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

The accuracy of preoperative implant size prediction achieved by digital templating in total knee arthroplasty is not affected by the quality of lateral knee radiographs

Background

Digital templating software can be used for preoperative implant size prediction in total knee arthroplasty (TKA). However, the accuracy of its prediction is reported to be low, and the impact of radiograph quality is unclear.

Purpose

To investigate on the application of lateral knee radiograph quality criteria for knee rotation (KR) and knee abduction/adduction (KA) and their impact on the accuracy of final implant size prediction achieved by preoperative digital templating for TKA.

Methods

A total of 191 radiographs of patients undergoing TKA were allocated into four groups according to their KR as measured at the posterior femoral condyles and their KA as measured at the distal femoral condyles on lateral knee radiographs: group A (KR ≤ 5 mm, KA ≤ 5 mm), B1 (KR > 5 mm, KA ≤ 5 mm), B2 (KR ≤ 5 mm, KA > 5 mm) and B3 (KR > 5 mm, KA > 5 mm). Preoperative templating of femoral and tibial implant size using digital templating software was carried out by two observers. Correlation coefficients (CCs) between planned and final implant size, percentage of cases with planned to final size match as well as percentage of cases within ±1 and ±2 of planned to final size were reported according to groups.

Results

Group A showed the highest percentage of cases with matching planned to final femoral implant size (45%) and the highest percentage of cases with ±1 planned to final implant size (86%) as compared to B1 (match 28%, ±1 84%), B2 (match 41%, ±1 84%) and B3 (match 35%, ±1 78%). CCs for planned to final implant size were reported at >0.75 in all groups. No statistically significant difference in the CCs of planned to final implant size amongst groups was found.

Conclusion

The accuracy of implant size prediction achieved by preoperative digital templating for TKA is neither affected by KR nor KA on lateral knee radiographs.

Level of evidence

Level III.

Accuracy and clinical role of digital templating for total knee arthroplasty performed on haemophilic knees

INTRODUCTION

In total knee arthroplasty (TKA), choosing the correct implant size is important. There is lack of data on accuracy of templating on haemophilic knees. Our aim was to test the accuracy of 2D digital templating for TKA on haemophilic arthropathy (HA) of knee.

MATERIALS AND METHODS

TKAs performed on HA between January 2011 and January 2022 were screened. Osteoarthritis (OA) group was created as control group by a one-to-one matching regarding type of implant used. Intra- and interobserver correlations were measured in HA, then correlation between templated and implanted sizes was investigated in four assessments (femur AP, femur lateral, tibia AP, tibia lateral), then compared with OA group. Fifty-eight knees in each group included.

RESULTS

Regarding intraobserver correlation in HA, there was excellent correlation for femur AP [.93 (.73-.98)], femur lateral [.98 (.91-.99)], and tibia AP (1.0) templating. Regarding interobserver correlation in HA, excellent correlation was observed for femur lateral [.93 (.74-.98)] and tibia AP templating [.90 (.65-.97)]. Regarding correlation of templated and applied sizes in HA; tibia AP, tibia lateral and femur lateral templating showed good correlation [.81 (.70-.89), .86 (.77-.91), .79 (.67-.87) while femur AP templating showed moderate correlation [.67 (.50-.79)]. Comparing HA and OA, there was no difference in correlation levels regarding femur AP, femur lateral, tibia AP and tibia lateral templating (p = .056, p = .781, p = .761, p = .083, respectively).

CONCLUSION

Although 2D digital templating shows comparable correlation in HA and OA, clinical applicability of templating on HA appears to be limited in its current state.

Improved intra-operative decision making in RA-TKR with the help of pre-operative CT scan

Background

Robotic-assisted total knee replacement (RA-TKR) is a significant advancement in orthopedic surgery, but intra-operative decision-making remains challenging. Pre-operative imaging techniques, particularly CT scans, have gained momentum, providing insights into the patient's anatomy, improving implant positioning and alignment. However, further research is needed to explore their influence on RA-TKR planning and execution.

