Introduction

Computer aided surgery aims to improve surgical outcomes with computer guidance. Navigated Freehand bone Cutting (NFC) takes this further by eliminating the need for cumbersome mechanical jigs, while decreasing cutting time and complexity. To reduce the footprint of the NFC tracking system (currently NDI Polaris) we designed and implemented “On-Tool Tracking” (OTT), a novel miniaturized tracking system that mounts onto the cutting instruments (Fig. 1). This study investigates the accuracy of the 3D-measurements of the OTT system.

Introduction

Computer aided surgery aims to improve surgical outcomes with image-based guidance. Navigated Freehand bone Cutting (NFC) takes this further by eliminating the need for cumbersome mechanical jigs. Multiple previous experiments on plastic and porcine bones, performed by surgeons with different level of expertise, suggested that the NFC technique was feasible. This study pushes NFC further by using the technique to perform complete total knee replacement (TKR) surgeries on cadavers (including implant cementing of tibia and femur).

Introduction

Navigated freehand cutting (NFC) technology simplifies bone cutting in laboratory trials by directly navigating implants and power tools [1]. Experiments showed that NFC bone cutting was faster than with conventional jigs. However, most delays occurred at the start of each cut [2]. Therefore, we further reduced starting times and gained more accuracy with a NaviPen and a ‘smart’ NaviPrinter [3]. There were used to physically mark a line on the bone surface indicating where each cut should start. (Fig. 1). Further gains are targeted with our introduction of the On-Tool Marker (OTM); a touch-less laser marking technology as a standalone device or mounted on the cutting instrument (e.g. on the saw). The OTM points the desired cut by projecting a laser image on the bone. That image (usually a line or cross) changes dynamically, so that for any given cut the line projection remains stationary on the bone regardless of the relative location of the device.

Introduction

Computer aided surgery aims to improve surgical outcomes with image-based guidance. Navigated Freehand bone Cutting (NFC) takes this further by eliminating the need for cumbersome mechanical jigs. Multiple previous experiments on plastic and porcine bones, performed by surgeons with different level of expertise, suggested that the NFC technique was feasible. This study pushes NFC further by using the technique to perform complete total knee replacement (TKR) surgeries on cadavers (including implant cementing of tibia and femur).

Formal surgical skill assessment and critical path analysis are not widely used in orthopaedic surgical training due to the lack of technology for objective quantification, reliability, and the discrimination insensitivity of existing methods. Current surgical skill assessment methods also require additional instrumentation, cost and time. Such problems can be overcome by a novel method that records the motion of surgical instrumentation for the purposes of documentation, surgical-skill assessment, and safety analysis. This method uses an existing computer-aided-orthopedic-surgery (CAOS) navigation system and does not compromise its functions of real-time tracking, rendering, or simulation. The stored data allows realistic playback in 3D of the complete bone cutting/refining process. This concept and its sensitivity were previously tested and validated using a robotic arm as a reliable actuator for a surgical instrument moving in controlled paths. In this study, the system was used to evaluate the surgical skills of actual orthopaedic residents in a hospital/lab setting.

Two chief orthopaedic surgery residents participated in the experiment. Each one cut all five distal cuts on four synthetic (right) femurs to accommodate the same femoral implant using NoMiss, an in-house built system for Navigated Freehand bone cutting. The motion of the surgical saw was recorded in real time by NoMiss during the whole procedure, but the real purpose of the experiment (and the recording) was not revealed to the residents until the end of all tests. Based on the data recorded by the navigation system, the following parameters were analyzed: cutting time, area-of-the-cut/time ratio, trajectory of the saw, errors in distance off the plane as well as errors in roll and pitch angles.

While no significant difference among the two subjects was found in bone cutting time (mean 531s vs. 642s, p=0.099), subject 1 (S1) was faster than subject 2 (S2) in total time, which included cutting, reshaping of the bone, and implantation (mean 719s vs. 958 s, p=0.035). Area-of-the-cut/time ratio revealed higher (not significant) proficiency for S1 compared to S2 (mean 16 mm2/s vs. 13 mm2/s, p=0.084). Nevertheless considering individual cuts, there was significant difference in the posterior chamfer cut (mean 9 vs. 5 mm2/s, p=0.015). The analysis of the trajectory of the saw showed less conservative motion (and less consistency) for S1 than for S2 (average total length of trajectory 8.6m (sd=2.1m) vs. 8.1m (sd=0.4m), as well as larger paths in between cuts (average 39% vs. 33% of the total trajectory).

The system/method was able to characterize different subjects without additional instrumentation, cost, time, awareness of or distraction to the user. Slightly better performance was detected for S1 compared to S2 presumably signifying superior skills. The main differences in this case appeared in the cutting of the chamfers, which might be considered the trickiest of the distal cuts in a navigated freehand cutting environment. A larger number of subjects with a wide level of expertise should be analyzed under similar conditions to establish quantitative acceptance limits (e.g. numerical determination for pass/fail criteria).

Computer aided orthopaedic surgery (CAOS) systems aim to improve surgeons’ consistency and outcomes by providing additional information and graphics, often displayed on one or more computer screens. Experience has shown that surgeons often feel uncomfortable looking away from the patient to focus on the computer screen, and multiple methods have attempted to address this (e.g. by using head mounted and semi-transparent displays). We present a new approach, with a small touch-screen wirelessly controlled from the main CAOS computer and micro-controlled electronics all mounted on the cutting instrument and placed along the surgeon’s line of sight from the instrument to the wound. In addition, the micro-controlled system improves the patient’s safety by controlling the cutting speed of the blade (or stopping it), based on the saw’s positioning deviations from the planned cuts. The (on board the saw) computer-user interface also transmits commands to the main computer, based on commands issued on the touch screen.

