Patient-specific instrumentation in total knee arthroplasty. Should we adopt it?

The Role of 3D-Printed Patient-Specific Instrumentation in Total Knee Arthroplasty: A Literature Review

Total knee arthroplasty (TKA) is currently one of the most common orthopedic surgeries due to the ever-increasing average life expectancy. The constant need for effective and accurate techniques was contributed to the development of three-dimensional (3D) printing in that field, especially for patient-specific instrumentation (PSI) and custom-made implants fabrication. PSI may offer numerous benefits, such as resection accuracy, mechanical axis alignment, cost-effectiveness, and time economy. Nonetheless, the results of existing studies are controversial. For this purpose, a review article of the published articles was conducted to summarize the role of 3D-printed PSI in TKA.

Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty

Previous studies have shown that the manufacturer's default preoperative plans for total knee arthroplasty with patient-specific guides require frequent, time-consuming changes by the surgeon. Currently, no research has been done on predicting preoperative plans for orthopedic surgery using machine learning. Therefore, this study aims to evaluate whether artificial intelligence (AI) driven planning tools can create surgeon and patient-specific preoperative plans that require fewer changes by the surgeon. A dataset of 5409 preoperative plans, including the manufacturer's default and the plans corrected by 39 surgeons, was collected. Features were extracted from the preoperative plans that describe the implant sizes, position, and orientation in a surgeon- and patient-specific manner. Based on these features, non-linear regression models were employed to predict the surgeon's corrected preoperative plan. The average number of corrections a surgeon has to make to the preoperative plan generated using AI was reduced by 39.7% compared to the manufacturer's default plan. The femoral and tibial implant size in the manufacturer's plan was correct in 68.4% and 73.1% of the cases, respectively, while the AI-based plan was correct in 82.2% and 85.0% of the cases, respectively, compared to the surgeon approved plan. Our method successfully demonstrated the use of machine learning to create preoperative plans in a surgeon- and patient-specific manner for total knee arthroplasty.

Accelerometer-based, hand-held navigation for improved knee alignment in total knee arthroplasty: An observational study

BACKGROUND

Malalignment in total knee arthroplasty has been associated with poor implant longevity and clinical outcomes. The aim of this study was to investigate the accuracy of accelerometer-based navigation in restoring the mechanical axis.

METHODS

106 primary total knee arthroplasties performed during February 2016 to September 2017 at a tertiary care centre in India were enrolled in this observational study. We noted the intra-op tourniquet time. Two separate blinded observers measured the preoperative mechanical axis and the post operative radiological results (mechanical axis, coronal and sagittal alignment of femoral and tibial components) and the mean value was taken as final data. Interclass correlation was done to look for variability between the two observers.

RESULTS

The mean pre operative mechanical axis was 13.74 ± 10.44. The mean tourniquet time was 53.14 ± 7.42 min 91.5% (96/106) knees were within ±3° of neutral mechanical axis with a mean of 1.00° ± 2.68°. The femoral and tibial components with coronal alignment within ±3° perpendicular to the mechanical axis were 93.39% (99/106) and 89.62% (95/106) respectively. In the sagittal plane 89.62% of the femoral components and 87.73% of the tibial components were within ±3° perpendicular to the axis of tibia.

CONCLUSION

The Accelerometer based portable navigation system effectively reduces the coronal and sagittal alignment outliers in total knee arthroplasty and has no role in rotational alignment of components.

How will digitalisation affect patient treatment in arthroplasty? Part I: Intraoperative aspects

We cannot deny that technology has become an important part of our daily life, not only in automobiles, houses or cellphones but also in hospitals. In the OR, in particular for knee arthroplasty, image free navigation has proven to reduce the number of outliers and by that the revision rate in younger patients. Over the last years robotics has again been introduced into the operation theatres. However, in their present version they add time and costs, but only minimal benefits to the procedure. Therefore, future robots should be faster and instrumentation free. Beside those more economical aspects, the goal of this digital technology must be an improvement in clinical outcome. To achieve that, additional steps for analyzing the pre-, and intra-OP quantitative data is key. With the use of artificial intelligence and/or machine learning a data based algorithm will probably be developed, which helps the surgeon to integrate all parameters into his individual cutting and releasing plan for each patient. Digital data therefore, might become the key to enable the surgeon to treat patients more individual and by that hopefully deliver better outcome.