Materials and methods

The hospital based cross-sectional study was conducted in Orthopedics department of Sparsh Speciality Hospital, Bangalore & Sunshine Hospital, Hyderabad. A total of 1020 participants in the age group over 50 years during the study period were included based on convenient sampling. The axial CT images were taken preoperatively and RA-TKA was done for all the patients.

Results

The study participant's average age was 64.01 ± 7.13. Out of 1020 patients 259 (24.4%) were males and 761 (74.6%) were females. The median femoral, tibia and Polyethylene predicted and the actual component were same with the side of surgery and BMI. The median femoral predicted actual component was significantly higher among the age category of more than 80 years when compared to other age groups. The median femoral, tibia and Polyethylene predicted was higher in males when compared to females.

Conclusion

Pre-operative CT scans enhance RA-TKR procedures by providing precise anatomical insights, enhancing implant placement, and identifying potential issues, improving surgical outcomes and patient satisfaction.

Predictability of implant sizes during cruciate-retaining total knee arthroplasty using an image-free hand-held robotic system

The use of appropriately sized implants is critical for achieving optimal gap balance following total knee arthroplasty (TKA). Inappropriately sized implants could result in several complications. Robot-assisted TKA (RA-TKA) using CT-based pre-operative planning predicts implant sizes with high accuracy. There is scant literature describing the accuracy of image-free RA-TKA in predicting implant sizes. The purpose of this study was to assess the accuracy of an image-free robotic system in predicting implant sizes during RA-TKA. Patients who underwent cruciate-retaining RA-TKA for primary osteoarthritis, using an image-free hand-held robotic system were studied. The predicted and implanted sizes of the femoral component, tibial component and polyethylene insert, for 165 patients, were recorded. Agreement between robot-predicted and implanted component sizes was assessed in percentages, while reliability was assessed using Cohen's weighted kappa coefficient. The accuracy of the robotic system was 63% (weighted-kappa = 0.623, P < 0.001), 94% (weighted-kappa = 0.911, P < 0.001) and 99.4% (weighted-kappa = 0.995, P < 0.001), in predicting exact, ± 1 and ± 2 sizes of the femoral component, respectively. For the tibial component, an accuracy of 15.8% (weighted-kappa = 0.207, P < 0.001), 55.8% (weighted-kappa = 0.378, P < 0.001) and 76.4% (weighted-kappa = 0.568, P < 0.001) was noted, for predicting exact, ± 1 and ± 2 sizes respectively. An accuracy of 88.5%, 98.2% and 100%, was noted for predicting exact, ± 1 and ± 2 sizes of the polyethylene insert respectively. Errors in predicting accurate implant sizes could be multi-factorial. Though the accuracy of image-free RA-TKA with respect to alignment and component positioning is established, the surgeon's expertise should be relied upon while deciding appropriate implant sizes.

Development and Validation of an Artificial Intelligence Preoperative Planning and Patient-Specific Instrumentation System for Total Knee Arthroplasty

BACKGROUND

Accurate preoperative planning for total knee arthroplasty (TKA) is crucial. Computed tomography (CT)-based preoperative planning offers more comprehensive information and can also be used to design patient-specific instrumentation (PSI), but it requires well-reconstructed and segmented images, and the process is complex and time-consuming. This study aimed to develop an artificial intelligence (AI) preoperative planning and PSI system for TKA and to validate its time savings and accuracy in clinical applications.

METHODS

The 3D-UNet and modified HRNet neural network structures were used to develop the AI preoperative planning and PSI system (AIJOINT). Forty-two patients who were scheduled for TKA underwent both AI and manual CT processing and planning for component sizing, 20 of whom had their PSIs designed and applied intraoperatively. The time consumed and the size and orientation of the postoperative component were recorded.

RESULTS

The Dice similarity coefficient (DSC) and loss function indicated excellent performance of the neural network structure in CT image segmentation. AIJOINT was faster than conventional methods for CT segmentation (3.74 ± 0.82 vs. 128.88 ± 17.31 min, p < 0.05) and PSI design (35.10 ± 3.98 vs. 159.52 ± 17.14 min, p < 0.05) without increasing the time for size planning. The accuracy of AIJOINT in planning the size of both femoral and tibial components was 92.9%, while the accuracy of the conventional method in planning the size of the femoral and tibial components was 42.9% and 47.6%, respectively (p < 0.05). In addition, AI-based PSI improved the accuracy of the hip-knee-ankle angle and reduced postoperative blood loss (p < 0.05).

