J. A. de Guise

3D reconstruction of the spine from biplanar X-rays using parametric models based on transversal and longitudinal inferences

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.

A method for modeling noise in medical images

We have developed a method to study the statistical properties of the noise found in various medical images. The method is specifically designed for types of noise with uncorrelated fluctuations. Such signal fluctuations generally originate in the physical processes of imaging rather than in the tissue textures. Various types of noise (e.g., photon, electronics, and quantization) often contribute to degrade medical images; the overall noise is generally assumed to be additive with a zero-mean, constant-variance Gaussian distribution. However, statistical analysis suggests that the noise variance could be better modeled by a nonlinear function of the image intensity depending on external parameters related to the image acquisition protocol. We present a method to extract the relationship between an image intensity and the noise variance and to evaluate the corresponding parameters. The method was applied successfully to magnetic resonance images with different acquisition sequences and to several types of X-ray images.

Functional calibration procedure for 3D knee joint angle description using inertial sensors

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.

Assessment of the 3-D reconstruction and high-resolution geometrical modeling of the human skeletal trunk from 2-D radiographic images

This paper presents an in vivo validation of a method for the three-dimensional (3-D) high-resolution modeling of the human spine, rib cage, and pelvis for the study of spinal deformities. The method uses an adaptation of a standard close-range photogrammetry method called direct linear transformation to reconstruct the 3-D coordinates of anatomical landmarks from three radiographic images of the subjects trunk. It then deforms in 3-D 1-mm-resolution anatomical primitives (reference bones) obtained by serial computed tomography-scan reconstruction of a dry specimen. The free-form deformation is calculated using dual kriging equations. In vivo validation of this method on 40 scoliotic vertebrae gives an overall accuracy of 3.3 /spl plusmn/ 3.8 mm, making it an adequate tool for clinical studies and mechanical analysis purposes.

3D reconstruction method from biplanar radiography using non-stereocorresponding points and elastic deformable meshes.

Standard 3D reconstruction of bones using stereoradiography is limited by the number of anatomical landmarks visible in more than one projection. The proposed technique enables the 3D reconstruction of additional landmarks that can be identified in only one of the radiographs. The principle of this method is the deformation of an elastic object that respects stereocorresponding and non-stereo-corresponding observations available in different projections. This technique is based on the principle that any non-stereocorresponding point belongs to a line joining the X-ray source and the projection of the point in one view. The aim is to determine the 3D position of these points on their line of projection when submitted to geometrical and topological constraints. This technique is used to obtain the 3D geometry of 18 cadaveric upper cervical vertebrae. The reconstructed geometry obtained is compared with direct measurements using a magnetic digitiser. The order of precision determined with the point-to-surface distance between the reconstruction obtained with that technique and reference measurements is about 1 mm, depending on the vertebrae studied. Comparison results indicate that the obtained reconstruction is close to the actual vertebral geometry. This method can therefore be proposed to obtain the 3D geometry of vertebrae.

Reliability of a quantification imaging system using magnetic resonance images to measure cartilage thickness and volume in human normal and osteoarthritic knees

OBJECTIVE The aim of this study was to evaluate the reliability of a software tool that assesses knee cartilage volumes using magnetic resonance (MR) images. The objectives were to assess measurement reliability by: (1) determining the differences between readings of the same image made by the same reader 2 weeks apart (test-retest reliability), (2) determining the differences between the readings of the same image made by different readers (between-reader agreement), and (3) determining the differences between the cartilage volume readings obtained from two MR images of the same knee image acquired a few hours apart (patient positioning reliability). METHODS Forty-eight MR examinations of the knee from normal subjects, patients with different stages of symptomatic knee osteoarthritis (OA), and a subset of duplicate images were independently and blindly quantified by three readers using the imaging system. The following cartilage areas were analyzed to compute volumes: global cartilage, medial and lateral compartments, and medial and lateral femoral condyles. RESULTS Between-reader agreement of measurements was excellent, as shown by intra-class correlation (ICC) coefficients ranging from 0.958 to 0.997 for global cartilage (P<0.0001), 0.974 to 0.998 for the compartments (P<0.0001), and 0.943 to 0.999 for the condyles(P<0.0001). Test-retest reliability of within-reader data was also excellent, with Pearson correlation coefficients ranging from 0.978 to 0.999 (P<0.0001). Patient positioning reliability was also excellent, with Pearson correlation coefficients ranging from 0.978 to 0.999 (P<0.0001). CONCLUSIONS The results of this study establish the reliability of this MR imaging system. Test-retest reliability, between-reader agreement, and patient positioning reliability were all extremely high. This study represents a first step in the overall validation of an imaging system designed to follow progression of human knee OA.

