Automated Measurement of Patient-Specific Tibial Slopes from MRI

Automated Posterior Tibial Slope Measurement Using Lateral Knee Radiographs: A Novel Landmark-Based Approach Using Deep Learning

Background

A single universally accepted protocol does not exist for measuring the posterior tibial slope (PTS), limiting the application of cutoff values for surgical decision-making and risk stratification.

Purpose/Hypothesis

This purpose of this study was to validate an online computer vision model using anatomic landmarks for PTS measurement on uncalibrated lateral knee radiographs. It was hypothesized that this model would achieve similar accuracy to manual measurement.

Study Design

Cohort study; Level of evidence, 2.

Methods

A total of 10,007 lateral knee radiographs collected between January 2009 and December 2019 were utilized. The data set comprised 9277 (93%) training, 500 (5%) validation, and 230 (2%) test radiographs. After defining "A" as the distance from the tibial joint line to the proximal aspect of the tibial tuberosity, 2 landmark-based methods for determining the tibial shaft axis were developed based on lines connecting the tibia midpoints at distances: (1) 2A and 3A (short method) and (2) 2A and 4A (long method). The PTS was then calculated using each tibial shaft axis. Model performance was evaluated against orthopaedic specialists' measurements using inter- and intraobserver intraclass correlation coefficients (ICCs). Model performance on shortened images, subcategorized into normal, osteoarthritic, and implant-embedded knees, was also assessed, along with time efficiency comparisons.

Results

The overall interobservers ICCs were 0.91 for the short method and 0.92 for the long method against manual measurement. The ICCs for normal, osteoarthritic, and implant-embedded radiographs were 0.84, 0.90, and 0.97 for the short method and 0.88, 0.91, and 0.97 for the long method, respectively. The intraobserver ICC for the computer vision model was a perfect 1.00, while manual measurements showed ICCs of 0.89 for the short method and 0.95 for the long method. The mean model measurement time was 2.5 ± 0.7 seconds, compared with 26.1 ± 1.9 seconds for the manual measurement (P < .001).

Conclusion

A novel, time-efficient, deep learning model for measuring PTS demonstrated excellent accuracy and consistency across various lateral knee radiographs. If externally validated, this model may enable a pathway for direct clinical translation of research findings by providing a standardized measurement tool.

Enhanced reliability and time efficiency of deep learning-based posterior tibial slope measurement over manual techniques

PURPOSE

Multifaceted factors contribute to inferior outcomes following anterior cruciate ligament (ACL) reconstruction surgery. A particular focus is placed on the posterior tibial slope (PTS). This study introduces the integration of machine learning and artificial intelligence (AI) for efficient measurements of tibial slopes on magnetic resonance imaging images as a promising solution. This advancement aims to enhance risk stratification, diagnostic insights, intervention prognosis and surgical planning for ACL injuries.

METHODS

Images and demographic information from 120 patients who underwent ACL reconstruction surgery were used for this study. An AI-driven model was developed to measure the posterior lateral tibial slope using the YOLOv8 algorithm. The accuracy of the lateral tibial slope, medial tibial slope and tibial longitudinal axis measurements was assessed, and the results reached high levels of reliability. This study employed machine learning and AI techniques to provide objective, consistent and efficient measurements of tibial slopes on MR images.

RESULTS

Three distinct models were developed to derive AI-based measurements. The study results revealed a substantial correlation between the measurements obtained from the AI models and those obtained by the orthopaedic surgeon across three parameters: lateral tibial slope, medial tibial slope and tibial longitudinal axis. Specifically, the Pearson correlation coefficients were 0.673, 0.850 and 0.839, respectively. The Spearman rank correlation coefficients were 0.736, 0.861 and 0.738, respectively. Additionally, the interclass correlation coefficients were 0.63, 0.84 and 0.84, respectively.

CONCLUSION

This study establishes that the deep learning-based method for measuring posterior tibial slopes strongly correlates with the evaluations of expert orthopaedic surgeons. The time efficiency and consistency of this technique suggest its utility in clinical practice, promising to enhance workflow, risk assessment and the customization of patient treatment plans.

