Roland Opfer1,2, Ann-Christin Ostwaldt3, Christine Walker-Egger4, Praveena Manogaran4,5, Maria Pia Sormani6, Nicola De Stefano7, Sven Schippling4. 1. Neuroimmunology and Multiple Sclerosis Research, Department of Neurology, University Hospital Zurich and University of Zurich, Zurich, Switzerland. roland.opfer@jung-diagnostics.de. 2. Jung Diagnostics GmbH, Hamburg, Germany. roland.opfer@jung-diagnostics.de. 3. Jung Diagnostics GmbH, Hamburg, Germany. 4. Neuroimmunology and Multiple Sclerosis Research, Department of Neurology, University Hospital Zurich and University of Zurich, Zurich, Switzerland. 5. Department of Information Technology and Electrical Engineering, Swiss Federal Institute of Technology, Zurich, Switzerland. 6. Biostatistics Unit, Department of Health Sciences, University of Genoa, Genoa, Italy. 7. Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy.
Abstract
BACKGROUND: Measurements of brain volume loss (BVL) in individual patients are currently discussed controversially. One concern is the impact of short-term biological noise, like hydration status. METHODS: Three publicly available reliability MRI datasets with scan intervals of days to weeks were used. An additional cohort of 60 early relapsing multiple sclerosis (MS) patients with MRI follow-ups was analyzed to test whether after 1 year pathological BVL is detectable in a relevant fraction of MS patients. BVL was determined using SIENA/FSL. Results deviating from zero in the reliability datasets were considered as within-patient fluctuation (WPF) consisting of the intrinsic measurement error as well as the short-term biological fluctuations of brain volumes. We provide an approach to interpret BVL measurements in individual patients taking the WPF into account. RESULTS: The estimated standard deviation of BVL measurements from the pooled reliability datasets was 0.28%. For a BVL measurement of x% per year in an individual patient, the true BVL lies with an error probability of 5% in the interval x% ± (1.96 × 0.28)/(scan interval in years)%. To allow a BVL per year of at least 0.4% to be identified after 1 year, the measured BVL needs to exceed 0.94%. The median BVL per year in the MS patient cohort was 0.44%. In 11 out of 60 MS patients (18%) we found a BVL per year equal or greater than 0.94%. CONCLUSION: The estimated WPF may be helpful when interpreting BVL results on an individual patient level in diseases such as MS.
BACKGROUND: Measurements of brain volume loss (BVL) in individual patients are currently discussed controversially. One concern is the impact of short-term biological noise, like hydration status. METHODS: Three publicly available reliability MRI datasets with scan intervals of days to weeks were used. An additional cohort of 60 early relapsing multiple sclerosis (MS) patients with MRI follow-ups was analyzed to test whether after 1 year pathological BVL is detectable in a relevant fraction of MSpatients. BVL was determined using SIENA/FSL. Results deviating from zero in the reliability datasets were considered as within-patient fluctuation (WPF) consisting of the intrinsic measurement error as well as the short-term biological fluctuations of brain volumes. We provide an approach to interpret BVL measurements in individual patients taking the WPF into account. RESULTS: The estimated standard deviation of BVL measurements from the pooled reliability datasets was 0.28%. For a BVL measurement of x% per year in an individual patient, the true BVL lies with an error probability of 5% in the interval x% ± (1.96 × 0.28)/(scan interval in years)%. To allow a BVL per year of at least 0.4% to be identified after 1 year, the measured BVL needs to exceed 0.94%. The median BVL per year in the MSpatient cohort was 0.44%. In 11 out of 60 MSpatients (18%) we found a BVL per year equal or greater than 0.94%. CONCLUSION: The estimated WPF may be helpful when interpreting BVL results on an individual patient level in diseases such as MS.
Entities:
Keywords:
Brain atrophy; MRI; Multiple sclerosis; Reliability; SIENA
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