Analysis of structural features of deformed spines in frontal and sagittal projections

Smart Sensing Chairs for Sitting Posture Detection, Classification, and Monitoring: A Comprehensive Review

Incorrect sitting posture, characterized by asymmetrical or uneven positioning of the body, often leads to spinal misalignment and muscle tone imbalance. The prolonged maintenance of such postures can adversely impact well-being and contribute to the development of spinal deformities and musculoskeletal disorders. In response, smart sensing chairs equipped with cutting-edge sensor technologies have been introduced as a viable solution for the real-time detection, classification, and monitoring of sitting postures, aiming to mitigate the risk of musculoskeletal disorders and promote overall health. This comprehensive literature review evaluates the current body of research on smart sensing chairs, with a specific focus on the strategies used for posture detection and classification and the effectiveness of different sensor technologies. A meticulous search across MDPI, IEEE, Google Scholar, Scopus, and PubMed databases yielded 39 pertinent studies that utilized non-invasive methods for posture monitoring. The analysis revealed that Force Sensing Resistors (FSRs) are the predominant sensors utilized for posture detection, whereas Convolutional Neural Networks (CNNs) and Artificial Neural Networks (ANNs) are the leading machine learning models for posture classification. However, it was observed that CNNs and ANNs do not outperform traditional statistical models in terms of classification accuracy due to the constrained size and lack of diversity within training datasets. These datasets often fail to comprehensively represent the array of human body shapes and musculoskeletal configurations. Moreover, this review identifies a significant gap in the evaluation of user feedback mechanisms, essential for alerting users to their sitting posture and facilitating corrective adjustments.

An automatic method for feature segmentation of human thoracic and lumbar vertebrae

BACKGROUND AND OBJECTIVE

Because of the three-dimensional distribution of morphological features of human vertebrae and the whole spine, in recent years, to make more precise diagnoses and to design optimized surgical procedures, new protocols have been proposed based on analysing their three-dimensional (3D) models. In the related literature, processes of segmentation and morphological features recognition are essentially performed by a skilled operator that selects the interesting areas. So, being affected by the preparation and experience of the operator, this produces an evaluation that is poorly reproducible and repeatable for the uncertainties of a typical manual measurement process.

METHODS

To overcome this limitation, in this paper a new automatic method is proposed for feature segmentation and recognition of human vertebrae. The proposed computer-based method, starting from 3D high density discretized models of thoracic and lumbar vertebrae, automatically performs both the semantic and geometric segmentation of their morphological features. The segmentation and recognition rules codify some important definitions used in the traditional manual method, considering all the vertebra morphology information that is invariant inter-subject.

RESULTS

The automatic method proposed here is verified by analysing many real vertebrae, both acquired using a 3D scanner and coming from Computerized Tomography (CT) scans. The obtained results are critically discussed and compared with the traditional manual methods for vertebra analysis. The method has proven to be robust and reliable in the segmentation and recognition of morphological features of vertebrae. Furthermore, the proposed automatic method avoids the blurring of quantitative parameters get from vertebrae, resulting from poor repeatability and reproducibility of manual methods used in the state-of-the-art.

CONCLUSIONS

Starting from the automatic segmentation and recognition here proposed, it is possible to automatically calculate the parameters of thoracic or lumbar vertebrae used in archaeology, medicine, or biomechanics or define their new ones.

Contour and Angle-Function Based Scoliosis Monitoring: Relaxing the Requirement on Image Quality in the Measurement of Spinal Curvature

PURPOSE

A method for measuring spinal curvature that provides a useful analog to the Cobb angle and is tolerant of degraded image quality is proposed. Conventional methods require a higher standard of discernibility for vertebra features and suffer high variability.

METHODS

Assumption is made that the natural representation of the spine for the purpose of scoliosis monitoring is that of a continuous curved contour rather than a series of discrete vertebral bodies with individual orientations. The angle that a tangent line to this contour makes with the vertical, expressed as a continuous function of height, is proposed as a metric for characterization of the curve. The Cobb angle can be approximated as the difference between the extrema of this function, and details of the function shape can provide additional markers for tracking curve variation and evolution. A method for deriving the angle function from coronal images of the spine is proposed, and both manual and automatic variants of the procedure are described.

RESULTS

The method is applied to conventional coronal radiographs and to magnetic resonance (MR) coronal views derived from volumetric acquisitions of the spine. Included in the latter category is an image exhibiting poor discrimination of vertebra features due to motion artifacts. The method permits extraction of the curve and Cobb angles in all cases.

CONCLUSIONS

Because the spine contour is discernible even in low quality images where vertebral endplates may be obscured or poorly contrasted from surrounding tissue, the approach offers improved reliability, applicability across imaging modalities, and, in the case of x-rays, the possibility of a reduced radiation dose. Moreover, since it relies on larger image features and exploits the continuity of the spine, the contour-based approach is expected to reduce the variability associated with Cobb angle measurement.

