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Generalised boundary shift integral for longitudinal assessment of spinal cord atrophy.
Prados, Ferran; Moccia, Marcello; Johnson, Aubrey; Yiannakas, Marios; Grussu, Francesco; Cardoso, Manuel Jorge; Ciccarelli, Olga; Ourselin, Sebastien; Barkhof, Frederik; Wheeler-Kingshott, Claudia.
Afiliação
  • Prados F; Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, 90 High Holborn, London, WC1V 6LJ, UK; NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Science
  • Moccia M; NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, Russell Square, London, WC1B 5EH, UK; Multiple Sclerosis Clinical Care and Research Centre, Department of Neurosciences, Federico
  • Johnson A; Smith College, Northampton, MA, USA.
  • Yiannakas M; NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, Russell Square, London, WC1B 5EH, UK.
  • Grussu F; NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, Russell Square, London, WC1B 5EH, UK; Centre for Medical Image Computing (CMIC), Department of Computer Science, University Colle
  • Cardoso MJ; Department of Biomedical Engineering & Imaging Sciences, King's College London, UK.
  • Ciccarelli O; NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, Russell Square, London, WC1B 5EH, UK.
  • Ourselin S; Department of Biomedical Engineering & Imaging Sciences, King's College London, UK.
  • Barkhof F; Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, 90 High Holborn, London, WC1V 6LJ, UK; NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Science
  • Wheeler-Kingshott C; NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, Russell Square, London, WC1B 5EH, UK; Brain MRI 3T , UKCenter, IRCCS Mondino Foundation, Pavia, Italy; Department of Brain and Be
Neuroimage ; 209: 116489, 2020 04 01.
Article em En | MEDLINE | ID: mdl-31877375
ABSTRACT
Spinal cord atrophy measurements obtained from structural magnetic resonance imaging (MRI) are associated with disability in many neurological diseases and serve as in vivo biomarkers of neurodegeneration. Longitudinal spinal cord atrophy rate is commonly determined from the numerical difference between two volumes (based on 3D surface fitting) or two cross-sectional areas (CSA, based on 2D edge detection) obtained at different time-points. Being an indirect measure, atrophy rates are susceptible to variable segmentation errors at the edge of the spinal cord. To overcome those limitations, we developed a new registration-based pipeline that measures atrophy rates directly. We based our approach on the generalised boundary shift integral (GBSI) method, which registers 2 scans and uses a probabilistic XOR mask over the edge of the spinal cord, thereby measuring atrophy more accurately than segmentation-based techniques. Using a large cohort of longitudinal spinal cord images (610 subjects with multiple sclerosis from a multi-centre trial and 52 healthy controls), we demonstrated that GBSI is a sensitive, quantitative and objective measure of longitudinal spinal cord volume change. The GBSI pipeline is repeatable, reproducible, and provides more precise measurements of longitudinal spinal cord atrophy than segmentation-based methods in longitudinal spinal cord atrophy studies.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Medula Espinal / Imageamento por Ressonância Magnética / Interpretação de Imagem Assistida por Computador / Progressão da Doença / Neuroimagem / Esclerose Múltipla Tipo de estudo: Clinical_trials / Observational_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Medula Espinal / Imageamento por Ressonância Magnética / Interpretação de Imagem Assistida por Computador / Progressão da Doença / Neuroimagem / Esclerose Múltipla Tipo de estudo: Clinical_trials / Observational_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male Idioma: En Ano de publicação: 2020 Tipo de documento: Article