Long-leg Radiographs Research Articles

Impact of Aging and Knee Osteoarthritis on Lower Limb Alignment and CPAK Classification: Gender Differences in a Japanese Cohort.

Objective: This study investigates the impact of age and knee osteoarthritis (OA) on the coronal plane alignment of the lower extremity in Japanese males and females, utilizing the Coronal Plane Alignment of the Knee (CPAK) classification system. Methods: A cross-sectional analysis was conducted with 150 male and 150 female patients. Participants were divided into three groups according to age and OA progression. The mechanical lateral distal femoral angle (mLDFA) and mechanical medial proximal tibial angle (mMPTA) were measured using standard digital long-leg radiographs. Arithmetic hip-knee-ankle angle (aHKA) and joint line obliquity (JLO) were calculated, and the CPAK classification was performed to verify the distribution among the three groups. Results: The results showed increased varus alignment of the mean mLDFA correlated with OA in both genders and with aging in males. The mean mMPTA did not change in males but shifted toward varus in females with both aging and OA. Both genders demonstrated a constitutional varus alignment with the progression of osteoarthritis (males: 1.3 ± 2.4° to -3.5 ± 3.7°, p < 0.001; females: -1.2 ± 3.2° to -3.6 ± 2.9°, p < 0.001). However, this trend with aging was observed only in females (0.0 ± 2.5° to -1.2 ± 3.2°, p = 0.018). JLO maintained its apex distal position with aging and OA progression in all subjects. The study further revealed a notable transition from CPAK Type II to Type I with OA progression in both genders, additionally influenced by aging in females. Conclusions: Aging affects coronal alignment and CPAK classification differently across genders. With OA progression, there was a shift toward smaller aHKA, while JLO remained unchanged. Compared to other races, young Japanese people exhibit similar CPAK distributions, but distinct differences appear in OA-affected individuals, highlighting potential racial variations in CPAK classifications.

Joint line convergence angle should be considered when constitutional alignment is predicted based on arithmetic hip-knee-ankle angle: a retrospective cross-sectional observational study.

Few studies have illustrated the role of the joint line convergence angle (JLCA) in the correlation between the arithmetic hip-knee-ankle angle (aHKA) and mechanical hip-knee-ankle angle (mHKA). We aimed to determine this role and to evaluate the effect of the JLCA in predicting constitutional alignment using the aHKA. A total of 107 normal participants (214 knees) and 246 patients (477 knees) with osteoarthritis(OA) were retrospectively examined using long-leg radiographs. The formula was calculated geometrically on plain radiographs of the knee based on the relationships among the mHKA, aHKA, and JLCA, and the distribution of the JLCA between the groups was determined. The effect of the JLCA on the prediction of constitutional alignment using the aHKA were evaluated. The geometric formula was determined to be 'mHKA=180°+aHKA - JLCA', and was verified. The median (quartile 1, quartile 3) JLCA was 2.0° (1.0°, 3.5°) and 2.5° (1.0°, 4.5°) in the normal and OA groups, respectively. The JLCA affected the prediction of constitutional alignment based on the aHKA. It should be considered when constitutional alignment is predicted based on the aHKA in patients with high JLCA values.

Adjusted planning based on the joint line convergence angle improves correction accuracy in the standing position after opening wedge high tibial osteotomy

BackgroundPostoperative change of the joint line convergence angle (JLCA) is known to be a factor affecting correction error in opening wedge high tibial osteotomy (OWHTO). The purpose of this study was to assess whether preoperative planning that considers change of the JLCA can achieve accurate correction in the standing position after OWHTO.MethodsOWHTO was performed for 109 knees with osteoarthritis of the knee. The amount of angular correction was planned aiming to achieve mechanical valgus of 5° in 55 knees (conventional planning), and it was adjusted in 54 knees (adjusted planning) according to the preoperative JLCA as follows: not changed with JLCA ≤ 3°; decreased 1° with JLCA 4–6°; decreased 2° with JLCA 7–8°; and decreased 3° with JLCA ≥ 9°. The hip-knee-ankle (HKA) angle, JLCA, and medial proximal tibial angle (MPTA) were measured on standing long-leg radiographs. Correction error ≤ 2º was defined as the acceptable range, and correction error > 2º was defined as an outlier.ResultsThe conventional planning group had a significantly greater postoperative HKA angle than the adjusted planning group (6.1º and 4.9º, respectively). The mean JLCA decreased from 4.8º to 2.6º in the conventional planning group and from 4.6º to 2.7º in the adjusted planning group. The conventional planning group had significantly greater postoperative MPTA than the adjusted planning group (96.2º and 94.7º, respectively). The rate of outliers with correction error > 2º was significantly lower in the adjusted planning group (9%) than in the conventional planning group (24%). The rate of the MPTA > 95º was significantly lower in the adjusted planning group (30%) than in the conventional planning group (69%).ConclusionsThis study demonstrated that preoperative planning with adjustment of the correction angle according to the preoperative JLCA improved correction accuracy in the standing position after OWHTO.

