Lars Adde

Early, Accurate Diagnosis and Early Intervention in Cerebral Palsy: Advances in Diagnosis and Treatment

Importance Cerebral palsy describes the most common physical disability in childhood and occurs in 1 in 500 live births. Historically, the diagnosis has been made between age 12 and 24 months but now can be made before 6 months’ corrected age. Objectives To systematically review best available evidence for early, accurate diagnosis of cerebral palsy and to summarize best available evidence about cerebral palsy–specific early intervention that should follow early diagnosis to optimize neuroplasticity and function. Evidence Review This study systematically searched the literature about early diagnosis of cerebral palsy in MEDLINE (1956-2016), EMBASE (1980-2016), CINAHL (1983-2016), and the Cochrane Library (1988-2016) and by hand searching. Search terms included cerebral palsy, diagnosis, detection, prediction, identification, predictive validity, accuracy, sensitivity, and specificity. The study included systematic reviews with or without meta-analyses, criteria of diagnostic accuracy, and evidence-based clinical guidelines. Findings are reported according to the PRISMA statement, and recommendations are reported according to the Appraisal of Guidelines, Research and Evaluation (AGREE) II instrument. Findings Six systematic reviews and 2 evidence-based clinical guidelines met inclusion criteria. All included articles had high methodological Quality Assessment of Diagnostic Accuracy Studies (QUADAS) ratings. In infants, clinical signs and symptoms of cerebral palsy emerge and evolve before age 2 years; therefore, a combination of standardized tools should be used to predict risk in conjunction with clinical history. Before 5 months’ corrected age, the most predictive tools for detecting risk are term-age magnetic resonance imaging (86%-89% sensitivity), the Prechtl Qualitative Assessment of General Movements (98% sensitivity), and the Hammersmith Infant Neurological Examination (90% sensitivity). After 5 months’ corrected age, the most predictive tools for detecting risk are magnetic resonance imaging (86%-89% sensitivity) (where safe and feasible), the Hammersmith Infant Neurological Examination (90% sensitivity), and the Developmental Assessment of Young Children (83% C index). Topography and severity of cerebral palsy are more difficult to ascertain in infancy, and magnetic resonance imaging and the Hammersmith Infant Neurological Examination may be helpful in assisting clinical decisions. In high-income countries, 2 in 3 individuals with cerebral palsy will walk, 3 in 4 will talk, and 1 in 2 will have normal intelligence. Conclusions and Relevance Early diagnosis begins with a medical history and involves using neuroimaging, standardized neurological, and standardized motor assessments that indicate congruent abnormal findings indicative of cerebral palsy. Clinicians should understand the importance of prompt referral to diagnostic-specific early intervention to optimize infant motor and cognitive plasticity, prevent secondary complications, and enhance caregiver well-being.

Early prediction of cerebral palsy by computer-based video analysis of general movements: a feasibility study

Aim  The aim of this study was to investigate the predictive value of a computer‐based video analysis of the development of cerebral palsy (CP) in young infants.

The relationship between trunk control in sitting and during gait in children and adolescents with cerebral palsy.

To assess the relationship between trunk control in sitting and trunk control during gait in children and adolescents with cerebral palsy (CP).

Reliability and validity of the Trunk Impairment Scale in children and adolescents with cerebral palsy

