Quantifying walking speeds in relation to ankle biomechanics on a real-time interactive gait platform: a musculoskeletal modeling approach in healthy adults.

Background: Given the inherent variability in walking speeds encountered in day-to-day activities, understanding the corresponding alterations in ankle biomechanics would provide valuable clinical insights. Therefore, the objective of this study was to examine the influence of different walking speeds on biomechanical parameters, utilizing gait analysis and musculoskeletal modelling. Methods: Twenty healthy volunteers without any lower limb medical history were included in this study. Treadmill-assisted gait-analysis with walking speeds of 0.8 m/s and 1.1 m/s was performed using the Gait Real-time Analysis Interactive Lab (GRAIL®). Collected kinematic data and ground reaction forces were processed via the AnyBody® modeling system to determine ankle kinetics and muscle forces of the lower leg. Data were statistically analyzed using statistical parametric mapping to reveal both spatiotemporal and magnitude significant differences. Results: Significant differences were found for both magnitude and spatiotemporal curves between 0.8 m/s and 1.1 m/s for the ankle flexion (p < 0.001), subtalar force (p < 0.001), ankle joint reaction force and muscles forces of the M. gastrocnemius, M. soleus and M. peroneus longus (α = 0.05). No significant spatiotemporal differences were found between 0.8 m/s and 1.1 m/s for the M. tibialis anterior and posterior. Discussion: A significant impact on ankle joint kinematics and kinetics was observed when comparing walking speeds of 0.8 m/s and 1.1 m/s. The findings of this study underscore the influence of walking speed on the biomechanics of the ankle. Such insights may provide a biomechanical rationale for several therapeutic and preventative strategies for ankle conditions.

Which parameters predict correction of the intermetatarsal angle after first metatarsophalangeal fusion?

Fusion of the first metatarsophalangeal joint (MTPJ) is a commonly performed surgical procedure. Although the effect of first MTPJ fusion on reduction of Intermetatarsal angle (IMA) is well described, contributing factors remain unclear. The aim of this study was to identity predictive parameters for IMA reduction. Fifty-one patients (68 feet) who underwent a first MTPJ fusion and had an IMA greater than fourteen degrees were assessed retrospectively. The average age was 68 (31.4-79.3) years. Sixteen demographic and radiographic variables were evaluated using a multivariate regression analysis for association with change in IMA after surgery. The mean preoperative IMA was 16.11 (range, 14.0-22.5) degrees with a mean reduction of 4.95 (range, 0-17) degrees after surgery. Multivariate regression analysis revealed three significant independent predictors of the change in IMA. Increased preoperative IMA (ß = .663, CI = .419, .908, P <.001), increased preoperative translation at base of MT1 (ß = .490, CI = 0.005, .974, P = 0.039), and less postoperative translation in the fusion (ß= -0.693, CI= -1.054, -.331, P= 0.002) significantly increased the amount of IMA reduction. Pre-operative IMA and translation at the base of the first metatarsal were positive predictors for correction of IMA after first MTPJ fusion. Translation at the level of the MTP I fusion was a negative predictor for the amount of IMA correction. Based on these findings, we recommend minimizing the lateral translation of the proximal phalanx relative to the metatarsal head to optimize IMA correction after MTPJ fusion.

Application of external torque enhances the detection of subtle syndesmotic ankle instability in a weight-bearing CT.

PURPOSE: Acute syndesmotic ankle injuries continue to impose a diagnostic dilemma and it remains unclear whether weightbearing and/or external rotation should be added during the imaging process. Therefore, the aim of this study was to assess if combined weightbearing and external rotation increases the diagnostic sensitivity of syndesmotic ankle instability using weightbearing CT (WBCT) imaging, compared to isolated weightbearing. METHODS: In this retrospective study, patients with an acute syndesmotic ankle injury were analysed using a WBCT (N = 21; Age = 31.6 ± 14.1 years old). Inclusion criteria were an MRI confirmed syndesmotic ligament injury imaged by a WBCT of the ankle during weightbearing and combined weightbearing-external rotation. Exclusion criteria consisted of fracture associated syndesmotic injuries. Three-dimensional (3D) models were generated from the CT slices. Tibiofibular displacement and talar rotation were quantified using automated 3D measurements (anterior tibiofibular distance (ATFD), Alpha angle, posterior Tibiofibular distance (PTFD) and Talar rotation (TR) angle in comparison to the contralateral non-injured ankle. RESULTS: The difference in neutral-stressed Alpha angle and ATFD showed a significant difference between patients with a syndesmotic ankle lesion and contralateral control (P = 0.046 and P = 0.039, respectively). The difference in neutral-stressed PTFD and TR angle did not show a significant difference between patients with a syndesmotic ankle lesion and healthy ankles (n.s.). CONCLUSION: Application of combined weightbearing-external rotation reveals an increased ATFD in patients with syndesmotic ligament injuries. This study provides the first insights based on 3D measurements to support the potential relevance of applying external rotation during WBCT imaging. In clinical practice, this could enhance the current diagnostic accuracy of subtle syndesmotic instability in a non-invasive manner. However, to what extent certain displacement patterns require operative treatment strategies has yet to be determined in future studies. LEVEL OF EVIDENCE: Level III.

