New robotic total knee arthroplasty (TKA) technology enables force-controlled pre-resection joint gap assessment. Its accuracy across surgeons and patient factors remains unknown. This study evaluated how accurately this technology achieved planned joint gaps and whether accuracy was influenced by surgeon, preoperative deformity, sex, BMI, and age. Six hundred seventy-two consecutive robotic TKAs from five surgeons were retrospectively reviewed. A robotic ligament tensioner applied 70–100 N medially and laterally before bony resections. Mean (ME) and mean absolute (MAE) predicted gap errors (final minus planned) were calculated at 10°, 45°, and 90° flexion. Linear regression evaluated associations between error and preoperative alignment and sex. A sub-analysis included BMI and age. Wilcoxon rank-sum tests compared errors between surgeons and deformity groups. Overall, MAE was 1.1 mm medially and 1.3 mm laterally. The largest ME occurred laterally in flexion in varus knees (-0.7 mm; tighter than plan), and laterally in extension in valgus knees (0.6 mm; looser than plan). Extension errors were similar in flexion-contracture and sagittal-neutral knees (ME within ± 0.1 mm), while hyper-extended knees were 0.5 mm looser than planned. Increasing BMI was associated with lateral flexion gap tightening (-0.59 mm per 10 kg/m2 increase, p = 0.018). ME was within 1.4 mm across all surgeons and flexion angles. Robotic TKA with force-controlled pre-resection gap assessment accurately achieved targeted joint gaps across a large patient cohort. While surgeon and patient factors influenced joint gap error, these effects were small. Awareness of these variations may help optimize implant planning.

BACKGROUND:Coronal plane alignment of the knee (CPAK) categorizes knee phenotypes according to joint line obliquity (JLO) and the arithmetic hip‒knee‒ankle angle (aHKA). CPAK is traditionally measured via long leg radiographs, but recently other modalities such as computed tomography (CT), image-based, and imageless navigation have been used. Machine learning (ML) is a field of artificial intelligence focused on enabling systems to learn from data and improve their performance without explicit programming. The aim of this study is to understand how accurately imageless navigation measures CPAK parameters relative to CT using generic cartilage wear assumptions and ML models. METHODS:152 TKAs performed via imageless navigation with preoperative CT data were retrospectively reviewed. MPTA and LDFA were measured from both the preoperative CT and the intraoperative imageless navigation landmark data and used to calculate JLO and aHKA. Three articular cartilage wear assumptions were applied to the imageless navigation data. The first applied no wear correction, whilst the second used traditional preoperative coronal HKA thresholds with a 2 mm cartilage thickness wear assumption on both the femoral and tibial side. A third model used retrospective thresholds aimed at optimally reducing error. Mean, SD, mean difference and Mean Absolute Error (MAE) were calculated. A fourth ML model, using random forest modeling with cross validation on an 80-20 test-train split, was used to determine MAE of navigated data from corresponding CT values. RESULTS:The average age was 73 ± 8 years, with 61% women, and an average preoperative coronal deformity of 3.5 ± 4.2° varus. The ML based wear assumptions had the lowest MAE for all CPAK parameters, with MAE ≤1.2° for MPTA and LDFA, and ≤1.8° for JLO and aHKA. This was better than MAE for aHKA for the no wear assumption model (2.5°) and generic wear model (2.6°). CONCLUSION:Imageless navigation can measure MPTA and LDFA with a mean error of <1.2° compared to CT when using ML models to predict cartilage wear. These results indicate that imageless navigation can be used to effectively measure CPAK parameters, achieving comparable results to a CT-based approach.

