Kate Himmelmann1, Veronka Horber2, Javier De La Cruz3, Karen Horridge4, Vlatka Mejaski-Bosnjak5, Katalin Hollody6, Ingeborg Krägeloh-Mann7. 1. Department of Pediatrics, Institute of Clinical Sciences, Sahlgrenska Academy at the University of Gothenburg, Göteborg, Sweden. 2. Department of Child Neurology, University Children's Hospital Tübingen, Tübingen, Germany. 3. Biomedical Research Institute Imas12-Ciberesp, 12 Octubre University Hospital, Madrid, Spain. 4. City Hospitals Sunderland NHS Foundation Trust, Sunderland Royal Hospital, Sunderland, UK. 5. Department of Neuropediatrics, Children's Hospital Zagreb, School of Medicine, University of Zagreb, Zagreb, Croatia. 6. Department of Paediatrics, University of Pecs, Pecs, Hungary. 7. Department of Paediatric Neurology, University Children's Hospital Tübingen, Tübingen, Germany.
Abstract
AIM: To develop and evaluate a classification system for magnetic resonance imaging (MRI) findings of children with cerebral palsy (CP) that can be used in CP registers. METHOD: The classification system was based on pathogenic patterns occurring in different periods of brain development. The MRI classification system (MRICS) consists of five main groups: maldevelopments, predominant white matter injury, predominant grey matter injury, miscellaneous, and normal findings. A detailed manual for the descriptions of these patterns was developed, including test cases (www.scpenetwork.eu/en/my-scpe/rtm/neuroimaging/cp-neuroimaging/). A literature review was performed and MRICS was compared with other classification systems. An exercise was carried out to check applicability and interrater reliability. Professionals working with children with CP or in CP registers were invited to participate in the exercise and chose to classify either 18 MRIs or MRI reports of children with CP. RESULTS: Classification systems in the literature were compatible with MRICS and harmonization possible. Interrater reliability was found to be good overall (k=0.69; 0.54-0.82) among the 41 participants and very good (k=0.81; 0.74-0.92) using the classification based on imaging reports. INTERPRETATION: Surveillance of Cerebral Palsy in Europe (SCPE) proposes the MRICS as a reliable tool. Together with its manual it is simple to apply for CP registers.
AIM: To develop and evaluate a classification system for magnetic resonance imaging (MRI) findings of children with cerebral palsy (CP) that can be used in CP registers. METHOD: The classification system was based on pathogenic patterns occurring in different periods of brain development. The MRI classification system (MRICS) consists of five main groups: maldevelopments, predominant white matter injury, predominant grey matter injury, miscellaneous, and normal findings. A detailed manual for the descriptions of these patterns was developed, including test cases (www.scpenetwork.eu/en/my-scpe/rtm/neuroimaging/cp-neuroimaging/). A literature review was performed and MRICS was compared with other classification systems. An exercise was carried out to check applicability and interrater reliability. Professionals working with children with CP or in CP registers were invited to participate in the exercise and chose to classify either 18 MRIs or MRI reports of children with CP. RESULTS: Classification systems in the literature were compatible with MRICS and harmonization possible. Interrater reliability was found to be good overall (k=0.69; 0.54-0.82) among the 41 participants and very good (k=0.81; 0.74-0.92) using the classification based on imaging reports. INTERPRETATION: Surveillance of Cerebral Palsy in Europe (SCPE) proposes the MRICS as a reliable tool. Together with its manual it is simple to apply for CP registers.
Authors: Grace McIlvain; James B Tracy; Charlotte A Chaze; Drew A Petersen; Gabrielle M Villermaux; Henry G Wright; Freeman Miller; Jeremy R Crenshaw; Curtis L Johnson Journal: J Child Neurol Date: 2020-03-23 Impact factor: 1.987
Authors: Catherine Arnaud; Virginie Ehlinger; Malika Delobel-Ayoub; Dana Klapouszczak; Oliver Perra; Owen Hensey; David Neubauer; Katalin Hollódy; Daniel Virella; Gija Rackauskaite; Andra Greitane; Kate Himmelmann; Els Ortibus; Ivana Dakovic; Guro L Andersen; Antigone Papavasiliou; Elodie Sellier; Mary Jane Platt; Inge Krägeloh-Mann Journal: Front Neurol Date: 2021-05-20 Impact factor: 4.003