Farida Cheriet

Human Atlas of the Cardiac Fiber Architecture: Study on a Healthy Population

Cardiac fibers, as well as their local arrangement in laminar sheets, have a complex spatial variation of their orientation that has an important role in mechanical and electrical cardiac functions. In this paper, a statistical atlas of this cardiac fiber architecture is built for the first time using human datasets. This atlas provides an average description of the human cardiac fiber architecture along with its variability within the population. In this study, the population is composed of ten healthy human hearts whose cardiac fiber architecture is imaged ex vivo with DT-MRI acquisitions. The atlas construction is based on a computational framework that minimizes user interactions and combines most recent advances in image analysis: graph cuts for segmentation, symmetric log-domain diffeomorphic demons for registration, and log-Euclidean metric for diffusion tensor processing and statistical analysis. Results show that the helix angle of the average fiber orientation is highly correlated to the transmural depth and ranges from -41° on the epicardium to +66° on the endocardium. Moreover, we find that the fiber orientation dispersion across the population (13°) is lower than for the laminar sheets (31°). This study, based on human hearts, extends previous studies on other mammals with concurring conclusions and provides a description of the cardiac fiber architecture more specific to human and better suited for clinical applications. Indeed, this statistical atlas can help to improve the computational models used for radio-frequency ablation, cardiac resynchronization therapy, surgical ventricular restoration, or diagnosis and followups of heart diseases due to fiber architecture anomalies.

Geometric Variability of the Scoliotic Spine Using Statistics on Articulated Shape Models

This paper introduces a method to analyze the variability of the spine shape and of the spine shape deformations using articulated shape models. The spine shape was expressed as a vector of relative poses between local coordinate systems of neighboring vertebrae. Spine shape deformations were then modeled by a vector of rigid transformations that transforms one spine shape into another. Because rigid transformations do not naturally belong to a vector space, conventional mean and covariance could not be applied. The Frechet mean and a generalized covariance were used instead. The spine shapes of a group of 295 scoliotic patients were quantitatively analyzed as well as the spine shape deformations associated with the Cotrel-Dubousset corrective surgery (33 patients), the Boston brace (39 patients), and the scoliosis progression without treatment (26 patients). The variability of intervertebral poses was found to be inhomogeneous (lumbar vertebrae were more variable than the thoracic ones) and anisotropic (with maximal rotational variability around the coronal axis and maximal translational variability along the axial direction). Finally, brace and surgery were found to have a significant effect on the Frechet mean and on the generalized covariance in specific spine regions where treatments modified the spine shape.

Reliability of trunk shape measurements based on 3-D surface reconstructions

This study aimed to estimate the reliability of 3-D trunk surface measurements for the characterization of external asymmetry associated with scoliosis. Repeated trunk surface acquisitions using the Inspeck system (Inspeck Inc., Montreal, Canada), with two different postures A (anatomical position) and B (‘‘clavicle’’ position), were obtained from patients attending a scoliosis clinic. For each acquisition, a 3-D model of the patient’s trunk was built and a series of measurements was computed. For each measure and posture, intraclass correlation coefficients (ICC) were obtained using a bivariate analysis of variance, and the smallest detectable difference was calculated. For posture A, reliability was fair to excellent with ICC from 0.91 to 0.99 (0.85 to 0.99 for the lower bound of the 95% confidence interval). For posture B, the ICC was 0.85 to 0.98 (0.74 to 0.99 for the lower bound of the 95% confidence interval). The smallest statistically significant differences for the maximal back surface rotation was 2.5 and 1.5° for the maximal trunk rotation. Apparent global asymmetry and axial trunk rotation indices were relatively robust to changes in arm posture, both in terms of mean values and within-subject variations, and also showed a good reliability. Computing measurements from cross-sectional analysis enabled a reduction in errors compared to the measurements based on markers’ position. Although not yet sensitive enough to detect small changes for monitoring of curve natural progression, trunk surface analysis can help to document the external asymmetry associated with different types of spinal curves as well as the cosmetic improvement obtained after surgical interventions. The anatomical posture is slightly more reliable as it allows a better coverage of the trunk surface by the digitizing system.

