guide a surgeon through achieving their plan. Table 2 compares the two kinds of navigation systems (image-based and imageless). Keep in mind that many navigation systems combine elements of both types, for example, to facilitate optimized preoperative planning based on images, then real-time registration and intraoperative monitoring to compare progress against the plan.

In TKA and THA, Ahmed Magan prefers using image-based navigation. “It is also fantastic for planning complex cases with abnormal anatomy. However, for the few patients who may have reservations about radiation exposure, imageless navigation system would be suitable.

“In cases where urgent intervention is required, imageless navigation may be easier to use as there is no need to wait for a turnaround for computed tomography (CT) scans to be scheduled and performed. There is always an economic consideration on which type to use as well: imageless navigation systems tend to be less expensive than image-based ones.”


Table 2. Features of image-based and imageless navigation systems


One task that is common to both types of navigation is registration. The surgeon goes through a set sequence of actions unique to each system to manually identify key anatomical landmarks for the computer [41]. Paired with software that helps surgeons digitally plan an optimized procedure, accurate registration is critical to the success of a navigated procedure.


Image-based navigation

In image-based navigation, a computer creates a 3D volumetric model of the patient’s anatomy using information from preoperative images taken with either x-rays, CT, or magnetic resonance imaging (MRI). Ultrasound images can be obtained before and during a procedure [42]. Fluoroscopy is used to gather 2D or 3D images intraoperatively.

Navigation systems can integrate a combination of these, for example preoperative CT scans with intraoperative fluoroscopy, or use just one whereby the preoperative images are registered against positioning determined by a static marker fixed to a patient. Then, images either taken pre- or intraoperatively are correlated with the patient’s anatomy and/or what tracking cameras “see” during the operation—the process referred to as registration [43].

Types of imaging:

  • Computed tomography (CT): Commonly used in navigation because of its high-resolution images that offer good contrast between bone and soft tissue allowing precise modeling with short scanning times [44]. It is expensive [45], exposes patients and healthcare workers to ionizing radiation, and some may have adverse reactions to the contrast dyes used [46]. Requires drilling and “rigidly” mounting a tracking device/marker on the patient’s anatomy to infer their position, which is impossible to do for small bones and could prolong recovery [47].
  • Magnetic resonance imaging (MRI): Although it is also expensive [45], MRI results in higher-resolution images with better soft tissue contrast than CT. No ionizing radiation exposure but the strong magnetic field generated could heat or move existing implants within patients [48]. See Figure 1.



Figure 1. MRI scanner. Used with permission under CC by 2.0 license. By: Joyce Kaes.

  • Ultrasound: With no ionizing radiation exposure for patients and healthcare workers [47], this 3D image gathering modality showed promise in producing good registration for bone when paired with preoperative CT scans and used in real-time, intraoperatively [49, 50]. However, several technical challenges exist including imaging artifacts and bone surfaces appearing on screen with same intensity as soft tissue interfaces [45]. Does not require mounting a tracking device [47].
  • Fluoroscopy 2D and 3D: has a lower cost than the previously described imaging modalities [44].
    • 2D: C-arms needed to produce these images are readily available for many surgeons and there is less intraoperative radiation exposure than CT scans [47, 51]. However, drawbacks include inferior delineation of anatomical structures [51], overlapping images of bone [47], and distorted images [43].
    • 3D: Software constructs 3D volumetric images from up to a hundred 2D C-arm acquired images that are somewhat comparable to CT scans [43]. Some authors have reported this results in higher levels of ionizing radiation exposure when compared to 2D fluoroscopy [44] but others have determined the exposure to be less [52]. Better image quality than 2D fluoroscopy.


Imageless navigation

When compared with image-based systems, imageless navigation systems are touted for their reduced time and cost requirements, and some have referred to them as the “gold standard” [53] for navigation. Less personnel are needed to take intraoperative images, radiation exposure for the surgical team and patient is avoided, and no time needs to be allocated for scanning [54].

These systems were originally developed for THA and TKA surgery [44, 55]. No images are taken before or during the surgery, instead, the surgeon defines the anatomy by sliding the tip of a specialized instrument over its surface [24].

Markers (dynamic reference frame [DRF]) that emit infrared light are attached to target a bone and instruments (rigid bodies), and an optoelectrical tracker (camera) monitors their positioning in relation to each other with rapid and precise measurements [44, 53]. Markers are usually grouped in “constellations” of three to six to allow triangulation between them; more markers placed on each rigid body (up to six markers) increases accuracy [56].