Improving Visibility of Stereo-Radiographic Spine Reconstruction with Geometric Inferences

Complex deformities of the spine, like scoliosis, are evaluated more precisely using stereo-radiographic 3D reconstruction techniques. Primarily, it uses six stereo-corresponding points available on the vertebral body for the 3D reconstruction of each vertebra. The wireframe structure obtained in this process has poor visualization, hence difficult to diagnose. In this paper, a novel method is proposed to improve the visibility of this wireframe structure using a deformation of a generic spine model in accordance with the 3D-reconstructed corresponding points. Then, the geometric inferences like vertebral orientations are automatically extracted from the radiographs to improve the visibility of the 3D model. Biplanar radiographs are acquired from five scoliotic subjects on a specifically designed calibration bench. The stereo-corresponding point reconstruction method is used to build six-point wireframe vertebral structures and thus the entire spine model. Using the 3D spine midline and automatically extracted vertebral orientation features, a more realistic 3D spine model is generated. To validate the method, the 3D spine model is back-projected on biplanar radiographs and the error difference is computed. Though, this difference is within the error limits available in the literature, the proposed work is simple and economical. The proposed method does not require more corresponding points and image features to improve the visibility of the model. Hence, it reduces the computational complexity. Expensive 3D digitizer and vertebral CT scan models are also excluded from this study. Thus, the visibility of stereo-corresponding point reconstruction is improved to obtain a low-cost spine model for a better diagnosis of spinal deformities.

The use of a photogrammetric method for the three-dimensional evaluation of spinal correction in scoliosis

PURPOSE

Clinical parameters, characterizing the spinal deformations due to scoliosis, are still directly measured on the spinal curve plane projections.

METHODS

A 3D spinal curve has been reconstructed from its two projections, using photogrammetric techniques. Each spinal curve is a compound of several plane regions, where it is purely flexed, and short zones of connection, where abduction and axial rotation components are concentrated. All spinal curves are represented as linear chains of regional planes articulated together. The regional plane is represented by a triangle, where one summit corresponds to the point of maximum offset. The set of weight forces, representing pelvis and spine, forms a bundle of vertical forces. The dispersion of the bundle illustrates the postural stability of patients.

RESULTS AND CONCLUSIONS

The first objective was to numerically describe the changes of the 3D spinal feature, due to the correcting treatment. Changes are calculated from the comparison between 3D radiologic situations, between before and after treatment. The second objective was to determine the direction of the external force, which would be the most efficient for correcting the patient set spine/rib cage. A mild mechanical analysis is proposed, for representing the transit of the external force, from rib cage to thoracic regional plane.

Quantitative evaluation of the lumbosacral sagittal alignment in degenerative lumbar spinal stenosis

GOAL OF THE STUDY

This study intends to develop a method of quantitative sagittal balance parameters assessment, based on a geometrical model of lumbar spine and sacrum.

METHODS

One hundred eight patients were divided into 2 groups. In the experimental group have been included 59 patients with lumbar spinal stenosis on L1-5 level. Forty-nine healthy volunteers without history of any lumbar spine pathlogy were included in the control group. All patients have been examined with supine MRI. Lumbar lordosis has been adopted as circular arc and described either anatomical (lumbar lordosis angle), or geometrical (chord length, circle segment height, the central angle, circle radius) parameters. Moreover, 2 sacral parameters have been assessed for all patients: sacral slope and sacral deviation angle. Both parameters characterize sacrum disposition in horizontal and vertical axis respectively.

RESULTS

Significant correlation was observed between anatomical and geometrical lumbo-sacral parameters. Significant differences between stenosis group and control group were observed in the value of the "central angle" and "sacral deviation" parameters. We propose additional parameters: lumbar coefficient, as ratio of the lordosis angle to the segmental angle (Kl); sacral coefficient, as ratio of the sacral tilt (ST) to the sacral deviation (SD) angle (Ks); and assessment modulus of the mathematical difference between sacral and lumbar coefficients has been used for determining lumbosacral balance (LSB). Statistically significant differences between main and control group have been obtained for all described coefficients (p = 0.006, p = 0.0001, p = 0.0001, accordingly). Median of LSB value of was 0.18 and 0.34 for stenosis and control groups, accordingly.

CONCLUSION

Based on these results we believe that that spinal stenosis is associated with an acquired deformity that is measureable by the described parameters. It's possible that spinal stenosis occurs in patients with an LSB of 0.2 or less, so this value can be predictable for its development. It may suggest that spinal stenosis is more likely to occur in patients with the spinal curvature of this type because of abnormal distribution of the spine loads. This fact may have prognostic significance for develop vertebral column disease and evaluation of treatment results.

RELATIONSHIP BETWEEN SAGITTAL SPINAL CURVES AND BACK SURFACE PROFILES OBTAINED WITH RADIOGRAPHS

The purpose of this article is to introduce a novel approach, by using coupled video and radiographic analysis of back surface and spinal curves in the sagittal plane to decrease the ionizing radiation exposure for subjects requiring long-term follow-up of their spinal deformity. This approach is specifically designed for the use in a clinical set-up for the follow-up of subjects with progressive spinal deformities. The subjects are radiographed with nine steel balls embedded in circular markers evenly distributed on the subject's back surface over the spinous processes of C7 to S1. A technique allows to draw the external back profile and the spinal curve. Patient-specific transfer functions are defined moving the back profile to the spinal curve. Sixteen adult volunteers were tested to validate the concepts proposed. For each of them, the values of transfer functions between radiographic back surface profile and corresponding spinal curve have been calculated. Each internal curve is correctly simulated when based upon the back profile. Our research is now focused on the prediction of the internal curve of patients from their back surface profile based on patient-specific transfer functions.