LEVEL OF EVIDENCE

Level III, cross-sectional diagnostic study.

Correlation of medial tibial slope and lateral tibial slope measured on radiographs and magnetic resonance imaging in patients with anterior cruciate ligament injury

OBJECTIVES

The study aimed to investigate the correlation between medial tibial slope (MTS) and lateral tibial slope (LTS) on magnetic resonance imaging (MRI), MTS measured by different imaging, and the intra- and interobserver reliability of measurements between reviewers with gaps of experience over 10 years.

PATIENTS AND METHODS

This retrospective study included 97 patients (93 males, 4 females; mean age: 30.8±8.3 years; range, 17 to 49 years) with anterior cruciate ligament (ACL) injuries who subsequently underwent double-bundle ACL reconstruction by a single surgeon between January 2005 and December 2014. The MTS was measured on lateral knee radiographs, and MTS and LTS were measured on MRIs. Three different reviewers, including a postgraduate year doctor, an orthopedic resident, and an attending orthopedic surgeon, performed the measurements. Each reviewer measured the slope of the same image three times. The correlations of MTS on radiographs and MTS/LTS on MRIs were calculated. Intra- and interobserver reliability were evaluated.

RESULTS

The average MTS and LTS measured on MRI were not significantly different (6.4° and 6.9°, respectively; p=0.268) and exhibited a moderate positive correlation (r=0.544, p<0.001). The average MTS on radiographs was significantly greater than that on MRI (10.5° and 6.4°, respectively; p<0.001) with a low positive correlation (r=0.480, p<0.001). The intraobserver reliability of the postgraduate year doctor, the orthopedic resident, and the attending orthopedic surgeon were moderate to excellent. The interobserver reliability of MTS on radiographs was excellent (intraclass correlation coefficient [ICC]=0.925; p<0.001). The interobserver reliability of MTS on MRI as well as LTS on MRI was good (ICC=0.755 and 820, respectively; all p values <0.001).

CONCLUSION

Average MTS and LTS measured on MRI in patients with ACL injury exhibited a moderate positive correlation. The average MTS measured on radiographs was significantly greater than that on MRI with a low positive correlation.

Increased lateral femoral condyle ratio measured by MRI is associated with higher risk of solitary meniscus injury

Background: Past studies found that an increased lateral femoral condyle ratio is associated with anterior cruciate ligament injuries, but it is not clear if there is a link between MRI-measured lateral femoral condyle ratios and meniscal injuries. MRI provides a more accurate selection of measurement planes. Compared to X-rays, it further reduces data errors due to non-standard positions. Objective: To study the relationship between knee bone morphology and Solitary meniscal injuries by MRI. Methods: A total of 175 patients were included in this retrospective case-control study, including 54 cases of pure medial meniscus injury, 44 cases of pure lateral meniscus injury as the experimental group, and 77 control subjects. MRI images were used to measure the femoral notch width, femoral condylar width, femoral notch width index, lateral femoral condylar ratio (LFCR), posterior tibial slope, medial tibial plateau depth, and meniscus slope. In addition, carefully check for the presence of specific signs such as bone contusions and meniscal extrusions. Comparing the anatomical differences in multiple bone morphologies between the two groups, a stepwise forward multifactorial logistic analysis was used to identify the risk factors for Solitary meniscal injuries. Finally, ROC curves were used to determine the critical values and best predictors of risk factors. Results: MTS, LTS, and LFCR ended up as independent risk factors for meniscus injury. Among all risk factors, LFCR had the largest AUC of 0.781 (0.714-0.848) with a threshold of 72.75%. When combined with MTS (>3.63°), diagnostic performance improved with an AUC of 0.833 (0.774-0.892). Conclusion: Steep medial tibial plateau slope, steep lateral tibial plateau slope angle, and deep posterior lateral femoral condyles on MRI are independent risk factors for meniscal injuries. In patients with knee discomfort with the above imaging findings (X-ray, MRI), we should suspect and carefully evaluate the occurrence of meniscal injuries. It not only provides a theoretical basis to understand the mechanism of meniscus injury but also provides theoretical guidance for the prevention of meniscus injury and the development of intervention measures. Level of evidence III.