PURPOSE:Most implants currently used in total knee arthroplasty (TKA) were designed based on mechanical alignment (MA) principles. Modern alignment philosophies alter the orientation of these classic designs by following each individual's knee phenotype, which may have important implications on trochlear restoration. This study aims to compare the influence of different alignment strategies on trochlear anatomy recreation within predefined lateral distal femoral angle (LDFA) groups. METHODS:A total of 147 robotic-assisted, functionally aligned (FA) TKAs, performed with a digital ligament tensioner, were reviewed. Simulated femoral component positions were generated according to different alignment techniques; kinematic alignment (KA), restricted KA (rKA), restricted inverse KA (riKA), gap balancing (GB) and MA. Changes in trochlear angle (∆TA), mediolateral sulcus offset and trochlear over/understuffing were calculated relative to native. Alignment philosophies were compared across following LDFA groups: <84°(n = 22), 84°-87° (n = 57), 87°-90° (n = 50) and >90° (n = 18). Paired Wilcoxon-rank-sum tests were performed with Bonferroni corrections. RESULTS:In the lower LDFA groups more significant differences in ∆TA were identified between strategies with FA, KA and rKA showing lower values than riKA, GB and MA (p < 0.01). The LDFA < 84° group had the greatest range in mean ∆TA (2.8° ± 3.4 to 9° ± 3.2). At 10° flexion, MA and GB led to a significantly more lateral sulcus position in each LDFA group compared to the more native sulcus offset obtained with KA, rKA and FA (p < 0.05). All alignment strategies understuffed the trochlea in each LDFA group (3 mm ± 1.2 to 5.3 mm ± 1.5), with KA and rKA creating the least understuffing (p ≥ 0.05). CONCLUSION:KA, rKA and FA more closely recreate trochlear anatomy than riKA, MA and GB. The difference between strategies, especially in ∆TA, becomes more pronounced as the LDFA decreases. LEVEL OF EVIDENCE:Level IV.

Aims:There have been few studies that have investigated the effect of surgical approach on femoral component version in total hip arthroplasty (THA). The purpose of this study was to investigate the influence of the direct anterior approach (DAA) and the posterior approach (PA) on femoral component version in THA. Methods:A retrospective database review of 807 THAs in 807 patients who had both preoperative and postoperative CT scans was performed. Femoral component version was measured in the second CT scan and compared to the native neck axis measured in the first CT scan, using the posterior femoral condyles as the reference for both. Operations were performed using either a DAA (n = 291) or a PA (n = 516), with one of four femoral component designs: quadrangular taper, calcar-guided short stem, flat taper, or fit-and-fill. Subgroup analyses investigated changes in version for low (≤ 5°), neutral (5° to 25°), and high (≥ 25°) native version subgroups and for the different femoral component types. Results:Overall, DAA components had more mean anteversion relative to the native neck axis versus PA components (6.0° (SD 9.8°) vs 1.3° (SD 10.1°); p < 0.001). Predictors of increased femoral component anteversion postoperatively on multivariable regression analyses were approach (DAA), decreased native version preoperatively, decreased femoral sagittal bow angle, and component type (quadrangular taper). DAA components had greater mean anteversion relative to native than PA in hips with high native version (3.5° (SD 11.1°) vs -5.8° (SD 10.5°); p < 0.001) and neutral native version (5.2° (SD 9.3°) vs 1.3° (SD 9.4°); p < 0.001), but did not reach significance in the low native version subgroup (9.0° (SD 10.3°) vs 5.9° (SD 9.6°); p = 0.109). Quadrangular taper and calcar-guided short-component types had significantly more mean anteversion than native for DAA versus PA. Conclusion:Femoral components implanted with a DAA had more mean anteversion than those implanted with a PA. Future studies should aim to investigate the effect of femoral component version on postoperative clinical outcomes.

This study reports the relationship between posterior cruciate ligament (PCL) retention vs resection and soft tissue laxity and balance throughout flexion using a robotically controlled ligament tensioner. 55 robotic-assisted TKAs (Total knee arthroplasty) were retrospectively reviewe. The robotic ligament tensioner collected laxity data both before and after PCL resection. Medial and lateral coronal laxity were compared before and after PCL resection at 10°, 45°, and 90° flexion. Gap opening was compared between pre-operative coronal hip-knee-ankle groups. Lateral laxity was greater after PCL resection at 60° (12.7 ± 2 vs 11.5 ± 3 mm), 75° (13.2 ± 2 vs 11.8 ± 3 mm), and 90° (13.7 ± 2 vs 12.1 ± 3 mm). Medial laxity was significantly greater after PCL resection at 90° (10.1 ± 2 vs 9 ± 2 mm). After PCL resection, laxity in valgus knees increased more compared to neutral/varus knees laterally at 30° (1.2 ± 1 vs 0.3 ± 1 mm), 45° (1.6 ± 1 vs 0.6 ± 1 mm), and 60° (2.1 ± 2 vs 1 ± 1 mm). A similar, but non-significant trend was observed at 90° (2.7 ± 2 vs 1.5 ± 1 mm, p = 0.09). PCL resection increases flexion laxity laterally by up to 1.6 mm and medially by 1.1 mm on average, with valgus knees increasing more than neutral/varus knees. The findings emphasize that surgeons should consider the interplay between PCL resection and coronal deformity when planning and executing TKA procedures.