The many data points are synthesized by computer software to generate a virtual model. Joint kinetic information and bone morphology is also collected; some readings do not require surgical access, such as the center of the femoral head landmark which is calculated via the legs’ passive rotation around the acetabulum [43].


Patient-specific instrumentation (PSI)

Another application of CAS is the creation of single-use PSI or implant components. This was introduced in the 1990s for pedicle screw placement, TKA, decompression of the cervical spine, and triple osteotomy of the pelvis [57].

In the field of orthopedics, CT or MRI scans are used together with specialized software to develop and manufacture (or 3D print) cutting guides or “jigs” customized to a patient’s anatomy [58]. The idea is that these will help a surgeon perform exact resections that match the surgical plan generated by the software. A 2020 meta-analysis of PSI (cutting blocks) in TKA highlighted reduced blood loss and improved Knee Society Scores (KSS); compared with CT-based PSI, MRI-based PSI was associated with reduced operating time and fewer mechanical axis malalignments [59].

In discussing his personal experience using PSI in TKA, Ahmed Magan notes that he “found it relatively straight forward to use”, but cautions that “PSI is based on preoperative imaging and cannot be amended intraoperatively to accommodate soft tissue balance. Obtaining correct fit of the cutting guides can be a challenge, and if not applied correctly can cause implant malpositioning, which is sometimes difficult to ascertain intraoperatively.”


In this 4-minute video, Adolph Lombardi Jr, MD, FACS, discusses how patient-specific instrumentation has been used in orthopedic surgery (from

However, there have been numerous criticisms of PSI, such as the increased costs related to obtaining adequate imaging and the manufacturing— it can only be used once and is then discarded. One study showed that using PSI can add an additional CAD 1,787 per case [60]. Surgeons are also advised to keep a set of standard instruments available as back-up if the PSI do not work for any reason [61].


Optimized positioning system

Lower limb arthroplasty research and development continues at an impressive rate. The improved longevity of implants has led to an interest in further improvement in implant position to match patients’ own anatomy. The Optimized Positioning SystemTM (OPSTM, Corin, UK) merges biomechanical modelling of patients’ movement with PSI, adding a new layer of consideration for arthroplasties—pre-existing functionality.

In recent years, THA implants within the “normal safe zone” have been shown to not be safe for everyone and that spinopelvic motion does not always influence outcome. Stiff spines result in loss of normal spinopelvic mobility that may result in impingement and dislocation [62]. Based on preoperative x-ray and CT images, OPSTM software models/simulates the biomechanical loading of a hip joint as it moves during different daily activities. The consideration of how the femur, spine, and pelvis work together offers unique insight into dynamic relationships that influence optimized placement of implants. All this information is then synthesized to design a 3D-printed patient-specific guide for component placement [63–65]. Although OPSTM is in its infancy, the early data looks promising [66]. OPSTM utilizes PSI and patient-specific dynamic analysis to allow the surgeon to plan and insert acetabular cups with more accuracy.


Virtual and augmented reality

Virtual reality (VR) involves a computer generated 3D environment that a person can view on a screen and interact with in a seemingly realistic or physical manner [67]. It is increasingly being used in training for surgical procedures that can be deconstructed into steps, which a learner can rehearse and be assessed on without exposing a patient to undue risk [68, 69]. Using VR for training has been shown to reduce the operative time and complication rate for specific procedures performed by surgical trainees [66, 70].

Augmented reality (AR) enhances the perception of reality by layering a digital object on top of reality [71]. Called a “disruptive” technology in the medical sphere, AR as a CAS system overlays a projected 3D virtual model over the surgical field [72], or can show a surgeon images through special lenses or monitors [73]. For example, it can direct the safe corridors of screw placement to the surgeon or guide the surgeon in what instruments they need next [74].

In 2006, an early AR device was designed that took a near infrared image of veins in a patient then projected it on to the skin in a green light. It identified veins too shallow to be found with ultrasound and those invisible to the naked eye [75]. To illustrate how this technology has evolved, a 2020 publication describes participant surgeons using a head-mounted display called “System for Telementoring with Augmented Reality (STAR)” that connected them in VR to expert guidance to conduct leg fasciotomies on cadavers. Fewer errors, better performance scores, and self-reported higher confidence levels were reported when compared to participants who independently reviewed the procedure with a mentor, indicating the technology could be used to train and support surgeons in remote areas or low-volume centers [76].



In this video update on the capabilities and features of System for Telementoring with Augmented Reality (STAR), ultrasound, vital sign monitoring, and image stabilization are highlighted for their ability to communicate critical onsite patient information to remote mentors.

