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The robustness and accuracy of the intensity-based 3D/2D registration of a 3D model on planar X-ray image(s) is related to the quality of the image correspondences between the digitally reconstructed radiographs (DRR) generated from the 3D models (varying image) and the X-ray images (fixed target). While much effort may be devoted to generating realistic DRR that are similar to real X-rays (using complex X-ray simulation, adding densities information in 3D models, etc.), significant differences still remain between DRR and real X-ray images. Differences such as the presence of adjacent or superimposed soft tissue and bony or foreign structures lead to image matching difficulties and decrease the 3D/2D registration performance. In the proposed method, the X-ray images were converted into DRR images using a GAN-based cross-modality image-to-images translation. With this added prior step of XRAY-to-DRR translation, standard similarity measures become efficient even when using simple and fast DRR projection. For both images to match, they must belong to the same image domain and essentially contain the same kind of information. The XRAY-to-DRR translation also addresses the well-known issue of registering an object in a scene composed of multiple objects by separating the superimposed or/and adjacent objects to avoid mismatching across similar structures. We applied the proposed method to the 3D/2D fine registration of vertebra deformable models to biplanar radiographs of the spine. We showed that the XRAY-to-DRR translation enhances the registration results, by increasing the capture range and decreasing dependence on the similarity measure choice since the multi-modal registration becomes mono-modal.

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To date, 3D spine reconstruction from biplanar radiographs involves intensive user supervision and semi-automated methods that are time-consuming and not effective in clinical routine. This paper proposes a new, fast, and automated 3D spine reconstruction method through which a realistic statistical shape model of the spine is fitted to images using convolutional neural networks (CNN). The CNNs automatically detect the anatomical landmarks controlling the spine model deformation through a hierarchical and gradual iterative process. The performance assessment used a set of 68 biplanar radiographs, composed of both asymptomatic subjects and adolescent idiopathic scoliosis patients, in order to compare automated reconstructions with ground truths build using multiple experts-supervised reconstructions. The mean (SD) errors of landmark locations (3D Euclidean distances) were 1.6 (1.3) mm, 1.8 (1.3) mm, and 2.3 (1.4) mm for the vertebral body center, endplate centers, and pedicle centers, respectively. The clinical parameters extracted from the automated 3D reconstruction (reconstruction time is less than one minute) presented an absolute mean error between 2.8° and 4.7° for the main spinal parameters and between 1° and 2.1° for pelvic parameters. Automated and expert's agreement analysis reported that, on average, 89% of automated measurements were inside the expert's confidence intervals. The proposed automated 3D spine reconstruction method provides an important step that should help the dissemination and adoption of 3D measurements in clinical routine.

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BACKGROUND: Surgical parameters such as the selection of tibial and femoral attachment site, graft tension, and knee flexion angle at the time of fixation may influence the control of knee stability after lateral extra-articular reconstruction. This study aimed to determine how sensitive is the control of knee rotation and translation, during simulated pivot-shift scenarios, to these four surgery settings. METHODS: A computer model was used to simulate 625 lateral extra-articular reconstructions based upon five different variations of each of the following parameters: femoral and tibial attachment sites, knee flexion angle and graft tension at the time of fixation. For each simulated surgery, the lateral extra-articular reconstruction external rotation moment at the knee joint center was computed during simulated pivot-shift scenarios. The sensitivity of the control of knee rotation and translation to a given surgery setting was assessed by calculating the coefficient of variation of the lateral extra-articular reconstruction external rotation moment. FINDINGS: Graft tension had minimal influence on the control of knee rotation and translation with less than 2.4% of variation across the scenarios tested. Control of knee rotation and translation was the least affected by the femoral attachment site if the knee was close to full extension at the time of graft fixation. The choice of the tibial attachment site was crucial when the femoral fixation was proximal and posterior to the femoral epicondyle since 15 to 67% of variation was observed in the control of knee rotation and translation. INTERPRETATION: Femoral and tibial attachment sites as well as knee flexion angle at the time of fixation should be considered by surgeons when performing lateral extra-articular reconstruction. Variation in graft tension between the ranges 20-40 N has minimal influence on the control of knee rotation and translation.

