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Published: 2022-09-28

3D planning in revision total knee arthroplasty following periprosthetic joint infection. A pilot study

Department Orthopaedic and Traumatology. “Federico II” University, Naples, Italy
Department Orthopaedic and Traumatology. “Federico II” University, Naples, Italy
Department Orthopaedic and Traumatology. “Federico II” University, Naples, Italy
Department Orthopaedic and Traumatology. “Federico II” University, Naples, Italy
Department Orthopaedic and Traumatology. “Federico II” University, Naples, Italy
IRCCS Synlab SDN, Naples, Italy
Department Orthopaedic and Traumatology. “Federico II” University, Naples, Italy
total knee arthroplasty revision arthroplasty periprosthetic joint infection 3D planning 3D printing

Abstract

Objective. Revision total knee arthroplasty (TKA) following a periprosthetic joint infection (PJI) represents a considerable challenge. The geometry of bony defects can be hard to assess on standard x-rays, thus requiring CT evaluation. CT data can be processed to create physical replicas by 3D printing. This model can be used as means of 3D planning through surgical simulation. This study aims to compare the ability to predict the need for augmentation to restore limb alignment between 2D and 3D planning.
Methods. Ten consecutive patients undergoing second-stage TKA revision following PJI were included. Pre-operative CT and standard x-rays were obtained in all patients. CT data were used to produce a model using a 3D printer. The surgical simulation was then conducted using TKA revision instrumentation. Standard 2D planning and 3D planning were independently performed by two investigators. Interclass correlation coefficient was used to evaluate agreement on the use of augment.
Results. For femoral augment, 3D and 2D accuracies were 80.8 and 37.5%, respectively. For tibial augment, 3D and 2D accuracies were 66.7 and 23.0%, respectively.
Conclusions. 3D planning with surgical simulation has shown to be a valuable method to predict the need of augment in revision TKA following PJI.

Introduction

Currently, it is estimated that the number of primary total knee arthroplasties (TKA) in Italy will increase 45% by 2050 1. Similarly, we expect that revisions for aseptic and septic loosening will rise over time. Despite new clinical and technological advancements, periprosthetic joint infection (PJI) represents one of the most important causes of joint prosthesis failure, with an incidence estimated to range from 1-2% 2,3. The current strategies for treating chronic PJI are one-stage and two-stage revisions. Although one-stage approach has shown promising results at certain institutions, the two-stage protocol remains the most widely applied 4. The first stage consists of removing the infected hardware, thorough debridement, and implanting an antibiotic-laden spacer until infection eradication. In the second stage, the spacer is removed, a second debridement performed, and a revision TKA is implanted 5.

Revision TKA following PJI is still a challenge for the surgeon since the bone stock can be significantly reduced as a direct consequence of the infection or hardware removal 6, the soft tissues can be compromised as well 7. These are among the reasons for a high percentage of aseptic loosening in patients affected by PJI 8. Rigorous planning needs to be implemented for each patient to reduce the failure rate. A standard joint x-ray may be unhelpful to pre-operatively evaluate the best strategy to fulfill bone defects. A CT scan, providing high-quality imaging can help identify cavitary or segmentary defects, and may be more useful to overcome this issue 9. Furthermore, a three-dimensional reconstruction can be created from a CT image to help understand the location and characteristics of the bone defects. Such models can be 3D printed to produce accurate physical replicas of the patient’s anatomy 10, which can be used in a simulated TKA revision surgery, hence serving as a planning technique. The aim of our study was to compare standard 2D planning with 3D planning regarding the ability to predict the need for augmentation to correct the overall leg axis in the second stage (Fig. 1).