While AR has been used in neuro- and visceral surgical fields for some time, a systematic review of studies involving AR in orthopedics, published in 2020, found that AR showed promising results in implant placement, osteotomies, tumor surgery, trauma, and surgeon training/education. The authors of the review concluded: “AR has the potential to be a timesaving, risk and radiation reducing, and accuracy enhancing technology in orthopedic surgery.” [72]


Artificial intelligence

Reasoning, perception, planning, and learning are characteristics we generally associate with humans. However, as computer science evolves, the field of artificial intelligence (AI) is pushing our understanding and acceptance of what machines can do.

Often called “machine learning”, AI refers to human-like intelligence that machines can mimic. AI techniques are being used in healthcare to solve a wide range of problems such as generating equations to calculate more precise medication dosing [77], prescreening images and flagging irregularities for radiologists to review [78], and identifying and optimizing drug combinations to more effectively treat antibiotic resistant conditions [79]. In terms of surgery, experiments with autonomous robot surgeons that make their own decision are being conducted [80]. Another study reported that with a dataset of 129,450 clinical images consisting of 2,032 different skin diseases, a deep neural network learned to diagnose/classify skin cancer with the same diagnostic competence of board-certified dermatologists [81].

The ability to make millions of calculations in a timeframe almost unimaginable to humans translates into computers being able to identify patterns we might not be easily able to see within huge data sets. This holds interesting potential for huge banks of information, such as joint registries.


Open vs closed CAS robotic systems

In an open platform robotic CAS system, the technology is cross-compatible with more than one manufacturer’s implants. This has the added benefit of surgeons not being limited to a single brand of implant. In contrast, a closed platform robotic CAS system restricts the surgeon to a specific implant brand [82].

“There needs to be a balance between the two,” says Ahmed Magan. “As technology advances and implant costs come down, it would make sense for surgeons to be able to use their implant of choice for the best outcome for the patient.” See Part 3 of this article series for further discussion of open and closed platforms.


Path of development

Over the last 50 years, computers inside digital medical-grade equipment have increasingly been involved in patient care and monitoring [83]. Some of the first CAS systems to be developed are the descendants of the surgical robots we know today [3].


Robotics in surgery

The first use of the word “robot” as we understand it is attributed to Czech playwright Karel Čapek and his 1920 play R.U.R. (Rossum’s Universal Robots) [3, 84]. In 1942, science-fiction author Isaac Asimov first used the term “robotics” to describe the study of robots. Perhaps it is the surgical robot that most captures our collective imagination, a machine capable of autonomously performing every medical treatment we need, tirelessly and with a precision not attainable by imperfect humans. While this imagined future of surgical robots is currently out of reach, one report estimates that 5,000 robotic orthopedic surgery units are in use around the world [85], indicating that we are slowly moving closer to realizing this fantasy.

In the 1950s, the idea of robotic arms that could be controlled remotely and delivered a feeling of being somewhere else was conceptualized by NASA and called “telepresence”. These robotic manipulators were first developed for use in hazardous environments (space, deep sea, contamination) and industrial spaces [3].


Figure 2. DARPA's original concept for MEDFAST surgical unit, linked by mobile 2-way microwave communication link. © 2018 by JSLS, Journal of the Society of Laparoendoscopic Surgeons. Used with permission under CC BY-NC-ND 3.0 US license. Source: George EI, et al. Origins of Robotic Surgery: From Skepticism to Standard of Care. JSLS. 2018;22(4):e2018.00039

One can easily see how the ability to assess patients, perform surgeries, and monitor recoveries from afar would be of interest to the military. The US-based "Defense Advanced Research Projects Agency" (DARPA), in partnership with several private companies, is credited with developing and testing prototypes of a multipurpose teleoperated robotic system that brought the OR to the patient. See Figure 2.

The "Medical Forward Advanced Surgical Treatment" (MEDFAST) aimed to connect a mobile, remote surgical unit with off-site surgeons who would control robotic surgical equipment via telepresence, assisted by a bedside medic, while the patient was being transported. Despite promising demonstrations in 1993 and 1994, the MEDFAST system was never fully realized due to “political considerations” [34].


Early surgical robots

The discipline of orthopedics was the first to trial robotic technology in a real OR [86]. A team from Vancouver, Canada, is attributed with the first use of a surgical robot. In 1983, “Arthrobot” responded to “simple voice commands” from a surgeon and would assist with moving a patient’s limbs during orthopedic surgery; the surgeon would perform all aspects of the actual surgical procedure [3, 86, 87].


