L’impact des principes éthiques sur le marché d’assurance en présence de tests génétiques

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Scoliosis Follow-Up Using Noninvasive Trunk Surface Acquisition

Adolescent idiopathic scoliosis (AIS) is a musculoskeletal pathology. It is a complex spinal curvature in a 3-D space that also affects the appearance of the trunk. The clinical follow-up of AIS is decisive for its management. Currently, the Cobb angle, which is measured from full spine radiography, is the most common indicator of the scoliosis progression. However, cumulative exposure to X-rays radiation increases the risk for certain cancers. Thus, a noninvasive method for the identification of the scoliosis progression from trunk shape analysis would be helpful. In this study, a statistical model is built from a set of healthy subjects using independent component analysis and genetic algorithm. Based on this model, a representation of each scoliotic trunk from a set of AIS patients is computed and the difference between two successive acquisitions is used to determine if the scoliosis has progressed or not. This study was conducted on 58 subjects comprising 28 healthy subjects and 30 AIS patients who had trunk surface acquisitions in upright standing posture. The model detects 93% of the progressive cases and 80% of the nonprogressive cases. Thus, the rate of false negatives, representing the proportion of undetected progressions, is very low, only 7%. This study shows that it is possible to perform a scoliotic patient's follow-up using 3-D trunk image analysis, which is based on a noninvasive acquisition technique.

Multilevel Analysis of Trunk Surface Measurements for Noninvasive Assessment of Scoliosis Deformities.

Study Design. Reliability study. Objectives. To assess between-acquisition reliability of new multilevel trunk cross sections measurements, in order to define what is a real change when comparing 2 trunk surface acquisitions of a same patient, before and after surgery or throughout the clinical monitoring. Summary of Background Data. Several cross-sectional surface measurements have been proposed in the literature for noninvasive assessment of trunk deformity in patients with adolescent idiopathic scoliosis (AIS). However, only the maximum values along the trunk are evaluated and used for monitoring progression and assessing treatment outcome. Methods. Back surface rotation (BSR), trunk rotation (TR), and coronal and sagittal trunk deviation are computed on 300 cross sections of the trunk. Each set of 300 measures is represented as a single functional data, using a set of basis functions. To evaluate between-acquisition variability at all trunk levels, a test-retest reliability study is conducted on 35 patients with AIS. A functional correlation analysis is also carried out to evaluate any redundancy between the measurements. Results. Each set of 300 measures was successfully described using only 10 basis functions. The test-retest reliability of the functional measurements is good to very good all over the trunk, except above the shoulders level. The typical errors of measurement are between 1.20° and 2.2° for the rotational measures and between 2 and 6 mm for deviation measures. There is a very strong correlation between BSR and TR all over the trunk, a moderate correlation between coronal trunk deviation and both BSR and TR, and no correlation between sagittal trunk deviation and any other measurement. Conclusion. This novel representation of trunk surface measurements allows for a global assessment of trunk surface deformity. Multilevel trunk measurements provide a broader perspective of the trunk deformity and allow a reliable multilevel monitoring during clinical follow-up of patients with AIS and a reliable assessment of the esthetic outcome after surgery.

Noninvasive Clinical Assessment of Trunk Deformities Associated With Scoliosis

Besides the spinal deformity, scoliosis modifies notably the general appearance of the trunk resulting in trunk rotation, imbalance, and asymmetries that constitutes patients' major concern. Existing classifications of scoliosis, based on the type of spinal curve as depicted on radiographs, are currently used to guide treatment strategies. Unfortunately, even though a perfect correction of the spinal curve is achieved, some trunk deformities remain, making patients dissatisfied with the treatment received. The purpose of this study is to identify possible shape patterns of trunk surface deformity associated with scoliosis. First, trunk surface is represented by a multivariate functional trunk shape descriptor based on 3-D clinical measurements computed on cross sections of the trunk. Then, the classical formulation of hierarchical clustering is adapted to the case of multivariate functional data and applied to a set of 236 trunk surface 3-D reconstructions. The highest internal validity is obtained when considering 11 clusters that explain up to 65% of the variance in our dataset. Our clustering result shows a concordance with the radiographic classification of spinal curves in 68% of the cases. As opposed to radiographic evaluation, the trunk descriptor is 3-D and its functional nature offers a compact and elegant description of not only the type, but also the severity and extent of the trunk surface deformity along the trunk length. In future work, new management strategies based on the resulting trunk shape patterns could be thought of in order to improve the esthetic outcome after treatment, and thus patients satisfaction.