The role of preoperative templating in total knee arthroplasty: comparison of three prostheses

Prediction of Total Knee Arthroplasty Sizes with Demographics, including Hand and Foot Sizes

Anticipating implant sizes before total knee arthroplasty (TKA) allows the surgical team to streamline operations and prepare for potential difficulties. This study aims to determine the correlation and derive a regression model for predicting TKA sizes using patient-specific demographics without using radiographs. We reviewed the demographics, including hand and foot sizes, of 1,339 primary TKAs. To allow for comparison across different TKA designs, we converted the femur and tibia sizes into their anteroposterior (AP) and mediolateral (ML) dimensions. Stepwise multivariate regressions were performed to analyze the data. Regarding the femur component, the patient's foot, gender, height, hand circumference, body mass index, and age was the significant demographic factors in the regression analysis (R-square 0.541, p < 0.05). For the tibia component, the significant factors in the regression analysis were the patient's foot size, gender, height, hand circumference, and age (R-square 0.608, p < 0.05). The patient's foot size had the highest correlation coefficient for both femur (0.670) and tibia (0.697) implant sizes (p < 0.05). We accurately predicted the femur component size exactly, within one and two sizes in 49.5, 94.2, and 99.9% of cases, respectively. Regarding the tibia, the prediction was exact, within one and two sizes in 53.0, 96.0, and 100% of cases, respectively. The regression model, utilizing patient-specific characteristics, such as foot size and hand circumference, accurately predicted TKA femur and tibia sizes within one component size. This provides a more efficient alternative for preoperative planning.

The Accuracy of Computed Tomography-Based, Three-Dimensional Implant Planning in Robotic-Assisted Total Knee Arthroplasty

Advanced imaging used in robotic-assisted total knee arthroplasty (TKA), such as computed tomography (CT)-based three-dimensional (3D) planning, may provide an accurate means of implant sizing preoperatively. The purpose of this study was to examine preoperative CT-based implant planning accuracy for robotic-assisted TKA in patients who have (1) varus deformities, (2) valgus deformities, (3) neutral alignment, and (4) retained hardware. A total of 393 patients underwent a robotic-assisted TKA by a single surgeon received preoperative CT scans. The surgeon reviewed the CT-based model preoperatively and recorded the expected size of the components. The final implants used in each case were recorded and compared with the surgeon's preoperative plan. In all groups of patients, the surgeon's CT-based implant plan was within one size of the implant utilized 100% of the time for both the tibiae and femora. Overall, the surgeon was exactly matched in 319 (81%) and 315 (80%) cases for the femoral and tibial components, respectively. For the femoral component, the mean age for patients in whom the original plan was exactly matched was younger than those whose implants were upsized and older than patients those implants were downsized (p = 0.024). Other patient demographics and preoperative knee alignment were not associated with predictive accuracy for femoral or tibial components. Our results demonstrate how preoperative CT-based, 3D planning for robotic-assisted TKA is accurate to within one size of the components in every case (100%), and exactly matched in 80%. The results of this study are important because they demonstrate how CT-based preoperative implant planning for TKA is reliable and accurate across all native knee alignments and other patient-specific factors. In addition, they build on a previous study by the same single surgeon, demonstrating that predictive ability can improve over time. This may be important as we move toward more outpatient surgery with less ability for prostheses inventory at ambulatory sites.

Accuracy of one-dimensional templating on linear EOS radiography allows template-directed instrumentation in total knee arthroplasty

BACKGROUND

Templating for total knee arthroplasty (TKA) is routinely performed on two-dimensional standard X-ray images and allows template-directed instrumentation. To date, there is no report on one-dimensional (1D) anteroposterior (AP) templating not requiring specific templating software. We aim to describe a novel technique and explore its reliability, accuracy and potential cost-savings.

METHODS

We investigated a consecutive series of TKAs at one institution between January and July 2019. Patients with preoperative low-dose linear AP EOS radiography images were included. Implant component sizes were retrospectively templated on the AP view with the hospitals imaging viewing software by two observers who were blinded to the definitive implant size. Planning accuracy as well as inter- and intra-observer reliability was calculated. Cost-savings were estimated based on the reduction of trays indicated by the 1D templating size estimations.