Automated Measurements of Long Leg Radiographs in Pediatric Patients: A Pilot Study to Evaluate an Artificial Intelligence-Based Algorithm.

Assessment of long leg radiographs (LLRs) in pediatric orthopedic patients is an important but time-consuming routine task for clinicians. The goal of this study was to evaluate the performance of artificial intelligence (AI)-based leg angle measurement assistant software (LAMA) in measuring LLRs in pediatric patients, compared to traditional manual measurements. Eligible patients, aged 11 to 18 years old, referred for LLR between January and March 2022 were included. The study comprised 29 patients (58 legs, 377 measurements). The femur length, tibia length, full leg length (FLL), leg length discrepancy (LLD), hip-knee-ankle angle (HKA), mechanical lateral distal femoral angle (mLDFA), and mechanical medial proximal tibial angle (mMPTA) were measured automatically using LAMA and compared to manual measurements of a senior pediatric orthopedic surgeon and an advanced practitioner in radiography. Correct landmark placement with AI was achieved in 76% of the cases for LLD measurements, 88% for FLL and femur length, 91% for mLDFA, 97% for HKA, 98% for mMPTA, and 100% for tibia length. Intraclass correlation coefficients (ICCs) indicated moderate to excellent agreement between AI and manual measurements, ranging from 0.73 (95% confidence interval (CI): 0.54 to 0.84) to 1.00 (95%CI: 1.00 to 1.00). In cases of correct landmark placement, AI-based algorithm measurements on LLRs of pediatric patients showed high agreement with manual measurements.

The presence of an aberrant anterior tibial artery does not depend on the patient's morphotype.

The aberrant anterior tibial artery (ATA) runs along the posterior surface of the tibial cortex making it, particularly, at risk during high tibial osteotomy (HTO). This study aimed to analyze the prevalence of the ATA according to global morphotype and its anatomical features in consideration of knee surgery. This retrospective study included 1589 knees on magnetic resonance imaging (MRI) studies with long-leg radiographs. The anatomical characteristics of the ATA, its distance in surgical areas at risk and its lumen were defined on MRI. Its presence according to the patient's morphotype (varus, valgus or neutral) was assessed using a χ2 test. The ATA was present in 33 of 1589 knees, resulting in a prevalence of 2.1%. The anteroposterior distance of the ATA to the tibial head was 6.6 ± 2.5 mm at the height of the tibial plateau, 2.7 ± 1.6 mm at the footprint of the posterior cruciate ligament and 1.0 ± 0.6 mm under the top of the fibula (p < 0.01). For these three levels, the ratio between the distance from the ATA to the lateral tibial border and the total tibial width decreases progressively (p < 0.001). The mean lumen area of the ATA was 4.2 ± 2.5 mm2, and the lumen of the popliteal artery was 9.2 ± 3.6 mm2, representing a ratio of 49.4 ± 27.0%. The prevalence of ATA was similar between varus and valgus patients (n.s). The presence of an ATA is rare, found in one out of 50 cases, but can be easily identified on MRI in patients before knee surgery, especially before HTO. The patient's morphotype did not influence its presence, the lumen diameter is highly variable and its clinical impact has yet to be determined. Cross-sectional study. Level 3.

Artificial intelligence-based assessment of leg axis parameters shows excellent agreement with human raters: A systematic review and meta-analysis.

