A Patient-Specific Predictive Model Increases Preoperative Templating Accuracy in Hip Arthroplasty

A Patient-Specific Predictive Model Increases Preoperative Templating Accuracy in Hip Arthroplasty

The Journal of Arthroplasty xxx (2014) xxx–xxx Contents lists available at ScienceDirect The Journal of Arthroplasty journal homepage: www.arthropla...

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The Journal of Arthroplasty xxx (2014) xxx–xxx

Contents lists available at ScienceDirect

The Journal of Arthroplasty journal homepage: www.arthroplastyjournal.org

A Patient-Specific Predictive Model Increases Preoperative Templating Accuracy in Hip Arthroplasty Amir Pourmoghaddam, PhD, Marius Dettmer, PhD, Adam M. Freedhand, MD, Brian C. Domingues, BSc, Stefan W. Kreuzer, MD, MSc Memorial Bone & Joint Research Foundation, Department of Orthopaedic Surgery, The University of Texas Health Science Center at Houston–Medical School, Houston, Texas

a r t i c l e

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Article history: Received 12 July 2014 Accepted 8 November 2014 Available online xxxx Keywords: hip arthroplasty preoperative templating Traumacad anterior approach digital imaging

a b s t r a c t Application of digital radiography during preoperative templating has shown potential to reduce complications in total hip arthroplasty. In this study, we aimed to further improve digital templating by using a predictive model built on patients' specific data. The model was significant in improving the accuracy of templating within ± 1 size of acetabular component (χ2(1, N = 468) = 19.314, P b 0.0001, Φ = 0.604, and odds-ratio: 7.750 (95% CI 2.740–30.220)). We successfully achieved a 99% accuracy within ±2 of templated size. Additionally, patient demographics, such as height and weight, have shown significant effects on the predictive model. The outcome of this study may help reducing the costs of health care in the long term by minimizing implant inventory costs. © 2014 Published by Elsevier Inc.

Preoperative planning in total hip arthroplasty is an essential part of the procedure [1,2] because it prepares the surgical team and significantly reduces the surgical time by minimizing potential complications [3]. The utilization of digital radiography in clinical settings has grown significantly in the past few years. This technique is being used more commonly as a financially sound alternative compared to analogue radiography, as it provides the opportunity to store an unlimited number of images while reducing the costs of film storage and the need for recycling [4]. In addition, advanced computer programs have been developed to analyze the obtained digital information [5]. Historically, templating accuracy, particularly when utilizing analog radiography, has been reported to be relatively low; recently, the literature shows that digital templating can be successful in identifying the implant size within ±2 implant sizes [3–13]. In this study, we aimed to further improve the accuracy of predicting the implant size in total hip arthroplasty by considering some anthropometric characteristics of the patient. In today's digital world, due to the costs associated with expanding implant options and inventory management, digital templating could be of great benefit for surgical preparation and for reducing inventory in the field, thereby decreasing the overall cost of THA. Proper surgical preparation, including digital templating, can reduce surgical time and potential complications, but digital templating is rarely utilized to manage inventory flow in the field. Accurate templating requires proper

The Conflict of Interest statement associated with this article can be found at http:// dx.doi.org/10.1016/j.arth.2014.11.021. Reprint requests: Stefan W. Kreuzer, MD, MSc, Memorial Bone & Joint Research Foundation, Department of Orthopaedic Surgery, The University of Texas, Health Science Center at Houston–Medical School, 1140 Business Center Drive, Suite 101, Houston, TX 77043.

