Medical Policy: 06.01.24
Original Effective Date: January 2007
Reviewed: July 2017
Revised: July 2017
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This Medical Policy document describes the status of medical technology at the time the document was developed. Since that time, new technology may have emerged or new medical literature may have been published. This Medical Policy will be reviewed regularly and be updated as scientific and medical literature becomes available.
Computer-assisted navigation (CAN) in orthopedic procedures describes the use of navigational systems (computer-enabled tracking systems) to provide additional information and to further integrate preoperative planning with how the surgery is being performed. Computer-assisted navigational systems are typically used to improve placement and positioning of a prosthetic and/or surgical instrument during the procedure, and can also be used as an adjunct to fixation of fractures, ligament reconstruction, osteotomy, tumor resection, preparation of the bone for joint arthroplasty (knee and hip), and verification of intended implant placement.
The goal of computer-assisted navigation (CAN) is to increase surgical accuracy and reduce the chance of malposition. For total knee arthroplasty (TKA), malalignment is commonly defined as a variation of more than 3 degrees from the targeted position. Proper implant alignment is believed to be an important factor for minimizing long-term wear, risk of osteolysis, and loosening of the prosthesis. In addition to reducing the risk of substantial malalignment, CAN may improve soft tissue balance and patellar tracking. CAN is also being investigated for surgical procedures with limited visibility such as placement of the acetabular cup in total hip arthroplasty, resection of pelvic tumors, and minimally invasive orthopedic procedures. Other potential uses of CAN for surgical procedures of the appendicular skeleton include screw placement for fixation of femoral neck fractures, high tibial osteotomy, and tunnel alignment during reconstruction of the anterior cruciate ligament.
Computer-assisted navigation (CAN) may be image based or non-image based. Image based devices use preoperative computed tomography (CT) scans and operative fluoroscopy to direct implant positioning. Newer non-image based devices use information obtained in the operating room, typically with infrared probes. For total knee arthroplasty, specific anatomic reference points are made by fixing signaling transducers with pins into the femur and tibia. Signal-emitting cameras (e.g. infrared) detect the reflected signals and transmit the data to a dedicated computer. During the surgery, multiple surface points are taken from the distal femoral surfaces, tibial plateaus, and medial and lateral epicondyles. The femoral head center is typically calculated by kinematic methods that involve movement of the thigh through a series of circular arcs, with the computer producing a three dimensional (3D) model that includes the mechanical, transepicondylar, and tibial rotational axes. CAN systems direct the positioning of the cutting blocks and placement of the prosthetic implants based on digitized surface points and model of the bones in space. The accuracy of each step of the operation (cutting block placement, saw cut accuracy, seating of the implants) can be verified, thereby allowing adjustments to be made during surgery.
Computer-assisted navigation involves three steps: data acquisition, registration, and tracking.
For many orthopedic surgical procedures, optimal alignment is considered an important aspect of long-term success. For example, misplaced tunnels in anterior cruciate ligament (ACL) or posterior cruciate ligament (PCL) reconstruction or malalignment of arthroplasty components are some of the leading causes of instability and reoperation. In total hip arthroplasty (THA), orientation of the acetabular component of the THA is considered critical, while for total knee arthroplasty (TKA), alignment of the femoral and tibial components and ligament balancing are considered important outcomes. Ideally, one would prefer controlled trials comparing the long-term outcomes, including stability and reoperation rates. Intermediate outcomes include the number of procedures that achieve a predetermined level of acceptable alignment.
Computer-assisted navigation surgery has been described as an adjunct to pelvic, acetabular, or femoral fractures. For example, fixation of these fractures typically requires percutaneous placement of screws or guidewires. Conventional fluoroscopic guidance (i.e. C-arm fluoroscopy) provides imaging in only 1 plane. Therefore, the surgeon must position the implant in 1 plane and then get additional images in other planes in a trial-and-error fashion to ensure that the device has been properly placed. This process adds significant time in the operating room and radiation exposure. Computer-assisted navigation surgery may permit minimally invasive fixation and provide more versatile screw trajectories with less radiation exposure. Computer-assisted navigation is considered an alternative to the existing image guidance using C-arm fluoroscopy.