The aim of this study was to conduct a systematic review and meta-analysis on the reliability and applicability of artificial intelligence (AI)-based analysis of leg axis parameters. We hypothesized that AI-based leg axis measurements would be less time-consuming and as accurate as those performed by human raters. The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO). PubMed, Epistemonikos, and Web of Science were searched up to 24 February2024, using a BOOLEAN search strategy. Titles and abstracts of identified records were screened through a stepwise process. Data extraction and quality assessment of the included papers were followed by a frequentist meta-analysis employing a common effect/random effects model with inverse variance and the Sidik-Jonkman heterogeneity estimator. A total of 13 studies encompassing 3192 patients were included in this meta-analysis. All studies compared AI-based leg axis measurements on long-leg radiographs (LLR) with those performed by human raters. The parameters hip knee ankle angle (HKA), mechanical lateral distal femoral angle (mLDFA), mechanical medial proximal tibial angle (mMPTA), and joint-line convergence angle (JLCA) showed excellent agreement between AI and human raters. The AI system was approximately 3 min faster in reading standing long-leg anteroposterior radiographs (LLRs) compared with human raters. AI-based assessment of leg axis parameters is an efficient, accurate, and time-saving procedure. The quality of AI-based assessment of the investigated parameters does not appear to be affected by the presence of implants or pathological conditions. Level I.

Effects of three-dimensional femur and tibia postures on the parameters of standing long-leg radiographs for osteoarthritic knees in elderly female subjects

BackgroundLong-leg frontal radiographs of the lower extremities are used to assess knee osteoarthritis. Given the three-dimensional (3D) nature of alignment changes in osteoarthritis, postural alterations in the femur and tibia extend beyond the coronal plane (in-plane) to include the transverse and sagittal planes (out-of-plane). This study investigates the impact of these out-of-plane factors on in-plane knee alignment parameters observed in frontal radiographs. MethodsA total of 97 osteoarthritic knees in women were examined. Using a 3D-to-two-dimensional (2D) image matching technique, we evaluated the 3D postures of the femur and tibia in the standing position as viewed from frontal radiographs in the world coordinate system. Statistical analyses were conducted to explore associations between these 3D postures and 2D alignment parameters obtained from frontal radiographs under identical conditions. FindingsThe femur exhibited a medial inclination of 2.7°, a posterior inclination of 3.9°, and an internal rotation of 4.2°, whereas the tibia showed a lateral inclination of 6.4°, an anterior inclination of 6.7°, and an internal rotation of 6.7°. Both coronal and rotational postures of femur and tibia influenced the hip-knee-ankle angle, mechanical axis percentage, and medial proximal tibial angle. However, only coronal factors of tibia impacted tibial joint line obliquity relative to the floor. InterpretationAttention should be paid to the potential impact of the out-of-plane postures of the femur and tibia on parameters assessed in plain frontal radiographs of the lower extremities.

High in-vivo accuracy of a novel robotic-arm-assisted system for total knee arthroplasty.

Robotic-assisted total knee arthroplasty (TKA) has been shown to improve the accuracy and precision of bony resections and implant position. However, the in vivo accuracy of the full surgical workflow has not been widely reported. The primary objective of this study is to determine the accuracy and precision of a robotic-arm-assisted system throughout the intraoperative workflow. This was a retrospective cohort study of adult patients who underwent primary TKA with various workflows and alignment targets by three arthroplasty-trained surgeons with previous experience using the ROSA® Knee System (Zimmer Biomet) over a 3-month follow-up period. Accuracy and precision were determined by measuring the difference between various workflow time points, including the final preoperative plan (PP), robot-validated (RV) resection angleand postoperative radiographs (PR). The absolute mean difference between the measurements determined accuracy, and the standard deviation represented precision. The lateral distal femoral angle, medial proximal tibial angle, femoral flexion angle and tibial slope were measured on postoperative coronal long-leg radiographs and true short-leg lateral radiographs. A total of 77 patients were included in the final analyses. The accuracy for the coronal femoral angle was 1.62 ± 1.11°, 0.75 ± 0.79°and 1.96 ± 1.29° for the differences between PP and PR, PP and RVand RV and PR. The tibial coronal accuracy was 1.44 ± 1.03°, 0.81 ± 0.67°and 1.57 ± 1.14° for PP/PR, PP/RVand RV/PR, respectively. Femoral flexion accuracy was 1.39 ± 1.05°, 0.83 ± 0.59°and 1.81 ± 1.21° for PP/PR, PP/RVand RV/PR, respectively. Tibial slope accuracy was 0.99 ± 0.72°, 1.19 ± 0.87°and 1.63 ± 1.11°, respectively. The proportion of patients within 3° was 93.2%, 95.3%, 97.3%and 94.6% for the distal femur, proximal tibia, femoral flexionand tibial slope angles when the final intraoperative plan was compared to PRs. No patients had a postoperative complication at the final follow-up. The ROSA Knee System has acceptable accuracy and precision of coronal and sagittal plane resections with few outliers at various steps throughout the platform's entire workflow in vivo. Level III.

Strong Correlation Between Standing Long-Leg Radiographs and CT Scans in Measuring Coronal Knee Alignment.