Health costs and efficiencies of patient-specific and single-use instrumentation in total knee arthroplasty: a randomised controlled trial

Aim

To investigate whether patient-specific instrumentation (PSI) and single-use instrumentation (SUI) improve operating room efficiency in terms of time and cost to the healthcare provider over conventional/reusable instrumentation (CVR) when performing total knee arthroplasty (TKA).

Patients and methods

Patients requiring TKA were randomised into one of four surgical groups: CVR, CVS (conventional/SUI), PSR (PSI/reusable) and PSS (PSI/SUI). All surgical procedures were video recorded to determine specific surgical time intervals. Other variables reported included the number of instrument trays used, missing equipment, direct instrument costs and the weight of the instruments the staff had to handle. Oxford Knee Score (OKS), estimated blood loss and lengths of hospital stay were also recorded as markers of patient experience.

Results

PSR was significantly quicker in all the recorded time intervals, used less trays, experienced less missing equipment and resulted in lower blood loss and shorter hospital stays. SUI reported significantly slower operating room times and resulted in higher blood loss, but SUI was 88% lighter and 20% cheaper on average when compared with their reusable counterparts. Despite the economic advantages of PSI and SUI, the patients who reported greatest improvements in OKS were those allocated to the CVR group, but no clinically meaningful difference in OKS was found at any time point.

Conclusions

PSI and SUI for TKA have the potential of reducing operating room times over conventional, reusable sets. This reduction will benefit theatre personnel ergonomically, while presenting the healthcare provider with potential cost-saving benefits in terms of reduced sterilisation costs and surgical times.

Clinical Outcome of Total Knee Arthroplasty Performed Using Patient-Specific Cutting Guides

Background

Patient-specific instruments have recently gained attention for ensuring the accuracy of osteotomy and correct alignment in total knee arthroplasty (TKA). We aimed to report our experience with TKA performed by using CT-based 3D model of cutting guides in our clinic.

Material/Methods

A total of 36 patients (mean age, 67.58±8.46 years; 24 females, 12 males) who underwent TKA with 3D patient-specific cutting guides in our clinic were included in the study. Differences between preoperatively planned bone resections and actual bone resections were calculated. Femoral and tibial component angles were measured on radiographs of the knee. The change in knee pain was evaluated by patients on a 10-point visual analog scale (VAS). Patients were followed up for 6 months postoperatively.

Results

The actual bone resection was 0.5–1.5 mm higher than the planned resection for all sides, being statistically significant for posterior lateral and distal medial sides (1.1±1.3 mm and 1.5±0.9 mm, respectively; p<0.05). On postoperative radiographs, coronal tibial component angle was 88.8°±0.9° and coronal femoral component angle was 95.2°±1.6°, showing good postoperative alignment. The VAS pain score of patients significantly decreased from preoperative 3.9±0.8 to 1.1±0.9 at 6 months after the operation. One patient developed superficial tissue infection on postoperative follow-up, which was effectively treated. No other pathology was detected in the postoperative period.

Conclusions

Patient-specific cutting guides can provide intraoperative guidance for better placement of the implant in TKA and increase the accuracy of osteotomy and postoperative alignment.

An Approach to Developing Customized Total Knee Replacement Implants

Total knee replacement (TKR) has been performed for patients with end-stage knee joint arthritis to relieve pain and gain functions. Most knee replacement patients can gain satisfactory knee functions; however, the range of motion of the implanted knee is variable. There are many designs of TKR implants; it has been suggested by some researchers that customized implants could offer a better option for patients. Currently, the 3-dimensional knee model of a patient can be created from magnetic resonance imaging (MRI) or computed tomography (CT) data using image processing techniques. The knee models can be used for patient-specific implant design, biomechanical analysis, and creating bone cutting guide blocks. Researchers have developed patient-specific musculoskeletal lower limb model with total knee replacement, and the models can be used to predict muscle forces, joint forces on knee condyles, and wear of tibial polyethylene insert. These available techniques make it feasible to create customized implants for individual patients. Methods and a workflow of creating a customized total knee replacement implant for improving TKR kinematics and functions are discussed and presented in this paper.