CONCLUSION

AIJOINT significantly reduces the time needed for CT processing and PSI design without increasing the time for size planning, accurately predicts the component size, and improves the accuracy of lower limb alignment in TKA patients, providing a meaningful supplement to the application of AI in orthopaedics.

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.

Preoperative predictors of implant size in patients undergoing total knee arthroplasty: a retrospective cohort study

BACKGROUND

Traditionally, the size of total knee arthroplasty (TKA) components is predicted by preoperative radiographic templating, which is of limited accuracy. This study aimed to evaluate the role of demographic data and ankle volume in predicting implant size in TKA candidates.

METHODS

In a retrospective study, 415 patients who underwent TKA at a single institution were included. The mean age of the patients was 67.5 ± 7.1 years. The mean BMI of the patients was 31.1 ± 4.7 kg/m2. TKA implants were Zimmer Biomet NexGen LPS-Flex Knee in all cases. The demographic data included age, sex, height, weight, BMI, ethnicity, and ankle volume. Ankle volume was assessed with the figure-of-eight method. Multivariate linear regression analysis was used for predicting factors of implant size.

RESULTS

Multivariate linear regression analysis showed that the Sex (β:1.41, P < 0.001), height (β:0.058, P < 0.001), ankle volume (β:0.11, P < 0.001), and Age (β:0.017, P = 0.004) were significant predictors of tibial component size. Sex (β:0.89, P < 0.001), height (β:0.035, P < 0.001), and ankle volume(β:0.091, P < 0.001) were significant predictors of femoral component size in the multivariate analysis.

CONCLUSION

Demographic data, adjunct with the ankle volume, could provide a promising model for preoperative prediction of the size of tibial and femoral components in TKA candidates.

Preoperative Virtual Total Knee Arthroplasty Surgery Using a Computed Tomography-based 3-dimensional Model With Variation in Reference Points and Target Alignment to Predict Femoral Component Sizing

Background

The purpose of this study was to investigate the size differences of 19 different femoral component placements from the standard position in total knee arthroplasty using 3-dimensional virtual surgery.

Methods

Three-dimensional bone models were reconstructed from the computed tomography data of 101 varus osteoarthritic knees. The distal femoral bone was cut perpendicular to the femoral mechanical axis (MA) in the coronal plane. Twenty different component placements consisting of 5 cutting directions (perpendicular to MA, 3° and 5° extension relative to MA [3°E-MA and 5°E-MA, respectively], and 3° and 5° flexion relative to MA [3°F-MA and 5°F-MA, respectively]) in the sagittal plane, 2 rotational alignments (clinical epicondylar axis [CEA] and surgical epicondylar axis [SEA]), and 2 rotational types of anterior reference guide (central [CR] and medial [MR]) were simulated.

Results

The mean anteroposterior dimension of femur ranged from 54.3 mm (5°F-MA, SEA, CR) to 62.5 mm (5°E-MA, CEA, MR). The largest and smallest differences of anteroposterior dimension from the standard position (3°F-MA, SEA, and CR) were 7.1 ± 1.3 mm (5°E-MA, CEA, and MR) and −1.2 ± 0.2 mm (5°F-MA, SEA, and CR), respectively. Multiple regression analysis revealed that flexion cutting direction, SEA, and CR were associated with smaller component size.

Conclusions

The femoral component size can be affected easily by not only cutting direction but also the reference guide type and the target alignment. Our findings could provide surgeons with clinically useful information to fine-tune for unintended loose or tight joint gaps by adjusting the component size.

Preoperative radiographic parameters in the case of using a narrow-version femoral implant in total knee arthroplasty

BACKGROUND

Recently, total knee arthroplasty (TKA) designs that allow the use of narrow-version femoral implants have been introduced to avoid femoral overhang. The purpose of this study was to investigate the frequency of the use of narrow-version femoral implants and identify the difference in radiographic parameters between using a narrow-version femoral implant and a standard-version femoral implant in TKA.