The objective of this study was to evaluate the correlation in measurements of the lower-limb coronal alignment between long-leg radiographs (LLRs) and computed tomography (CT) scanograms that were made during preoperative planning for robotic-arm-assisted knee arthroplasty. On the basis of published evidence demonstrating a good correlation between these imaging modalities in measuring the lower-limb mechanical axis, we hypothesized that there would be no significant differences between the 2 in the present study. This multicenter cohort study across 3 tertiary centers included 300 patients undergoing primary robotic-arm-assisted total knee arthroplasty (TKA) or unicompartmental knee arthroplasty (UKA) for whom LLRs and CT scanograms were available preoperatively. The study involved measuring the medial proximal tibial angle (MPTA), lateral distal femoral angle (LDFA), hip-knee-ankle angle (HKA), joint line obliquity (JLO), joint-line convergence angle (JLCA), and arithmetic HKA (aHKA). The aHKA represents a method for estimating constitutional alignment using angles that are unaffected by joint-space narrowing. Strong correlations (p < 0.001) between the imaging modalities were found for the HKA (correlation coefficient, 0.912), aHKA (0.883), MPTA (0.820), LDFA (0.871), and JLO (0.778). A weaker correlation was observed for the JLCA in valgus knees as compared with varus knees (Spearman coefficients, 0.412 and 0.518, respectively). Regression models demonstrated that the degree of agreement was associated with the preoperative intra-articular deformity and the positioning of the lower limb during the CT scan (i.e., the lower-limb rotational angle). An initial JLCA within ±5° was associated with higher agreement. We observed a strong correlation between LLRs and CT scanograms that were made during the preoperative planning stage of robotic-arm-assisted knee arthroplasty, implying that CT scanograms can reliably be utilized to estimate the coronal alignment of the knee, potentially replacing the need for LLRs. Nevertheless, to attain a higher degree of agreement, it is crucial to ensure appropriate radiographic positioning of the lower limb. Additionally, surgeons must remain vigilant regarding potential discrepancies in cases involving substantial deformities. Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.

How reliable is the soft tissue radiological knee index in predicting superficial surgical site infection following total knee arthroplasty?

The purpose of this study was to evaluate the association between the Soft Tissue Radiological Knee (SToRK) Index and the risk of developing a superficial surgical site infection (SSSI) following primary total knee arthroplasty (TKA). The SToRK Index was measured using calibrated long leg radiographs (LLR) in 174 patients undergoing TKA. A moderate correlation was found between the SToRK Index and body mass index (BMI) (rs=0.574; p < 0.001). The SToRK Index was a better predictor of SSSI in females than males. In females, a SToRK Index cutoff of 2.01 had a sensitivity and specificity of 41.3% and 74.6% for developing SSSI, respectively, with a positive likelihood ratio of 1.63. The SToRK Index can be used as an additional tool in assessing the risk for SSSI after TKA. It might be more predictive in females due to the different fat distribution compared to males.

Automatic measurement of lower limb alignment in portable devices based on deep learning for knee osteoarthritis

BackgroundFor knee osteoarthritis patients, analyzing alignment of lower limbs is essential for therapy, which is currently measured from standing long-leg radiographs of anteroposterior X-ray (LLR) manually. To address the time wasting, poor reproducibility and inconvenience of use caused by existing methods, we present an automated measurement model in portable devices for assessing knee alignment from LLRs.MethodWe created a model and trained it with 837 conforming LLRs, and tested it using 204 LLRs without duplicates in a portable device. Both manual and model measurements were conducted independently, then we recorded knee alignment parameters such as Hip knee ankle angle (HKA), Joint line convergence angle (JCLA), Anatomical mechanical angle (AMA), mechanical Lateral distal femoral angle (mLDFA), mechanical Medial proximal tibial angle (mMPTA), and the time required. We evaluated the model’s performance compared with manual results in various metrics.ResultIn both the validation and test sets, the average mean radial errors were 2.778 and 2.447 (P<0.05). The test results for native knee joints showed that 92.22%, 79.38%, 87.94%, 79.82%, and 80.16% of the joints reached angle deviation<1° for HKA, JCLA, AMA, mLDFA, and mMPTA. Additionally, for joints with prostheses, 90.14%, 93.66%, 86.62%, 83.80%, and 85.92% of the joints reached that. The Chi-square test did not reveal any significant differences between the manual and model measurements in subgroups (P>0.05). Furthermore, the Bland-Altman 95% limits of agreement were less than ± 2° for HKA, JCLA, AMA, and mLDFA, and slightly more than ± 2 degrees for mMPTA.ConclusionThe automatic measurement tool can assess the alignment of lower limbs in portable devices for knee osteoarthritis patients. The results are reliable, reproducible, and time-saving.