A versatile 3D reconstruction system of the spine and pelvis for clinical assessment of spinal deformities

This paper presents a three-dimensional (3D) reconstruction system of the human spine for the routine evaluation of musculoskeletal pathologies like idiopathic scoliosis. The main objective of this 3D reconstruction system is to offer a versatile and robust tool for the 3D analysis of spines in any healthcare centre with standard clinical setup using standard uncalibrated radiographic images. The novel system uses a self-calibration algorithm and a weak-perspective method to reconstruct the 3D coordinates of anatomical landmarks from bi-planar radiographic images of a patient’s trunk. Additionally, a small planar object of known dimensions is proposed to warrant an accurately scaled model of the spine. In order to assess the validity of the 3D reconstructions yielded by the proposed system, a clinical study using 60 pairs of digitized X-rays of adolescents was conducted. The subject cohort in the study group was composed of 51 scoliotic and 9 non-scoliotic patients, with an average Cobb angle on the frontal plane of 25°. For each case, a 3D reconstruction of the spine and pelvis was obtained with the previous system used at our hospital (which requires a positioning apparatus and a calibration jacket), and with the proposed method. Results show that 3D reconstructions obtained with the new system using uncalibrated X-ray images yield geometrically accurate models with insignificant differences for 2D and 3D clinical indexes commonly used in the evaluation of spinal deformities. This demonstrates the system to be a viable and accurate tool for clinical studies and biomechanical analysis purposes, with the added advantage of versatility to any clinical setup for routine follow-ups and surgical planning.

Clinical methods for quantifying body segment posture: a literature review

Purpose. Clinicians commonly assess posture in persons with musculoskeletal disorders and tend to do so subjectively. Evidence-based practice requires the use of valid, reliable and sensitive tools to monitor treatment effectiveness. The purpose of this article was to determine which methods were used to assess posture quantitatively in a clinical setting and to identify psychometric properties of posture indices measured from these methods or tools. Methods. We conducted a comprehensive literature review. Pertinent databases were used to search for articles on quantitative clinical assessment of posture. Searching keywords were related to posture and assessment, scoliosis, back pain, reliability, validity and different body segments. Results. We identified 65 articles with angle and distance posture indices that corresponded to our search criteria. Several studies showed good intra- and inter-rater reliability for measurements taken directly on the persons (e.g., goniometer, inclinometer, flexible curve and tape measurement) or from photographs, but the validity of these measurements was not always demonstrated. Conclusion. Taking measurements of all body angles directly on the person is a lengthy process and may affect the reliability of the measurements. Measurement of body angles from photographs may be the most accurate and rapid way to assess global posture quantitatively in a clinical setting.

Accuracy assessment of human trunk surface 3D reconstructions from an optical digitising system

The lack of reliable techniques to follow up scoliotic deformity from the external asymmetry of the trunk leads to a general use of X-rays and indices of spinal deformity. Young adolescents with idiopathic scoliosis need intensive follow-ups for many years and, consequently, they are repeatedly exposed to ionising radiation, which is hazardous to their long-term health. Furthermore, treatments attempt to improve both spinal and surface deformities, but internal indices do not describe the external asymmetry. The purpose of this study was to assess a commercial, optical 3D digitising system for the 3D reconstruction of the entire trunk for clinical assessment of external asymmetry. The resulting surface is a textured, high-density polygonal mesh. The accuracy assessment was based on repeated reconstructions of a manikin with markers fixed on it. The average normal distance between the reconstructed surfaces and the reference data (markers measured with CMM) was 1.1±0.9 mm.

A Novel System for the 3-D Reconstruction of the Human Spine and Rib Cage From Biplanar X-Ray Images

The main objective of this study was to develop a 3D X-ray reconstruction system of the spine and rib cage for an accurate 3D clinical assessment of spinal deformities. The system currently used at Sainte-Justine Hospital in Montreal is based on an implicit calibration technique based on a direct linear transform (DLT), using a sufficiently large rigid object incorporated in the positioning apparatus to locate any anatomical structure to be reconstructed within its bounds. During the time lapse between the two successive X-ray acquisitions required for the 3D reconstruction, involuntary patient motion introduce errors due to the incorrect epipolar geometry inferred from the stationary object. An approach using a new calibration jacket and explicit calibration algorithm is proposed in this paper. This approach yields accurate results and compensates for involuntary motion occurring between X-ray exposures.

