Fallacies of CT based component size prediction in total knee arthroplasty - Are patient specific instruments the answer?

Role of Image-Free Robotic-Assisted Technology in Enhancing Accuracy of Implant Sizing for Total Knee Arthroplasty

Background The selection of properly sized implants is essential to achieve a well-balanced knee and favorable clinical outcomes following Total Knee Arthroplasty (TKA). There is limited evidence in the literature regarding the effectiveness of robotic-assisted technology (RA-TKA) without imaging in accurately predicting implant sizes. Our aim was to provide an evidence-based assessment of this technology's accuracy in selecting appropriate implant sizes during robotic-assisted, image-free TKA. Methods This study included 50 consecutive patients who underwent image-free robotic-assisted primary TKA for end-stage knee osteoarthritis, excluding those with prior knee surgeries or undergoing revision TKA. The same surgical team performed all procedures using a medial parapatellar approach and an image-free robotic system with a handheld saw. Initial data from the first 10 cases showed 100% accuracy in implant size prediction. We calculated a sample size of 28 patients to achieve a 90% reduction in prediction error. Femoral registration points were marked (femur center, Whiteside's line, distal medial condyle, distal lateral condyle, posterior medial condyle, posterior lateral condyle, and anterior femur cortex), and implant sizing suggested by the robotic system was verified against trial components by an independent observer. Efficacy was compared with historical controls using the Chi-square test, with significance set at p<0.05. Results The image-free robotic system had an accuracy of 92% (46 out of 50) in predicting the exact femoral component and 100% (50 out of 50) accuracy in predicting ±1 size femur component. Compared to the historical control, the accuracy of implant size prediction using the image-free robotic system was statistically significant (Chi-square test, p = 0.0005 and p = 0.0021, respectively). Conclusion The findings from this study highlight the effectiveness of image-free robotic-assisted technology in achieving precise implant sizing during primary TKA for end-stage osteoarthritis over traditional approaches. The system's improved accuracy in femoral sizing suggests a potential shift toward more reliable, data-driven implant selection that could minimize intraoperative adjustments. By promoting a standardized approach to component fitting, image-free robotics may help optimize surgical consistency, thereby supporting better long-term implant performance and patient satisfaction. These results encourage further exploration into image-free robotic systems as a valuable tool in advancing knee arthroplasty outcomes.

The Accuracy of CT-Based Three-Dimensional Templating in Predicting Implant Sizes in Patients Undergoing Robot-Assisted Total Knee Arthroplasty

Background

Computed tomography (CT) based three-dimensional templating is increasingly being used to predict implant sizes in total knee arthroplasty (TKA). However, the existing data is heterogeneous, and the majority of studies lack adequate statistical power. This study investigated whether preoperative CT-based planning in robot-assisted TKA (RA-TKA) helps in predicting the accurate size of implant used.

Methods

This is a single-center retrospective study of 632 consecutive RA-TKA surgeries. All surgeries were performed using a fully automatic Cuvis RA-TKA system. Cohen's Kappa (κ) coefficient was used to measure the level of agreement between the predicted and the final implant sizes.

Results

A total of 632 knees were operated on 384 patients. A total of 136 unilateral cases whereas 248 patients had both knees operated on. For the tibial component, in 21.7% cases a bigger implant size was used while in 11.8% cases a smaller size was used. For the femoral component, in 5.1% cases a bigger implant size was used while in 4.9% cases a smaller size was used. The agreement between the predicted and actual implant sizes was moderate for the tibial component [κ = 0.56 (95% CI: 0.51 to 0.61); p < 0.001] and almost perfect for the femoral component [κ = 0.87 (95% CI: 0.84 to 0.90); p < 0.001].

Conclusion

This study suggests that planning of RA-TKA using a CT-based model can be valuable to surgeons in accurately predicting the component size for femur and to a lesser degree for tibia. Future studies should investigate the potential predictors of discordance between the predicted and actual tibial implant sizes.

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.

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.