Developing a Computer Vision Model to Automate Quantitative Measurement of Hip-Knee-Ankle Angle in Total Hip and Knee Arthroplasty Patients

BackgroundIncreasing deformity of the lower extremities, as measured by the hip-knee-ankle angle (HKAA), is associated with poor patient outcomes after total hip and knee arthroplasty (THA, TKA). Automated calculation of HKAA is imperative to reduce the burden on orthopaedic surgeons. We proposed a detection-based deep learning (DL) model to calculate HKAA in THA and TKA patients and assessed the agreement between DL-derived HKAAs and manual measurement. MethodsWe retrospectively identified 1,379 long-leg radiographs (LLRs) from patients scheduled for THA or TKA within an academic medical center. There were 1,221 LLRs used to develop the model (randomly split into 70% training, 20% validation, and 10% held-out test sets); 158 LLRs were considered “difficult,” as the femoral head was difficult to distinguish from surrounding tissue. There were 2 raters who annotated the HKAA of both lower extremities, and inter-rater reliability was calculated to compare the DL-derived HKAAs with manual measurement within the test set. ResultsThe DL model achieved a mean average precision of 0.985 on the test set. The average HKAA of the operative leg was 173.05 ± 4.54°; the nonoperative leg was 175.55 ± 3.56°. The inter-rater reliability between manual and DL-derived HKAA measurements on the operative leg and nonoperative leg indicated excellent reliability (intraclass correlation (2,k) = 0.987 [0.96, 0.99], intraclass correlation (2, k) = 0.987 [0.98, 0.99, respectively]). The standard error of measurement for the DL-derived HKAA for the operative and nonoperative legs was 0.515° and 0.403°, respectively. ConclusionsA detection-based DL algorithm can calculate the HKAA in LLRs and is comparable to that calculated by manual measurement. The algorithm can detect the bilateral femoral head, knee, and ankle joints with high precision, even in patients where the femoral head is difficult to visualize.

The influence of the weight-bearing state on three-dimensional (3D) planning in lower extremity realignment – analysis of novel vs. state-of-the-art planning approaches

BackgroundThe use of 3D planning to guide corrective osteotomies of the lower extremity is increasing in clinical practice. The use of computer-tomography (CT) data acquired in supine position neglects the weight-bearing (WB) state and the gold standard in 3D planning involves the manual adaption of the surgical plan after considering the WB state in long-leg radiographs (LLR). However, this process is subjective and dependent on the surgeons experience. A more standardized and automated method could reduce variability and decrease costs.PurposeThe aim of the study was (1) to compare three different three-dimensional (3D) planning modalities for medial open-wedge high tibial osteotomy (MOWHTO) and (2) to describe the current practice of adapting NWB CT data after considering the WB state in LLR. The purpose of this study is to validate a new, standardized approach to include the WB state into the 3D planning and to compare this method against the current gold standard of 3D planning. Our hypothesis is that the correction is comparable to the gold standard, but shows less variability due compared to the more subjective hybrid approach.MethodsThree surgical planning modalities were retrospectively analyzed in 43 legs scheduled for MOWHTO between 2015 and 2019. The planning modalities included: (1) 3D hybrid (3D non-weight-bearing (NWB) CT models after manual adaption of the opening angle considering the WB state in LLR, (2) 3D NWB (3D NWB CT models) and (3) 3D WB (2D/3D registration of 3D NWB CT models onto LLR to simulate the WB state). The pre- and postoperative hip-knee-ankle angle (HKA) and the planned opening angle (°) were assessed and differences among modalities reported. The relationship between the reported differences and BMI, preoperative HKA (LLR), medial meniscus extrusion, Outerbridge osteoarthritis grade and joint line convergence angle (JLCA) was analyzed.ResultsThe mean (std) planned opening angle of 3D hybrid did not differ between 3D hybrid and 3D WB (0.4 ± 2.1°) (n.s.) but was higher in 3D hybrid compared to 3D NWB (1.1° ± 1.1°) (p = 0.039). 3D WB demonstrated increased preoperative varus deformity compared to 3D NWB: 6.7 ± 3.8° vs. 5.6 ± 2.7° (p = 0.029). Patients with an increased varus deformity in 3D WB compared to 3D NWB (> 2 °) demonstrated more extensive varus alignment in LLR (p = 0.009) and a higher JLCA (p = 0.013).ConclusionSmall intermodal differences between the current practice of the reported 3D hybrid planning modality and a 3D WB approach using a 2D/3D registration algorithm were reported. In contrast, neglecting the WB state underestimates preoperative varus deformity and results in a smaller planned opening angle. This leads to potential under correction in MOWHTO, especially in patients with extensive varus deformities or JLCA.Clinical RelevanceIncorporating the WB state in 3D planning modalities has the potential to increase accuracy and lead to a more consistent and reliable planning in MOWHTO. The inclusion of the WB state in automatized surgical planning algorithms has the potential to reduce costs and time in the future.