RESULTS

A total of 141 consecutive TKAs in 113 patients were included. Accuracy of 1D templating was as follows: exact match in 53% femoral and 63% tibial components, within one size in 96% femoral and 98% tibial components. Overall 58% of TKA components were planned correctly and 97% within one size. Inter- and intra-rater reliability was good (κ = 0.66) and very good (κ = 0.82), respectively. This templating process can reduce instrumentation from six to three trays per case and therefore halve sterilisation costs.

CONCLUSIONS

The new 1D templating method using EOS AP imaging predicts component sizes in TKA within one size 97% of the time and can halve the number of instrumentation trays and sterilisation costs.

Demographic data is more predictive of component size than digital radiographic templating in total knee arthroplasty

Background

Preoperative radiographic templating for total knee arthroplasty (TKA) has been shown to be inaccurate. Patient demographic data, such as gender, height, weight, age, and race, may be more predictive of implanted component size in TKA.

Materials and methods

A multivariate linear regression model was designed to predict implanted femoral and tibial component size using demographic data along a consecutive series of 201 patients undergoing index TKA. Traditional, two-dimensional, radiographic templating was compared to demographic-based regression predictions on a prospective 181 consecutive patients undergoing index TKA in their ability to accurately predict intraoperative implanted sizes. Surgeons were blinded of any predictions.

Results

Patient gender, height, weight, age, and ethnicity/race were predictive of implanted TKA component size. The regression model more accurately predicted implanted component size compared to radiographically templated sizes for both the femoral (P = 0.04) and tibial (P < 0.01) components. The regression model exactly predicted femoral and tibial component sizes in 43.7 and 43.7% of cases, was within one size 90.1 and 95.6% of the time, and was within two sizes in every case. Radiographic templating exactly predicted 35.4 and 36.5% of cases, was within one size 86.2 and 85.1% of the time, and varied up to four sizes for both the femoral and tibial components. The regression model averaged within 0.66 and 0.61 sizes, versus 0.81 and 0.81 sizes for radiographic templating for femoral and tibial components.

Conclusions

A demographic-based regression model was created based on patient-specific demographic data to predict femoral and tibial TKA component sizes. In a prospective patient series, the regression model more accurately and precisely predicted implanted component sizes compared to radiographic templating.

Level of evidence

Prospective cohort, level II.

Algorithm based automatic templating is less accurate than manual digital templating in total knee arthroplasty

The purpose of the study was to evaluate the accuracy of a commercial automatic digital templating algorithm compared to manual digital templating in total knee arthroplasty (TKA). The study also evaluated if race and the presence of a standardized calibration marker on preoperative radiographs effect the accuracy of digital templating. One hundred twenty-five consecutive patients undergoing primary TKA were included in the study. Patient demographics, etiology of arthritis, and the presence of a standardized calibration marker on preoperative anteroposterior (AP) and lateral radiographs was recorded. Manual digital templating and the use of the "auto-knee" templating algorithm with "Traumacad" software was performed and recorded. Intraoperative sizes of the actual implants used were recorded. Pearson χ2 test was used to evaluate the accuracy of auto versus manual templating. Manual templating was within 1 size of the implant used intraoperatively for femoral and tibial implants 97.6% and 94.2% of the time, respectively. The "auto-knee" algorithm was within one size of the implant used for femoral and tibial implants 51.2% and 71.2% of the time, respectively. The presence of a standardized calibration marker on the AP view did not change accuracy of templating for both components. There was no difference in accuracy of templating between races. We caution surgeons from exclusively using an automatic algorithm as it is less accurate than manual templating for TKA.

Prospective Comparison of Available Primary Total Knee Arthroplasty Sizing Equations

BACKGROUND

Several studies have proposed regression equations that can increase the accuracy of predicting femur and tibia component sizes for total knee arthroplasty (TKA). This study compared available regression equations in their ability to prospectively predict component size in a unique patient series.

METHODS

Demographic data and implanted femur and tibia TKA component sizes were collected on a consecutive 382 patients undergoing index TKA. Equations by Bhowmik-Stoker et al, Ren et al, Sershon et al, and Miller et al were identified that used age, race, ethnicity, gender, height, weight, or body mass index. Equation outputs were converted to implant-corrected sizes and compared to the implanted component.

RESULTS

Femur and tibia sizes were accurately predicted within 1 size 88% and 92%, 84% and 86%, and 79% and 92% for Bhowmik-Stoker et al, Sershon et al, and Miller et al, respectively. Ren et al was within 1 tibia size 88% of the time. Adding one more common implant size improved this accuracy by an average of 9.1% and 6.6% for the femur and tibia, respectively. For femur components, Bhowmik-Stoker et al outperformed Sershon et al by 0.14 sizes (P < .001) and Miller et al by 0.21 sizes (P < .001) on average. For tibia components, Bhowmik-Stoker et al outperformed Sershon et al by 0.09 sizes (P = .028) and Ren et al by 0.11 sizes (P = .005) on average.