Standardized clinical tools are useful for treatment planning and evaluation, however clinical tools to assess quality in trunk movements in children with cerebral palsy (CP) are sparse. We have recently reported good intra- and inter-observer reliability of the Trunk Impairment Scale (TIS) in 5-12 year old children with CP. The aim of this study was to assess reliability in adolescents (13-19 years old), and to assess the construct validity in children and adolescents in the whole age spectrum from 5 to 19 years. Video recordings of 17 children with CP with Gross Motor Function Classification (GMFCS) level I-IV were analyzed by three observers on two occasions. For construct validity the TIS was compared with Gross Motor Function Measure (GMFM), in 37 children with GMFCS levels I-IV. Intraclass correlation coefficients varied between 0.82 and 0.98, and 86% of the kappa values varied between 0.61 and 1.00, suggesting high inter- and intra-observer reliability. The smallest detectable difference (SDD) of the TIS (scale range 0-23) varied between 2.55 and 3.82 for intra- and 4.07-8.23 for inter-observer observations. The high inter-observer SDD was partly due to consistently lower TIS scores by one observer. The correlation between the TIS total score and the dimension scores of the GMFM was high (Spearmans rho: 0.80-0.87), while decreasing GMFCS levels were associated with increasing total TIS score; both findings indicating good construct validity of the TIS. This study suggests that the TIS is a reliable and valid measure of trunk control for both children and adolescents with cerebral palsy.

Motion Segmentation with Weak Labeling Priors

Motions of organs or extremities are important features for clinical diagnosis. However, tracking and segmentation of complex, quickly changing motion patterns is challenging, certainly in the presence of occlusions. Neither state-of-the-art tracking nor motion segmentation approaches are able to deal with such cases. Thus far, motion capture systems or the like were needed which are complicated to handle and which impact on the movements. We propose a solution based on a single video camera, that is not only far less intrusive, but also a lot cheaper. The limitation of tracking and motion segmentation are overcome by a new approach to integrate prior knowledge in the form of weak labeling into motion segmentation. Using the example of Cerebral Palsy detection, we segment motion patterns of infants into the different body parts by analyzing body movements. Our experimental results show that our approach outperforms current motion segmentation and tracking approaches.

Gait characteristics in children and adolescents with cerebral palsy assessed with a trunk-worn accelerometer

This study aimed to investigate gait characteristics reflecting balance and progression in children and adolescents with cerebral palsy (CP) compared with typically developing (TD) children. Gait characteristics variables representing aspects of balance were trunk acceleration, interstride regularity and asymmetry of accelerations while gait characteristics representing progression were gait speed, cadence, step time and step length. Children in the age range 5-18 years (mean age 11.1 years) with spastic CP (n=41) and a gross motor function corresponding to GMFCS I-III and children with TD (n=29) were included. The children walked back and forth along a 5m pathway with a tri-axial accelerometer worn on the lower back to allow assessment of their gait characteristics. Data were recorded along the anterioposterior (AP), mediolateral (ML), and vertical (V) axes. To assess the magnitude of potential differences in gait characteristics, standard deviation scores were calculated, using TD children as reference. Gait parameters related to balance, such as AP, ML, and V accelerations, were higher in the children with CP (z-scores between 0.4 and 0.7) and increased with increasing GMFCS levels. The differences in accelerations in the AP and V directions increased between children with CP and TD children with increasing speed. Also asymmetry in trunk accelerations differed significantly between the two groups in all three directions (z-scores between 0.8 and 1.8 higher in the CP group), while interstride regularity differed only slightly between children with CP and TD children, and only in the AP direction. Gait characteristics also differed between children with the spastic subtypes unilateral and bilateral CP, for accelerations and asymmetry in the AP and ML directions. Our results showed significant differences in gait characteristics between children with CP and TD children. The differences may be more related to balance than progression, and these problems seem to rise with increasing gross motor impairment and speed.

Identification of fidgety movements and prediction of CP by the use of computer-based video analysis is more accurate when based on two video recordings

This study evaluates the role of postterm age at assessment and the use of one or two video recordings for the detection of fidgety movements (FMs) and prediction of cerebral palsy (CP) using computer vision software. Recordings between 9 and 17 weeks postterm age from 52 preterm and term infants (24 boys, 28 girls; 26 born preterm) were used. Recordings were analyzed using computer vision software. Movement variables, derived from differences between subsequent video frames, were used for quantitative analysis. Sensitivities, specificities, and area under curve were estimated for the first and second recording, or a mean of both. FMs were classified based on the Prechtl approach of general movement assessment. CP status was reported at 2 years. Nine children developed CP of whom all recordings had absent FMs. The mean variability of the centroid of motion (CSD) from two recordings was more accurate than using only one recording, and identified all children who were diagnosed with CP at 2 years. Age at assessment did not influence the detection of FMs or prediction of CP. The accuracy of computer vision techniques in identifying FMs and predicting CP based on two recordings should be confirmed in future studies.