Multicentric development and validation of a multi-scale and multi-task deep learning model for comprehensive lower extremity alignment analysis

Osteoarthritis of the knee, a widespread cause of knee disability, is commonly treated in orthopedics due to its rising prevalence. Lower extremity misalignment, pivotal in knee injury etiology and management, necessitates comprehensive mechanical alignment evaluation via frequently-requested weight-bearing long leg radiographs (LLR). Despite LLR’s routine use, current analysis techniques are error-prone and time-consuming. To address this, we conducted a multicentric study to develop and validate a deep learning (DL) model for fully automated leg alignment assessment on anterior–posterior LLR, targeting enhanced reliability and efficiency. The DL model, developed using 594 patients’ LLR and a 60%/10%/30% data split for training, validation, and testing, executed alignment analyses via a multi-step process, employing a detection network and nine specialized networks. It was designed to assess all vital anatomical and mechanical parameters for standard clinical leg deformity analysis and preoperative planning. Accuracy, reliability, and assessment duration were compared with three specialized orthopedic surgeons across two distinct institutional datasets (136 and 143 radiographs). The algorithm exhibited equivalent performance to the surgeons in terms of alignment accuracy (DL: 0.21 ± 0.18°to 1.06 ± 1.3°vs. OS: 0.21 ± 0.16°to 1.72 ± 1.96°), interrater reliability (ICC DL: 0.90 ± 0.05 to 1.0 ± 0.0 vs. ICC OS: 0.90 ± 0.03 to 1.0 ± 0.0), and clinically acceptable accuracy (DL: 53.9%–100% vs OS 30.8%–100%). Further, automated analysis significantly reduced analysis time compared to manual annotation (DL: 22 ± 0.6 s vs. OS; 101.7 ± 7 s, p ≤ 0.01). By demonstrating that our algorithm not only matches the precision of expert surgeons but also significantly outpaces them in both speed and consistency of measurements, our research underscores a pivotal advancement in harnessing AI to enhance clinical efficiency and decision-making in orthopaedics.

What Is the Correlation between Coronal Plane Alignment Measured on Pre- and Postoperative Weight-bearing Radiographs and Intraoperative Navigation When Stress Is Applied to the Knee?

This study examines the correlation between the weight-bearing (WB) long leg radiograph (LLR)-derived hip-knee-ankle angle (HKAA) and intraoperative supine computer-assisted surgery (CAS)-derived HKAA measurements at the beginning and end of total knee arthroplasty (TKA). The primary aim of the study was to determine if WB alignment could be mimicked or inferred based on intraoperative alignment findings. We conducted a prospective analysis from a cohort of 129 TKAs undergoing a CAS TKA at a single center by a single surgeon. The HKAA was recorded using the CAS navigation system immediately postregistration of navigation data and after implantation of the prosthesis. The intraoperative HKAA was recorded in both the supine "resting" position of the knee and also while the knee was manipulated in an effort to replicate the patient's WB alignment. These measurements were compared with the HKAA recorded on pre- and postoperative WB LLRs. There was a strong correlation between the preoperative WB LLR HKAA and the intraoperative preimplant CAS-derived stressed HKAA (R = 0.946). However, there was no correlation between the postoperative WB LLR HKAA and the postimplant insertion HKAA as measured intraoperatively via CAS for either a "resting" or "stressed" position of the operated knee (R = 0.165 and R = 0.041, respectively). Thus, the interpretation of intraoperative alignment data is potentially problematic. Despite technological advances in the development and utilization of computer navigation and robotics in arthroplasty to help obtain the optimal alignment, it would seem apparent from our study that this alignment does not correlate to upright stance postoperatively. Surgeons should apply caution to the strength of assumptions they place on intraoperative coronal plane alignment findings.