Deep Learning Artificial Intelligence Tool for Automated Radiographic Determination of Posterior Tibial Slope in Patients With ACL Injury

Background

An increased posterior tibial slope (PTS) corresponds with an increased risk of graft failure after anterior cruciate ligament (ACL) reconstruction (ACLR). Validated methods of manual PTS measurements are subject to potential interobserver variability and can be inefficient on large datasets.

Purpose/Hypothesis

To develop a deep learning artificial intelligence technique for automated PTS measurement from standard lateral knee radiographs. It was hypothesized that this deep learning tool would be able to measure the PTS on a high volume of radiographs expeditiously and that these measurements would be similar to previously validated manual measurements.

Study Design

Cohort study (diagnosis); Level of evidence, 2.

Methods

A deep learning U-Net model was developed on a cohort of 300 postoperative short-leg lateral radiographs from patients who underwent ACLR to segment the tibial shaft, tibial joint surface, and tibial tuberosity. The model was trained via a random split after an 80 to 20 train-validation scheme. Masks for training images were manually segmented, and the model was trained for 400 epochs. An image processing pipeline was then deployed to annotate and measure the PTS using the predicted segmentation masks. Finally, the performance of this combined pipeline was compared with human measurements performed by 2 study personnel using a previously validated manual technique for measuring the PTS on short-leg lateral radiographs on an independent test set consisting of both pre- and postoperative images.

Results

The U-Net semantic segmentation model achieved a mean Dice similarity coefficient of 0.885 on the validation cohort. The mean difference between the human-made and computer-vision measurements was 1.92° (σ = 2.81° [P = .24]). Extreme disagreements between the human and machine measurements, as defined by ≥5° differences, occurred <5% of the time. The model was incorporated into a web-based digital application front-end for demonstration purposes, which can measure a single uploaded image in Portable Network Graphics format in a mean time of 5 seconds.

Conclusion

We developed an efficient and reliable deep learning computer vision algorithm to automate the PTS measurement on short-leg lateral knee radiographs. This tool, which demonstrated good agreement with human annotations, represents an effective clinical adjunct for measuring the PTS as part of the preoperative assessment of patients with ACL injuries.

Anatomical factors associated with the development of anterior tibial spine fractures based on MRI measurements

BACKGROUND

Numerous studies have investigated anatomic factors for anterior cruciate ligament (ACL) injuries, such as posterior tibial slope (PTS) and notch width index (NWI). However, anterior tibial spine fracture (ATSF) as a specific pattern of ACL injury, a bony avulsion of the ACL from its insertion on the intercondylar spine of the tibia, has rarely been explored for its anatomical risk factors. Identifying anatomic parameters of the knee associated with ATSF is important for understanding injury mechanisms and prevention.

METHODS

Patients who underwent surgery for ATSF between January 2010 and December 2021 were retrospectively reviewed, and 38 patients were included in the study group. Thirty-eight patients who suffered from isolated meniscal tear without other pathologic findings were matched in a 1:1 fashion by age, sex and BMI to the study group. The lateral posterior tibial slope (LPTS), medial posterior tibial slope (MPTS), medial tibial depth, lateral tibial height, lateral femoral condyle ratio (LFCR) and NWI were measured and compared between the ATSF and control groups. Binary logistic regressions identified independent predictors of ATSF. Receiver operator characteristic (ROC) curves were performed to compare the diagnostic performance and determine the cutoff values of associated parameters.

RESULTS

The LPTS, LFCR and MPTS were significantly larger in the knees in the ATSF group than in the control group (P = 0.001, P = 0.012 and P = 0.005, respectively). The NWI was significantly smaller in the knees in the ATSF group than in the control group (P = 0.005). According to the results of logistic regression analysis, the LPTS, LFCR and NWI were independently associated with ATSF. The LPTS was the strongest predictor variable, and the ROC analysis revealed 63.2% sensitivity and 76.3% specificity (area under the curve, 0.731; 95% CI 0.619-0.844) for values above 6.9.