Background:This study quantified the relative impact of single-vs multi-radius femoral implant designs on coronal ligament laxity throughout flexion when gap planning at 10 and 90° flexion. These changes in laxity were also compared to those resulting from a change in the implant alignment technique. Methods:One hundred fifty-four consecutive robotic-assisted TKAs performed with a robotic ligament tensioning device, a cruciate-retaining single-radius (SR) femoral implant and an inverse kinematic alignment (iKA) technique were reviewed. Intraoperative data from each case was used to simulate implantation of a multi-radius (MR) implant of equivalent size, aligning both implants at 10 and 90° flexion to achieve a balanced knee. A mechanical alignment (MA) technique with SR implant was also simulated. Average mediolateral (ML) laxity and balance throughout flexion were compared for SR vs. MR and for iKA vs. MA. Results:At 0° (extension) the SR implant had 0.7 mm greater laxity than MR, while at 20° and 30° flexion SR had 0.4 mm less laxity medially and laterally. The difference in laxity between the two systems was ≤0.2 mm beyond 45° flexion. The difference in average ML laxity for MA vs iKA was greater than the difference in laxity due to SR vs MR throughout flexion (p < 0.001), with mean differences ranging from 1.3 to 1.7 mm between alignment techniques. Conclusion:When aligning SR and MR implants to achieve balance at 10° of flexion, SR will have more laxity at full extension (0°) and less laxity in early flexion and mid-flexion (20-40° flexion) compared to MR. The laxity difference in extension is almost 1 mm and may be clinically apparent. Surgeons should be aware of the difference in laxity profiles when using implants of different designs. These differences however are less than those encountered when changing alignment technique from MA to iKA.

BACKGROUND:Displacement of the native hip center of rotation (COR) following total hip arthroplasty (THA) alters biomechanical load distribution and may adversely affect outcomes. This analysis quantified alterations in the COR following THA and their relationship with postoperative axial femoral rotation. METHODS:There were 938 patients evaluated following staged bilateral THA. Each underwent a three-dimensional preoperative planning analysis. Automated registration between preoperative and postoperative computed tomography scans enabled the hip COR to be accurately compared preoperatively versus postoperatively. Changes in global anterior-posterior (AP) shift were defined by the combined difference between the anteriorization of the femoral COR and the posteriorization of the pelvic COR. Changes in global AP shift versus femoral internal rotation were assessed using linear regression. RESULTS:The mean acetabular COR was medialized by 4.6 mm and femoral COR by 5.1 mm relative to the native COR, resulting in a global medial-lateral offset increase of 0.5 mm. Similarly, the achieved acetabular and femoral CORs were shifted proximally by 0.4 and 2.8 mm, respectively, resulting in an average increase in hip length of 2.4 mm. Acetabular and femoral CORs were shifted anteriorly by -1.7 and -0.8 mm, respectively, resulting in a global AP shift decrease of 0.9 mm. Change in global AP shift was moderately correlated with change in femoral internal rotation (r = 0.5), with a regression slope indicating an average increase in femoral internal rotation of 0.6° per millimeter increase in global AP shift (P < 0.0001). Global AP shift increased by > 5 mm in 24% of cases, resulting in an average increase in femoral internal rotation of 10°. CONCLUSIONS:Acetabular COR is medialized by approximately five mm following THA with a compensatory increase in femoral offset, increasing muscle moment arms and increasing torque at the bone-stem interface. On average, global AP shift decreased by 1.0 mm, though there was significant patient-specific variability. When these changes exceed five mm, they can significantly alter axial rotational limb alignment.