Imageless robotic total knee arthroplasty determines similar coronal plane alignment of the knee (CPAK) parameters to long leg radiographs

BackgroundThe coronal plane alignment of the knee (CPAK) classification was first developed using long leg radiographs (LLR) and has since been reported using image-based and imageless robotic total knee arthroplasty (TKA) systems. However, the correspondence between imageless robotics and LLR-derived CPAK parameters has yet to be investigated. This study therefore examined the differences in CPAK parameters determined with LLR and imageless robotic navigation using either generic or optimized cartilage wear assumptions.MethodsMedial proximal tibial angle (MPTA) and lateral distal femoral angle (LDFA) were determined from the intraoperative registration data of 61 imageless robotic TKAs using either a generic 2 mm literature-based wear assumption (Navlit) or an optimized wear assumption (Navopt) found using an error minimization algorithm. MPTA and LDFA were also measured from preoperative LLR by two observers and intraclass correlation coefficients (ICCs) were calculated. MPTA, LDFA, joint line obliquity (JLO), and arithmetic hip-knee-ankle angle (aHKA) were compared between the robotic and the average LLR measurements over the two observers.ResultsICCs between observers for LLR were over 0.95 for MPTA, LDFA, JLO, and aHKA, indicating excellent agreement. Mean CPAK differences were not significant between LLR and Navlit (all differences within 0.6°, P > 0.1) or Navopt (all within 0.1°, P > 0.83). Mean absolute errors (MAE) between LLR and Navlit were: LDFA = 1.4°, MPTA = 2.0°, JLO = 2.1°, and aHKA = 2.7°. Compared to LLR, the generic wear classified 88% and the optimized wear classified 94% of knees within one CPAK group. Bland–Altman comparisons reported good agreement for LLR vs. Navlit and Navopt, with > 95% and > 91.8% of measurements within the limits of agreement across all CPAK parameters, respectively.ConclusionsImageless robotic navigation data can be used to calculate CPAK parameters for arthritic knees undergoing TKA with good agreement to LLR. Generic wear assumptions determined MPTA and LDFA with MAE within 2° and optimizing wear assumptions showed negligible improvement.

Tibiofemoral Subluxation on Radiograph as a Predictor of Location and Size of Osteochondritis Dissecans Lesions of the Knee.

Lower limb malalignment has been associated with osteochondritis dissecans (OCD). However, the location of the OCD lesion often is not concordant with the mechanical leg axis. Other potentially modifiable alignment parameters may influence the propensity for impingement of the femoral condyles. To assess differences in lower limb alignment (LLA) and relative tibiofemoral position between patients with medial (MFC-OCD) or lateral OCD (LFC-OCD) of the femoral condyle. Cohort study; Level of evidence, 3. Patients ≤30 years old who were diagnosed with unicondylar OCD between January 2010 and January 2020 were eligible for this study. Included were 55 patients (age, 20.8 ± 4.5 years)-46 with MFC-OCD and 9 with LFC-OCD. Preoperative standing long-leg radiographs were studied to obtain primary outcomes-including LLA and mechanical alignment analyses-and secondary outcomes-including knee joint obliquity angle; rotation angle; medial, central (c-subluxation), and lateral subluxation (L-subluxation) of the tibia relative to the femur in the coronal plane; and tibiofemoral joint line center distance (TFJCD). With regard to primary outcomes, LLA was significantly different between MFC-OCD (1.7°± 3.1° varus) and LFC-OCD (2.7 ± 3.1° valgus) (P < .001), and 78% (36/46) of patients with MFC-OCD had varus alignment, whereas 78% (7/9) of patients with LFC-OCD had valgus alignment (P < 0.002). With regard to secondary outcomes, patients with MFC-OCD had a more medial tibial position in relation to the femur, with a significantly smaller rotation angle (5.6°± 2.4° vs 9.6°± 3.6°; P < .001), a smaller C-subluxation (7.2 ± 6.6 vs 14.9 ± 8.8 mm; P < .01), a smaller L-subluxation (2.3 ± 2.6 vs 4.4 ± 2.7 mm; P < .05), and reduced TFJCD (3.5 ± 1.7 vs 6.6 ± 1.8 mm; P < .001) compared with the LFC-OCD group. For patients with MFC-OCD, the size of the OCD was significantly correlated with C-subluxation (r = 0.412; P = .006). LLA was significantly different according to OCD location. In patients with MFC-OCD, the tibia was subluxated medially, resulting in a change of joint geometry by approximation of the medial tibial eminence toward the medial femoral condyle, potentially causing excessive pressure overload and microtrauma of the cartilage. Interestingly, the extent of subluxation was correlated with OCD size.