CONCLUSION

The LPTS, LFCR and NWI were found to be associated with the ATSF; in particular, LPTS could provide the most accurate predictive performance. The findings of this study may aid clinicians in identifying people at risk for ATSF and taking individualized preventive measures. However, further investigation regarding the pattern and biomechanical mechanisms of this injury is required.

Tibial slope in the posterolateral quadrant with and without ACL injury

INTRODUCTION

An increased tibial slope is a risk factor for rupture of the anterior cruciate ligament. In addition, a tibial bone bruise or posterior lateral impression associated with slope changes also poses chronic ligamentous instability of the knee joint associated with an anterior cruciate ligament (ACL) injury. In the majority of cases, the slope is measured in one plane X-ray in the lateral view. However, this does not sufficient represent the complex anatomy of the tibial plateau and especially for the posterolateral quadrant. Normal values from a "healthy" population are necessary to understand if stability of the knee joint is negatively affected by an increasing slope in the posterolateral area. Until now there are no data about the physiological slope in the posterolateral quadrant of the tibial plateau.

MATERIALS AND METHODS

In 116 MRI scans of patients without ligamentous lesions and 116 MRI scans with an ACL rupture, tibial slope was retrospectively determined using the method described by Hudek et al. Measurements were made in the postero-latero-lateral (PLL) and postero-latero-central (PLC) segments using the 10-segment classification. In both segments, the osseous as well as the cartilaginous slope was measured. Measurements were performed by two independent surgeons.

RESULTS

In the group without ligamentous injury the mean bony PLL slope was 5.8° ± 4.8° and the cartilaginous PLL slope was 6.7° ± 4.8°. In the PLC segment the mean bony slope was 6.6° ± 5.0° and the cartilaginous slope was 9.4° ± 5.7°. In the cohort with ACL rupture, the bony and cartilaginous slope in both PLL and PCL were significantly higher (P < 0.001) than in the group without ACL injury (bony PLL 9.8° ± 4.8°, cartilage PLL 10.4° ± 4.7°, bony PLC 10.3° ± 4.8°, cartilage PLL 12.8° ± 4.3°). Measurements were performed independently by two experienced surgeons. There were good inter- (CI 87-98.7%) and good intraobserver (CI 85.8-99.6%) reliability.

CONCLUSION

The bony and the cartilaginous slope in the posterolateral quadrant of the tibial plateau are different but not independent. Patients with an anterior cruciate ligament injury have a significantly steeper slope in the posterolateral quadrant compared to a healthy group. Our data indicate that this anatomic feature might be a risk factor for a primary ACL injury which has not been described yet.

LEVEL OF EVIDENCE

III.

Morphological Analysis of the Tibial Slope in 720 Adult Knee Joints

Background: The tibial slope (TS) defines the posterior inclination of the tibial plateau (TP). The “individual physiological” TS plays a crucial role in knee-joint stability and should be taken into account in knee-joint surgery. The aim of this study was to analyse the specific morphology of the TS for the medial (med) and lateral (lat) TP in relation to patient characteristics and the measurement method. Methods: In this retrospective study, MRI images of knee joints from 720 patients (mean age: 49.9 years [±17.14]) were analysed. The TS was assessed using two established methods according to Hudek (TSH) and Karimi (TSK) for the med and lat TP and gender/side specificity was analysed. Results: TSH for the med and lat TP showed significantly (p < 0.001) different values compared to TSK (TSKmed: 2.6° (±3.7), TSHmed: 4.8° (±3.5); TSKlat: 3.0° (±4.0), TSHlat: 5.2° (±3.9)). The angles of the lat TP were significantly higher than those of the med TP (TSK: p < 0.001; TSH: p = 0.002). Females showed a higher med and lat TS compared to males (p < 0.001). Conclusions: The measurement method has an influence on the values of the TS in knee-joint MRIs. The TS is significantly different for the med and lat TP regardless of the measurement method. There are gender-specific differences for the TS.

Increased lateral femoral condyle ratio measured by MRI is associated with higher risk of noncontact anterior cruciate ligament injury

BACKGROUND

Studies have shown a significant association between the radiographically measured lateral femoral condyle ratio (LFCR) and anterior cruciate ligament (ACL) injury. However, it is unclear whether LFCR measured by magnetic resonance imaging (MRI) is associated with a higher risk of noncontact ACL injury.

