ScolioMedIS: web-oriented information system for idiopathic scoliosis visualization and monitoring

Predictive analysis of the scoliotic curve using a subject's 3D model

A predictive analysis of the conservative scoliosis treatment is necessary, in which a 3D model of an optimal treatment algorithm is a basic part in the design of a prosthetic corset. Since CAD technology has proven to be very useful in the field of prosthetics and orthotics, we used an open-source software to plan the correction of the scoliotic curve on a virtual model of the subject's torso. The shape of the scoliosis was simplified by means of a directional polygon, which was drawn in a reverse manner depending on the directional arcs of the scoliotic curve. The resulting scoliosis correction, simulated in a predictive analysis, was defined by changing the Cobb angle, eccentricity, and torso height. With the proposed low-cost method of predictive analysis, it is possible to help CPOs to a more accurate and effective design of orthoses and corrective aids and to comprehensively determine the entire treatment procedure.

An ontology-based module of the information system ScolioMedIS for 3D digital diagnosis of adolescent scoliosis

BACKGROUND AND OBJECTIVE

Conventional information systems are built on top of a relational database. The main weakness of these systems is impossibility to define stable data schema ahead when the knowledge of the system is evolving and dynamic. The widely accepted alternatives to relational databases are ontologies that can be used for designing information systems. Many research papers describe various methods for improving reliability and precision in generating the type of the Lenke classification based on the image processing techniques or a computer program, but all of them require radiograph images. The main objective of this paper is to demonstrate the development of an ontology-based module of the information system ScolioMedIS for adolescent idiopathic scoliosis (AIS) diagnosis and monitoring, which uses optical 3D methods to determine the Lenke classification of AIS and to avoid harmful effects of traditional radiation diagnosis.

METHODS

For creating an ontology-based module of the ScolioMedIS we used the following steps: specification, conceptualization, formalization and implementation. In the specification and conceptualization phase we performed data collection and analysis to define domain, concepts and relationships for ontology design. In the formalization and implementation stage we developed the OBR-Scolio ontology and the ontology-based module of the ScolioMedIS. The module employs the Protégé-OWL API, as a collection of Java interfaces for the OBR-Scolio ontology, which enables the creating, deleting, and editing of the basic elements of the OBR-Scolio ontology, as well as the querying of the ontology.

RESULTS

The ontology-based module of ScolioMedIS is tested on the datasets of 20 female and 15 male patients with AIS between the ages of 11 and 18, to categorize spinal curvatures and to automatically generate statistical indicators about the frequency of the basic spinal curvatures, degree of progression or regression of deformity and statistical indicators about curvature characteristics according to the Lenke classification system and Lenke scoliosis types. Results are then compared with analysis of the Lenke classification of 315 observed patients, performed using traditional radiation techniques.

CONCLUSIONS

This part of the system allows continuous monitoring of the progression/regression of spinal curvatures for each registered patient, which may provide a better management of scoliosis (diagnosis and treatment).

Measurement and Geometric Modelling of Human Spine Posture for Medical Rehabilitation Purposes Using a Wearable Monitoring System Based on Inertial Sensors

This paper presents a mathematical model that can be used to virtually reconstruct the posture of the human spine. By using orientation angles from a wearable monitoring system based on inertial sensors, the model calculates and represents the curvature of the spine. Several hypotheses are taken into consideration to increase the model precision. An estimation of the postures that can be calculated is also presented. A non-invasive solution to identify the human back shape can help reducing the time needed for medical rehabilitation sessions. Moreover, it prevents future problems caused by poor posture.

Determination of the human spine curve based on laser triangulation

Background

The main objective of the present method was to automatically obtain a spatial curve of the thoracic and lumbar spine based on a 3D shape measurement of a human torso with developed scoliosis. Manual determination of the spine curve, which was based on palpation of the thoracic and lumbar spinous processes, was found to be an appropriate way to validate the method. Therefore a new, noninvasive, optical 3D method for human torso evaluation in medical practice is introduced.

Methods

Twenty-four patients with confirmed clinical diagnosis of scoliosis were scanned using a specially developed 3D laser profilometer. The measuring principle of the system is based on laser triangulation with one-laser-plane illumination. The measurement took approximately 10 seconds at 700 mm of the longitudinal translation along the back. The single point measurement accuracy was 0.1 mm. Computer analysis of the measured surface returned two 3D curves. The first curve was determined by manual marking (manual curve), and the second was determined by detecting surface curvature extremes (automatic curve). The manual and automatic curve comparison was given as the root mean square deviation (RMSD) for each patient. The intra-operator study involved assessing 20 successive measurements of the same person, and the inter-operator study involved assessing measurements from 8 operators.

Results

The results obtained for the 24 patients showed that the typical RMSD between the manual and automatic curve was 5.0 mm in the frontal plane and 1.0 mm in the sagittal plane, which is a good result compared with palpatory accuracy (9.8 mm). The intra-operator repeatability of the presented method in the frontal and sagittal planes was 0.45 mm and 0.06 mm, respectively. The inter-operator repeatability assessment shows that that the presented method is invariant to the operator of the computer program with the presented method.

Conclusions

The main novelty of the presented paper is the development of a new, non-contact method that provides a quick, precise and non-invasive way to determine the spatial spine curve for patients with developed scoliosis and the validation of the presented method using the palpation of the spinous processes, where no harmful ionizing radiation is present.

CAROTID - a web-based platform for optimal personalized management of atherosclerotic patients

Carotid atherosclerosis is the main cause of fatal cerebral ischemic events, thereby posing a major burden for public health and state economies. We propose a web-based platform named CAROTID to address the need for optimal management of patients with carotid atherosclerosis in a twofold sense: (a) objective selection of patients who need carotid-revascularization (i.e., high-risk patients), using a multifaceted description of the disease consisting of ultrasound imaging, biochemical and clinical markers, and (b) effective storage and retrieval of patient data to facilitate frequent follow-ups and direct comparisons with related cases. These two services are achieved by two interconnected modules, namely the computer-aided diagnosis (CAD) tool and the intelligent archival system, in a unified, remotely accessible system. We present the design of the platform and we describe three main usage scenarios to demonstrate the CAROTID utilization in clinical practice. Additionally, the platform was evaluated in a real clinical environment in terms of CAD performance, end-user satisfaction and time spent on different functionalities. CAROTID classification of high- and low-risk cases was 87%; the corresponding stenosis-degree-based classification would have been 61%. Questionnaire-based user satisfaction showed encouraging results in terms of ease-of-use, clinical usefulness and patient data protection. Times for different CAROTID functionalities were generally short; as an example, the time spent for generating the diagnostic decision was 5min in case of 4-s ultrasound video. Large datasets and future evaluation sessions in multiple medical institutions are still necessary to reveal with confidence the full potential of the platform.