METHODS

A retrospective study was conducted on 504 primary TKAs using a TKA system (Anthem or Persona) that allowed narrow-version femoral implants. Anteroposterior (AP) dimension, mediolateral (ML) dimension, and modified aspect percentage ratio (ML/AP dimension) of the distal femur in preoperative radiographs were compared between a standard-version group (n = 275) and a narrow-version group (n = 229). A cut-off value of a modified aspect percentage ratio indicating the need for a narrow-version femoral implant was determined using the receiver operating characteristic (ROC) curve.

RESULTS

Mean ML dimension was 80.9 ± 6.1 mm in the standard-version group and 77.3 ± 4.4 mm in the narrow-version group (p < 0.001). Mean modified aspect percentage ratio was 138.8 ± 8.1% in the standard-version group and 131.7 ± 6.3% in the narrow-version group (p < 0.001). The optimum cut-off point of the modified aspect percentage ratio for narrow-version femoral implants was 135.4% (sensitivity: 72.0%; specificity: 66.7%) for Anthem and 133.3% (sensitivity: 75.9%, specificity: 76.4%) for Persona.

CONCLUSION

In the narrow-version femoral implant group, the ML dimension and the mean modified aspect percentage ratio were smaller than in the standard-version femoral implant group. A smaller modified aspect percentage ratio of the distal femur in preoperative radiographs could predict the need for narrow-version femoral implants in TKA. It was suggested that the cut-off point could be suggested as 135.4% for Anthem TKA design and 133.3% for Persona TKA design. These radiographic parameters are cost-effective and easily applicable for planning a TKA.A smaller modified aspect percentage ratio of the distal femur in preoperative radiographs could predict the need for narrow-version femoral implants in TKA. The cut-off point was 135.4% for Anthem TKA design and 133.3% for Persona TKA design.

Magnification assessment of radiographs for knee replacement (MARKeR) - A pilot study in a low-resource setting

Background

Selecting the correct size of implants to be used in total knee arthroplasty is critical for a successful outcome. Marker-less templating systems use an institutionally derived magnification factor for all radiographs.

Purpose

To determine the institutional magnification of knee radiographs for patients awaiting total knee arthroplasty.

Material and Methods

Eighty patients awaiting total knee arthroplasty underwent preoperative knee radiographs using a standardized protocol. A marker attached to the patients’ knees at the level of the knee joint was used to calculate the magnification factor on both anteroposterior (AP) and lateral (LAT) views. Two independent observers estimated the magnification to determine the intra and inter-observer reliability.

Results

The mean magnification of the AP (15.3%) radiograph was significantly greater than the LAT (12.1%) radiograph (p< 0.0001). Patients with absent markers on their radiographs were heavier than patients in whom the marker was visible (84.7 kgs vs. 76.6 kgs, p=0.01). No marker was visible on the radiographs in 56.3% (45/80) of patients. There was excellent inter and intra-observer reliability of both the AP and LAT measurements.

Conclusion

After standardizing the protocol for preoperative knee radiographs, our results show significantly greater institutional magnification of the anteroposterior compared with the lateral images. Accurate templating in knee arthroplasty requires both radiographic images. To reduce errors in implant sizing, we recommend surgeons use different institutional magnification factors for the anteroposterior and lateral radiographs.

Robotic arm-assisted total knee arthroplasty improves preoperative planning and intraoperative decision-making

Background

The reliability of robotic arm-assisted total knee arthroplasty (RA-TKA) has been previously reported. In this study, we evaluated the predictive accuracy of the RA-TKA system in determining the required bone resection and implant size preoperatively and its effect on intraoperative decision-making.

Methods

Data on the outcomes of RA-TKA procedures performed in our department were prospectively collected. A three-dimensional model of the femur, tibia, and fibula was reconstructed using standard computed tomography (CT) images. The model was used preoperatively to predict bone required resection for the femur and tibia and implant size. Intraoperatively, the images were registered to the local anatomy to create a patient-specific model for decision-making, including real-time measurement of the medial-to-lateral difference in the extension/flexion gap and TKA component alignment. Differences between predicted and real bone resections and implant size were evaluated, and the post-TKA mechanical axis of the lower limb and difference in medial-to-lateral flexion/extension gap were measured.