patient positioning and standardized X-ray techniques to generate images of sufficient quality. A major concern with templating, particularly computer-assisted, image-processing software, is the issue of “inaccurate magnification ratio.” Generally with computer-assisted templating, an initial 20% magnification of the image is assumed. This ratio can be affected by patient-related factors, such as obesity and body habitus, or technical factors, such as the distance of the X-ray tube to the joint being X-rayed. Traditional preoperative planning utilizes a tube-to-film a distance of 48 inches for X-ray imaging, resulting in an estimated magnification of 20% compared to the actual size. However, the accuracy of such magnification has been questioned and can vary widely [4]. Traditional templates provided by implant manufacturers come in different magnifications and are overlaid on standard X-rays to provide the templated implant size. A similar concept is utilized in digital radiography, in which the digital radiographs are adjusted for magnification by utilizing a magnification marker or a constant magnification ratio and software is used to create digital overlays of implant sizes to select the appropriate size and orientation of the component. Table 1 summarizes some of the recent studies conducted in different institutions representing the relationship between the preoperative templating and the actual implant sizes used for the patients. Although many of the previous studies indicated high accuracy, other studies have raised concerns about relying on the outcome of templating. Efe et al reported that, in approximately 9% (15 out of 169) of their cases, the intraoperative implant size could not be predicted, even within 2 sizes [14]. These concerns have inspired our research to find other factors that might facilitate and improve the accuracy of preoperative templating. Thus, the main goal of this study was to improve accuracy of preoperative templating by using a predictive model that includes patient-specific demographics (i.e., height, weight, body mass

http://dx.doi.org/10.1016/j.arth.2014.11.021 0883-5403/© 2014 Published by Elsevier Inc.

Please cite this article as: Pourmoghaddam A, et al, A Patient-Specific Predictive Model Increases Preoperative Templating Accuracy in Hip Arthroplasty, J Arthroplasty (2014), http://dx.doi.org/10.1016/j.arth.2014.11.021

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A. Pourmoghaddam et al. / The Journal of Arthroplasty xxx (2014) xxx–xxx

Table 1 Examples of Previous Studies Investigating the Accuracy of Preoperative Templating of Femoral and Acetabular Components. Study

Whiddon et al (2011) – Digital Whiddon et al (2011) – Manual measurement Shaarani et al (2013) Maratt (2012) Maratt (2012) – Acetate

Exact Size (%)

±1 Size (%)

±2 Size (%)

Total

Femoral

Acetabular

Femoral

Acetabular

Femoral

Acetabular

51 51 100 20 20

61 33 38 NA NA

39 31 36 NA NA

90 82 80 75 93

78 67 75 73 63

96 100 98 93 98

96 88 98 96 86

index (BMI)). Thus, the purpose of this study was to develop a prediction model to enhance the accuracy of preoperative digital templating by considering a multitude of patient variables, such as height, age, sex, BMI, etc. We hypothesized that anthropometric variables impact the accuracy of the preoperative templating size of acetabular and femoral components. Methods A retrospective review of preoperative radiographs for 468 individuals (224 females/244 males) who received total hip arthroplasty was conducted. The preoperative templated sizes were compared to actual implant sizes used at the time of surgery. The data were collected from August 2012 to December 2013 at a single institution. The average age was 59.96 ± 12.50 years, 436 diagnosed with osteoarthritis, 53 with avascular necrosis, 13 with failed THA, 2 with infection, 4 post trauma, and 13 with failed hemi arthroplasty. All patients underwent direct anterior total hip arthroplasty. The level of the femoral osteotomy was performed based on preoperative templating. Acetabular reaming and cup impaction were performed in standard fashion. Supplemental screw fixation was utilized when needed. The final acetabular component size was selected based on the final reamer size and a quality press fit in the bleeding bone. An attempt was made to restore the native hip center of rotation in all cases. During the study period, two different implant manufacturers for the acetabular component (Stryker Orthopedics and Corin Inc.) were utilized. Acetabular reaming was performed according to the manufacturers' recommendation to achieve a solid interference fit. All preoperative radiographs were taken with a standardized X-ray source-to-image distance of 1 m when the patients were at the standing position. All radiographs were taken by a single team of radiology technicians. However, no magnification marker was used in these radiographs for the purpose of referencing. For THA templating in the anteroposterior view the pelvis image was centered over the pubic symphysis, while the hip was internally rotated between 10° and 15°. Fig. 1 depicts a sample of the templated joints that was used in predicting the implant size. The digital radiographs were all analyzed utilizing the TraumaCad software system (TraumaCad, BRAINLAB, Westchester, IL, USA) [15]. The initial implant model was adjusted and magnified by a factor of 120% to provide an acceptable overlay on the hip joint. All intraoperative data were collected prospectively using online, Web-based, data-entry software from an IRB-approved joint registry (IRB # HSC-GEN-09-0143), including the final implant sizes selected by the surgeon.