CONCLUSION

Equations by Bhowmik-Stoker et al more accurately predicted implanted TKA size. In cases of greater uncertainty, the practicing surgeon may err on having more common TKA sizes available.

Digital templating of rotating hinge revision and primary total knee arthroplasty

Preoperative digital templating in total knee arthroplastiy (TKA) is useful in predicting implant size, the level of bone resections and the need for special implants. This study should evaluate the templating of a rotating hinge prosthesis and the realization of the preoperative plan. Two observers with different experience levels templated 40 cases which received TKA and R-TKA using digital planning on standard preoperative x-rays. The examiners templated all cases independently and were blinded to the component sizes used intraoperatively. The kappa coefficient and Pearson coefficient were determined. The accuracy in predicting the correct implant size in revision TKA varied from 67,9% to 82,1% depending on the training level of the observer. The two observers show moderate and substantial correlation. The coefficient indicates a substantial agreement in between the two observers in templating revision TKA. The accuracy depends on the experience of the observer. In the cases were the templating was incorrect, the prosthesis was implanted smaller than the preoperative plan. With this knowledge very good results can be made with this prosthesis.

Using Patient Demographics and Statistical Modeling to Predict Knee Tibia Component Sizing in Total Knee Arthroplasty

BACKGROUND

Preoperative planning is important to achieve successful implantation in primary total knee arthroplasty (TKA). However, traditional TKA templating techniques are not accurate enough to predict the component size to a very close range.

METHODS

With the goal of developing a general predictive statistical model using patient demographic information, ordinal logistic regression was applied to build a proportional odds model to predict the tibia component size. The study retrospectively collected the data of 1992 primary Persona Knee System TKA procedures. Of them, 199 procedures were randomly selected as testing data and the rest of the data were randomly partitioned between model training data and model evaluation data with a ratio of 7:3. Different models were trained and evaluated on the training and validation data sets after data exploration.

RESULTS

The final model had patient gender, age, weight, and height as independent variables and predicted the tibia size within 1 size difference 96% of the time on the validation data, 94% of the time on the testing data, and 92% on a prospective cadaver data set.

CONCLUSION

The study results indicated the statistical model built by ordinal logistic regression can increase the accuracy of tibia sizing information for Persona Knee preoperative templating. This research shows statistical modeling may be used with radiographs to dramatically enhance the templating accuracy, efficiency, and quality. In general, this methodology can be applied to other TKA products when the data are applicable.

Pre-operative templating for knee arthroplasty shows low accuracy with standard X-rays

OBJECTIVES

The purpose of this study was to evaluate the accuracy and reliability of pre-operative templating in predicting the size of femoral and tibial components and the effect of coronal deformity on templating accuracy.

METHODS

This was a retrospective study of 39 pre-operative templates prepared by three different surgeons with different levels of training. The accuracy and reliability measures were evaluated by alpha and kappa coefficients of agreement. The analysis of the effect of coronal deformity on the accuracy of the template was measured by the Spearman's correlation test.

RESULTS

Templating was accurate for the femoral component in 28.21% of anterposterior (AP) radiographs and 35.90% of lateral radiographs. Kappa coefficients were respectively 0.111 (95% confidence interval [95%CI]: -0.19 to 0.241) and 0.200 (95%CI: -0.010 to 0.401), indicating poor agreement. Templating accuracy for the tibial component were, respectively, 37.61% and 47.01% for AP and lateral views. Kappa coefficients were 0.186 (95%CI: -0.070 to 0.379) for the AP view and 0.315 (95%CI: -0.199 to 0.431) for the lateral view, showing poor and slight agreement respectively. Considering a margin of error of ±1 sizes, the agreement level improved for all components, particularly for tibia, where agreement levels become very good. The inter-observer agreement was fair for all components, except for the lateral view of the femoral component, whose agreement was good. The Spearman correlation test showed no correlation between accuracy of templating and coronal deformity.

CONCLUSION

Pre-operative templating is an unreliable and inaccurate tool. There is no relation between coronal deformity and accuracy of templating.