Results

The analysis was based on the data of 28 patients who underwent TKA to treat severe osteoarthritis. The RA-TKA system successfully predicted the femoral and tibial component within one implant size in 28/28 cases (100%). For the 168 bone resections performed, including both femoral and tibial cuts, the resection was within 1 mm of the predicted value in 120/168 (71%) of the cuts. The actual versus predicted bone resection was statistically different only for the lateral tibial plateau (p = 0.018). The medial-to-lateral gap difference was between − 1 and 1 mm, except in one case. The achieved lower limb alignment was accurate overall, with the alignment being within < 1.0° of the neutral mechanical axis in 13/28 cases (46%) and within < 3.0° in 28/28 cases (100%).

Conclusions

The RA-TKA system provided considerable pre- and intraoperative surgical assistance to achieve accurate bone resection, appropriate component sizing, and postoperative alignment after RA-TKA.

Patient Demographics and Anthropometric Measurements Predict Tibial and Femoral Component Sizing in Total Knee Arthroplasty

Background

Accurate sizing is critical for the overall success of a total knee arthroplasty (TKA). This study's primary purpose was to investigate the ability to predict the tibial and femoral component size in a single implant system from patient demographics and anthropometric data. A secondary goal was to compare the predicted tibial and femoral component sizes from our statistical model with a previously validated electronic application used to predict the implant size.

Methods

A consecutive series of 484 patients undergoing a primary TKA at a single institution was reviewed. Data on height, weight, body mass index, sex, age, and component size were collected. A proportional odds model was developed to predict tibial and femoral component sizes. The relationship between the proportional odds model predictions was also compared with the component sizes determined by the Arthroplasty Size Predictor electronic application.

Results

Weight, height, and sex predicted the implanted component size with an accuracy of 54.0% (n = 247/484) for the tibia and 51.1% (n = 231/484) for the femur. The accuracy improved to 94.4% (n = 457/484) for the tibia and 93.4% (n = 452/484) for the femur within ±1 component size. Our data are highly correlated to the Arthroplasty Size Predictor for the predicted tibial component size (ρ = 0.91, P < .001) and femoral component size (ρ = 0.89, P < .001).

Conclusions

Our novel templating model may improve operative efficiency for a single TKA system. Our findings have a high concordance with a widely available electronic application used to predict implant sizes for a variety of TKA systems.

Agreement in component size between preoperative measurement, navigation and final implant in total knee replacement

Background

One of the possible causes of dissatisfaction reported by many patients after total knee replacement (TKR) is the lack of agreement between component size and bone structure. To avoid this complication and facilitate the procedure, preoperative planning with digitized templates is recommended. Surgical navigation indicates the best position and the most adequate size of arthroplasty and may therefore replace preoperative radiographic measurement. The objective of the study was to check agreement between the sizes of TKR components measured before surgery with digitized templates, the size recommended by the navigation and sizes actually implanted.

Methods

In 103 patients scheduled for TKR, preoperative full-limb radiography was performed to measure the mechanical and anatomical axes of the limb, femur and tibia. The most adequate size of the femoral and tibial components was planned by superimposing digitized templates. The size recommended in navigation and the size of the finally implanted components were also recorded.

Results

A high level of agreement was found between the sizes of femoral and tibial components measured by X-rays and in navigation (0.750 and 0.772, respectively) (intraclass correlation and Cronbach's alpha). Agreement between the sizes recommended by X-rays and navigation and those finally implanted was 0.886 for the femur and 0.891 for the tibia. Agreement levels were not different in cases with prior deformities of limb axis.

Conclusions

The high level of agreement found in component sizes between radiographic measurement with digitized templates and navigation suggests that preoperative X-ray measurement is not needed when navigation is used for placement of implants during TKR.

The translational potential of this article

Computer-assisted surgery may avoid preoperative measurement with templates in TKR.