Skip to main content
Log in

Entwicklungsneurologie – vernetzte Medizin und neue Perspektiven

Developmental neurology – networked medicine and new perspectives

  • Leitthema
  • Published:
Der Nervenarzt Aims and scope Submit manuscript

Zusammenfassung

Die Entwicklungsneurologie ist einer der großen Bereiche der Kinderneurologie. Sie hat u. a. die (gesetzliche) Aufgabe, mithilfe standardisierter Nachsorgeuntersuchungen die motorische, kognitive und psychosoziale Entwicklung von Frühgeborenen vor der 32. Schwangerschaftswoche (unter 1500 g Geburtsgewicht), ebenso aber auch aller anderen Risikokinder engmaschig und standardisiert zu begleiten. Abweichungen von der „normalen“ altersentsprechenden Entwicklung sollen durch eine frühestmögliche Diagnosestellung zu einer frühen Therapieeinleitung („early intervention“) führen und die Langzeitprognose der Patienten positiv beeinflussen. Die hierfür zu Verfügung stehenden Methoden mit Schwerpunkt auf aktuellen Neuentwicklungen werden beleuchtet. Mit einem Fokus auf Früherkennung wird besonders auf den prädiktiven Wert der „general movements“ (GMs) eingegangen. Dabei wird die fortschreitende Entwicklung der automatisierten, markerlosen Bewegungsanalyse beispielhalft an drei Patienten (gesund vs. genetisches Syndrom vs. Zerebralparese) im Alter von 12 Wochen mithilfe herkömmlicher Tiefenbildkameras veranschaulicht und diskutiert.

Abstract

Developmental neurology is one of the major areas of neuropediatrics and is among other things (legally) responsible for monitoring the motor, cognitive and psychosocial development of all infants using standardized monitoring investigations. The special focus is on infants born at risk and/or due to premature birth before 32 weeks of gestation or a birth weight less than 1500 g. Early diagnosis of deviations from normal, age-related development is a prerequisite for early interventions, which may positively influence development and the long-term biopsychosocial prognosis of the patients. This article illustrates the available methods in developmental neurology with a focus on recent developments. Particular attention is paid to the predictive value of general movements (GM). The current development of markerless automated detection of spontaneous movements using conventional depth imaging cameras is demonstrated. Differences in spontaneous movements in infants at the age of 12 weeks are illustrated and discussed exemplified by three patients (healthy versus genetic syndrome versus cerebral palsy).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Abb. 1
Abb. 2

Literatur

  1. Anderson PJ, Treyvaud K, Neil JJ et al (2017) Associations of newborn brain magnetic resonance imaging with long-term neurodevelopmental impairments in very preterm children. J Pediatr. https://doi.org/10.1016/j.jpeds.2017.04.059

    Google Scholar 

  2. Arnaud C, Daubisse-Marliac L, White-Koning M et al (2007) Prevalence and associated factors of minor neuromotor dysfunctions at age 5 years in prematurely born children: the EPIPAGE Study. Arch Pediatr Adolesc Med 161:1053–1061

    Article  PubMed  Google Scholar 

  3. Barrington KJ (2001) The adverse neuro-developmental effects of postnatal steroids in the preterm infant: a systematic review of RCTs. BMC Pediatr. https://doi.org/10.1186/1471-2431-1-1

    PubMed  PubMed Central  Google Scholar 

  4. Bennema AN, Schendelaar P, Seggers J et al (2016) Predictive value of general movements’ quality in low-risk infants for minor neurological dysfunction and behavioural problems at preschool age. Early Hum Dev 94:19–24

    Article  PubMed  Google Scholar 

  5. Bosanquet M, Copeland L, Ware R et al (2013) A systematic review of tests to predict cerebral palsy in young children. Dev Med Child Neurol 55:418–426

    Article  PubMed  Google Scholar 

  6. Bruggink JL, Einspieler C, Butcher PR et al (2008) The quality of the early motor repertoire in preterm infants predicts minor neurologic dysfunction at school age. J Pediatr 153:32–39