Predicted osteotomy planes are accurate when using patient-specific instrumentation for total knee arthroplasty in cadavers: a descriptive analysis

PURPOSE

Malalignment of implants is a major source of failure during total knee arthroplasty. To achieve more accurate 3D planning and execution of the osteotomy cuts during surgery, the Signature (Biomet, Warsaw) patient-specific instrumentation (PSI) was used to produce pin guides for the positioning of the osteotomy blocks by means of computer-aided manufacture based on CT scan images. The research question of this study is: what is the transfer accuracy of osteotomy planes predicted by the Signature PSI system for preoperative 3D planning and intraoperative block-guided pin placement to perform total knee arthroplasty procedures?

METHODS

The transfer accuracy achieved by using the Signature PSI system was evaluated by comparing the osteotomy planes predicted preoperatively with the osteotomy planes seen intraoperatively in human cadaveric legs. Outcomes were measured in terms of translational and rotational errors (varus, valgus, flexion, extension and axial rotation) for both tibia and femur osteotomies.

RESULTS

Average translational errors between the osteotomy planes predicted using the Signature system and the actual osteotomy planes achieved was 0.8 mm (± 0.5 mm) for the tibia and 0.7 mm (± 4.0 mm) for the femur. Average rotational errors in relation to predicted and achieved osteotomy planes were 0.1° (± 1.2°) of varus and 0.4° (± 1.7°) of anterior slope (extension) for the tibia, and 2.8° (± 2.0°) of varus and 0.9° (± 2.7°) of flexion and 1.4° (± 2.2°) of external rotation for the femur.

CONCLUSION

The similarity between osteotomy planes predicted using the Signature system and osteotomy planes actually achieved was excellent for the tibia although some discrepancies were seen for the femur. The use of 3D system techniques in TKA surgery can provide accurate intraoperative guidance, especially for patients with deformed bone, tailored to individual patients and ensure better placement of the implant.

Can Demographic Variables Accurately Predict Component Sizing in Primary Total Knee Arthroplasty?

BACKGROUND

As health care reform drives providers to reduce costs and improve efficiencies without compromising patient care, preoperative planning has become imperative. The purpose of this study is to determine whether height, weight, and gender can accurately predict total knee arthroplasty (TKA) sizing.

METHODS

A consecutive series of 3491 primary TKAs performed by 2 surgeons was reviewed. Height, weight, gender, implant, preoperative templating sizes, and final implant sizes were collected. Implant-specific dimensions were collected from vendors. Using height, weight, and gender, a multivariate linear regression was performed with and without the inclusion of preoperative templating. Accuracy of the model was reported for commonly used implants.

RESULTS

There was a significant linear correlation between height, weight, and gender for femoral (R² = 0.504; P < .001) and tibial sizes (R² = 0.610; P < .001). Adding preoperative templating to the regression analysis increased the overall model fit for both the femoral (R² = 0.756; P < .001) and tibial sizes (R² = 0.780; P < .001). Femoral and tibial sizes were accurately predicted within 1 size of the final implant 71%-92% and 81%-97% using demographics alone or 85%-99% and 90%-99% using both templating and demographics, respectively.

CONCLUSION

This novel TKA templating model allows final implants to be predicted to within 1 size. The model allows for simplified preoperative planning and potential implementation into a cost-savings program that limits inventory and trays required for each case.

The accuracy and reliability of pre-operative templating in revision total knee arthroplasty. A comparison of analogue and digital methods

AIMS

To determine whether the size of the prostheses used in revision knee arthroplasty may be accurately and reproducibly predicted using analogue or digital pre-operative templating techniques.

METHODS

Pre-operative radiographs were templated using analogue radiographs and acetate templates, digital radiographs and acetate templates and digital radiographs and digital templating software.

RESULTS

Overall accuracy of predicting the size of implant used at surgery was 44%. There was no significant difference in the accuracy of the various templating techniques (p = 0.098).

CONCLUSIONS

Templating in revision knee arthroplasty is neither of suitable accuracy nor reliability enough to safely recommend its use for implant size prediction.

Toward the interpretation of the combined effect of size and body weight on the tribological performance of total knee prostheses

PURPOSE

The research questions of the present study were: (1) Is total knee prosthesis wear behaviour influenced by implant size, body weight and their combined effect? (2) Are these findings significant and helpful from a clinical point of view?