Three-Dimensional Classification of Spinal Deformities Using Fuzzy Clustering

Study Design. A prospective study of a large set of three-dimensional (3D) reconstructions of spinal deformities in adolescent idiopathic scoliosis (AIS). Objectives. To determine the value of fuzzy clustering techniques to automatically detect clinically relevant 3D curve patterns within this set of 3D spine models. Summary of Background Data. Classification is important for the assessment of AIS and has been mainly used to guide surgical treatment. Current classification systems are based on visual curve pattern identification using two-dimensional radiologic measurements but remain controversial because of their low interobserver and intraobserver reliability. A clinically useful 3D classification remains to be found. Methods. An unsupervised learning algorithm, fuzzy k-means clustering, was applied on 409 3D spine models. Analysis of data distribution using clinical parameters was performed by studying similar curve patterns, near each cluster center identified. Results. The algorithm determined that the entire sample of models could be segmented in five easily differentiated curve patterns similar to those of the Lenke and King classifications. Furthermore, a system with 12 classes made possible the identification of subpatterns of spinal deformity with true 3D components. Conclusions. Automatic and clinically relevant 3D classification of AIS is possible using an unsupervised learning algorithm. This approach can now be used to build a relevant 3D classification of AIS using appropriate key features of 3D models selected by a panel of expert spinal deformity surgeons.

Texture Analysis for Automatic Segmentation of Intervertebral Disks of Scoliotic Spines From MR Images

This paper presents a unified framework for automatic segmentation of intervertebral disks of scoliotic spines from different types of magnetic resonance (MR) image sequences. The method exploits a combination of statistical and spectral texture features to discriminate closed regions representing intervertebral disks from background in MR images of the spine. Specific texture features are evaluated for three types of MR sequences acquired in the sagittal plane: 2-D spin echo, 3-D multiecho data image combination, and 3-D fast imaging with steady state precession. A total of 22 texture features (18 statistical and 4 spectral) are extracted from every closed region obtained from an automatic segmentation procedure based on the watershed approach. The feature selection step based on principal component analysis and clustering process permit to decide among all the extracted features which ones resulted in the highest rate of good classification. The proposed method is validated using a supervised k-nearest-neighbor classifier on 505 MR images coming from three different scoliotic patients and three different MR acquisition protocols. Results suggest that the selected texture features and classification can contribute to solve the problem of oversegmentation inherent to existing automatic segmentation methods by successfully discriminating intervertebral disks from the background on MRI of scoliotic spines.

Personalized X-Ray 3-D Reconstruction of the Scoliotic Spine From Hybrid Statistical and Image-Based Models

This paper presents a novel 3-D reconstruction method of the scoliotic spine using prior vertebra models with image-based information taken from biplanar X-ray images. We first propose a global modeling approach by exploiting the 3-D scoliotic curve reconstructed from a coronal and sagittal X-ray image in order to generate an approximate statistical model from a 3-D database of scoliotic patients based on a transformation algorithm which incorporates intuitive geometrical properties. The personalized 3-D reconstruction of the spine is then achieved with a novel segmentation method which takes into account the variable appearance of scoliotic vertebrae (rotation, wedging) from standard quality images in order to segment and isolate individual vertebrae on the radiographic planes. More specifically, it uses prior 3-D models regulated from 2-D image level set functionals to identify and match corresponding bone structures on the biplanar X-rays. An iterative optimization procedure integrating similarity measures such as deformable vertebral contours regulated from high-level anatomical primitives, morphological knowledge and epipolar constraints is then applied to globally refine the 3-D anatomical landmarks on each vertebra level of the spine. This method was validated on twenty scoliotic patients by comparing results to a standard manual approach. The qualitative evaluation of the retro-projection of the vertebral contours confirms that the proposed method can achieve better consistency to the X-ray images natural content. A comparison to synthetic models and real patient data also yields good accuracy on the localization of low-level primitives such as anatomical landmarks identified by an expert on each vertebra. The experiments reported in this paper demonstrate that the proposed method offers a better matching accuracy on a set of landmarks from biplanar views when compared to a manual technique for each evaluated cases, and its precision is comparable to 3-D models generated from magnetic resonance images, thus suitable for routine 3-D clinical assessment of spinal deformities.