Computer-aided method for quantification of cartilage thickness and volume changes using MRI: validation study using a synthetic model

The primary objective of this study was to develop a computer-aided method for the quantification of three-dimensional (3-D) cartilage changes over time in knees with osteoarthritis (OA). We introduced a local coordinate system (LCS) for the femoral and tibial cartilage boundaries that provides a standardized representation of cartilage geometry, thickness, and volume. The LCS can be registered in different data sets from the same patient so that results can be directly compared. Cartilage boundaries are segmented from 3-D magnetic resonance (MR) slices with a semi-automated method and transformed into offset-maps , defined by the LCS. Volumes and thickness are computed from these offset-maps. Further anatomical labeling allows focal volumes to be evaluated in predefined subregions. The accuracy of the automated behavior of the method was assessed, without any human intervention, using realistic, synthetic 3-D MR images of a human knee. The error in thickness evaluation is lower than 0.12 mm for the tibia and femur. Cartilage volumes in anatomical subregions show a coefficient of variation ranging from 0.11% to 0.32%. This method improves noninvasive 3-D analysis of cartilage thickness and volume and is well suited for in vivo follow-up clinical studies of OA knees.

A Biplanar Reconstruction Method Based on 2D and 3D Contours: Application to the Distal Femur

A three-dimensional (3D) reconstruction algorithm based on contours identification from biplanar radiographs is presented. It requires, as technical prerequisites, a method to calibrate the biplanar radiographic environment and a surface generic object (anatomic atlas model) representing the structure to be reconstructed. The reconstruction steps consist of: the definition of anatomical regions, the identification of 2D contours associated to these regions, the calculation of 3D contours and projection onto the radiographs, the associations between points of the X-rays contours and points of the projected 3D contours, the optimization of the initial solution and the optimized object deformation to minimize the distance between X-rays contours and projected 3D contours. The evaluation was performed on 8 distal femurs comparing the 3D models obtained to CT-scan reconstructions. Mean error for each distal femur was 1 mm.

Morphometric evaluations of personalised 3D reconstructions and geometric models of the human spine

In the past, several techniques have been developed to study and analyse the 3D characteristics of the human spine: multi-view radiographic or biplanar 3D reconstructions, CT-scan 3D reconstructions and geometric models. Extensive evaluations of three of these techniques that are routinely used at Sainte-Justine Hospital (Montréal, Canada) are presented. The accuracy of these methods is assessed by comparing them with precise measurements made with a coordinate measuring machine on 17 thoracic and lumbar vertebrae (T1-L5) extracted from a normal cadaveric spine specimen. Multi-view radiographic 3D reconstructions are evaluated for different combinations of X-ray views: lateral (LAT), postero-anterior with normal incidence (PAOo) and postero-anterior with 20o angled down incidence (PA20o). The following accuracies are found for these reconstructions obtained from different radiographic setups: 2.1±1.5 mm for the combination with PAOo-LAT views, and 5.6±4.5 mm for the PAOo-PA20o stereopair. Higher errors are found in the postero-anterior direction, especially for the PAOo-PA20o view combination. Pedicles are found to be the most precise landmarks. Accuracy for CT-scan 3D reconstructions is about 1.1±0.8 mm. As for a geometric model built using a multiview radiographic reconstruction based on six landmarks per vertebra, accuracies of about 2.6±2.4 mm for landmarks and 2.3±2.0 mm for morphometric parameters are found. The geometric model and 3D reconstruction techniques give accurate information, at low X-ray dose. The accuracy assessment of the techniques used to study the 3D characteristics of the human spine is important, because it allows better and more efficient quantitative evaluations of spinal dysfunctions and their treatments, as well as biomechanical modelling of the spine.

Quantitative assessment of skin-bone movement at the knee

Abstract Thick soft tissue and structures involved in the knees function surround the knee thus hiding the underlying kinematics. This makes diagnosis of pathologies and analysis of biomechanics difficult. This study accurately quantifies the relative movement between skin and the underlying bone, via X-ray flouroscopy and a mathematical model, in the interest of improving non-invasive knee movement analysis methods. It was found that skin-bone movement varies significantly over both medial and lateral femoral condyles (from 2 to 17 mm rms) and is, therefore, the greatest obstacle by far to obtaining accurate movement data non-intrusively. Data from the proposed method is fundamental to improving acquisition methods for knee biomechanics and prosthetic analysis and can help in understanding soft tissue movement for orthotic analysis.