METHODS

Two very different sizes of the same total knee prosthesis (TKP), previously tested with ISO 14243 parameters, were tested on a knee simulator for a further two million cycles using a modified ISO 14243 load waveform. Roughness examination was performed on the metallic components. Gravimetric and micro-Raman spectroscopic analyses were carried out on the polyethylene inserts.

RESULTS

The average volumetric mass loss was 69 ± 3 mm(3) and 88 ± 4 mm(3) for smaller and bigger size, respectively. Bigger TKPs are little influenced by an increased load, while the wear trend of the smaller TKP showed a redoubled slope, and more significant morphology changes were observed. However, the two sizes seem to behave similarly when subjected to a load increase of 15 %; the slope of the volumetric mass loss trend was comparable for the two sets of inserts, which did not appear significantly different also at the molecular level. Roughness average parameters of the lateral femoral condyle support this evidence.

CONCLUSIONS

It can be asserted that the body weight and implant size are relevant to the understanding of TKP wear behaviour. A post-implantation body weight increase in a patient with smaller knee dimensions could results in more critical effects on prosthesis long-term performance.

Total knee arthroplasty component templating: a predictive model

Preoperative planning is essential to total knee arthroplasty (TKA); however, TKA templating is historically inaccurate. To improve on templating accuracy and streamline preoperative planning, we set out to predict component sizes based on patient characteristics without radiographs. A total of 123 consecutive patients undergoing unilateral TKA were identified and included in the model study. Input variables consisted of age, gender (as a binary number), height, weight, and body mass index. A linear regression model was created. The models predicted component size exactly in 74% of femurs and 85% of tibias. All model predictions were within a ±1 size of the actual components implanted. Our models were more accurate than any previous model for TKA reported.

Method for selection of femoral component in total knee arthroplasty (tka)

A method is proposed enabling a surgeon to preoperatively determine the preeminent type and size of prosthesis, from those available, to be used in a particular patient undergoing knee replacement surgery. Parameters of healthy knee geometry were estimated by employing an unsupervised neural network. These estimated parameters were then applied in a χ(2) goodness of fit (GoF) test to determine which femoral prosthesis type and size delivers the most appropriate fit. This approach was used to determine the most suitable match of three implants for 34 different cases. Implant C performed the best and was the optimal fit in 59% of the cases, Implant A was the best fit in 38% of the cases and Implant B the best fit in 3% of the cases. This method shows promise in aiding a surgeon to select the optimal prosthesis type and size from an array of different conventional total knee replacements.

The reliability and accuracy of digital templating in total knee replacement

We aimed to determine the reliability, accuracy and the clinical role of digital templating in the pre-operative work-up for total knee replacement.

Initially a sample of ten pre-operative digital radiographs were templated by four independent observers to determine the inter- and intra-observer reliability of the process. Digital templating was then performed on the radiographs of 40 consecutive patients undergoing total knee replacement by a consultant surgeon not involved with the operation, who was blinded to the size of the implant inserted. The Press Fit Condylar Sigma Knee system was used in all the patients. The size of the implant as judged by templating was then compared to that of the size used.

Good inter- and intra-observer agreement was demonstrated for both femoral and tibial templating. However, the correct size of the implant was predicted in only 48% of the femoral and 55% of the tibial components. Albeit reproducible, digital templating does not currently predict the correct size of component often enough to be of clinical benefit.

Determination of femoral component size in unicompartmental knee replacement

It is difficult to determine the ideal size of femoral component when a unicompartmental knee replacement (UKR) is implanted with a minimally invasive approach. The aim of the study was to identify the best method of determining femoral component size pre-operatively. This was done by assessing the accuracy with which it could be predicted by pre-operative templating, patient height, gender and tibial component size. One hundred patients who had had Oxford UKR were studied. Pre-operative radiographs were templated and patient height, gender and implanted tibial component size were recorded. From a review of post-operative radiographs and the known size of component used the ideal size of component that should have been used was established. By relating patient height, gender and tibial component size to the ideal femoral component size the range of these various parameters that best predicted each component size was identified. The reliability of these predictions was assessed assuming that a component one size off ideal was acceptable and two sizes off was unacceptable. Templating was correct in 67% of cases, acceptable in 33% and was never unacceptable. Height alone was correct in 56%, acceptable in 38% and unacceptable in 6%. Height based on gender was correct in 75%, acceptable in 25% and was never unacceptable. Tibial size was correct in 56%, acceptable in 41% and unacceptable in 3%. We conclude that both templating and height based on gender are reliable methods of assessing femoral component size. However because errors can occur surgeons are advised to use both.