Background:The aim of this study was to assess whether replication of native acetabular anatomy would satisfy cup orientation targets using 3 commonly described hip-spine algorithms. Whether spinopelvic characteristics influence ability to achieve cup orientation targets when replicating native anatomy and the agreement between algorithm recommendations was tested. Methods:A prospective database was queried to identify patients with adverse (n = 70) spinopelvic characteristics. These were matched for age and sex with patients without adverse characteristics (n = 70). Spinopelvic characteristics were obtained from radiographs and computed tomography (CT) scans. CT scans were segmented to determine native acetabular anatomy, particularly anteversion. Three hip-spine planning algorithms were evaluated for each patient (Optimized Positioning System [OPS], Combined-Sagittal Index [CSI], Hip-Spine Classification). Differences between target orientations and native anatomy were determined. Agreement between algorithms was tested. Results:OPS plan had significantly reduced inclination compared with native (39° vs. 52°, p < 0.001). No significant difference between OPS and native anteversions was seen (18° vs. 18°, p = 0.1) for the adverse group. OPS-planned anteversion was greater than native (23° vs. 16°, p < 0.001) in the nonadverse group. Most native orientations met published CSI targets (90% nonadverse, 59% adverse). Most native acetabular orientations (61% adverse and 58% nonadverse) failed to meet Hip-Spine Classification targets. Overall, in 88% of cases, replication of native acetabular version and 40° of inclination satisfied at least one suggested target. Agreement of all 3 algorithms was 31%; greater agreement was seen between Hip-Spine Classification and OPS (64%). Conclusions:Native acetabular anteversion and radiographic inclination of 40° are reliable targets, satisfying at least one hip-spine algorithm and thus justifying such practice, when advanced hip-spine analysis is not performed. The discrepancy between suggested orientations by the various published techniques, despite their validated low dislocation rates, emphasizes that although achieving a target cup orientation is important, the nature of hip stability is multifactorial and merits a holistic approach.

Radiographic measurement of patient-specific spinopelvic mobility is standard-of-care in total hip arthroplasty (THA). Current manual methods are time-consuming, subjective, and error-prone. This study utilized deep learning (DL) to classify functional positions and measure pelvic tilt (PT), sacral slope (SS) and lumbar lordotic angle (LLA). A DL pipeline integrating image classification, vertebra detection, and landmark detection was developed using data from an international joint registry, comprising 52,772 images for classification, 9,875 for object detection, and 25,249 for landmark detection. Performance was evaluated using area under the curve (AUC), F1 score, and mean absolute error (MAE). Accuracy was compared to annotations by three expert engineers and validated by two senior engineers and a surgeon. Radiographs were processed in 1.96 ± 0.04 s, achieving precision, recall, Receiver-operator-characteristic-AUC, and Precision-Recall-AUC metrics above 0.994. Anatomical landmark predictions resulted in errors of: PT: 1.6°±2.1°, SS: 3.3°±2.6°, LLA: 4.2°±3.2°. There was no significant difference in PT and LLA between expert engineers and the DL pipeline, and 0.5° difference in SS (p = 0.043). Clinical validation showed no difference in landmark rejection rates (p > 0.05). We developed and clinically validated a DL pipeline that accurately measures patient-specific spinopelvic mobility from lateral functional radiographs, providing a scalable method for routine characterization in THA patients.