A computational tool for automatic selection of total knee replacement implant size using X-ray images

Purpose: The aim of this study was to outline a fully automatic tool capable of reliably predicting the most suitable total knee replacement implant sizes for patients, using bi-planar X-ray images. By eliminating the need for manual templating or guiding software tools via the adoption of convolutional neural networks, time and resource requirements for pre-operative assessment and surgery could be reduced, the risk of human error minimized, and patients could see improved outcomes.

Methods: The tool utilizes a machine learning-based 2D—3D pipeline to generate accurate predictions of subjects’ distal femur and proximal tibia bones from X-ray images. It then virtually fits different implant models and sizes to the 3D predictions, calculates the implant to bone root-mean-squared error and maximum over/under hang for each, and advises the best option for the patient. The tool was tested on 78, predominantly White subjects (45 female/33 male), using generic femur component and tibia plate designs scaled to sizes obtained for five commercially available products. The predictions were then compared to the ground truth best options, determined using subjects’ MRI data.

Results: The tool achieved average femur component size prediction accuracies across the five implant models of 77.95% in terms of global fit (root-mean-squared error), and 71.79% for minimizing over/underhang. These increased to 99.74% and 99.49% with ±1 size permitted. For tibia plates, the average prediction accuracies were 80.51% and 72.82% respectively. These increased to 99.74% and 98.98% for ±1 size. Better prediction accuracies were obtained for implant models with fewer size options, however such models more frequently resulted in a poor fit.

Conclusion: A fully automatic tool was developed and found to enable higher prediction accuracies than generally reported for manual templating techniques, as well as similar computational methods.

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.

The Accuracy of Three-Dimensional CT Scan Software in Predicting Prosthetic Utilization in Total Shoulder Arthroplasty

INTRODUCTION

Recent innovations in shoulder arthroplasty include three-dimensional (3D) CT software imaging that can be used to predict which prosthetic implants will be used intraoperatively. Correct prediction of the implants may optimize supply chain logistics for the surgeon, hospital, ambulatory surgery center, and the implant company. The purpose of this study was to examine a single surgeon's experience with this software to determine its predictive accuracy in determining which implants would be used intraoperatively.

METHODS

A retrospective review of patients undergoing total shoulder arthroplasty (TSA) performed by a single surgeon was performed. Inclusion criteria were patients undergoing anatomic (aTSA) or reverse (rTSA) TSA examined preoperatively with the 3D CT planning software. A chart review was performed to compare the accuracy of the preoperative plan in predicting the actual prostheses implanted at surgery.

RESULTS

Two hundred seventy-eight shoulders from 260 patients were included. One hundred fifty-one shoulders underwent aTSA, and 127 shoulders underwent rTSA. The surgeon was able to predict the type of arthroplasty (anatomic versus reverse) implanted in 269 of 278 (97%) shoulders. Using the 3D CT software, the surgeon was able to predict all the implants implanted in 68 shoulders (24%). For aTSA, 3D CT imaging successfully predicted all implants implanted in 43 shoulders (28%), glenoid implants implanted in 120 of 148 shoulders (81%), and humeral implants implanted in 54 shoulders (36%). For rTSA, 3D CT imaging successfully predicted all implants implanted in 26 shoulders (20%), glenoid implants implanted in 106 shoulders (83%), and humeral implants implanted in 39 shoulders (31%).

CONCLUSIONS

The 3D CT software combined with surgeon's judgment provided a high accuracy (97%) in determining the type of arthroplasty, a moderately high accuracy in determining the glenoid implants (81% to 83%), a low accuracy in determining humeral implants (31% to 36%), and a low accuracy in determining all prostheses used for each surgery (20% to 28%).

LEVEL OF EVIDENCE

LOE IV-Diagnostic Case Series.