Watch original 1980s video footage of Arthrobot in action. ©Dr Brian Day.

In 1985, the PUMA 560 integrated CT to insert a needle into a specific part of the brain in a stereotaxic operation to collect a tissue sample for biopsy. The idea was that the smooth movement of a robot would eliminate the slight tremor of a human hand and make needle placement more precise [12].



Degrees of freedom

When designing surgical robots to replicate procedures, a robot’s range of motion is compared to that of a human arm; the human arm is the most versatile actuator known to man. The three joints in a human arm (shoulder, elbow, wrist) provide “seven degrees of freedom” (DoF)—the different axes about which an object is able to move in 3D space. Terminology, originating in the nautical world, is used to describe DoF [88]:

  • Pitch: tilting in the vertical vector (shoulder, elbow, wrist)
  • Yaw: turning to the left or right (shoulder, wrist)
  • Roll: tilting from side to side (shoulder, wrist)


In 1992, Computer Motion developed the Automated Endoscopic System for Optimal Positioning (AESOP). It was the world’s first surgical robot to be approved by the US Food and Drug Administration (FDA) in 1994. AESOP was controlled by a foot pedal, and later by voice commands, and intraoperatively maneuvered an endoscope, with a laparoscope being added to the ZEUS unit in 1996, which was based on the AESOP platform. Interestingly, ZEUS had the potential to be used in telesurgery and was the robot used in the 2001 transatlantic “Lindbergh Operation”, although it was discontinued in 2003. AESOP was adopted in over 1,000 hospitals [34].

Compared with a human surgeon, Robodoc was able to more quickly and precisely prepare a femoral cavity to accept a hip replacement in 1993 [12, 87, 89]. A 1998 study reported that in over 900 cementless total hip replacement procedures using the robot, not a single intraoperative femoral fracture occurred [90]. See Figure 3.


Figure 3. The ROBODOC system was comprised of ORTHODOC, a 3D preoperative planning workstation, and ROBODOC surgical assistant, a 5-axis SACARA type surgical robot. Used with permission under CC BY-NC 3.0 license. Source: Sugano N. Computer-assisted orthopaedic surgery and robotic surgery in total hip arthroplasty. Clin Orthop Surg. 2013;5(1):1–9.

Renamed to TSolution-One®, this autonomous robot continues to be used to this day. It incorporates image-based preoperative planning software and is used in ORs around the globe for both hip and knee replacements [91]. It has also been shown to effectively remove all bone cement, without causing femoral fracture during hip revision surgery [92].

Although it did not receive FDA approval until 2000 [93], the da Vinci Surgical System [See Figure 4] from Intuitive Surgical also has its roots in the 1990s. It is still in use today, purportedly having performed over 5 million surgeries over 20 years [94].


Figure 4. DaVinci Xi surgical robot. Image in public domain. Source: Marcy Sanchez.

It is mostly used in prostatectomies, cardiac valve repair, and gynecologic surgical procedures. The current version of the system includes a surgeon console in the same room as the patient and a side cart with four robotic arms (one arm is a 3D camera, the other three are for tools). See Part 2 of this article series for further discussion of CAS currently in use in orthopedics. Figure 5 provides an overview of the history of robots in surgery.

Figure 5. History of robotic surgery. An overview. Used with permission. Source: IDTechEx Report Innovations in Robotic Surgery 2020-2030.



CAS systems encompass a wide range of technology that has been successfully incorporated into many surgical fields, including orthopedics. From planning software and navigation, to PSI and robots, the potential of CAS will continue to evolve as the technology that drives surgery advances. Part 2 of this article series narrows the CAS focus to just orthopedics and takes a closer look at how CAS is currently being used to improve patient outcomes.


Contributing experts

This series of articles was created with the support of the following specialists (in alphabetical order):

Justin Chang

MBBS, MRCS (Eng), FRCSC, University College London Hospital NHS Foundation Trust, Trauma and Orthopaedics Department, UK

Ahmed Magan

BM BSc (Hons) MRCS (Eng) FRCS (Eng), Trauma & Orth. University College London Hospital NHS Foundation Trust, Trauma and Orthopaedics Department, UK

Mark Roussot

MBChB, MPhil, MMed, FC Orth (SA), FRCS (Tr & Orth), University College London Hospital, Department of Trauma and Orthopaedics, UK

Georges Vles

MD, PhD, University Hospitals Leuven, Division of Orthopedic Surgery, Belgium

This issue was created by Word+Vision Media Productions, Switzerland


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