PURPOSE:Robotic total knee arthroplasty (TKA) enables the acquisition of ligament balance data at various stages in the surgical workflow to inform implant planning. This study aims to compare pre-resection joint balancing versus inverse-kinematic workflows on implant positioning, joint line obliquity and coronal plane alignment of the knee (CPAK) phenotype. METHODS:A single-surgeon single-institution series of 422 primary posterior-cruciate sacrificing TKAs using a digital ligament tensioner was reviewed. The first 213 cases assessed gaps after tibial and before femoral resections (tibia-first group) in an inverse-kinematic alignment (iKA) workflow. The subsequent 174 cases assessed gaps before any bone resections (pre-resection group) in a femur-first kinematic alignment (KA) workflow. Native and postoperative medial proximal tibial angle (MPTA) and lateral distal femoral angle (LDFA) were compared using Wilcoxon rank-sum tests, and CPAK phenotype distributions were compared using chi-square tests. RESULTS:Mean preoperative MPTA and LDFA were within 0.5° between groups. Postoperative measurements differed between tibia-first and pre-resection for both MPTA (88.3° ± 1.5° vs. 86.7° ± 1.7°, p < 0.001) and LDFA (90.7° ± 2.1° vs. 89.4° ± 2.4°, p < 0.001). The tibia-first group had greater preoperative to postoperative change in MPTA (0.7° ± 1.3° vs. -0.5° ± 1.7°, p < 0.001), LDFA (2.5° ± 1.7° vs. 1.4° ± 1.5°, p < 0.001) and joint line obliquity (3.2° ± 2.5° vs. 0.9° ± 2.6°, p < 0.001). The pre-resection group had more patients whose CPAK phenotype did not change postoperatively (35% vs. 25%, p < 0.05), and fewer patients with CPAK changes > 1 (9% vs. 29%, p < 0.001). Final mediolateral balance was within 1 mm of neutral for both groups throughout flexion. CONCLUSIONS:While both techniques achieved a similar balance, a pre-resection ligament balancing workflow better restored native joint line obliquity and CPAK phenotype compared to an iKA workflow. LEVEL OF EVIDENCE:Level III.

BACKGROUND:This study examines the agreement and error between manual gap assessment, and assessment with a robotic soft-tissue tensioning device in total knee arthroplasty across multiple surgeons. METHODS:517 consecutive robotic-assisted TKAs were retrospectively reviewed across six surgeons following ethics approval. Robotic and manual mediolateral (ML) balance and medial and lateral gaps were compared using Intraclass Correlation Coefficient (ICC). ΔML balance (manual-robotic) was compared between right and left knees. RESULTS:Manual and robotic ML balance showed poor agreement (ICC = 0.368). Surgeons had low to moderate correlations (ICC range: 0.152-0.633) and significant differences throughout flexion. Four measured greater medial gaps manually and two measured greater lateral gaps compared to robotics. All showed significant ΔML balance differences between the leg sides (p < 0.05), with surgeon-specific variations in gap patterns. CONCLUSIONS:Manual ML balance correlated poorly and differed significantly from robotic assessment, with surgeon-specific variation. Surgeons should appreciate the variability in subjective versus objective gap measurements.

Introduction:The Coronal Plane Alignment of The Knee (CPAK) classification aims to restore the constitutional knee alignment, although it neglects the patellofemoral joint. Therefore, this study aims to examine the correlation between trochlear groove wear (TGW) patterns and CPAK classifications. Methods:Our institutional database was queried to include unilateral primary total knee arthroplasties (TKA) between 2021 and 2025. TGW was categorized into central, medial, lateral, and no TGW based on the most prominent wear observed intraoperatively. Using OMNIBotics® surgical navigation system (Corin Ltd.), nine CPAK phenotypes were determined by intraoperative registration of the arithmetic hip-knee-ankle angles (aHKA), joint line obliquity (JLO), lateral distal femoral angle (LDFA), and medial proximal tibial angle (MPTA). Results:Among 559 cases, central TGW (53.7 %), followed by lateral (21.8 %) and medial (15.2 %), were the most frequent TGW. Lateral TGW had a higher mean of MPTA (88.5 ± 2.3), while medial TGW had a significantly higher mean of LDFA (87.3 ± 2.2) than the other groups. Central TGW was the most prevalent wear in all aHKA groups, with the lateral TGW being more frequent (33 %) in the valgus knees than the medial TGW (8.4 %). Forty-two percent of cases with lateral TGW had CPAK type Ⅲ, followed by CPAK type Ⅱ (30 %) and CPAK type Ⅵ (13.0 %). The most frequently observed CPAK phenotypes with the central TGW were type Ⅱ (40 %), type Ⅲ (25 %), and typeⅠ (17 %). The same trend was detected for medial TGW and those without wear. Conclusion:The interplay between joint health and structural alignment can impact surgical planning, as we observed a significant association between the TGW and CPAK parameters. Surgeons may adjust femoral component rotation in CPAK Ⅲ with lateral TGW to address patellar maltracking, though further research is needed.