Materials and methods

We retrospectively analyzed 10 consecutive (2 men and 8 women) patients with a mean age of 73 ± 4 years who completed the two-stage approach following a PJI of a TKA at our institution from May 2020 to September 2020. After implant removal patients underwent two weeks of intravenous antibiotic therapy 13. Drug choice was based on pre-operative synovial fluid culture when available. In case of negative cultures empiric therapy was used, selecting antibiotics active against gram-positive methicillin resistant bacteria. This regiment was then modified according to the results yield by the intra-operative cultures. In the present series all patients had at least one intra-operative positive culture. Following the first two weeks of parental therapy the patients were then switch to oral antibiotic therapy based on the microbiological evaluations. The median time between first and second stage was 8 weeks (6-12), and the therapeutic regiment was continued for 15 days after reimplantation 14. No patients in our series discontinued antibiotic therapy because of side effects. According to our institution’s standard protocol, all complex TKA revisions undergo a CT scan with 3D reconstruction. Due to the study’s retrospective nature, no ethical committee approval was needed. Before reimplantation, all patients underwent a standard caliper x-ray and CT of the leg with MARS protocol 15 and a transverse slice thickness of 0.5 mm. All the data were gathered and anonymized by one of the experimenters who was not involved in the following phases. Each patient was assigned 2 codes, one for x-ray images and one for CT data. Two investigators independently planned the cases, one using the x-ray images and the other carried out 3D planning with surgical simulation. Patients’ defects were categorized according to the Anderson Orthopaedic Research Institute (AORI) classification of bone defects 16. Patient demographics and characteristics are summarized in Table I.

CT data were then segmented using MIMICS Innovation Suite (Materialise Interactive Medical Image Control System Software, Materialise, Leuven, Belgium) to obtain a stereolithography (STL) file. The STL file was further manipulated; spacer components were removed, lines matching the femoral and tibial mechanical axis were drawn, and a code specific to the anonymization protocol was added. The file was then sliced using Ultimaker CURA (Ultimaker Cura 4.5, Ultimaker B.V., 4191 PN Geldermalsen, The Netherlands) and printed using polylactic acid (PLA) on a Creality Ender-3 FDM 3D printer. Models were then mounted on a support and carefully studied to assess the best strategy to obtain a mechanical alignment. Using revision TKA instrumentation, the appropriate cuts were made and augment selected. 2D planning was performed on the standard x-rays using Traumacad (Brainlab AG, Munich, Germany; Fig. 2) digital templating software. The necessity of prosthetic augments to fill the bone defect and restore the implant alignment in the two planning methods and collected intra-operatively.

Statistical analysis was performed using IBM SPSS statistics 27 (IBM Corp. in Armonk, NY) using intraclass correlation coefficients (ICCs) with a two-way random-effects model. This analysis measured the level of agreement between the final augment used in the implant and the planned ones from both the 2D and 3D evaluations. The accuracy of both planning methods was also measured by calculating the percentage of correct predictions. These were then compared using the chi-square test.

Results

The 3D planning successfully predicted the need for femoral and tibial augment in 80.8% and 66.7% of cases, respectively. Higher ICC values for the femoral augments were retrieved than tibial augments (0.808 [0.454-0.944] vs 0.667 [0.187-0.896]). These results suggest an excellent level of agreement between the 3D planned and final use of augments for the femoral component. The results were highly significant (femoral: p = 0.001; tibial p = 0.007). The standard 2D planning predicted 23% of tibial augment and 37.5% of femoral ones. The difference in correct prediction between the two planning method was statistically significant for tibial (χ2: 6.6 p: 0.010) but not for femoral augment (χ2: 2.394 p: 0.127) (Fig. 3).

Discussion

3D printing is becoming hugely popular in orthopedic 17 with its technology becoming cheaper and more available by the day. Images obtained from CT scans can be processed to accurately reconstruct the patient’s anatomy.