systematically removes the predictors that do not have significant contribution in defining the changes in the model. In addition, we used a multiple regression model that includes all the variables of interest in this study to explore their effects as well and provide a more standardized equation for future studies. Finally, to assess the improvement in the accuracy of the templating we used a nonparametric McNemar's test to compare the binomial accuracy outcome (i.e., yes vs. no) between the templating alone method versus utilizing the model. The effect size and odds ratio of the McNemar's test were calculated for the significant differences. In the cases in which the number of cells in the McNemar's test was less than 5 we used an exact McNemar's test. A significance level of .05 was assumed in this study. The analysis was conducted by using SPSS 21.0.0 (SPSS Inc., Chicago, Illinois, USA). Results Table 2 includes the demographics of the individuals who participated in this study. The Acetabular Component The backward stepwise model has demonstrated that, for the acetabular component size, four significant predictors were achieved, which were templated acetabulum size, height, BMI, and templated femoral size. This model had the R2 = .0.797 with adjusted R 2 = .795 with standard error of 1.726. Gender and weight were not significant factors in this model. The outcome of a full regression model is demonstrated in the acetabular model, in which gender and weight are also included in the prediction.

Statistical Model A multiple regression model was used to develop the predictive model and to investigate the contribution of each factor to the model to predict the actual size of the implant from the preoperative measurements. These variables included, preoperative acetabular size, preoperative femoral size, body mass index (BMI), age, gender, height, and weight. In each model, a backward stepwise algorithm was used to identify the variables, resulting in significant model demonstration. This algorithm initially enters all variables into the model but

Fig. 1. A sample of templated hip joints by using TraumaCad.

Please cite this article as: Pourmoghaddam A, et al, A Patient-Specific Predictive Model Increases Preoperative Templating Accuracy in Hip Arthroplasty, J Arthroplasty (2014), http://dx.doi.org/10.1016/j.arth.2014.11.021

A. Pourmoghaddam et al. / The Journal of Arthroplasty xxx (2014) xxx–xxx

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Table 2 Patients' Preoperative and Intraoperative Measurements.

Age (years) Height (cm) Weight (kg) BMI Templated acetabulum size (mm) Templated femoral size (mm) Actual acetabulum size (mm) Actual femoral size (mm)

Average

SD

61.01 172 84.83 28.5 54.63 4.73 55.61 4.82

12.50 10.67 20.13 5.26 4.07 1.81 3.77 1.77

Acetabular Component Model ActEstimated ¼ 4:532 þ 0:661  ActTemp þ 0:202  FemTemp þ 0:067  Height−0:024  Weight þ 0:138  BMI þ ε In which ActEstimated is the estimated size of acetabulum cup, ActTemp is the preoperative templated acetabulum size from digital radiography, FemTemp is the preoperative templated femoral size, and ε is the residual error term. Gender is defined as a binomial variable (female = 0 and male = 1). This model resulted in an estimated acetabular size of 54.96 ± 3.41 mm. This model was significant overall to predict the acetabular size (mean square = 1331.40, F(6,461) = 302.338, P b .0001).

Fig. 3. The distribution of the prediction error for both acetabulum cup size and femoral stem size.

For the acetabular component, two cases were predicted within ±3 size and two cases were predicted within ± 4 size. However, for the femoral component, the model predicted with less accuracy, and in 11 cases the implant size was correctly predicted in ± 3 size and in two cases within ±4 size as depicted in Fig. 3.

The Femoral Component Accuracy Improvements The backward stepwise model indicated that the femoral component size could only be significantly determined by the preoperative femoral component measurements. This model had an R 2 = .727 with adjusted R 2 = .727 and standard error of 0.935. Femoral component model was developed based on a fully factored model, including the preoperative measurements of the patients to develop a prediction model for estimating the femoral size.

The results of the McNemar's test and McNemar's exact test are summarized in Appendix 1. The outcomes suggest that using the model overall improved accuracy of the templating as summarized in Table 3. The improvement in accuracy was significant in the acetabular component within ±1 size (χ2(1, N = 468) = 19.314, P b 0.0001, Φ = 0.604, and odds ratio: 7.750 (95% CI 2.740–30.220)). The details of the test and cross-tab tables are presented in the Appendix 1.

