Monitoring Scoliosis with 3D Ultrasound

• Research type

  Research Study

• Full title

  Monitoring and predicting the curve progression of patients with adolescent idiopathic scoliosis using three-dimensional ultrasound

• IRAS ID

  139473

• Contact name

  Adam Shortland

• Contact email

  Adam.shortland.gstt.nhs.uk

• Sponsor organisation

  Guy's and St. Thomas' NHS Trust

• Research summary

  Scoliosis is a three-dimensional deformity of the spine and the trunk. This deformity is typically quantified using the Cobb angle from x-ray images. Due to the risk of curve progression, patients with a Cobb angle > 10°, frontal and lateral images are acquired typically every 4-6 months. Routine X-rays in children and young adults has been demonstrated as presenting a significant cancer risk in this group. Furthermore, planar x-ray images are a 2D projection of a 3D curve and the derived Cobb angle is insensitive to the axial rotation that deforms the attached ribs. Monitoring scoliosis in 3D will provide more clinically useful parameters to better predict progression of their scoliosis and may identify those at greatest risk of developing cardiopulmonary complications.

  We propose a new method for measuring spinal curvature that could improve the monitoring of patients with scoliosis. By combining motion capture technology with conventional ultrasound, complete images of the spine can be generated and the complex 3D curvature quantified. The clinical validation phase of the project will evaluate the level agreement of MRI and 3D ultrasound data of 30 subjects with scoliosis lying in a standardised position

  The current clinical practice is to routinely monitor AIS patients with a Cobb angle greater than 10°. However, only around 5% of adolescents experience curve progression beyond a Cobb angle of 30° necessitating intervention. The second phase of the project will aim to identify the risk of progression by applying statistical shape analysis on the 3D spine profile of 100 patients with and without a progressing curve with a view to identify characteristic features. If this approach can successfully predict the risk, only 5% of patient would need monitoring/intervention. This will lead to a significant resource saving for the NHS and significantly reduced radiation exposure to patients.

• REC name

  London - London Bridge Research Ethics Committee

• REC reference

  14/LO/0280

• Date of REC Opinion

  2 Apr 2014

• REC opinion

  Further Information Favourable Opinion