Reliability of a novel, semi-quantitative scale for classification of structural brain magnetic resonance imaging in children with cerebral palsy

Developmental Medicine and Child Neurology

Volumn 56, Issue 9, 2014, Pages 839-845

  Fiori, Simona ^a   Cioni, Giovanni ^a,b   Klingels, Katrjin ^c   Ortibus, Els ^c   Van Gestel, Leen ^c   Rose, Stephen ^d   Boyd, Roslyn N ^e   Feys, Hilde ^c   Guzzetta, Andrea ^a,b  

^a DEPARTMENT OF DEVELOPMENTAL NEUROSCIENCE   (Italy)

^b UNIVERSITY OF PISA   (Italy)

^c UNIVERSITY OF LEUVEN   (Belgium)

^d ROYAL BRISBANE AND WOMEN'S HOSPITAL   (Australia)

^e UNIVERSITY OF QUEENSLAND   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ADOLESCENT; ARTICLE; BASAL GANGLION; BRAIN DAMAGE; BRAIN RADIOGRAPHY; BRAIN STEM; CEREBRAL PALSY; CHILD; CLINICAL ARTICLE; CORPUS CALLOSUM; DISEASE SEVERITY; FEMALE; GROSS MOTOR FUNCTION CLASSIFICATION SYSTEM; HEMISPHERE; HUMAN; IMAGE ANALYSIS; INTERRATER RELIABILITY; INTRARATER RELIABILITY; MALE; NUCLEAR MAGNETIC RESONANCE IMAGING; PRESCHOOL CHILD; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; SCHOOL CHILD; SCORING SYSTEM; TREATMENT RESPONSE;

ADOLESCENT; BRAIN; CEREBRAL PALSY; CHILD; CHILD, PRESCHOOL; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; REPRODUCIBILITY OF RESULTS; SEVERITY OF ILLNESS INDEX;

EID: 84905743130     PISSN: 00121622     EISSN: 14698749     Source Type: Journal    
DOI: 10.1111/dmcn.12457     Document Type: Article

References (22)

1. Ashwal S, Russman BS, Blasco PA, et al. Practice parameter: diagnostic assessment of the child with cerebral palsy: report of the Quality Standards Subcommittee of the American Academy of Neurology and the Practice Committee of the Child Neurology Society. Neurology 2004; 62: 851-63.
2. Bosquanot M, Copeland L, Boyd RN. A systematic review of tests to predict Cerebral Palsy in Young Children. Dev Med Child Neurol 2013; 55: 418-26.
3. Krägeloh-Mann I, Horber V. The role of magnetic resonance imaging in elucidating the pathogenesis of cerebral palsy: a systematic review. Dev Med Child Neurol 2007; 49: 144-51.
4. Robinson MN, Peake LJ, Ditchfield MR, Reid SM, Lanigan A, Reddihough DS. Magnetic resonance imaging findings in a population-based cohort of children with cerebral palsy. Dev Med Child Neurol 2009; 51: 39-45.
5. Korzeniewski SJ, Birbeck G, DeLano MC, Potchen MJ, Paneth N. A systematic review of neuroimaging for cerebral palsy. J Child Neurol 2008; 23: 216-27.
6. Feys H, Eyssen M, Jaspers E, et al. Relation between neuroradiological findings and upper limb function in hemiplegic cerebral palsy. Eur J Paediatr Neurol 2010; 14: 169-77.
7. Scheck SM, Boyd RN, Rose SE. New insights into the pathology of white matter tracts in cerebral palsy from diffusion magnetic resonance imaging: a systematic review. Dev Med Child Neurol 2012; 54: 684-96.
8. Damasio H, Damasio AR. Lesion Analysis in Neuropsychology. New York, NY: Oxford University Press, 1989.
9. Arnfield E, Guzzetta A, Boyd R. Relationship between brain structure on magnetic resonance imaging and motor outcomes in children with cerebral palsy: a systematic review. Res Dev Disabil 2013; 34: 2234-50.
10. Holmes CJ, Hoge R, Collins L, Woods R, Toga AW, Evans AC. Enhancement of MR images using registration for signal averaging. J Comput Assist Tomogr 1998; 22: 324-33.
11. Evans AC, Collins DL, Mills SR, Brown ED, Kelly RL, Peters TM. 3D statistical neuroanatomical models from 305 MRI volumes. Nuclear Science Symposium and Medical Imaging Conference. Proc IEEE 1993; 1813-7.
12. Mazziotta J, Toga A, Evans A, et al. A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). Philos Trans R Soc Lond B Biol Sci 2001; 356: 1293-322.
13. Talairach J, Tournoux P. Co-planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System: An Approach to Cerebral Imaging. New York, NY: Thieme Medical Publishers, 1988.
14. Palisano R, Rosenbaum P, Walter S, Russell D, Wood E, Galuppi B. Development and reliability of a system to classify gross motor function in children with cerebral palsy. Dev Med Child Neurol 1997; 39: 214-23.
15. Portney LG, Watkins MP. Foundations for of Clinical Research: Application to Practice, 3rd edn. Upper Saddle River, NJ: Pearson Prentice Hall, 2009.
16. Walter SD, Eliasziw M, Donner A. Sample size and optimal designs for reliability studies. Stat Med 1998; 17: 101-10.
17. de Vet HC, Terwee CB, Knol DL, Bouter LM. When to use agreement versus reliability measures. J Clin Epidemiol 2006; 59: 1033-9.
18. Katz JN, Larson MG, Phillips CB, Fossel AH, Liang MH. Comparing measurement sensitivity of short and longer health status instruments. Med Care 1992; 30: 917-25.
19. Landis RJ, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977; 86: 420-8.
20. Surveillance of Cerebral Palsy in Europe. Surveillance of cerebral palsy in Europe: a collaboration of cerebral palsy surveys and registers. Surveillance of Cerebral Palsy in Europe (SCPE). Dev Med Child Neurol 2000; 42: 816-24.
21. Parazzini C, Baldoli C, Scotti G, Triulzi F. Terminal zones of myelination: MR evaluation of children aged 20-40 months. AJNR Am J Neuroradiol 2002; 23: 1669-73.
22. Himmelmann K, Hagberg G, Uvebrant P. The changing panorama of cerebral palsy in Sweden. X. Prevalence and origin in the birth-year period 1999-2002. Acta Paediatr 2010; 99: 1337-43.