    Article  PubMed  Google Scholar 

  7. Cheong JL, Doyle LW, Burnett AC et al (2017) Association between moderate and late preterm birth and neurodevelopment and social-emotional development at age 2 years. JAMA Pediatr 171:e164805

    Article  PubMed  Google Scholar 

  8. Datta AN, Furrer MA, Bernhardt I et al (2017) Fidgety movements in infants born very preterm: predictive value for cerebral palsy in a clinical multicentre setting. Dev Med Child Neurol 59:618–624

    Article  PubMed  Google Scholar 

  9. Di Rosa G, Cavallaro T, Alibrandi A et al (2016) Predictive role of early milestones-related psychomotor profiles and long-term neurodevelopmental pitfalls in preterm infants. Early Hum Dev 101:49–55

    Article  PubMed  Google Scholar 

  10. Dobson KG, Ferro MA, Boyle MH et al (2017) Socioeconomic attainment of extremely low birth weight survivors: the role of early cognition. Pediatrics. https://doi.org/10.1542/peds.2016-2545

    PubMed  Google Scholar 

  11. Einspieler C, Prechtl HF (2005) Prechtl’s assessment of general movements: a diagnostic tool for the functional assessment of the young nervous system. Ment Retard Dev Disabil Res Rev 11:61–67

    Article  PubMed  Google Scholar 

  12. Glass HC, Costarino AT, Stayer SA et al (2015) Outcomes for extremely premature infants. Anesth Analg 120:1337–1351

    Article  PubMed  PubMed Central  Google Scholar 

  13. Hadders-Algra M (2004) General movements: a window for early identification of children at high risk for developmental disorders. J Pediatr 145:12–18

    Article  Google Scholar 

  14. Heinze F, Hesels K, Breitbach-Faller N et al (2010) Movement analysis by accelerometry of newborns and infants for the early detection of movement disorders due to infantile cerebral palsy. Med Biol Eng Comput 48:765–772

    Article  PubMed  Google Scholar 

  15. Hesse N, Schröder AS, Müller-Felber W et al (2017) Body pose estimation in depth images for infant motion analysis. EMBC 2017, 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Jeju Island, Korea, S 1909–1912

    Google Scholar 

  16. Hesse N, Hesse N, Schröder AS, Müller-Felber W et al (2017) Markerless motion analysis for early detection of infantile movement disorders. In: Eskola H, Väisänen O, Viik J, Hyttinen J (Hrsg) EMBEC NBC 2017 European Medical and Biological Engineering Confernce. Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, Tampere, Finland. IFMBE Proceedings, Bd. 65, S 197–200 https://doi.org/10.1007/978-981-10-5122-7_50

    Chapter  Google Scholar 

  17. Hesse N, Stachowiak G, Breuer T et al (2015) Estimating body pose of infants in depth images using random ferns. IEEE International Conference on Computer Vision Workshops (ICCVW), S 35–43

    Google Scholar 

  18. Himmelmann K, Hagberg G, Beckung E et al (2005) The changing panorama of cerebral palsy in Sweden. IX. Prevalence and origin in the birth-year period 1995–1998. Acta Paediatr 94:287–294

    Article  CAS  PubMed  Google Scholar 

  19. Karch D, Kang KS, Wochner K et al (2012) Kinematic assessment of stereotypy in spontaneous movements in infants. Gait Posture 36:307–311

    Article  PubMed  Google Scholar 

  20. Keller H, Haarwood R (2009) Culture and developmental pathways of relationship formation. In: Beckman S, Kasu-Koc A (Hrsg) Perspectives on human development, family, and culture. Cambridge University Press, Cambridge https://doi.org/10.1017/CBO9780511720437.013

    Google Scholar 

  21. Loh WY, Anderson PJ, Cheong JLY et al (2017) Neonatal basal ganglia and thalamic volumes: very preterm birth and 7‑year neurodevelopmental outcomes. Pediatr Res. https://doi.org/10.1038/pr.2017.161