Femoral Component Model Discussion FemEstimated ¼ 3:387 þ 0:016  ActTemp þ 0:814  FemTemp −0:018  Height þ 0:018  Weight−0:061  BMI þ ε In which FemEstimated is the estimated size of the femoral stem. This model resulted in an estimated femoral size of 4.82 ± 1.51 mm. This model was significant overall to predict the femoral size (mean square = 178.32, F(6,460) = 204.152, P b .0001) (Fig. 2.).

The use of digital radiography and preoperative templating is increasingly common and can improve the success of joint replacement surgery [3]. Pre-surgical planning is critical in the performance of joint replacement surgery and should be used to optimize patient outcomes. Pre-surgical planning can also be used to enhance OR efficiency and implement cost savings through inventory and supply chain

Fig. 2. The accuracy of the model to retrospectively predict the implant sizes in the current study. The femoral component size was predicted accurately in 97.2% of cases of within ±2 size and more than 99.1% for acetabular component size within ±2 size.

Please cite this article as: Pourmoghaddam A, et al, A Patient-Specific Predictive Model Increases Preoperative Templating Accuracy in Hip Arthroplasty, J Arthroplasty (2014), http://dx.doi.org/10.1016/j.arth.2014.11.021

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A. Pourmoghaddam et al. / The Journal of Arthroplasty xxx (2014) xxx–xxx

Table 3 The Accuracy of the Identifying the Proper Implant Component Size While Utilizing the Model Versus the Preoperative Templating Size. Acetabular Component Size Exact Method Model Preop size Change

±1 Size

±2 Size

N

%

N

%

N

%

229 225 4

48.93 48.08 0.85

437 410 27

93.38 87.60 5.77

464 462 2

99.13 98.70 0.43

46.15 44.65 1.07

415 414 1

88.74 88.52 0.22

462 460 2

98.7 98.48 0.44

Femoral Component Size Model 216 Preop size 209 Change 5 Total number of cases was 468.

management. Operating room efficiency depends on a coordinated team effort, the use of specialized equipment, and the shared knowledge of pertinent patient information. We routinely use preoperative templating to streamline our surgical efforts, minimize the use of unnecessary equipment, optimize patient outcomes, and minimize cost. In this study we used a multiple regression model to identify factors that would allow us to predict component size during hip replacement surgery to within ±1 size. For the acetabulum, the significant factors were the templated acetabular size, templated femoral size, weight, and height. For the femoral component, the preoperative femoral templating was the only significant factor. In our retrospective review of 468 patients, the exact acetabular implant size was identified by the model with an accuracy of 48.93%, which was slightly higher than results achieved by using only preoperative digital templating size to predict the exact acetabular cup size (i.e., 48.08%). Application of the model was further justified when the gap between the accuracy of identifying proper acetabular cup within ±1 size of the actual implant was improved significantly by utilizing the model. This statistically significant increase was a more than 5% improvement (27 cases in this study). The high effect size of the findings (indicated by Φ N 0.4) and the significance of the improvement suggest that utilizing the model will enhance the accuracy of preoperative templating. Table 3 depicts the improvement in accuracy of identifying the appropriate acetabular size while using the model. Similar outcome was found in predicating the actual femoral stem size, and the application of the model improved the accuracy of identifying the proper size (Table 3). Our results resemble the findings of Della Valle et al, who reported 99% prediction within one size for the acetabular component and 99% within two sizes for the femoral component [16]. Our results were similar to previous studies, including those conducted with TraumaCad [10]. Table 3 depicts the differences between the predicted model versus the