Planning on CT-Based 3D Virtual Models Can Accurately Predict the Component Size for Total Knee Arthroplasty

The ability to predict accurate sizing of the implant components for total knee arthroplasty surgery can have several benefits in the operating room, in terms of simplifying the workflow and reducing the number of required instrument trays. Planning on a three-dimensional (3D) virtual model can be used to predict size. The aim of this study was to quantify the accuracy of the surgeon-validated plan prediction on a computed tomography (CT)-based system. The clinical records of 336 cases (267 patients), operated using a CT-based patient-specific instrumentation, have been reviewed for the size of implanted components. Preoperative default planning (according to the preferences of the surgeon) and approved planning have been compared with the size of implanted components for both the femur and tibia. The prosthesis size, preplanned by the manufacturers, was modified by the surgeon during the validation process in 0.9% of cases for the femoral component and in 2.7% of cases for the tibial component. The prosthesis size, preplanned by the surgeon after the validation process, was used in 95.8% for the femur and 92.6% for the tibia. Concordance on the size of the surgeon-validated plan and the finally implanted size was perfect for both, the femoral (κ  =  0.951; 95% confidence interval [CI]: 0.92-0.98) and the tibial component (κ  =  0.902; 95% CI: 0.86-0.94). The most frequent change of size (51%) was an increase by one size of the planned tibial component. Planning of knee arthroplasty surgery on a 3D virtual, CT-based model is useful to surgeons to help predict the size of the implants to be used in surgery. The system we have used can accurately predict the component size for both the femur and tibia. This study reflects a study of level III evidence.

Current status and challenges of Additive manufacturing in orthopaedics: An overview

Additive manufacturing is a rapidly emerging technology which is being successfully implemented in the various field of medicine as well as in orthopaedics, where it has applications in reducing cartilage defects and treatments of bones. The technology helps through systematic collection of information about the shape of the "defects" and precise fabrication of complex 3D constructs such as cartilage, heart valve, trachea, myocardial bone tissue and blood vessels. In this paper, a large number of the relevant research papers on the additive manufacturing and its application in medical specifically orthopaedics are identified through Scopus had been studied using Bibliometric analysis and application analysis is undertaken. The bibliometric analysis shows that there is an increasing trend in the research reports on additive manufacturing applications in the field of orthopaedics. Discussions are on using technological advancement like scanning techniques and various challenges of the orthopaedic being met by additive manufacturing technology. For patient-specific orthopaedic applications, these techniques incorporate clinical practice and use for effective planning. 3D printed models printed by this technology are accepted for orthopaedic surgery such as revision of lumbar discectomy, pelvic surgery and large scapular osteochondroma. The applications of additive manufacturing in orthopaedics will experience a rapid translation in future. An orthopaedic surgeon can convert need/idea into a reality by using computer-aided design (CAD) software, analysis software to facilitate the manufacturing. Thus, AM provides a comprehensive opportunity to manufacture orthopaedic implantable medical devices.

Publication trends and knowledge mapping in 3D printing in orthopaedics

PURPOSE

Three dimensional (3D) printing, also called 'rapid prototyping' and 'additive manufacturing' is considered as a "second industrial revolution." With this rapidly emerging technology, CT or MR images are used for the creation of graspable objects from 3D reconstituted images. Patient-specific anatomical models can be, therefore, manufactured efficiently. These can enhance surgeon's understanding of their patients' patho-anatomy and also help in precise preoperative planning. The 3D printed patient-specific guides can also help in achieving accurate bony cuts, precise implant placement, and nice surgical results. Customized implants, casts, orthoses and prosthetics can be created to match an individual patient's anatomy. The 3D printing of individualized artificial cartilage scaffolds and 3D bioprinting are some other areas of growing interest. We aim to study the publication trends in 3D printing as applied to the field of orthopaedics.

