Cardoso, MJ

Ciccarelli, O

De Angelis, F

Grussu, F

Miller, DH

Ourselin, S

Plantone, D

Prados Carrasco, F

Wheeler-Kingshott, CAM

Yiannakas, MC

UCL Discovery

Computing spinal cord atrophy using the Boundary Shift Integral a new feasible outcome for clinical trials  Ferran Prados1,2, Marios C Yiannakas2, Manuel Jorge Cardoso1, Francesco Grussu2, Floriana De Angelis2, Domenico Plantone2, David H Miller2, Olga Ciccarelli2, Claudia Angela Michela Gandini Wheeler-Kingshott2,3, and Sebastien Ourselin2  1 Translational Imaging Group, Medical Physics and Biomedical Engineering, University College London, London, United Kingdom  2 NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, United Kingdom  3 Brain Connectivity Center, C. Mondino National Neurological Institute, Pavia, Italy  Background: Atrophy measurements obtained from structural MRI are useful biomarkers of neurodegeneration. Spinal cord atrophy in multiple sclerosis (MS) has been shown to correlate with clinical disability but its measurements using MRI has been limited by poor reproducibility and responsiveness making difficult its application as outcome in clinical trials.  Aims: to demonstrate the feasibility of using Boundary Shift Integral (BSI) for computing atrophy in the spinal cord and introduce it as a potential outcome in MS clinical trials.  Methods: we included 10 healthy subjects (age: 45.5±8.9 years, gender 6F:4M) and 17 MS patients (age: 54.01±12.8 years, gender 9F:8M, including 6 RRMS, 4 PPMS and 7 SPMS). T1-weighted MPRAGE volume (1x1x1mm) at baseline and at 18 months was acquired using a 3T Philips scanner with a 16-channel neurovascular coil (which permitted coverage of the entire cervical spinal cord). One experienced observer manually outlined the SC between C2 and C5 at both time points. Then images were denoised, bias field corrected, straightened, rigid registered to the half-way space, symmetrical bias field corrected and finally we calculated the atrophy at intensity changes in the vicinity of the tissue boundaries using BSI. Moreover, in order to enable a fair comparison between methods, atrophy values based on cross-sectional area (CSA) were computed using the same manual masks.   Results: BSI and CSA atrophy results are annualised. Atrophy mean, standard deviation and confidence interval (CI) values for controls BSI=-0.01±0.13 CI(-0.09 to 0.07) and CSA=0.07±1.83 CI(-1.06 to 1.21), and patients BSI=-0.05±0.07 CI(-0.09 to -0.02) and CSA=-0.06±1.28 CI(-0.67 to 0.55). There is no evidence of differences in performance between the two techniques (p=0.87). Sample size with and without controlling for normal ageing were computed, for a hypothetical trial with 80% power at the 5% significance level and looking for 25% reduction in disease progression. Sample size without controlling for normal ageing BSI=465 vs CSA=108527, and with controlling for normal ageing BSI=675 vs CSA=22461.  Conclusion: we have demonstrated the feasibility of BSI for computing atrophy in the spinal cord, as a sensitive, quantitative and objective measure of longitudinal tissue volume change. Furthermore, BSI produces a significant reduction in sample sizes needed in clinical trials in comparison with CSA.              Disclosure  Dr Ferran Prados no disclosures.  Dr Marios Yiannakas no disclosures.  Dr Manuel Jorge Cardoso no disclosures.   Dr Francesco Grussu no disclosures.  Dr Floriana De Angelis no disclosures.  Dr Domenico Plantone no disclosures.  Prof David Miller has received honoraria from Biogen Idec, Novartis, GlaxoSmithKline, and Bayer Schering, and research grant support for doing MRI analysis in multiple sclerosis trials sponsored by GlaxoSmithKline, Biogen Idec, and Novartis.  Prof Olga Ciccarelli serves as a consultant for Biogen and General Electric and receives research support from the UK MS Society, UCL/UCLH NIHR BRC, and EPSRC.   Prof Claudia Wheeler-Kingshott serves as a consultant for Biogen and receives research support from the UK MS Society, UCL/UCLH NIHR BRC, EPSRC, ISRT, Wings for Life, New Zealand Brain Research Centre, Novartis, and Biogen.   Prof Sebastien Ourselin receives research support from the UCL/UCLH NIHR BRC, MRC, EPSRC and EU-FP7. 

Computing spinal cord atrophy using the Boundary Shift Integral: a more powerful outcome measure for clinical trials?

http://discovery.ucl.ac.uk/1519778/1/Prados%20Carrasco%20Computing%20spinal%20cord%20atrophy%20using%20the%20Boundary%20Shift%20Integral%20AAM.pdf

Computing spinal cord atrophy using the Boundary Shift Integral: a more powerful outcome measure for clinical trials?

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