This study evaluated the accuracy of an automated 2D–3D registration software for matching preoperative 3D models of the pelvis and acetabular component to intraoperative 2D fluoroscopy images in total hip arthroplasty (THA). We developed a 2D–3D registration software that registers a 3D model of the pelvis from preoperative CT and a 3D model of the acetabular implant to intraoperative fluoroscopic imaging, thereby calculating the implant position relative to the 3D pelvic reference frame. A total of 145 datasets were used including 65 digitally reconstructed radiographs, 20 dry bone phantoms datasets and 60 clinical datasets with preoperative CT and intraoperative fluoroscopy imaging. Achieved acetabular positions from the clinical images were determined from post-operative CT using a 3D/3D registration method. Accuracy was assessed by comparing the calculated acetabular position from the 2D–3D software to the ground truth data. Mean absolute difference between ground truth and the 2D–3D software was 1.9° [signed error range: −4.4, 4.8] for inclination, 1.5° [−7.3, 4.1] for anteversion, 1.6 mm [−5, 3.8] for cup height and 1.8 mm [−7.3, 4.1] for depth across all datasets. In total, 100

Background The Coronal Plane Alignment of the Knee (CPAK) classification has been proposed to guide the alignment strategy in total knee arthroplasty (TKA). However, the classification does not take into account the variability of the soft-tissue envelope unique to each knee. The purpose of our study was to determine the variability and similarity of extension balance across each CPAK phenotype. Methods Using the anatomic and ligament data acquired from 4,362 robotic TKAs, the distraction of the medial and lateral joint spaces was simulated and classified across CPAK phenotypes I to VI. The joint balance was calculated for both the arthritic and nonarthritic states, accounting for cartilage wear. The extension joint balance for each CPAK phenotype was compared to another to determine the degree of variability and overlap across the various CPAK classes. In addition, a sensitivity analysis was performed by widening the boundaries of CPAK II and V from the anatomic hip-knee-ankle axis up to five degrees. Results Although there were differences in extension balance across the various CPAK phenotypes in the arthritic knee, there was also major variability and overlap. When accounting for cartilage loss, the similarities further increased. The greatest extension balance overlap was observed between CPAK II and IV (74%), whereas CPAK I and VI were expectedly dissimilar (6%). Accounting for cartilage wear, the similarity between CPAK II and IV and I and VI increased to 84 and 40%, respectively. Increasing the anatomic hip-knee-ankle boundaries for CPAK II and V to ± 3 degrees saw the greatest increase in reduction of extension balance overlap between neutrally aligned and varus knees. Conclusions The knee is highly complex and variable. While the CPAK classification provides a description of commonly encountered knee morphologies undergoing TKA in a single plane, it does not account for soft-tissue characteristics. Refinement of this classification system is required to improve its predictive value both intraoperatively and postoperatively.

BACKGROUND: Passive smartphone-based apps are becoming more common for measuring patient progress after total hip arthroplasty (THA). Optimum activity levels during early THA recovery have not been well documented. OBJECTIVES: Correlations between step-count and patient reported outcome measures (PROMs) during early recovery were explored. This study also investigated how demographics impact step-count during early post-operative recovery. METHODS: Smartphone captured step-count data from 666 THA patients was retrospectively reviewed. Mean age was 64 +/- 11 years. 55% were female. Mean BMI was 29 +/- 8kg/m(2). Mean daily step-count was calculated for each patient over four time-windows: 60 days prior to surgery (preop), 42-49 days postop (6 weeks), 91-98 days postop (3 months), and 183-197 days postop (6 months). Spearman correlation coefficients and linear regression were used to assess the association between PROMs (HOOS-12, HOOS-Jr, and UCLA) and step-count. Patients were separated into three step-count levels: low (< 2500 steps/day), medium (2500-5500 steps/day), and high (> 5500 steps/day). Age > 65 years, BMI > 35 kg/m(2), and sex were used for demographic comparisons. Post hoc analyses were performed using Welch's unequal variances t-tests, or Wilcoxon rank-sum tests, both with Bonferroni corrections, where appropriate when comparing between groups. Chi-squared analyses were also used when comparing categorical variables. RESULTS: UCLA correlated with step-count at all time-windows (p < 0.001). HOOS12-Function correlated with step-count preoperatively, at 6 weeks, and at 3 months (p <0.001). High step-count individuals had improved UCLA scores compared to low step-count individuals preoperatively (Delta 1.5, p < 0.001), at 6 weeks (Delta 0.9, p <0.001), at 3 months (Delta 1.4, p < 0.001), and at 6 months (Delta 1.4, p <0.001). High step-count individuals had improved HOOS12-Function scores compared to low step-count individuals preoperatively (Delta 9.6, p <0.001), at 6 weeks (Delta 5.3, p <0.001), and at 3 months (Delta 6.1, p <0.001). Males had greater step-count at all time points (p <0.001). Younger patients and low BMI patients had greater step-count across all time CONCLUSION: High step-count improved PROMs scores compared to low step-count. Early post-operative step-count was significantly impacted by age, sex, and BMI. Generic recovery profiles may not be appropriate across diverse populations.