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The aim of this study was to quantify the tibio-femoral contact point (CP) locations in healthy and osteoarthritic (OA) subjects during a weight-bearing squat using stand-alone biplanar X-ray images. Ten healthy and 9 severe OA subjects performed quasi-static squats. Bi-planar X-ray images were recorded at 0°, 15°, 30°, 45°, and 70° of knee flexion. A reconstruction/registration process was used to create 3D models of tibia, fibula, and femur from bi-planar X-rays and to measure their positions at each posture. A weighted centroid of proximity algorithm was used to calculate the tibio-femoral CP locations. The accuracy of the reconstruction/registration process in measuring the quasi-static kinematics and the contact parameters was evaluated in a validation study. The quasi-static kinematics data revealed that in OA knees, adduction angles were greater (p<0.01), and the femur was located more medially relative to the tibia (p<0.01). Similarly, the average CP locations on the medial and lateral tibial plateaus of the OA patients were shifted (6.5±0.7mm; p<0.01) and (9.6±3.1mm; p<0.01) medially compared to the healthy group. From 0° to 70° flexion, CPs moved 8.1±5.3mm and 8.9±5.3mm posteriorly on the medial and lateral plateaus of healthy knees; while in OA joints CPs moved 10.1±8.4mm and 3.6±2.8mm posteriorly. The average minimum tibio-femoral bone-to-bone distances of the OA joints were lower in both compartments (p<0.01). The CPs in the OA joints were located more medially and displayed a higher ratio of medial to lateral posterior translations compared to healthy joints.

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In clinical practice, knee MRI sequences with 3.5~5 mm slice distance in sagittal, coronal, and axial planes are often requested for the knee examination since its acquisition is faster than high-resolution MRI sequence in a single plane, thereby reducing the probability of motion artifact. In order to take advantage of the three sequences from different planes, a 3D segmentation method based on the combination of three knee models obtained from the three sequences is proposed in this paper. In the method, the sub-segmentation is respectively performed with sagittal, coronal, and axial MRI sequence in the image coordinate system. With each sequence, an initial knee model is hierarchically deformed, and then the three deformed models are mapped to reference coordinate system defined by the DICOM standard and combined to obtain a patient-specific model. The experimental results verified that the three sub-segmentation results can complement each other, and their integration can compensate for the insufficiency of boundary information caused by 3.5~5 mm gap between consecutive slices. Therefore, the obtained patient-specific model is substantially more accurate than each sub-segmentation results.

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The gait movement is a complex and essential process of the human activity. Yet, many types of diseases (neurological, muscular, orthopedic, etc.) can be diagnosed from the gait analysis. This paper introduces a novel method to quickly visualize the different body parts related to an (temporally shift-invariant) asymmetric movement in the human gait of a patient for daily clinical usage. The goal is to provide a cheap and easy-to-use method that measures the gait asymmetry and display results in a perceptual and intuitive way. This method relies on an affordable consumer depth sensor, the Kinect, which is very suitable for small room and fast diagnostic, since it is easy to setup and marker-less.

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PURPOSE: Surgical instrumentation for adolescent idiopathic scoliosis (AIS) is a complex procedure where selection of the appropriate curve segment to fuse, i.e., fusion region, is a challenging decision in scoliosis surgery. Currently, the Lenke classification model is used for fusion region evaluation and surgical planning. Retrospective evaluation of Lenke classification and fusion region results was performed. METHODS: Using a database of 1,776 surgically treated AIS cases, we investigated a topologically ordered self organizing Kohonen network, trained using Cobb angle measurements, to determine the relationship between the Lenke class and the fusion region selection. Specifically, the purpose was twofold (1) produce two spatially matched maps, one of Lenke classes and the other of fusion regions, and (2) associate these two maps to determine where the Lenke classes correlate with the fused spine regions. RESULTS: Topologically ordered maps obtained using a multi-center database of surgically treated AIS cases, show that the recommended fusion region agrees with the Lenke class except near boundaries between Lenke map classes. Overall agreement was 88%. CONCLUSION: The Lenke classification and fusion region agree in the majority of adolescent idiopathic scoliosis when reviewed retrospectively. The results indicate the need for spinal fixation instrumentation variation associated with the Lenke classification.