Ideally, investigators would conduct controlled trials comparing operating room time, radiation exposure, and long-term outcomes of those whose surgery was conventionally guided using C-arm versus image guided using computer assisted navigation. Based on review of the literature, several in vitro (technique of performing a given procedure in a controlled environment) and review studies have been published to include 1 clinical trial of computer-assisted surgery in trauma or fracture cases.
There is limited literature on the use of computer-assisted navigation for trauma or fractures. Additional controlled studies that measure health outcomes are needed to evaluate this technology for these indications.
A 2014 Cochrane review compared the effects of CAN with conventional operating techniques for anterior cruciate ligament (ACL) or posterior cruciate ligament (PCL) reconstruction. Five randomized controlled trials (RCTs; 366 participants) on ACL reconstruction were included in the updated review; no studies on PCL reconstruction. The quality of evidence ranged from moderate to very low. Pooled data showed no statistically or clinically relevant differences in self-reported health outcomes (International Knee Documentation Committee (IKDC) subjective scores and Lysholm Keen Questionnaire scores) at 2 or more years of follow-up. No significant differences were found for secondary outcomes, including knee stability, range of motion, and tunnel placement. Overall, there was insufficient evidence for or against the use of computer-assisted navigation (CAN).
Based on review of the peer reviewed medical literature the evidence on computer-assisted navigation (CAN) for anterior cruciate ligament (ACL) or posterior cruciate ligament (PCL) reconstruction includes a systematic review of 5 RCTs. These RCTs, of moderate to low quality, did not consistently demonstrate more accurate tunnel placement with CAN. No studies have shown an improvement in functional outcomes or need for revision when CAN is used for ACL or PCL reconstruction.
Relatively few RCTs have evaluated computer-assisted navigation (CAN) for hip procedures. Although there was early interest in this technology, no recent RTCs have been identified. There is inconsistent evidence from small trials as to whether CAN improves alignment with conventional or minimally invasive total hip arthroplasty (THA). One RCT found improved alignment when CAN was used for hip resurfacing, but there was little evidence of improved outcomes at short-term follow up. Overall, improved health outcomes have not been demonstrated with computer-assisted navigation for any hip procedures.
Alignment of a knee prosthesis can be measured along several different axes, including the mechanical axis, and the frontal and sagittal axes of both the femur and tibia.
A 2007 TEC Assessment by BCBS Association evaluated computer-assisted navigation (CAN) for TKA. Nine studies from 7 RCTs were reviewed. Selection criteria for the RCTs included having at least 25 patients per group and comparing limb alignment and surgical or functional outcomes following TKA with CAN or conventional methods. Also reviewed were cohort and case series that evaluated long-term associations between malalignment of prosthetic components and poor outcomes. In the largest of the cohort studies, which included more than 2000 patients (3000 knees) with an average of 5-year follow-up, 41 revisions for tibial component failure (1.3% of the cohort) were identified. The relative risk (RR) for age was estimated at 8.3, with a greater risk observed in younger, more active patients. For malalignment (defined as >3 degrees varus or valgus), the relative risk was estimated to be 17.3.
Pooled data from the prospective RCTs showed:
As a result of deficiencies in the available evidence (e.g, potential for bias in observational studies, lack of long-term follow-up in the RCTs), the TEC reviewers concluded that it was not possible to determine whether the degree of improvement in alignment reported in the RCTs led to meaningful improvements in clinically relevant outcomes such as pain, function, or revision surgery.
A 2012 meta-analysis included 21 randomized trials (total N=2658 patients) that reported clinical outcomes with or without the use of CAN. Most studies included in the review had short-term follow-up. As was found in the 2007 TEC Assessment, surgical time was significantly increased with CAN for TKA, but there was no significant difference between approaches in total operative blood loss, the Knee Society Score (KSS), or range of motion. Rebal et al (2014) conducted a meta-analysis of 20 RCTs (total N=1713 knees) that compared imageless navigation technology with conventional manual guides. Nine studies were considered to have a low risk of bias due to the blinding of patients or surgical personnel. Fifteen studies were considered to have a low risk of bias due to evaluator blinding. The improvement in KSS was statistically superior in the CAN group at 3 months (4 studies; 68.5 vs 58.1, p=0.03) and at 12 to 32 months (5 studies; 53.1 vs 45.8, p<0.01). However, these improvements did not achieve the minimal clinically significant difference, defined as a change of 34.5 points.