Acetabular component positioning is commonly referenced with the pelvis in the supine position in direct anterior approach THA. Changes in pelvic tilt (PT) from the pre-operative supine to the post-operative standing positions have not been well investigated and may have relevance to optimal acetabular component targeting for reduced risk of impingement and instability. The aims of this study were therefore to determine the change in PT that occurs from pre-operative supine to post-operative standing, and whether any factors are associated with significant changes in tilt ≥13° in posterior direction. 13° in a posterior direction was chosen as that amount of posterior rotation creates an increase in functional anteversion of the acetabular component of 10°. 1097 THA patients with pre-operative supine CT and standing lateral radiographic imaging and 1 year post-operative standing lateral radiographs (interquartile range 12–13 months) were reviewed. Pre-operative supine PT was measured from CT as the angle between the anterior pelvic plane (APP) and the horizontal plane of the CT device. Standing PT was measured on standing lateral x-rays as the angle between the APP and the vertical line. Patients with ≥13° change from supine pre-op to standing post-op (corresponding to a 10° change in cup anteversion) were grouped and compared to those with a <13° change using unpaired student's t-tests. Mean pre-operative supine PT (3.8±6.0°) was significantly different from mean post-operative standing PT (−3.5±7.1°, p<0.001), ie mean change of −7.3±4.6°. 10.4% (114/1097) of patients had posterior PT changes ≥13° supine pre-op to standing post-op. A significant number of patients, ie 1 in 10, undergo a clinically significant change in PT and functional anteversion from supine pre-op to standing post-op. Surgeons should be aware of these changes when planning component placement in THA.

Background The 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. Methods Medial 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 (Nav lit ) or an optimized wear assumption (Nav opt ) 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. Results ICCs 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 Nav lit (all differences within 0.6°, P > 0.1) or Nav opt (all within 0.1°, P > 0.83). Mean absolute errors (MAE) between LLR and Nav lit 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. Nav lit and Nav opt , with > 95% and > 91.8% of measurements within the limits of agreement across all CPAK parameters, respectively. Conclusions Imageless 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.

BACKGROUND:The impact of femoral anteversion changes on femoral rotation and anterior offset following total hip arthroplasty (THA) has not been well studied. This study therefore investigated the relationship among femoral anteversion, anterior offset, and femoral rotation before and after THA. METHODS:There were 995 patients who had staged primary bilateral THAs who received a preoperative supine computerized axial tomography (CT) scan, following a standardized protocol, for surgical planning prior to each THA. The following measurements were performed for the first operative hip preoperatively and postoperatively on the first and second CT scans, respectively: femoral anatomic anteversion, defined as the angle between the native femoral neck or stem neck axis and the posterior condylar axis; femoral rotation, defined as the angle of the posterior condylar axis relative to the coronal plane of the CT; and femoral anterior offset, defined as the shortest distance between the femoral head center and a femoral plane containing the epicondyles and the piriformis fossa. The mean time between imagings was 11 months (range, 2 to 44). Associations are described using linear regression (β = slope) and Pearson correlation (r) coefficients. A t distribution was used for testing correlation. RESULTS:Femoral anteversion correlated with femoral anterior offset preoperatively (β = 0.565, r = 0.914, P < 0.001) and postoperatively (β = 0.671, r = 0.958, P < 0.001), and with femoral rotation preoperatively (β = 0.623, r = 0.575, P < 0.001) and postoperatively (β = 0.459, r = 0.517, P < 0.001). Increasing anteversion from preoperatively to postoperatively increased anterior offset (β = 0.621, r = 0.908, P < 0.001) and femoral internal rotation (IR) (β = 0.241, r = 0.273, P < 0.001). Patients who had >20° increase in anteversion (mean increase 26°, range 20 to 40.5°, n = 71) had a mean increase in femoral IR of 9.6 ± 9.8°. CONCLUSIONS:Increasing femoral anteversion increases anterior offset and IR of the femur, with approximately a 1° increase in IR for every 4° increase in anteversion on average. Surgeons should appreciate the implications of changing anteversion during THA planning.