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In clinical routine, lower limb analysis relies on conventional X-ray (2D view) or computerised tomography (CT) Scan (lying position). However, these methods do not allow 3D analysis in standing position. The aim of this study is to propose a fast and accurate 3D-reconstruction-method based on parametric models and statistical inferences from biplanar X-rays with clinical measurements' (CM) assessment in standing position for a clinical routine use. For the reproducibility study, the 95% CI was under 2.7° for all lower limbs' angular measurements except for tibial torsion, femoral torsion and tibiofemoral rotation ( < 5°). The 95% CI were under 2.5 mm for lower limbs' lengths and 1.5 to 3° for the pelvis' CM. Comparisons between X-rays and CT-scan based 3D shapes in vitro showed mean differences of 1.0 mm (95% CI = 2.4 mm). Comparisons of 2D lower limbs' and 3D pelvis' CM between standing 'Shifted-Feet' and 'Non-Shifted-Feet' position showed means differences of 0.0 to 1.4°. Significant differences were found only for pelvic obliquity and rotation. The reconstruction time was about 5 min.

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PURPOSE: Quantitative assessment of 3D clinical indices may be crucial for elbow surgery planning. 3D parametric modeling from bi-planar radiographs was successfully proposed for spine and lower limb clinical investigation as an alternative for CT-scan. The aim of this study was to adapt this method to the upper limb with a preliminary validation. METHODS: CT-scan 3D models of humerus, radius and ulna were obtained from 20 cadaveric upper limbs and yielded parametric models made of geometric primitives. Primitives were defined by descriptor parameters (diameters, angles...) and correlations between these descriptors were found. Using these correlations, a semi-automated reconstruction method of humerus using bi-planar radiographs was achieved: a 3D personalized parametric model was built, from which clinical parameters were computed [orientation and projections on bone surface of trochlea sulcus to capitulum (CTS) axis, trochlea sulcus anterior offset and width of distal humeral epiphysis]. This method was evaluated by accuracy compared to CT-scan and reproducibility. RESULTS: Points-to-surface mean distance was 0.9 mm (2 RMS = 2.5 mm). For clinical parameters, mean differences were 0.4-1.9 mm and from 1.7° to 2.3°. All parameters except from angle formed by CTS axis and bi-epicondylar axis in transverse plane were reproducible. Reconstruction time was about 5 min. CONCLUSIONS: The presented method provides access to morphological upper limb parameters with very low level of radiation. Preliminary in vitro validation for humerus showed that it is fast and accurate enough to be used in clinical daily practice as an alternative to CT-scan for total elbow arthroplasty pre operative evaluation.

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Biomechanical modelling of the spine is of high clinical significance, either for implant evaluation or for surgery planning. Nevertheless, assessment of patient specific material properties still remains an issue, especially the viscoelastic characteristics of lumbar intervertebral discs (IVD). MRI, a dedicated system for IVD examination, provides a signal that is correlated with the biochemical content of the disc. Since IVD composition and its mechanical properties are related, the objectives of this study were to investigate how MRI could inform about viscoelastic properties of lumbar discs, determined from creep experiments. For that purpose, an in vitro protocol was carried out regarding 14 human L1-L2 IVDs; each unfrozen specimen was imaged using MRI and biomechanically tested with 10 min creep under 400 N load. Three-parameter rheologic models were used to fit the experimental curves. Additionally, geometry was obtained and degeneration was assessed using both MRI grading and physical inspection (destructive analysis). Mean creep displacement was 0.19 mm after 10 min. MRI scaling categorized elastic modulus and viscosity of the IVDs in 2 clearly distinct groups without overlaps according to degeneration: mean values for elastic modulus were 12.9 MPa and 5.7 MPa, respectively for mildly and severely degenerated IVDs; mean values for viscosity were 5.7 GPa s and 2.2 GPa s, respectively for mildly and severely degenerated IVDs. Classification derived from physical inspection did not reveal a clear discrimination. MRI could hence provide a quantification of IVDs viscoelastic properties, leading to in vivo direct estimation of material characteristics necessary for patient specific modelling.

