Computing spinal cord atrophy using the Boundary Shift Integral: a more powerful outcome measure for clinical trials?
Author(s): ,
F Prados
Affiliations:
Translational Imaging Group, Department of Medical Physics and Biomedical Engineering, University College London;NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, United Kingdom
,
M.C Yiannakas
Affiliations:
NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, United Kingdom
,
M.J Cardoso
Affiliations:
Translational Imaging Group, Department of Medical Physics and Biomedical Engineering, University College London
,
F Grussu
Affiliations:
NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, United Kingdom
,
F De Angelis
Affiliations:
NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, United Kingdom
,
D Plantone
Affiliations:
NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, United Kingdom
,
D.H Miller
Affiliations:
NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, United Kingdom
,
O Ciccarelli
Affiliations:
NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, United Kingdom
,
C.A Wheeler-Kignshott
Affiliations:
NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, United Kingdom;Brain MRI 3T Center, C. Mondino National Neurological Institute, Pavia, Italy
S Ourselin
Affiliations:
Translational Imaging Group, Department of Medical Physics and Biomedical Engineering, University College London
ECTRIMS Online Library. Prados F. 09/16/16; 146033; P1605
Ferran Prados
Ferran Prados
Contributions
Abstract

Abstract: P1605

Type: LB Poster

Abstract Category: Late Breaking News

Background: Atrophy measurements obtained from structural magnetic resonance imaging (MRI) are useful biomarkers of neurodegeneration. Spinal cord (SC) atrophy in multiple sclerosis (MS) is strongly correlated with clinical disability but its measurement using MRI is limited by poor reproducibility and responsiveness making difficult its application as an outcome measure in clinical trials.

Aims: To demonstrate the feasibility of using Boundary Shift Integral (BSI) for computing atrophy in the SC and consider it as a potential outcome measure for MS clinical trials.

Methods: We included 10 healthy subjects (age: 45.5±8.9 years, gender 6F) and 17 MS patients (age: 54±12.8 years, gender 9F). A T1-weighted MPRAGE volume (1x1x1mm3) of the entire cervical SC was acquired at baseline and at 18 months using a 3T Philips MR system with a 16-channel neurovascular coil. One experienced observer semi-automatically outlined the SC between C2 and C5 at both time points using active surface modelling. Then images were denoised, bias field corrected, straightened, rigid registered to the half-way space and symmetrical bias field corrected. We then calculated the atrophy from intensity changes in the vicinity of the SC tissue boundaries using BSI. The values obtained were compared to those based on subtracting the baseline from follow-up cross-sectional area (CSA) using the same masks.

Results: BSI (mm3) and CSA (mm2) atrophy results were annualised. Atrophy mean, standard deviation and confidence interval (CI) values for controls were BSI=-0.01±0.13 (CI -0.09 to 0.07) and CSA=0.07±1.83 (CI -1.06 to 1.21), and for patients were BSI=-0.05±0.07 (CI -0.09 to -0.02) and CSA=-0.06±1.28 (CI -0.67 to 0.55). There was no evidence of differences in performance between the two techniques (p=0.87). Sample sizes with and without controlling for normal ageing were computed, for a hypothetical trial with 80% power at the 5% significance level and detecting 25% reduction in cord atrophy. Sample sizes without controlling for normal ageing: BSI=465 vs CSA=108527, and controlling for normal ageing: BSI=675 vs CSA=22461.

Conclusion: We demonstrate the feasibility of a registration-based technique such as BSI for computing atrophy in the SC, providing 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 a standard CSA method.

Disclosure:

Dr F Prados no disclosures.

Dr M Yiannakas no disclosures.

Dr M Cardoso no disclosures.

Dr F Grussu receives financial support from the H2020-EU.3.1 CDS-QUAMRI grant (ref.:634541)

Dr F De Angelis no disclosures.

Dr Domenico Plantone no disclosures.

Prof D 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 O 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 C 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 S Ourselin receives research support from the UCL/UCLH NIHR BRC, MRC, EPSRC and EU-FP7.

Abstract: P1605

Type: LB Poster

Abstract Category: Late Breaking News

Background: Atrophy measurements obtained from structural magnetic resonance imaging (MRI) are useful biomarkers of neurodegeneration. Spinal cord (SC) atrophy in multiple sclerosis (MS) is strongly correlated with clinical disability but its measurement using MRI is limited by poor reproducibility and responsiveness making difficult its application as an outcome measure in clinical trials.

Aims: To demonstrate the feasibility of using Boundary Shift Integral (BSI) for computing atrophy in the SC and consider it as a potential outcome measure for MS clinical trials.

Methods: We included 10 healthy subjects (age: 45.5±8.9 years, gender 6F) and 17 MS patients (age: 54±12.8 years, gender 9F). A T1-weighted MPRAGE volume (1x1x1mm3) of the entire cervical SC was acquired at baseline and at 18 months using a 3T Philips MR system with a 16-channel neurovascular coil. One experienced observer semi-automatically outlined the SC between C2 and C5 at both time points using active surface modelling. Then images were denoised, bias field corrected, straightened, rigid registered to the half-way space and symmetrical bias field corrected. We then calculated the atrophy from intensity changes in the vicinity of the SC tissue boundaries using BSI. The values obtained were compared to those based on subtracting the baseline from follow-up cross-sectional area (CSA) using the same masks.

Results: BSI (mm3) and CSA (mm2) atrophy results were annualised. Atrophy mean, standard deviation and confidence interval (CI) values for controls were BSI=-0.01±0.13 (CI -0.09 to 0.07) and CSA=0.07±1.83 (CI -1.06 to 1.21), and for patients were BSI=-0.05±0.07 (CI -0.09 to -0.02) and CSA=-0.06±1.28 (CI -0.67 to 0.55). There was no evidence of differences in performance between the two techniques (p=0.87). Sample sizes with and without controlling for normal ageing were computed, for a hypothetical trial with 80% power at the 5% significance level and detecting 25% reduction in cord atrophy. Sample sizes without controlling for normal ageing: BSI=465 vs CSA=108527, and controlling for normal ageing: BSI=675 vs CSA=22461.

Conclusion: We demonstrate the feasibility of a registration-based technique such as BSI for computing atrophy in the SC, providing 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 a standard CSA method.

Disclosure:

Dr F Prados no disclosures.

Dr M Yiannakas no disclosures.

Dr M Cardoso no disclosures.

Dr F Grussu receives financial support from the H2020-EU.3.1 CDS-QUAMRI grant (ref.:634541)

Dr F De Angelis no disclosures.

Dr Domenico Plantone no disclosures.

Prof D 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 O 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 C 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 S Ourselin receives research support from the UCL/UCLH NIHR BRC, MRC, EPSRC and EU-FP7.

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