Personalized statistical modeling of soft tissue structures in the knee.

Background and Objective: As in vivo measurements of knee joint contact forces remain challenging, computational musculoskeletal modeling has been popularized as an encouraging solution for non-invasive estimation of joint mechanical loading. Computational musculoskeletal modeling typically relies on laborious manual segmentation as it requires reliable osseous and soft tissue geometry. To improve on feasibility and accuracy of patient-specific geometry predictions, a generic computational approach that can easily be scaled, morphed and fitted to patient-specific knee joint anatomy is presented. Methods: A personalized prediction algorithm was established to derive soft tissue geometry of the knee, originating solely from skeletal anatomy. Based on a MRI dataset (n = 53), manual identification of soft-tissue anatomy and landmarks served as input for our model by use of geometric morphometrics. Topographic distance maps were generated for cartilage thickness predictions. Meniscal modeling relied on wrapping a triangular geometry with varying height and width from the anterior to the posterior root. Elastic mesh wrapping was applied for ligamentous and patellar tendon path modeling. Leave-one-out validation experiments were conducted for accuracy assessment. Results: The Root Mean Square Error (RMSE) for the cartilage layers of the medial tibial plateau, the lateral tibial plateau, the femur and the patella equaled respectively 0.32 mm (range 0.14-0.48), 0.35 mm (range 0.16-0.53), 0.39 mm (range 0.15-0.80) and 0.75 mm (range 0.16-1.11). Similarly, the RMSE equaled respectively 1.16 mm (range 0.99-1.59), 0.91 mm (0.75-1.33), 2.93 mm (range 1.85-4.66) and 2.04 mm (1.88-3.29), calculated over the course of the anterior cruciate ligament, posterior cruciate ligament, the medial and the lateral meniscus. Conclusion: A methodological workflow is presented for patient-specific, morphological knee joint modeling that avoids laborious segmentation. By allowing to accurately predict personalized geometry this method has the potential for generating large (virtual) sample sizes applicable for biomechanical research and improving personalized, computer-assisted medicine.

Validation of a personalized ligament-constraining discrete element framework for computing ankle joint contact mechanics.

BACKGROUND AND OBJECTIVE: Computer simulations of joint contact mechanics have great merit to improve our current understanding of articular ankle pathology. Owed to its computational simplicity, discrete element analysis (DEA) is an encouraging alternative to finite element analysis (FEA). However, previous DEA models lack subject-specific anatomy and may oversimplify the biomechanics of the ankle. The objective of this study was to develop and validate a personalized DEA framework that permits movement of the fibula and incorporates personalized cartilage thickness as well as ligamentous constraints. METHODS: A linear and non-linear DEA framework, representing cartilage as compressive springs, was established, verified, and validated. Three-dimensional (3D) bony ankle models were constructed from cadaveric lower limb CT scans imaged during application of weight (85 kg) and/or torque (10 Nm). These 3D models were used to generate cartilage thickness and ligament insertion sites based on a previously validated statistical shape model. Ligaments were modelled as non-linear tension-only springs. Validation of contact stress prediction was performed using a simple, axially constrained tibiotalar DEA model against an equivalent FEA model. Validation of ligamentous constraints compared the final position of the ankle mortise to that of the cadaver after application of torque and sequential ligament sectioning. Finally, a combined ligamentous-constraining DEA model was validated for predicted contact stress against an equivalent ligament-constraining FEA model. RESULTS: The linear and non-linear DEA model reproduced a mean articular contact stress within 0.36 MPa and 0.39 MPa of the FEA calculated stress, respectively. With respect to the ligamentous validation, the DEA ligament-balancing algorithm could reproduce the position of the distal fibula within the ankle mortise to within 0.97 mm of the experimental observed distal fibula. When combining the ligament-constraining and contact stress algorithm, DEA was able to reproduce a mean articular contact stress to within 0.50 MPa of the FEA calculated contact stress. CONCLUSION: The DEA framework presented herein offers a computationally efficient alternative to FEA for the prediction of contact stress in the ankle joint, manifesting its potential to enhance the mechanical understanding of articular ankle pathologies on both a patient-specific and population-wide level. The novelty of this model lies in its personalized nature, inclusion of the distal tibiofibular joint and the use of non-linear ligament balancing to maintain the physiological ankle joint articulation.