In the present study, we explored the use of these models as a planning method and compared its accuracy with standard 2D planning. To our knowledge, this is the first study comparing 2D and 3D planning in revision total knee arthroplasty, especially following PJI. A physical model of the patient’s anatomy is a valuable resource for the skilled surgeon and residents approaching the complexity of TKA revision. As a University Hospital, our focus has to be both on the patient and the trainee; therefore, offering the opportunity to simulate surgery beforehand helps the team revise surgery in a step-to-step fashion. TKA revision is typically planned using standard x-ray images. Interestingly the 3D planning showed a statistically significant higher accuracy for 3D planning when compared to standard 2D templating for tibial augment. As seen in a previous study 9 a cavitary defect might not be evident on x-ray and can only be revealed with CT. 3D printing technique presents more then few drawbacks among which we have the inability to evaluate soft tissue, which can require to modify the implant intra-operatively. Furthermore, the need for a CT scan greatly increases radiation exposure, even with Whole Body Low Dose CT scan 18. 3D planning by surgical simulation requires times, expertise and resources that might undermine its wider application. On the other hand, standard calipered x-rays require minimal radiation exposure and are widely available. The present study has limitations due to the small sample, which did not allow further statistical analysis to be performed, therefore giving only an indication on the use of augment. No information could be extracted on implant size because of the risk of biasing the analysis. The current study focuses on the reliability of 3D planning, and no clinical data are yet available regarding patients’ outcomes. Further studies are needed in order to investigate the utility of 3D planning by surgical simulation and its cost-effectiveness.

Conclusions

3D planning via simulated surgery has shown to be a valuable method to predict the need for augment in revision TKA following PJI.

Acknowledgements

The Authors thank Dr. Cristiano De Franco for his unvaluable contribution. No benefits in any form have been received or will be received from a commercial party related directly or indirectly to the subjects of this article.

Conflict of interest statement

The Authors declare no conflict of interest.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Authors’ contributions

GB, VDM: study design; GB, RV, RDG, DB,VDM: data curation; ML: statistical analysis; ML;RDG: writing-original draft preparation; GB: writing-review and editing; MM: supervision. All Authors have read and agreed to the published version of the manuscript.

Ethical consideration

No experimental procedures have been conducted. Due to the retrospective nature of the study ethical committee approval was not necessary. Patients were treated according to the ethical standards of the Helsinki Declaration, and were invited to read, understand, and sign the informed consent form.

Figures and tables

Figure 1.3D printed model with the trail components for TKA revision in place.

Figure 2.Digital 2D templating for the case showed in Figure 1.

Figure 3.Graph displaying percentage of agreement for the two planning techniques.* indicates statistical significance with p < 0.05

Patient Sex- age Implant removed Time from TKA Spacer type Defect AORI (femoral/tibia)
1 F-70 Primary TKA 3 y Articulated 2A/2A
2 F-66 Revision TKA 2 y Articulated 1/2B
3 F-71 Primary TKA 2 y Articulated 2A/1
4 F-73 Primary TKA 1 y Articulated 1/3
5 M-74 Primary TKA 1 y Static 2B/2A
6 F-67 Primary TKA 2 y Static 2B/2B
7 F-72 Primary TKA 2 y Articulated 1/2A
8 M-74 Primary TKA 1 y Articulated 1/2A
9 F-71 Primary TKA 13 y Articulated 1/2A
10 F-78 Primary TKA 5 y Articulated 1/2A
Table I.Patients’ demographics and characteristics.

References

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Affiliations

Giovanni Balato

Department Orthopaedic and Traumatology. “Federico II” University, Naples, Italy

Marco Lenzi

Department Orthopaedic and Traumatology. “Federico II” University, Naples, Italy

Vincenzo de Matteo

Department Orthopaedic and Traumatology. “Federico II” University, Naples, Italy

Raffaele Verrazzo

Department Orthopaedic and Traumatology. “Federico II” University, Naples, Italy

Roberto de Giovanni

Department Orthopaedic and Traumatology. “Federico II” University, Naples, Italy

Dario Baldi

IRCCS Synlab SDN, Naples, Italy

Massimo Mariconda

Department Orthopaedic and Traumatology. “Federico II” University, Naples, Italy

Copyright

© © Ortopedici Traumatologi Ospedalieri d’Italia (O.T.O.D.i.) , 2022

How to Cite

[1]
Balato, G., Lenzi, M., de Matteo, V., Verrazzo, R., de Giovanni, R., Baldi, D. and Mariconda, M. 2022. 3D planning in revision total knee arthroplasty following periprosthetic joint infection. A pilot study. Lo Scalpello - Journal. 36, 2 (Sep. 2022), 131-134. DOI:https://doi.org/10.36149/0390-5276-265.
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