actual implant size (acetabular and femoral). The error is larger in the acetabular cup size. This may be due to the limited number of commercially available acetabular cup sizes. In our study we were limited by the total number of personnel who performed the preoperative templating; hence, we were not able to evaluate the interrater reliability factor and measure potential errors that may be added to the model if different evaluators are used such as those reported by Maratt et al [8]. However, our assumption in the current study was that the employment of digital radiography and application of standard templating techniques could minimize this potential error. Future studies may focus on retrospectively estimating preoperative implant sizes by using different trained technicians. Another limitation is in the difficulty in templating patients with severe bone loss or proximal femoral or acetabular deformity. We analyzed the patients whose predicted model was more than ±2 sizes different from the actual implant size used at the time of surgery and found that, in each case, there was severe distortion of the hip anatomy that made templating difficult and subsequently inaccurate. An example of such case is depicted in Fig. 4. These cases typically required preoperative CT scan to assess the anatomy, assess bone stock for implant fixation, and identify specific component needs (i.e., augments, cages, revision stems, and the need for bone grafting). Thus, employing preoperative templating should be used with caution in more complex cases in which the hip anatomy is severely distorted. All cases were templated the week before the actual procedure. Single instrument trays were prepared, consisting of a basic set of surgical tools in addition to the specifically sized implants and size-matched tools. Only specifically required instruments were standard components of the tray. Additionally, there was a general backup set in case of significantly inaccurate templating results (size according to templating off by more than two sizes). However, there was a 99% success rate using the templating technique, which meant the backup was rarely required. In conclusion, this study presented a prediction model to better estimate the actual size of implants. We routinely use this information to create patient-specific trays to simplify patient care, improve OR efficiency, and optimize patient outcomes. This practice can also produce significant cost savings in the delivery of joint replacement care. Acknowledgments The authors would like to thank Mr. David Balderree for his assistance with preparing the collected data. We would also like to thank Mr. Brian Caballero and Ms. Lauren Hennecke for their assistance with pre-operative and post-operative data collection. Finally, we are grateful to Dr. Ashish Arya for assistance with editing this manuscript and providing insightful comments.

Fig. 4. Anterior-posterior view X-ray of an example case that was not templated within 2 implant sizes. The margins of the acetabulum and femoral head are not clearly shown in the X-ray due to severe deformity of the limb.

Please cite this article as: Pourmoghaddam A, et al, A Patient-Specific Predictive Model Increases Preoperative Templating Accuracy in Hip Arthroplasty, J Arthroplasty (2014), http://dx.doi.org/10.1016/j.arth.2014.11.021

A. Pourmoghaddam et al. / The Journal of Arthroplasty xxx (2014) xxx–xxx

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±1 Size

Appendix 1. Femoral Exact Size

Model Accurate

Model Accurate

Templated

Accuracy

No Yes

No

Yes

235 17

24 192

Templated

Accuracy

No Yes

No

Yes

27 4

31 406

(χ2(1, N = 468) = 19.314, P b 0.0001, Φ = 0.604, and odds-ratio: 7.750 (95% CI 2.740–30.220)) ±2 Acetabular Size

(χ2(1, N = 468) = 0.878, P = 0.3487) ±1 Femoral Size Model

Model

Accurate

Templated

Accuracy

No Yes

Accurate

No

Yes

48 5

6 409

Exact McNemar's test results indicated that the two-sided probability was P = .5 thus in ±1 size no significant improvement was provided by the model.  P ¼2

11 6



2

0

 0:5  0:5 ¼ 0:45

Templated

Accuracy

No Yes

No

Yes

2 2

4 460

Exact McNemar's test results indicated that the two-sided probability was P = .5 thus in ±2 size no significant improvement was provided by the model. P ¼2

  6 2 0  0:5  0:5 ¼ 0:47 4

±2 Femoral Size References Model Accurate

Templated

Accuracy

No Yes

No

Yes

6 0

2 460

Exact McNemar's test results indicated that the two-sided probability was P = .5 thus in ±2 size no significant improvement was provided by the model. P ¼2

  2 2 0  0:5  0:5 ¼ 0:5 2

Acetabular Exact Size Model Accurate

Templated

Accuracy

No Yes

(χ2(1, N = 468) = 0.105, P = 7463)

No

Yes

198 41

45 184

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Please cite this article as: Pourmoghaddam A, et al, A Patient-Specific Predictive Model Increases Preoperative Templating Accuracy in Hip Arthroplasty, J Arthroplasty (2014), http://dx.doi.org/10.1016/j.arth.2014.11.021