OBJECTIVE

To investigate the effect of LFCR on the risk of noncontact ACL injury by MRI. 2 to investigate the association of LFCR measured by MRI with multiple bone morphological risk factors and evaluate the most sensitive risk predictors of noncontact ACL injury.

METHODS

A total of 116 patients, including 58 subjects with noncontact ACL injury and 58 age-matched and sex-matched controls with only meniscus injury, were included in this retrospective case-control study. LFCR, lateral tibial slope (LTS), lateral tibial height (LTH), medial tibial slope (MTS), and medial tibial depth (MTD) were measured on MRI. The differences in each index between the two groups were compared, and risk factors were screened by single-factor logistic regression analysis. Indicators with P values < 0.1 were included in the logistic regression equation. The critical values and areas under the curve (AUCs) of independent risk factors were determined by receiver operating characteristic (ROC) curve analysis. Finally, the diagnostic performance of each risk factor was evaluated by the Z-test.

RESULTS

A total of 116 patients who met the inclusion criteria were included in the final analysis (58 cases in the noncontact ACL injury group and 58 cases in the control group). Patients with noncontact ACL injury had a higher femoral LFCR (0.64 ± 0.03) than patients with isolated meniscus tears. Among all the risk factors for ACL injury, the AUC for LFCR was the largest, at 0.81 (95% CI, 0.73-0.88), and when the critical value was 0.61, the sensitivity and specificity for the diagnosis of ACL injury were 0.79 and 0.67, respectively. When combined with LTH (> 2.35 mm), the diagnostic performance was improved. The AUC was 0.85 (95% CI, 0.78-0.92), the sensitivity was 0.83, and the specificity was 0.76.

CONCLUSION

This study shows that an increased LFCR is related to an increased risk of noncontact ACL injury as determined by MRI. LFCR and LTH are sensitive risk factors for noncontact ACL injury and may help clinicians identify individuals prone to ACL injury, allowing prevention and intervention measures to be applied.

Automated Motion Analysis of Bony Joint Structures from Dynamic Computer Tomography Images: A Multi-Atlas Approach

Dynamic computer tomography (CT) is an emerging modality to analyze in-vivo joint kinematics at the bone level, but it requires manual bone segmentation and, in some instances, landmark identification. The objective of this study is to present an automated workflow for the assessment of three-dimensional in vivo joint kinematics from dynamic musculoskeletal CT images. The proposed method relies on a multi-atlas, multi-label segmentation and landmark propagation framework to extract bony structures and detect anatomical landmarks on the CT dataset. The segmented structures serve as regions of interest for the subsequent motion estimation across the dynamic sequence. The landmarks are propagated across the dynamic sequence for the construction of bone embedded reference frames from which kinematic parameters are estimated. We applied our workflow on dynamic CT images obtained from 15 healthy subjects on two different joints: thumb base (n = 5) and knee (n = 10). The proposed method resulted in segmentation accuracies of 0.90 ± 0.01 for the thumb dataset and 0.94 ± 0.02 for the knee as measured by the Dice score coefficient. In terms of motion estimation, mean differences in cardan angles between the automated algorithm and manual segmentation, and landmark identification performed by an expert were below 1°. Intraclass correlation (ICC) between cardan angles from the algorithm and results from expert manual landmarks ranged from 0.72 to 0.99 for all joints across all axes. The proposed automated method resulted in reproducible and reliable measurements, enabling the assessment of joint kinematics using 4DCT in clinical routine.

Reliability of Plain Radiographs Versus Magnetic Resonance Imaging to Measure Tibial Slope in Sports Medicine Patients: Can They Be Used Interchangeably?

Background:

The slope of the tibial plateau has been proposed as a reason for failure of anterior cruciate ligament reconstruction.

Purpose:

To evaluate the interobserver reliability of measurements of tibial slope on radiographs versus magnetic resonance imaging (MRI) scans and to assess whether the modalities can be used interchangeably for this purpose.

Study Design:

Cohort study (diagnosis); Level of evidence, 3.