Personalised statistical modelling of soft tissue structures in the ankle.

BACKGROUND AND OBJECTIVE: Revealing the complexity behind subject-specific ankle joint mechanics requires simultaneous analysis of three-dimensional bony and soft-tissue structures. 3D musculoskeletal models have become pivotal in orthopedic treatment planning and biomechanical research. Since manual segmentation of these models is time-consuming and subject to manual errors, (semi-) automatic methods could improve the accuracy and enlarge the sample size of personalised 'in silico' biomechanical experiments and computer-assisted treatment planning. Therefore, our aim was to automatically predict ligament paths, cartilage topography and thickness in the ankle joint based on statistical shape modelling. METHODS: A personalised cartilage and ligamentous prediction algorithm was established using geometric morphometrics, based on an 'in-house' generated lower limb skeletal model (N = 542), tibiotalar cartilage (N = 60) and ankle ligament segmentations (N = 10). For cartilage, a population-averaged thickness map was determined by use of partial least-squares regression. Ligaments were wrapped around bony contours based on iterative shortest path calculation. Accuracy of ligament path and cartilage thickness prediction was quantified using leave-one-out experiments. The novel personalised thickness prediction was compared with a constant cartilage thickness of 1.50 mm by use of a paired sample T-test. RESULTS: Mean distance error of cartilage and ligament prediction was 0.12 mm (SD 0.04 mm) and 0.54 mm (SD 0.05 mm), respectively. No significant differences were found between the personalised thickness cartilage and segmented cartilage of the tibia (p = 0.73, CI [-1.60 .10-17, 1.13 .10-17]) and talus (p = 0.95, CI[ -1.35 .10-17, 1.28 .10-17]). For the constant thickness cartilage, a statistically significant difference was found in 89% and 92% of the tibial (p < 0.001, CI [0.51, 0.58]) and talar (p < 0.001, CI [0.33, 0.40]) cartilage area. CONCLUSIONS: In this study, we described a personalised prediction algorithm of cartilage and ligaments in the ankle joint. We were able to predict cartilage and main ankle ligaments with submillimeter accuracy. The proposed method has a high potential for generating large (virtual) sample sizes in biomechanical research and mitigates technological advances in computer-assisted orthopaedic surgery.

Three-dimensional displacement after a medializing calcaneal osteotomy in relation to the osteotomy angle and hindfoot alignment.

BACKGROUND: A medializing calcaneal osteotomy is frequently performed to correct adult-acquired flatfoot deformities, but there is lack of data on the associated three-dimensional variables defining the final correction. The aim of this study was to assess the correlation between the pre-operative hindfoot valgus deformity and calcaneal osteotomy angles and the post-operative calcaneal displacement. METHODS: Weight-bearing CT scans obtained pre- and post-operatively were retrospectively analyzed for sixteen patients. Corresponding three-dimensional bone models were used to measure valgus deformity pre- and post-operatively, inclination of the osteotomy and displacement of the calcaneus. Linear regression was conducted to assess the relationship between these measurements. RESULTS: On average, the hindfoot valgus changed from 13.1° (±4.6) pre-operatively to 5.7° (±4.3) post-operatively. A mean inferior displacement of 3.2mm (±1.3) was observed along the osteotomy with a mean inclination of 54.6° (±5.6), 80.5° (±10.7), -13.7° (±15.7) in the axial, sagittal and coronal planes, respectively. A statistically significant positive relationship (p<.05, R2=0.6) was found between the pre-operative valgus, the axial osteotomy inclination, and the inferior displacement. CONCLUSIONS: This study shows that the degree of pre-operative hindfoot valgus and the axial osteotomy angle are predictive factors for the amount of post-operative inferior displacement of the calcaneus. These findings demonstrate the added value of a computer-based pre-operative planning in clinical practice. Level of evidence II Prospective comparative study.

Reliability and correlation analysis of computed methods to convert conventional 2D radiological hindfoot measurements to a 3D setting using weightbearing CT.