    PubMed  Google Scholar 

  22. Michaelis R (2004) Das Grenzsteinprinzip als Orientierungshilfe für die pädiatrische Entwicklungsbeurteilung. In: Schlack HG (Hrsg) Entwicklungspädiatrie. Marseille, München

    Google Scholar 

  23. Moore T, Hennessy EM, Myles J et al (2012) Neurological and developmental outcome in extremely preterm children born in England in 1995 and 2006: the EPICure studies. BMJ 345:e7961. https://doi.org/10.1136/bmj.e7961

    Article  PubMed  PubMed Central  Google Scholar 

  24. Noble Y, Boyd R (2012) Neonatal assessments for the preterm infant up to 4 months corrected age: a systematic review. Dev Med Child Neurol 54:129–139

    Article  PubMed  Google Scholar 

  25. Novak I et al (2017) Early, accurate diagnosis and early intervention in cerebral palsy: advances in diagnosis and treatment. JAMA Pediatr. https://doi.org/10.1001/jamapediatrics.2017.1689

    PubMed  Google Scholar 

  26. O’meagher S, Kemp N, Norris K et al (2017) Risk factors for executive function difficulties in preschool and early school-age preterm children. Acta Paediatr. https://doi.org/10.1111/apa-13915

    PubMed  Google Scholar 

  27. Philippi H, Karch D, Kang KS et al (2014) Computer-based analysis of general movements reveals stereotypies predicting cerebral palsy. Dev Med Child Neurol 56:960–967

    Article  PubMed  Google Scholar 

  28. Prechtl HF, Einspieler C, Cioni G et al (1997) An early marker for neurological deficits after perinatal brain lesions. Lancet 349:1361–1363

    Article  CAS  PubMed  Google Scholar 

  29. Sellier E, Platt MJ, Andersen GL et al (2016) Decreasing prevalence in cerebral palsy: a multi-site European population-based study, 1980 to 2003. Dev Med Child Neurol 58:85–92

    Article  PubMed  Google Scholar 

  30. Spittle A, Orton J, Anderson PJ et al (2015) Early developmental intervention programmes provided post hospital discharge to prevent motor and cognitive impairment in preterm infants. Cochrane Database Syst Rev. https://doi.org/10.1002/14651858.CD005495.pub4

    PubMed  Google Scholar 

  31. Spittle AJ, Spencer-Smith MM, Cheong JL et al (2013) General movements in very preterm children and neurodevelopment at 2 and 4 years. Pediatrics 132(2):e452–e458

    Article  PubMed  Google Scholar 

  32. Van Iersel PA, Bakker SC, Jonker AJ et al (2016) Does general movements quality in term infants predict cerebral palsy and milder forms of limited mobility at 6 years? Dev Med Child Neurol 58:1310–1316

    Article  PubMed  Google Scholar 

  33. Vaucher YE, Peralta-Carcelen M, Finer NN et al (2012) Neurodevelopmental outcomes in the early CPAP and pulse oximetry trial. N Engl J Med 367:2495–2504

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to U. Tacke.

Ethics declarations

Interessenkonflikt

U. Tacke, H. Weigand-Brunnhölzl, A. Hilgendorff, R. M. Giese, A. W. Flemmer, H. König, B. Warken-Madelung, M. Arens, N. Hesse und A.S. Schroeder geben an, dass kein Interessenkonflikt besteht.

Dieser Beitrag beinhaltet keine von den Autoren durchgeführten Studien an Menschen oder Tieren.

Additional information

Dieser Artikel ist dem Nestor der Entwicklungsneurologie in Deutschland, Richard Michaelis aus Tübingen (1934–2017), gewidmet.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tacke, U., Weigand-Brunnhölzl, H., Hilgendorff, A. et al. Entwicklungsneurologie – vernetzte Medizin und neue Perspektiven. Nervenarzt 88, 1395–1401 (2017). https://doi.org/10.1007/s00115-017-0436-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00115-017-0436-6

Schlüsselwörter

Keywords

Navigation