Validation of a Three-Dimensional Weight-Bearing Measurement Protocol for Medial Open-Wedge High Tibial Osteotomy.

Three-dimensional (3D) deformity assessment and leg realignment planning is emerging. The aim of this study was to (1) validate a novel 3D planning modality that incorporates the weight-bearing (WB) state (3D WB) by comparing it to existing modalities (3D non-weight-bearing (NWB), 2D WB) and (2) evaluate the influence of the modality (2D vs. 3D) and the WB condition on the measurements. Three different planning and deformity measurement protocols were analyzed in 19 legs that underwent medial open-wedge high tibial osteotomy (HTO): (1) a 3D WB protocol, after 2D/3D registration of 3D CT models onto the long-leg radiograph (LLR) (3D WB), (2) a 3D NWB protocol based on the 3D surface models obtained in the supine position (3D NWB), and (3) a 2D WB protocol based on the LLR (2D WB). The hip-knee-ankle angle (HKA), joint line convergence angle (JLCA), and the achieved surgical correction were measured for each modality and patient. All the measurement protocols demonstrated excellent intermodal agreement for the achieved surgical correction, with an ICC of 0.90 (95% CI: 0.76-0.96)) (p < 0.001). Surgical correction had a higher mean absolute difference compared to the 3D opening angle (OA) when measured with the WB protocols (3D WB: 2.7 ± 1.8°, 3D NWB: 1.9 ± 1.3°, 2D WB: 2.2 ± 1.3°), but it did not show statistical significance. The novel planning modality (3D WB) demonstrated excellent agreement when measuring the surgical correction after HTO compared to existing modalities.

Distances and angles in standing long-leg radiographs: comparing conventional radiography, digital radiography, and EOS

ObjectiveDistances and angles measured from long-leg radiographs (LLR) are important for surgical decision-making. However, projectional radiography suffers from distortion, potentially generating differences between measurement and true anatomical dimension. These phenomena are not uniform between conventional radiography (CR) digital radiography (DR) and fan-beam technology (EOS). We aimed to identify differences between these modalities in an experimental setup.Materials and methodsA hemiskeleton was stabilized using an external fixator in neutral, valgus and varus knee alignment. Ten images were acquired for each alignment and each modality: one CR setup, two different DR systems, and an EOS. A total of 1680 measurements were acquired and analyzed.ResultsWe observed great differences for dimensions and angles between the 4 modalities. Femoral head diameter measurements varied in the range of > 5 mm depending on the modality, with EOS being the closest to the true anatomical dimension. With functional leg length, a difference of 8.7% was observed between CR and EOS and with the EOS system being precise in the vertical dimension on physical-technical grounds, this demonstrates significant projectional magnification with CR-LLR. The horizontal distance between the medial malleoli varied by 20 mm between CR and DR, equating to 21% of the mean.ConclusionsProjectional distortion resulting in variations approaching 21% of the mean indicate, that our confidence on measurements from standing LLR may not be justified. It appears likely that among the tested equipment, EOS-generated images are closest to the true anatomical situation most of the time.

Distribution of coronal plane alignment of the knee classification in Chinese osteoarthritic and healthy population: a retrospective cross-sectional observational study.

Few studies have reported the coronal constitutional alignment of the lower limbs in mainland China. This study aimed to analyse the distribution of the coronal plane alignment of the knee (CPAK) classification in the osteoarthritic (OA) and healthy Chinese populations. The CPAK distributions of 246 patients (477 knees) with OA and 107 healthy individuals (214 knees) were retrospectively examined using long-leg radiographs. Radiological measurements and CPAK classification of different Kellgren-Lawrence grades in patients with unilateral total knee arthroplasty (TKA) were compared. The clinical outcomes of patients with CPAK type I who underwent mechanical alignment or restricted kinematic alignment during TKA were examined. The most common distributions in the OA and healthy groups were type I and type II, respectively. In patients who underwent unilateral TKA, the most common distribution of knees graded as Kellgren-Lawrence 3-4 was type I. However, the most common distributions of contralateral knees graded as Grade 0-2 were type I and II. For patients with CPAK type I, the mechanical alignment and restricted kinematic alignment groups did not differ significantly concerning postoperative clinical outcomes at 3 months. The most common distributions in Chinese osteoarthritic and healthy populations were types I and II, respectively. In addition, OA progression may lead to changes in the CPAK classification.