PURPOSE: The exact radiographic assessment of the hindfoot alignment remains challenging. This is reflected in the different measurement methods available. Weightbearing CT (WBCT) has been demonstrated to be more accurate in hindfoot measurements. However, current measurements are still performed in 2D. This study wants to assess the use of computed methods to convert the former uniplanar hindfoot measurements obtained after WBCT towards a 3D setting. METHODS: Forty-eight patients, mean age of 39.6 ± 13.2 years, with absence of hindfoot pathology were included. A WBCT was obtained, and images were subsequently segmented and analyzed using computer-aided design operations. In addition to the hindfoot angle (HA), other ankle and hindfoot parameters such as the anatomical tibia axis, talocalcaneal axis (TCA), talocrural angle, tibial inclination (TI), talar tilt, and subtalar vertical angle were determined in 2D and 3D. RESULTS: The mean [Formula: see text] was [Formula: see text] of valgus ± 3.2 and the [Formula: see text] was [Formula: see text] of valgus ± 6.5. These angles differed significantly from each other with a [Formula: see text]. The correlation between both showed to be good by [Formula: see text] Pearson correlation coefficient (r) of 0.72 ([Formula: see text]). The [Formula: see text] showed to be excellent when compared to the [Formula: see text], which was good. Similar findings were obtained in other angles. The highest correlation was seen between the [Formula: see text] and [Formula: see text] (r = 0.83, [Formula: see text]) and an almost perfect agreement in the [Formula: see text] ([Formula: see text]). CONCLUSION: This study shows a good and reliable correlation between the [Formula: see text] and [Formula: see text]. However, the [Formula: see text] overcomes the shortcomings of inaccuracy and provides valuable spatial data that could be incorporated during computer-assisted surgery to assess the multiplanar correction of a hindfoot deformity.

Weightbearing CT in normal hindfoot alignment - Presence of a constitutional valgus?

BACKGROUND: The normal hindfoot angle is estimated between 2° and 6° of valgus in the general population. These results are solely based on clinical findings and plain radiographs. The purpose of this study is to assess the hindfoot alignment using weightbear CT. METHODS: Forty-eight patients, mean age of 39.6±13.2 years, with clinical and radiological absence of hindfoot pathology were included. A weightbear CT was obtained and allowed to measure the anatomical tibia axis (TAx) and the hindfoot alignment (HA). The HA was firstly determined using the inferior point of the calcaneus (HAIC). A density measurement of this area was subsequently performed to analyze if this point concurred with an increased ossification, indicating a higher load exposure. Secondly the HA was determined by dividing the calcaneus in the long axial view (HALA) and compared to the (HAIC) to point out any possible differences attributed to the measurement method. Reliability was assessed using an intra class correlation coefficient (ICC). RESULTS: The mean HAIC equaled 0.79° of valgus±3.2 (ICCHA IC=0.73) with a mean TAx of 2.7° varus±2.1 (ICCTA=0.76). The HALA equaled 9.1° of valgus±4.8 (ICCHA LA=0.71) and differed significantly by a P<0.001 from the HAIC, which showed a more neutral alignment. Correlation between both was shown to be good by a Spearman's correlation coefficient of 0.74. The mean density of the inferior calcaneal area equaled 271.3±84.1 and was significantly higher than the regional calcaneal area (P<0.001). CONCLUSIONS: These results show a more neutral alignment of the hindfoot in this group of non-symptomatic feet as opposed to the generally accepted constitutional valgus. This could have repercussion on hindfoot position during fusion or in quantifying the correction of a malalignment. The inferior calcaneus point in this can be used during pre-operative planning of a hindfoot correction as an anatomical landmark due to its shown influence on load transfer.

Measuring hindfoot alignment in weight bearing CT: A novel clinical relevant measurement method.

BACKGROUND: A precise pre-operative measurement of hindfoot malalignment is paramount to plan and obtain an accurate surgical correction. Hindfoot alignment is currently determined on standard weightbearing radiographs. However this is hampered by the superposition of the skeletal structures. Recent technology developed weightbearing cone beam CT to overcome this problem. The objective is to introduce a clinically relevant and reproducible method to measure hindfoot alignment on weightbearing CT. METHODS: Sixty malalignments of the hindfoot were divided in to two groups; group one containing a valgus alignment (n=30) and group two a varus alignment (n=30) of the hindfoot. Imaging techniques used were standard radiographs and a weightbearing CT (pedCAT®). Following angles were measured by two different authors: standard long axial hindfoot angle both on standard radiographs and on CT, clinical hindfoot, novel hindfoot angle, talar shift (distance from a neutral alignment), tibial inclination angle, talar tilt and subtalar vertical angle on CT. RESULTS: Hindfoot alignment angles showed to significantly differ from each other (P<0.001). The novel hindfoot alignment angle showed the highest correlation with the clinical measurement method. Correlation of this novel angle with the talar shift showed a Spearman's correlation coefficient=0.87. Interclass correlation coefficient of the novel hindfoot alignment angle=0.72 and was the highest among the hindfoot alignment angles. CONCLUSION: Weightbearing CT is allows to objectively assess hindfoot alignment. The proposed novel hindfoot alignment angle showed to be both clinically relevant and reproducible as compared to previous methods. The lateral tibiocalcaneal shift, on which the angle is highly correlated to, can help the surgeon in determining how much translation is necessary to obtain a neutral alignment during a calcaneal osteotomy. LEVEL OF EVIDENCE: Level III: retrospective cohort study.