ENIGMA - Enhanced interactive general movement assessment

General movement assessment is an accurate clinical method for predicting severe neurological dysfunctions such as cerebral palsy in young infants. Development of a computer-based diagnosis support system based on the General Movement Assessment method is dependent on features being effectively elicited from a General Movement expert. We present ENIGMA, a software tool for General Movement knowledge elicitation and modeling. Video and motion data were collected in 15 recordings containing both normal and abnormal general movements from the fidgety period of infant development. ENIGMA shows video in synchrony with different visualized features of recorded motion data. Movement patterns are modeled through an iterative and incremental process, where the General Movement expert is guiding the modeling process through comparing movement patterns observed in video with corresponding visual patterns observed in visualized features, and giving feedback to the knowledge engineer. Three visualized features were developed for exploring the so-called fidgety movements. The interactive work procedure introduced by ENIGMA enabled explicit motion features to be defined based on unconscious expert knowledge. Normal fidgety movements were found to be partly characterized by periodic patterns. Our results demonstrate that ENIGMA is a capable tool for General Movement expert knowledge elicitation. It facilitates the modeling process and provides a basis for detailed discussions. Clinical and technical concepts are communicated well through visual notions.

Video-based early cerebral palsy prediction using motion segmentation

Analysing distinct motion patterns that occur during infancy can be a way through early prediction of cerebral palsy. This analysis can only be performed by well-trained expert clinicians, and hence can not be widespread, specially in poor countries. In order to decrease the need for experts, computer-based methods can be applied. If individual motions of different body parts are available, these methods could achieve more accurate results with better clinical insight. Thus far, motion capture systems or the like were needed in order to provide such data. However, these systems not only need laboratory and experts to set up the experiment, but they could be intrusive for the infants motions. In this paper we build up our prediction method on a solution based on a single video camera, that is far less intrusive and a lot cheaper. First, the motions of different body parts are separated, then, motion features are extracted and used to classify infants to healthy or affected. Our experimental results show that visually obtained motion data allows cerebral palsy detection as accurate as state-of-the-art electromagnetic sensor data.

Relationship between white matter pathology and performance on the General Movement Assessment and the Test of Infant Motor Performance in very preterm infants

BACKGROUND Cerebral Magnetic Resonance Imaging, the General Movement Assessment, and the Test of Infant Motor Performance are all tools that can predict neurodevelopmental outcome in preterm infants. However, how these tests relate to each other is unclear. AIMS To examine the relationship between cerebral Magnetic Resonance Imaging measured at term age, and the General Movement Assessment and Test of Infant Motor Performance measured at 10-15 weeks post-term age. STUDY DESIGN Prospectively collected data in a sample of very preterm infants. SUBJECTS Fifty-three infants (23 female, 30 male) with a median gestational age of 28 weeks (range: 23-30 weeks) and a median birth weight of 1000 g (range: 515-1465 g). OUTCOME MEASURES Test of Infant Motor Performance, General Movement Assessment. RESULTS Infants with abnormal white matter were significantly more likely to have both abnormal general movements (p=0.01) and abnormal Test of Infant Motor Performance scores (p=0.001). Infants with abnormal general movements were significantly more likely to have lower Test of Infant Motor Performance Scores (p=0.01). CONCLUSIONS Abnormal white matter is related to motor deviations as measured by the General Movement Assessment and the Test of Infant Motor Performance as early as 3 months post-term age in a cohort of preterm infants.