BACKGROUND:The study investigated the relationship between computed bony range of motion (BROM) and actual functional range of motion (FROM) as directly measured in cadaveric hips. The hypothesis was that some hip movements are not substantially restricted by soft tissues, and therefore, computed BROM for these movements may effectively represent FROM, providing a reliable parameter for computational pre-operative planning. METHODS:Maximum passive FROM was measured in nine cadaveric hips using optical tracking. Each hip was measured in at least ninety FROM positions, covering flexion, extension, abduction, flexion-internal rotation (IR), flexion-external rotation (ER), extension-IR, and extension-ER movements. The measured FROM was virtually recreated using 3D models of the femur and pelvis derived from CT scans, and the corresponding BROM was computed. The relationship between FROM and BROM was classified into three groups: close (mean difference<5°), moderate (mean difference 5-15°), and weak (mean difference>15°). RESULTS:The relationship between FROM and BROM was close for pure flexion (difference = 3.1° ± 3.9°) and IR in deep (>70°) flexion (difference = 4.3° ± 4.6°). The relationship was moderate for ER in minimal flexion (difference = 10.3° ± 5.8°) and ER in minimal extension (difference = 11.7° ± 7.2°). Bony impingement was observed in some cases during these movements. Other movements showed a weak relationship: large differences were observed in extension (51.9° ± 14.4°), abduction (18.6° ± 11.3°), flexion-IR at flexion<70° (37.1° ± 9.4°), extension-IR (79.6° ± 4.8°), flexion-ER at flexion>30° (45.9° ± 11.3°), and extension-ER at extension>20° (15.8° ± 4.8°). CONCLUSION:BROM simulations of hip flexion, IR in deep flexion, and ER in low flexion/extension may be useful in dynamic pre-operative planning of total hip arthroplasty.

Background This study investigates the association between intra-operative balance and 2-year outcomes within subgroups defined by demographics and pre-operative joint balance. Our hypothesis is that patient demographics and the pre-operative state of the joint will impact patient sensitivity to post-operative balance and laxity and subsequent impact on outcome. Methods A retrospective analysis of prospectively captured data across 5 sites with 5 surgeons was performed. All cases completed pre-operative demographics surveys, 2-year post-operative Knee Injury and Osteoarthritis Outcome Score (KOOS) and had a robot assisted total knee arthroplasty with an integrated digital joint balancing tool. Differences in associations between intra-operative final joint balance and 2-year KOOS pain outcomes in demographic and pre-operative balance subgroups were characterized. Associations informed clinically relevant thresholds to optimize TKA treatment for subgroups. Results A total of 276 patients completed 2-year KOOS scores. Subgroups were defined from Sex, Age, BMI and pre-operative extension laxity. Men prefer a tight tolerance medially in extension and mid-flexion while females prefer a tight lateral flexion gap. Patients <70 years show a strong preference for equal rectangular gaps in extension, mid-flexion, and flexion, while older patients do not show a preference. Patients with BMI ≤30 demonstrate a preference for rectangular gaps, while patients with higher BMI do not. Finally, patients with looser pre-operative extension laxity (>3mm) preferred a TKA with increased extension laxity compared to patients with minimal preoperative laxity. Conclusion Intraoperative differences in knee balance can influence patient outcome scores among different demographic groups at two years postoperatively. This suggests further research is warranted to determine how ligament balance and laxity may be optimized based on individual patient factors.