More recent studies (2014, 2015) have also found longer surgical times and few differences in clinical outcome measures at 1-year follow-up.
Most studies comparing outcomes at mid- to long-term generally have shown a reduction in the number of outliers with CAN, but little to no functional difference between the CAN and conventional TKA groups.
Follow-up from 4 randomized trials were published between 2013 and 2016; they assessed mid-term functional outcomes following CAN for TKA. Blakeney et al (2014) reported 46-month follow-up for 107 patients from a randomized trial of CAN versus conventional surgery. There was a trend toward higher scores on the Oxford Knee Questionnaire with CAN, with a mean score of 40.6 for the CAN group compared with 37.6 and 36.8 in extramedullary and intramedullary control groups. There were no significant differences in the 12-Item Short-Form Health Survey Physical Component or Mental Component Summary scores. The trial was underpowered, and the clinical significance of this trend for the Oxford Knee Questionnaire is unclear.
Lutzner et al (2013) reported 5-year follow-up for 67 of 80 patients randomized to CAN or conventional TKA. There was a significant decrease in the number of outliers with CAN (3 vs 9, p=0.048), but no significant differences between groups on the KSS or EuroQoL questionnaire for quality of life. Cip et al (2014) found a significant decrease in malalignment with CAN, but no significant differences in implant survival or consistent differences clinical outcome measures between the navigated (n=100) and conventional (n=100) TKA groups at minimum 5-year follow-up. Song et al (2016) also reported a reduction in the number of outliers with CAN (7.3% vs 20%, p=0.006), with no significant differences in clinical outcomes at 8-year follow-up. The trial, which assessed 80 patients (88 knees) was powered to detect a 3-point difference in KSS results.
Other comparative study designs have found no significant differences in clinical outcomes following CAN. In a 2009 comparative study of 160 bilateral TKAs performed by experienced surgeons in Asia, differences in alignment measures between the conventionally prepared knee and the knee prepared with CAN-assistance were minimal. In 2012, this group reported longer term follow-up (mean, 10.8 years) on 520 patients who underwent CAN for 1 knee and conventional TKA for the other knee (randomized). There were no significant differences between groups for knee function or pain measures. Kaplan-Meier survivorship at 10.8 years was 98.8% in the CAN knee and 99.2% for the conventional knee. Two additional nonrandomized comparative studies (2012, 2013) found an improvement in alignment with CAN, but no difference in clinical or functional outcomes at 5-year follow-up compared with conventional TKA.
Hoffart et al (2012) used alternate allocation design with 195 patients to compare functional outcomes following CAN-assisted TKA versus conventional instrumentation. An independent observer performed the pre- and postoperative assessments. After 5 years, complete clinical scores were only available for 121 (62%) patients. There was no significant difference in the frequency of malalignment between the 2 groups. The CAN group had a better mean KSS as well as mean function and knee scores. Mean pain scores did not differ between groups. Limitations of this study include the high loss to follow-up and lack of subject blinding.
In 2016, Dyrhovden et al compared survivorship and the relative risk of revision at 8-year follow-up for 23,684 cases from the Norwegian Arthroplasty Register. Overall prosthesis survival and risk of revision were similar for the 2 groups, although revisions due to malalignment were reduced with CAN (RR=0.5; 95% CI, 0.3 to 0.9; p=0.02). There were no significant differences between the groups for other reasons for revision (eg, aseptic loosening, instability, periprosthetic fracture, decreased range of motion). At 8 years, the survival rate was 94.8% (95% CI, 93.8% to 95.8%) in the CAN group and 94.9% (95% CI, 94.5% to 95.3%) for conventional surgery.
Based on review of the peer reviewed medical literature a large number of RCTs have compared outcomes between total knee arthroplasty (TKA) with computer-assisted navigation (CAN) and conventional TKA without CAN. Results are consistent in showing a reduction in the proportion of outliers greater than 3 degrees in alignment. Results up to 10 years postoperatively have not shown that these differences in alignment lead to improved patient outcomes.
