Measuring Neuroplasticity Associated with Cerebral Palsy Rehabilitation: An MRI based Power Analysis

If they can measure neuroplasticity for CP we can demand our doctors measure it for stroke. How the hell do we even know neuroplasticity is working without something like this? The words used in here are way above my pay grade.
http://www.sciencedirect.com/science/article/pii/S0736574816303586

• Lee B. Reid^{a, b, 1, 2,} ,
• Alex M. Pagnozzi^{a, b, 1, 2,} ,
• Simona Fiori^{c, 3,} ,
• Roslyn N. Boyd^{b, 4,} ,
• Nicholas Dowson^{a, 2,} ,
• Stephen E. Rose^{a, ,}

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http://dx.doi.org/10.1016/j.ijdevneu.2017.01.010

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Highlights

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Power analysis for imaging-measures of neuroplasticity in cerebral palsy.

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Details enrolment numbers needed to detect changes in structural and diffusion MRI.

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A range of assumptions tested, including differences in treatment response.

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Recommendations made for studies with under 100 participants for improving power.

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Abstract

Researchers in the field of child neurology are increasingly looking to supplement clinical trials of motor rehabilitation with neuroimaging in order to better understand the relationship between behavioural training, brain changes, and clinical improvements. Randomised controlled trials are typically accompanied by sample size calculations to detect clinical improvements but, despite the large cost of neuroimaging, not equivalent calculations for concurrently acquired imaging neuroimaging measures of changes in response to intervention. To aid in this regard, a power analysis was conducted for two measures of brain changes that may be indexed in a trial of rehabilitative therapy for cerebral palsy: cortical thickness of the impaired primary sensorimotor cortex, and fractional anisotropy of the impaired, delineated corticospinal tract. Power for measuring fractional anisotropy was assessed for both region-of-interest-seeded and fMRI-seeded diffusion tractography. Taking into account practical limitations, as well as data loss due to behavioural and image-processing issues, estimated required participant numbers were 101, 128 and 59 for cortical thickness, region-of-interest-based tractography, and fMRI-seeded tractography, respectively. These numbers are not adjusted for study attrition. Although these participant numbers may be out of reach of many trials, several options are available to improve statistical power, including careful preparation of participants for scanning using mock simulators, careful consideration of image processing options, and enrolment of as homogeneous a cohort as possible. This work suggests that smaller and moderate sized studies give genuine consideration to harmonising scanning protocols between groups to allow the pooling of data.