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OBJECTIVE: This study aims to compare knee joint instability and postural impairments during the performance of a unipodal stance task between patients having knee osteoarthritis (OA) and healthy elderly subjects using knee accelerations and center of pressure (COP) measurements. MATERIALS AND METHODS: Twenty patients with medial knee OA and nine healthy individuals participated in this study. Three-dimensional (3D) knee joint accelerations and COP were measured during unipodal stance. The range and the root mean square (RMS) were extracted from medial lateral (ML) and anterior-posterior (AP) knee accelerations, whereas sway area, velocity, and ML and AP ranges were measured from the COP. The average parameters of three trials for each subject were compared between groups. RESULTS: Results show that knee OA patients exhibited a significantly higher range of knee acceleration in both ML (0.22±0.08 g vs 0.15±0.05 g) and AP (0.17±0.06 g vs 0.06±0.01 g) directions and a lower COP velocity (136.6±22.3 mm/s vs 157.6±18.4 mm/s) than did the healthy age-matched group. Significant correlations between the COP and knee acceleration parameters were also obtained. CONCLUSIONS: This study confirmed that patients with knee OA displayed greater body sway than did able-bodied subjects. Moreover, using an accelerometric-based method, this study highlighted the higher knee joint instability in the frontal and sagittal planes in knee OA patients compared with able-bodied subjects during a unipodal standing task.

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A computer-aided method for the tracking of morphological markers in fluoroscopic images of a rat walking on a treadmill is presented and validated. The markers correspond to bone articulations in a hind leg and are used to define the hip, knee, ankle and metatarsophalangeal joints. The method allows a user to identify, using a computer mouse, about 20% of the marker positions in a video and interpolate their trajectories from frame-to-frame. This results in a seven-fold speed improvement in detecting markers. This also eliminates confusion problems due to legs crossing and blurred images. The video images are corrected for geometric distortions from the X-ray camera, wavelet denoised, to preserve the sharpness of minute bone structures, and contrast enhanced. From those images, the marker positions across video frames are extracted, corrected for rat "solid body" motions on the treadmill, and used to compute the positional and angular gait patterns. Robust Bootstrap estimates of those gait patterns and their prediction and confidence bands are finally generated. The gait patterns are invaluable tools to study the locomotion of healthy animals or the complex process of locomotion recovery in animals with injuries. The method could, in principle, be adapted to analyze the locomotion of other animals as long as a fluoroscopic imager and a treadmill are available.

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3D reconstructions of the spine from a frontal and sagittal radiographs is extremely challenging. The overlying features of soft tissues and air cavities interfere with image processing. It is also difficult to obtain information that is accurate enough to reconstruct complete 3D models. To overcome these problems, the proposed method efficiently combines the partial information contained in two images from a patient with a statistical 3D spine model generated from a database of scoliotic patients. The algorithm operates through two simultaneous iterating processes. The first one generates a personalized vertebra model using a 2D/3D registration process with bone boundaries extracted from radiographs, while the other one infers the position and the shape of other vertebrae from the current estimation of the registration process using a statistical 3D model. Experimental evaluations have shown good performances of the proposed approach in terms of accuracy and robustness when compared to CT-scan.