The “smart” navigated saw was built by integrating a microcontroller, optical trackers, a small 4x6cm viewable touch-screen, and a surgical oscillating saw. Bidirectional wireless communication was established between the saw and a Navigated Freehand Cutting (NFC) CAOS system allowing dynamic speed control of the blade, slowing it down for smaller errors in position/alignment (relative to planned cuts), and stopping it for bigger errors and/or risk of tissue damage. The sensitivity of the correction and width of the allowed error envelope were made adjustable to cater for the individual surgeon preferences. The touch-screen on the saw provided the surgeon with a visual aid for cutting without them having to look away while simultaneously providing control of the interface settings by touch. After electronic bench tests, two orthopaedic residents prepared eight synthetic distal femurs with the NFC system and the prototype saw to accept a commonly used TKR implant.

All parts were integrated into a usable stand-alone device, with no software, hardware, or logical failure registered during the tests. The speed control responded to the established threshold errors and the preferred dynamically adjustable settings were found to be 0.5mm to 10mm of error in location and 0.5° to 10° in pitch or roll angle. The surgeons were satisfied with the user-interface for graphical guidance and system control. No significant difference in implant alignment, fit and cutting time were found compared with the standard NFC system with standard size computer monitors.

By a wireless link between a CAOS system computer and the cutting instrument (with a graphical touch display screen on board), the patient’s safety and surgeon’s visibility needs were addressed allowing the screen to be aligned with the wound. With a user interface on the saw, and automatic speed and stopping control of the cutting instrument based on navigation, the surgeon is prevented from cutting in the wrong place. This surgeon-actuated but “software cutting jig” fulfils the same functions of cumbersome autonomous or passive surgical robots with their sophisticated servo and haptic interfaces, but with startling utility bringing in the era of the modern “smart” hand-held bone cutting instruments.

Computer aided orthopaedic surgical (CAOS) technology has been around for over 20 years, and while it appears to provide better outcomes compared to conventional jigs, less than 1% of orthopaedic surgeons in USA have adopted it. This study surveyed the arguments against CAOS usage, highlighting those reasons which may continue to prevent CAOS from becoming truly widely accepted.

The survey has identified several concerns with navigation systems. For example, the pin tracts from navigation reference frames cause stress risers that increase the risk of bone fracture and soft tissue/muscle damage. Additionally, infrared trackers take footprint space (as they require line of sight access to the tracking camera), increase risk of infection, and present a potential distraction to the surgical team. With current CAOS systems, even more nstrumentation is needed than with non-navigated surgical systems, and it is arguable that navigation makes surgery more complex, requiring a knowledge of anatomic landmarks, an increased number of tasks prior to and during surgery, and an assortment of different and perhaps unfamiliar instruments. These complexities very likely result in a slow learning curve on current CAOS systems, a learning curve that is mostly not started by the majority of surgeons.

Other items of concern are the accuracy of morphed/generated bones in imageless systems (and how these models assume non-deformed anatomy), inaccuracies or distortion of the measurements (operating room lighting interfering with infrared trackers or field deformation of electromagnetic systems due to ferromagnetic instruments at the surgical site) and computer reliability. Considering the high cost (or low cost-effectiveness) of integrating CAOS into arthroplasty, and the lack of enough studies documenting truly better long term clinical results or fewer actual complications, it is evident why navigation is not yet a popular option for TKR.

As a result of the critical findings from this study, it is our view that any successful new technique/tool in surgery should make the overall procedure easier, faster, cheaper and better (or at least equally as good) as the current techniques. While robotic surgery seems to be re-emerging, we hypothesize that the next real breakthrough will come from newer more utilitarian light weight small foot print technologies actuated by surgeons themselves, with enhanced computer guidance that will allow them to reduce instrumentation, complexity, and surgical time such as navigated free-hand bone cutting. Alternative navigation technologies (e.g. UWB 3D positioning radar) where line of sight becomes less crucial, image based systems (rather than image free), artificial vision, and smart instrumentation are likely to play a major role in achieving widespread future acceptance of CAOS in TKR.

Most navigation systems for TKR help in the alignment of bulky cutting jigs. We hypothesized that TKR bone cutting could be done free hand without cutting jigs, by navigating a bone saw directly. This would allow smaller incisions, faster recovery time and simpler procedures. The goal of this study was to evaluate the results of free-hand cutting by using in-house developed CAOS software against cuts with traditional jigs.

Experiments were carried out on the five planar cuts of the TKR distal femur, using first the conventional cutting jig and then freehand. The Freehand cutting system navigated and displayed 3D realistic models of the saw, the bone and the planes along which the blade should be orientated. Two experienced arthroplasty surgeons and one engineer performed the experiments on 18 identical synthetic femurs. Each performed one using jigs and five freehand. The experiments were timed and > 50 direct measurements were made for each (cut) bone with a computer digitizer, digital caliper and protractor to assess their quality.

Surgeon’s comments, qualitative and quantitative assessments of the cuts proved the concept’s feasibility and its encouraging potential. The engineer’s time improvement with freehand navigation has implications for easier TKR for trainee surgeons.