Geometric Structure of 3D Spinal Curves: Plane Regions and Connecting Zones

This paper presents a new study of the geometric structure of 3D spinal curves. The spine is considered as an heterogeneous beam, compound of vertebrae and intervertebral discs. The spine is modeled as a deformable wire along which vertebrae are beads rotating about the wire. 3D spinal curves are compound of plane regions connected together by zones of transition. The 3D spinal curve is uniquely flexed along the plane regions. The angular offsets between adjacent regions are concentrated at level of the middle zones of transition, so illustrating the heterogeneity of the spinal geometric structure. The plane regions along the 3D spinal curve must satisfy two criteria: (i) a criterion of minimum distance between the curve and the regional plane and (ii) a criterion controlling that the curve is continuously plane at the level of the region. The geometric structure of each 3D spinal curve is characterized by the sizes and orientations of regional planes, by the parameters representing flexed regions and by the sizes and functions of zones of transition. Spinal curves of asymptomatic subjects show three plane regions corresponding to spinal curvatures: lumbar, thoracic and cervical curvatures. In some scoliotic spines, four plane regions may be detected.

Reliability assessment of Cobb angle measurements using manual and digital methods

BACKGROUND CONTEXT

The vertebral spine angle in the frontal plane is an important parameter in the assessment of scoliosis and may be obtained from panoramic X-ray images. Technological advances have allowed for an increased use of digital X-ray images in clinical practice.

PURPOSE

In this context, the objective of this study is to assess the reliability of computer-assisted Cobb angle measurements taken from digital X-ray images.

STUDY DESIGN/SETTING

Clinical investigation quantifying scoliotic deformity with Cobb method to evaluate the intra- and interobserver variability using manual and digital techniques.

PATIENT SAMPLE

Forty-nine patients diagnosed with idiopathic scoliosis were chosen based on convenience, without predilection for gender, age, type, location, or magnitude of the curvature.

OUTCOME MEASURES

Images were examined to evaluate Cobb angle variability, end plate selection, as well as intra- and interobserver errors.

METHODS

Specific software was developed to digitally reproduce the Cobb method and calculate semiautomatically the degree of scoliotic deformity. During the study, three observers estimated the Cobb angle using both the digital and the traditional manual methods.

RESULTS

The results showed that Cobb angle measurements may be reproduced in the computer as reliably as with the traditional manual method, in similar conditions to those found in clinical practice.

CONCLUSIONS

The computer-assisted method (digital method) is clinically advantageous and appropriate to assess the scoliotic curvature in the frontal plane using Cobb method.

Classification of pelvic and spinal postural patterns in upright position. Specific cases of scoliotic patients

The 3D analyses of spinal shapes and postural features give a great number of data. The global patient posture includes his pelvic morphology and tilting, and his pelvic and spinal balance. In some scoliotic spines, the spinal curve belongs to a unique plane. In other scoliotic patients, the spinal curve shows several plane regions. The spinal structures are modeled from parameters locating the structural planes and by values of maximum curvatures. Some parameters have been introduced for describing the postural patterns and the spinal deformities. For each tested patient, each major parameter has been characterized by an index of class.

A review of methods for quantitative evaluation of spinal curvature

The aim of this paper is to provide a complete overview of the existing methods for quantitative evaluation of spinal curvature from medical images, and to summarize the relevant publications, which may not only assist in the introduction of other researchers to the field, but also be a valuable resource for studying the existing methods or developing new methods and evaluation strategies. Key evaluation issues and future considerations, supported by the results of the overview, are also discussed.

Personalized models of bones based on radiographic photogrammetry

The radiographic photogrammetry is applied, for locating anatomical landmarks in space, from their two projected images. The goal of this paper is to define a personalized geometric model of bones, based uniquely on photogrammetric reconstructions. The personalized models of bones are obtained from two successive steps: their functional frameworks are first determined experimentally, then, the 3D bone representation results from modeling techniques. Each bone functional framework is issued from direct measurements upon two radiographic images. These images may be obtained using either perpendicular (spine and sacrum) or oblique incidences (pelvis and lower limb). Frameworks link together their functional axes and punctual landmarks. Each global bone volume is decomposed in several elementary components. Each volumic component is represented by simple geometric shapes. Volumic shapes are articulated to the patient's bone structure. The volumic personalization is obtained by best fitting the geometric model projections to their real images, using adjustable articulations. Examples are presented to illustrating the technique of personalization of bone volumes, directly issued from the treatment of only two radiographic images. The chosen techniques for treating data are then discussed. The 3D representation of bones completes, for clinical users, the information brought by radiographic images.