Methods:

This retrospective study included 81 patients aged 18 to 30 years who were evaluated in a sports medicine setting for knee pain and who had lateral knee radiographs as well as knee MRI scans on file. Medial and lateral tibial plateau slope measurements were made by 3 blinded reviewers from the radiographs and MRI scans using graphic overlay software. The paired t test was used to compare measurements of the medial tibial plateau slope (MTPS) and lateral tibial plateau slope (LTPS) from radiographs and MRI scans. Intraclass correlation coefficients (ICCs) were calculated to determine intra- and interobserver reliability of measurements within each imaging modality, and Pearson correlation coefficients were calculated to determine the relationship between measurements on radiographs versus MRI scans.

Results:

Imaging from 81 patients were included. The average MTPS was significantly larger on radiographs compared with MRI scans (8.7° ± 3.6° vs 3.7° ± 3.4°; P < .001), and the average LTPS was also significantly larger on radiographs compared with MRI scans (7.9° ± 3.4° vs 5.7° ± 3.7°; P < .001). ICC values indicated good to excellent intraobserver agreement for all imaging modalities (ICC, 0.81-0.97; P ≤ .009). The ICCs for interobserver reliability of MTPS and LTPS measurements were 0.92 and 0.85 for radiographs, 0.87 and 0.83 for MRI based off the subchondral bone, and 0.86 and 0.71 for MRI based off the cartilage, respectively (P < .001). Medium correlation was noted between radiographic and MRI measurements; Pearson correlation coefficients for radiographic versus subchondral MRI measurements were 0.30 and 0.37 for MTPS and LTPS, respectively.

Conclusion:

The average MTPS and LTPS were significantly larger on radiographs compared with MRI scans. Although tibial slope measurements using radiography and those using MRI are reliable between individuals, the measurements from radiographs and MRI scans cannot be used interchangeably, and caution should be used when interpreting and comparing studies using measurements of the tibial slope.

Is Proximal Tibia Sufficient for Accurate Measurement of Tibial Slope Angles on Three-dimensional Tomography-based Anatomical Models?

BACKGROUND

Tibial slope measurements performed using only the proximal part of tibia ignore the native tibial anatomical axis. Our first aim is to measure the native medial, lateral and total tibial slope angles of gender groups using the whole tibial anatomical axis on computerized tomography-based three-dimensional anatomical models. The second aim is to determine the correlation between proximal and whole tibial anatomical axis for measurement of medial, lateral, and total tibial slope angles.

METHODS

We randomly selected 100 females and 100 males between 18-60 years of age. Three-dimensional anatomical models of right and left tibia were created. The gender-specific differences of medial, lateral, and total tibial slope angles according to proximal and whole tibial anatomical axis were measured. Correlation coefficients (r) of medial, lateral, and total tibial slope angles measured with proximal and whole tibial anatomical axis were calculated.

RESULTS

The mean age was 47.1 years. A statistically significant difference was observed between female (7.1 ± 3) and male (8.2 ± 2.5) groups in terms of mean lateral tibial slope angles according to the whole tibial anatomical axis (p=0.008). A strong correlation between proximal and whole tibial anatomical axis for all tibial slope angle measurements was detected.

CONCLUSION

The method we determined for 3D measurement of medial, lateral and total tibial slope angles using proximal tibial anatomical axis has a strong correlation with slope angles measured in accordance with the whole tibial anatomical axis. Our 3D tibial slope angle measurement method on the proximal tibia has high reliability and could be used in the daily practice.

The EOS 3D imaging system reliably measures posterior tibial slope

Background

One of the values determined during the assessment of knee issues is the posterior tibial slope (PTS). A new option for measuring the PTS is the EOS 3D imaging system, which provides anteroposterior (AP) and lateral long leg radiographs (LLRs) using less radiation than a conventional LLR. We investigated the reliability of the EOS 3D imaging system with respect to PTS measurements.