MATERIALS AND METHODS

A literature search was performed to extract all papers related to 3D printing applications in orthopaedics and allied sciences on the Pubmed, Web of Science and SCOPUS databases. Suitable keywords and boolean operators ("3D Printing" OR "3-dimensional printing" OR "3D printed" OR "additive manufacturing" OR "rapid prototyping") AND (''Orthopaedics" OR "Orthopaedics'') were used, in May 2018. Search was attempted in Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and Database of Abstracts of Review of Effectiveness (DARE) databases, using keywords 3d printing orthopaedics. A similar search was repeated in pubmed and SCOPUS to get more specific papers.No limits were set on the period or evidence level, as 3D printing in orthopaedics is relatively new and evidence available is usually limited to low-level studies. Trends in a publication on these topics were analyzed, focussing on publications, type of research (basic science or clinical), type of publication, authors, institution, and country. Some citations received by these papers were also analyzed in SCOPUS and Web of Science. MS Excel (2008 - Mac version) and VOS Viewer1.6.8 (2018- Mac version) software were used to analyze the search results and for citation mapping respectively. We also identified top 10 most cited articles in the field.

RESULTS

An increasing trend in publications in 3D printing-related work in orthopedic surgery and related fields was observed in the recent past. A search on Pubmed using the above strategy revealed 389 documents. A similar search revealed 653 documents on SCOPUS, many (314) of which were from an engineering background and only 271 were related to medicine. No papers were found in the Cochrane database. Search on TRIP database revealed 195 papers. A similar search revealed 237 papers on orthopedic applications on Pubmed and 269 documents on SCOPUS, whereas a search on Web of Science revealed only 23 papers. Publication trends were then analyzed on data derived from SCOPUS database. Overall, most papers were published from China, followed by United States, United Kingdom, and India.

CONCLUSION

There has been an upsurge of interest in 3D printing in orthopedic surgery, as is evident by an increasing trend in research and publications in this area in the recent years. Presently, 3D printing is in a primitive stage in the field of orthopedic surgery as our knowledge is still insufficient, and costs and learning curve are somewhat high. However, looking at latest publication trends, we are enthusiastic that it holds the key to future in orthopaedics and trauma cases.

Additive manufacturing applications in orthopaedics: A review

The applications of Additive Manufacturing (AM) have increased extensively in the area of orthopaedics. The AM applications are for making anatomic models, surgical instruments & tool design, splints, implants and prosthesis. A brief review of various research articles shows that patient-specific orthopaedic procedures provide multiple applications areas and provide directions for future developments. The purpose of this paper is to identify the best possible usage of additive manufacturing applications in orthopaedics field. It also presents the steps used to prepare a 3D printed model by using this technology and details applications in the field of orthopaedics. AM gives a flexible solution in orthopaedics area, where customised implants can be formed as per the required shape and size and can help substitution with customised products. A 3D model created by this technology gain an accurate perception of patient's anatomy which is used to perform mock surgeries and is helpful for highly complex surgical pathologies. It makes surgeon's job accessible and increases the success rate of the operation. AM provides a perfect fit implant for the specific patient by unlimited geometric freedom. Various scanning technologies capture the status of bone defects, and printing of the model is done with the help of this technology. It gives an exact generation of a physical model which is also helpful for medical education, surgical planning and training. This technology can help to solve present-day challenges as data of every patient is different from another.

Computed tomography based 3D printed patient specific blocks for total knee replacement

OBJECTIVES

3D printing is an emerging technology and its use in orthopaedics is being explored. We discuss the role of computed tomography based 3D printed patient specific jigs in total knee replacement. We also discuss the various advantages of 3D printed patient specific jigs and the future scope of their use in total knee replacement.

METHODS

A search of English literature was done and articles discussing the role of CT scan based 3D printed patient specific jigs in total knee replacement were included in the study.

RESULTS

The role of 3D printed jigs in total knee replacement have been found in the prediction of femoral valgus angle, component sizing and in retained hardware. They have shown promise with studies suggesting they might improve the overall mechanical alignment of the knee. There are studies which have also studied the combined role of patient specific instruments with navigation.

CONCLUSION

3D printed jigs hold promise in total knee replacement. Their use in total knee replacement in the presence of retained hardware is useful for the surgeon. They have also showed promise in improving prediction of component sizing and improving mechanical alignment of the knee. Further studies with longer follow up and larger sample size will help in establishing their role in total knee replacement.