AI Screening Tool for Adolescent Idiopathic Scoliosis

  • Research type

    Research Study

  • Full title

    Applying Artificial Intelligence Methods to create a 3D screening tool for Adolescent Idiopathic Scoliosis(AIS) based on a digital photograph

  • IRAS ID

    366969

  • Contact name

    Adrian Gardner

  • Contact email

    a.gardner2@aston.ac.uk

  • Sponsor organisation

    Aston University

  • Clinicaltrials.gov Identifier

    n/a, n/a

  • Duration of Study in the UK

    2 years, 11 months, 31 days

  • Research summary

    Adolescent idiopathic scoliosis (AIS) is a spinal curvature affecting young people typically from ages 10 to 18, and presents a significant healthcare challenge, often leading to reduced mobility and quality of life if left untreated. Current understanding and management of this condition are limited, highlighting the need for improved detection methodologies and better treatment approaches. This study is designed to address these challenges by creating a more accurate and detailed understanding of scoliosis through the development of an innovative screening technology.
    The primary aim of the project is to construct an automated artificial intelligence (AI) system capable of identifying scoliosis by detecting asymmetries (imbalances) in the shape of the spine and back. This objective will be achieved by (i) utilising previously collected patient imaging data to train AI models using deep learning technology; (ii) integrating smartphone-based 3D imaging and computer vision capabilities to enable rapid, automated detection of scoliosis; and (iii) developing a smartphone application that individuals and clinicians can use for screening and assessment of spinal curvature severity. This innovative approach is expected to provide a practical and accessible tool that will allow healthcare professionals to identify scoliosis earlier and more reliably.
    No new participants are required, as the study uses previously collected patient images and data such as X-rays , MRI & CT scans, RGB images and surface topography data.
    The anticipated outcome of this study is not only to enhance the detection of scoliosis but also to enable earlier intervention and treatment, potentially avoiding the need for surgery. The solutions derived from this study offer the prospect of improved patient care, better clinical outcomes, and enhanced quality of life for young people with scoliosis. If successful, this system could inform changes to NHS screening policies for scoliosis detection and significantly reduce the burden of this condition on patients and healthcare services.

  • REC name

    South Central - Hampshire A Research Ethics Committee

  • REC reference

    26/SC/0131

  • Date of REC Opinion

    21 Apr 2026

  • REC opinion

    Favourable Opinion