Methods

We retrospectively searched our radiological database for patients who underwent an EOS scan and a computed tomography (CT) scan of their lower extremities between January and December 2019. Fifty-six knees were included in the study. Medial and lateral PTSs were determined using both modalities. A radiologist and an orthopaedic surgeon each performed all measurements twice and the intraclass correlation (ICC) was calculated to assess inter- and intrarater reliability. The Student t test and Pearson correlation were used to compare the results of both imaging modalities.

Results

The mean medial PTS was 8.5° (95% confidence interval [CI], 8.1–8.9°) for the EOS system and 7.7° (95% CI, 7.3–8.1°) for CT, and the lateral PTS was 7.4° (95% CI, 6.9–7.9°) for the EOS system, and 7.0° (95% CI, 6.5–7.4°) for CT. Interrater reliability (ICC) with respect to medial and lateral PTSs measured on the EOS (0.880, 0.765) and CT (0.884, 0.887) images was excellent. The intrarater reliability of reader 1 (ICC range, 0.889–0.986) and reader 2 (ICC range, 0.868–0.980) with respect to the same measurements was excellent.

Conclusion

The PTS measurements from the EOS 3D imaging system are as reliable and reproducible as those from CT, the current gold standard method. We recommend using this system if possible, because it acquires more information (sagittal plane) in a scan than a conventional LLR, while exposing the patient to less radiation.

Level of evidence

Level III, Retrospective cohort study

A real 3D measurement technique for the tibial slope: differentiation between different articular surfaces and comparison to radiographic slope measurement

Background

The tibial slope plays an important role in knee surgery. However, standard radiographic measurement techniques have a low reproducibility and do not allow differentiation between medial and lateral articular surfaces. Despite availability of three-dimensional imaging, so far, no real 3D measurement technique was introduced and compared to radiographic measurement, which were the purposes of this study.

Methods

Computed tomography scans of 54 knees in 51 patients (41 males and 10 females) with a mean age of 46 years (range 22–67 years) were included. A novel 3D measurement technique was applied by two readers to measure the tibial slope of medial and lateral tibial plateau and rim. A statistical analysis was conducted to determine the intraclass correlation coefficient (ICC) for the new technique and compare it to a standard radiographic measurement.

Results

The mean 3D tibial slope for the medial plateau and rim was 7.4° and 7.6°, for the lateral plateau and rim 7.5° and 8.1°, respectively. The mean radiographic slope was 6.0°. Statistical analysis showed an ICC between both readers of 0.909, 0.987, 0.918, 0.893, for the 3D measurement of medial plateau, medial rim, lateral plateau and lateral rim, respectively, whereas the radiographic technique showed an ICC of 0.733.

Conclusions

The proposed novel measurement technique shows a high intraclass agreement and offers an applicable opportunity to assess the tibial slope three-dimensionally. Furthermore, the medial and lateral articular surfaces can be measured separately and one can differentiate the slope from the plateau and from the rim. As three-dimensional planning becomes successively more important, our measurement technique might deliver a useful supplement to the standard radiographic assessment in slope related knee surgery.

Level of evidence

Level III, diagnostic study.

Atlas-based algorithm for automatic anatomical measurements in the knee

We present an algorithm for automatic anatomical measurements in tomographic datasets of the knee. The algorithm uses a set of atlases, each consisting of a knee image, surface segmentations of the bones, and locations of landmarks required by the anatomical metrics. A multistage volume-to-volume and surface-to-volume registration is performed to transfer the landmarks from the atlases to the target volume. Manual segmentation of the target volume is not required in this approach. Metrics were computed from the transferred landmarks of a best-matching atlas member (different for each bone), identified based on a mutual information criterion. Leave-one-out validation of the algorithm was performed on 24 scans of the knee obtained using extremity cone-beam computed tomography. Intraclass correlation (ICC) between the algorithm and the expert who generated atlas landmarks was above 0.95 for all metrics. This compares favorably to inter-reader ICC, which varied from 0.19 to 0.95, depending on the metric. Absolute agreement with the expert was also good, with median errors below 0.25 deg for measurements of tibial slope and static alignment, and below 0.2 mm for tibial tuberosity-trochlear groove distance and medial tibial depth. The automatic approach is anticipated to improve measurement workflow and mitigate the effects of operator experience and training on reliability of the metrics.