For individuals who are undergoing orthopedic surgery for trauma or fracture, ligament reconstruction, hip arthroplasty and periacetabular osteotomy, or total knee arthroplasty who receive computer-assisted navigation (CAN), the evidence includes randomized controlled trials (RCTs) and nonrandomized comparative studies. Overall, the literature supports a decrease in variability of alignment with CAN, particularly with respect to the number of outliers. Although some observational data have suggested that malalignment may increase the probability of failure, recent RCTs with short to mid-term follow-up have not shown improved clinical outcomes with computer-assisted navigation (CAN). Given the low short-term revision rates associated with conventional procedures and the inadequate power of the available studies to detect changes in function using CAN, further studies are needed that assess health outcomes using CAN in a larger number of subjects with longer follow-up to permit greater certainty on the impact of this technology. The evidence is insufficient to determine the effects of the procedure on net health outcomes.
Also, no studies have been identified that directly compared any surgical navigation systems to each other. Therefore, no clinical evidence is available to determine whether any system works better than another system.
No society guidelines or position statements were identified regarding the utilization of computer-assisted navigation (CAN) for orthopedic procedures.
Because computer-assisted navigation (CAN) is a surgical information system in which the surgeon is only acting on the information that is provided by the navigation system, surgical navigation systems generally are subject only to 510(k) clearance from FDA. As such, FDA does not require data documenting the intermediate or final health outcomes associated with CAN. (In contrast, robotic procedures, in which the actual surgery is robotically performed, are subject to the more rigorous requirement of the premarket approval application process.)
A variety of surgical navigation procedures have received FDA clearance through the 510(k) process with broad labeled indications. The following is an example:
Several navigation systems (eg, PiGalileo™ Computer-Assisted Orthopedic Surgery System, PLUS Orthopedics; OrthoPilot® Navigation System, Braun; Navitrack® Navigation System, ORTHOsoft) have received FDA clearance specifically for TKA. FDA-cleared indications for the PiGalileo system are representative. This system “is intended to be used in computer-assisted orthopedic surgery to aid the surgeon with bone cuts and implant positioning during joint replacement. It provides information to the surgeon that is used to place surgical instruments during surgery using anatomical landmarks and other data specifically obtained intraoperatively (eg, ligament tension, limb alignment). Examples of some surgical procedures include but are not limited to:
FDA product code: HAW.
In 2013, the VERASENSE™ Knee System from OrthoSensor™ and the iASSIST™ Knee from Zimmer received 510(k) clearance from FDA. FDA product code ONN, OLO.
VERASENSE™ (OrthoSensor) is a single use device that replaces that standard plastic tibial trial spacer used in TKA. The device contains microprocessor sensors that quantify load and contact position of the femur on the tibia after resections have been made. The wireless sensors send the data to the graphic user interface that depicts the load. The device is intended to provide quantitative data on the alignment of the implant and on soft tissue balancing in place of intraoperative “feel.”
iASSIST™ Knee (Zimmer) is a guidance system to assist the surgeon in customizing the positioning of knee replacement system components intra-operatively. It involves surgical instruments and position sensors to determine alignment axes in relation to anatomical landmarks and to precisely position alignment instruments and implant components relative to those axes.
Computer-assisted navigation (CAN) as an adjunct in musculoskeletal orthopedic procedure(s) is considered investigational.
Note: Musculoskeletal system provides form, support, stability and movement to the body. It is made up of the bones of the skeleton, muscles, cartilage, tendons, ligaments, joints and other connective tissue that supports and binds tissues and organs together.
Based on the peer reviewed medical literature, the evidence includes randomized controlled trials (RCTs) and nonrandomized comparative studies. Overall, the literature supports a decrease in variability of alignment with computer-assisted navigation (CAN), particularly with respect to the number of outliers. Although some observational data have suggested that malalignment may increase the probability of early failure, recent RCTs with short to mid-term follow-up have not shown improved clinical outcomes with CAN. Given the low short-term revision rates associated with conventional procedures and the inadequate power of the available studies to detect changes in function using CAN, further studies are needed that assess health outcomes using CAN in a larger number of subjects with longer follow-up to permit greater certainty on the impact of this technology. The evidence is insufficient to determine the effects of the procedure on net health outcomes. Therefore, computer-assisted navigation (CAN) as an adjunct in musculoskeletal orthopedic procedure(s) is considered investigational.
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