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Measurement of three-dimensional (3D) knee joint angle outside a laboratory is of benefit in clinical examination and therapeutic treatment comparison. Although several motion capture devices exist, there is a need for an ambulatory system that could be used in routine practice. Up-to-date, inertial measurement units (IMUs) have proven to be suitable for unconstrained measurement of knee joint differential orientation. Nevertheless, this differential orientation should be converted into three reliable and clinically interpretable angles. Thus, the aim of this study was to propose a new calibration procedure adapted for the joint coordinate system (JCS), which required only IMUs data. The repeatability of the calibration procedure, as well as the errors in the measurement of 3D knee angle during gait in comparison to a reference system were assessed on eight healthy subjects. The new procedure relying on active and passive movements reported a high repeatability of the mean values (offset<1 degrees) and angular patterns (SD<0.3 degrees and CMC>0.9). In comparison to the reference system, this functional procedure showed high precision (SD<2 degrees and CC>0.75) and moderate accuracy (between 4.0 degrees and 8.1 degrees) for the three knee angle. The combination of the inertial-based system with the functional calibration procedure proposed here resulted in a promising tool for the measurement of 3D knee joint angle. Moreover, this method could be adapted to measure other complex joint, such as ankle or elbow.

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Patient-specific muscle geometry is not only an interesting clinical tool to evaluate different pathologies and treatments, but also provides an essential input data to more realistic musculoskeletal models. The protocol set up in our study provided the 3D-patient-specific geometry of the 13 main muscles involved in the knee joint motion from a few selected magnetic resonance images (MRIs). The contours of the muscles were identified on five to seven MRI axial slices. A parametric-specific object was then constructed for each muscle and deformed to fit those contours. The 13 muscles were obtained within 1 h, with less than 5% volume error and 5 mm point-surface error (2RMS). From this geometry, muscle volumes and volumic fractions of asymptomatic and anterior cruciate ligament deficient subjects could easily be computed and compared to previous studies. This protocol provides an interesting precision/time trade-off to obtain patient-specific muscular geometry.

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Reconstruction methods from biplanar X-rays provide 3D analysis of spinal deformities for patients in standing position with a low radiation dose. However, such methods require an important reconstruction time and there is a clinical need for fast and accurate techniques. This study proposes and evaluates a novel reconstruction method of the spine from biplanar X-rays. The approach uses parametric models based on longitudinal and transversal inferences. A first reconstruction level, dedicated to routine clinical use, allows to get a fast estimate (reconstruction time: 2 min 30 s) of the 3D reconstruction and accurate clinical measurements. The clinical measurements precision (evaluated on asymptomatic subjects, moderate and severe scolioses) was between 1.2 degrees and 5.6 degrees. For a more accurate 3D reconstruction (complex pathologies or research purposes), a second reconstruction level can be obtained within a reduced reconstruction time (10 min) with a fine adjustment of the 3D models. The mean shape accuracy in comparison with CT-scan was 1.0 mm. The 3D reconstruction method precision was 1.8mm for the vertebrae position and between 2.3 degrees and 3.9 degrees for the orientation. With a reduced reconstruction time, an improved accuracy and precision and a method proposing two reconstruction levels, this approach is efficient for both clinical routine uses and research purposes.

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OBJECTIVE: Knee instability and joint loading transmission are two important biomechanical factors in subjects with knee osteoarthritis (OA). However, the relationship between these factors in a rehabilitation treatment remains unclear. The purpose of this study is to determine the responsiveness of a new three-dimensional (3D) acceleration method used as an estimation of knee instability and joint loading transmission during gait in OA subjects after a rehabilitation treatment. METHOD: Twenty-four subjects with medial knee OA were included in this study. They had clinical and gait evaluations before and after 12 weeks of treatment. 3D linear knee accelerations, quadriceps and hamstring isometric strength and Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) pain were quantified, and compared between both evaluations. Nine asymptomatic subjects participated in this study for gait comparison. RESULTS: A significant reduction of the anterior posterior (AP) knee acceleration peak (P=0.02) had been detected after the treatment. No difference for both distal and lateral knee accelerations peak was found. A significant increase in quadriceps (P<0.001) and hamstring (P=0.006) strength was seen after treatment. The WOMAC of pain had shown significant reduction after the treatment (P<0.001). CONCLUSION: The present study demonstrates that the estimation of knee acceleration parameters is sensitive to changes in knee OA gait after a rehabilitation treatment. This study also indicates that a treatment of 3 months which combines therapeutic and exercises program could have benefits on knee OA by increasing AP knee stability and stabilize joint loading transmission during gait.

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