Diagnostic accuracy of early magnetic resonance imaging to determine motor outcomes in infants born preterm: a systematic review and meta-analysis

Diagnostic accuracy of the Hammersmith Neonatal Neurological Examination in predicting motor outcome at 12 months for infants born very preterm

AIM

To evaluate the predictive validity of the Hammersmith Neonatal Neurological Examination (HNNE) performed early (at 32 weeks postmenstrual age) and at term-equivalent age (TEA) for 12-month motor outcomes in infants born very preterm.

METHOD

This was a diagnostic study using data from a prospective birth cohort. A total of 104 infants born preterm at less than 31 weeks gestational age (males n = 61; mean = 28 weeks 1 day [SD 1 week 6 days], range 23 weeks 1 day-30 weeks 6 days) underwent HNNE early and at TEA, which were scored by comparison with term data. Motor outcomes at 12 months corrected age were determined using the Bayley Scales of Infant and Toddler Development, Third Edition (scores ≤85). Cut-off points were determined using receiver operating characteristic curves.

RESULTS

Sixteen (15%) infants born preterm had motor impairment at 12 months corrected age. The HNNE total score cut-off points with the best combination of sensitivity and specificity at early and TEA assessments were 15.2 or lower (sensitivity 77%, 95% confidence interval [CI] = 46%-95%; specificity 74%, 95% CI = 63%-83%) and 23.5 or lower (sensitivity 67%, 95% CI = 38%-88%; specificity 66%, 95% CI = 54%-76%) respectively. The most predictive subscale at the early assessment was reflexes (sensitivity 86%, 95% CI = 57%-98%; specificity 62%, 95% CI = 51%-72%; cut-off point ≤3); at TEA, it was spontaneous movements (sensitivity 73%, 95% CI = 45%-92%; specificity 60%, 95% CI = 48%-70%; cut-off point ≤2).

INTERPRETATION

The HNNE provides moderate predictive accuracy for motor outcome at 12 months corrected age in infants born very preterm. Although modest at both time points, early assessment had stronger predictive ability for motor outcomes than TEA when scored using term data, highlighting the value of performing the HNNE earlier in the neonatal period. Performing HNNE earlier may assist risk stratification when planning follow-up services.

Predictors of Risk for Cerebral Palsy: A Review

PURPOSE

To identify the earliest predictors of risk for diagnosis of cerebral palsy (CP).

METHODS

A comprehensive literature search was conducted using various databases. The publications were reviewed to identify risk factors for CP from conception to early infancy. Studies were critically appraised with Joanna Briggs Institute guidelines for quality appraisal and evaluated for risk of bias using the Agency for Health Care Research and Quality guidelines.

RESULTS

The initial search yielded 129 studies and 20 studies were included. Forty-seven risk factors for CP were extracted of which several were duplicate terms. The significant risk factors found to be indicative of CP were low birth weight (<1500 g), birth at less than 28 weeks of gestational age, periventricular leukomalacia, grade 3 or 4 intraventricular hemorrhage, preeclampsia, prematurity, an Apgar score of less than 4 at the first minute, birth asphyxia, preterm premature rupture of membrane, and absent fidgety movements.

CONCLUSION

Twenty-three factors were consistently reported as predictors of CP.

Early brain morphometrics from neonatal MRI predict motor and cognitive outcomes at 2-years corrected age in very preterm infants

Infants born very preterm face a range of neurodevelopmental challenges in cognitive, language, behavioural and/or motor domains. Early accurate identification of those at risk of adverse neurodevelopmental outcomes, through clinical assessment and Magnetic Resonance Imaging (MRI), enables prognostication of outcomes and the initiation of targeted early interventions. This study utilises a prospective cohort of 181 infants born <31 weeks gestation, who had 3T MRIs acquired at 29-35 weeks postmenstrual age and a comprehensive neurodevelopmental evaluation at 2 years corrected age (CA). Cognitive, language and motor outcomes were assessed using the Bayley Scales of Infant and Toddler Development - Third Edition and functional motor outcomes using the Neuro-sensory Motor Developmental Assessment. By leveraging advanced structural MRI pre-processing steps to standardise the data, and the state-of-the-art developing Human Connectome Pipeline, early MRI biomarkers of neurodevelopmental outcomes were identified. Using Least Absolute Shrinkage and Selection Operator (LASSO) regression, significant associations between brain structure on early MRIs with 2-year outcomes were obtained (r = 0.51 and 0.48 for motor and cognitive outcomes respectively) on an independent 25% of the data. Additionally, important brain biomarkers from early MRIs were identified, including cortical grey matter volumes, as well as cortical thickness and sulcal depth across the entire cortex. Adverse outcome on the Bayley-III motor and cognitive composite scores were accurately predicted, with an Area Under the Curve of 0.86 for both scores. These associations between 2-year outcomes and patient prognosis and early neonatal MRI measures demonstrate the utility of imaging prior to term equivalent age for providing earlier commencement of targeted interventions for infants born preterm.

Neurological examination at 32-weeks postmenstrual age predicts 12-month cognitive outcomes in very preterm-born infants

BACKGROUND

To determine the diagnostic accuracy of Hammersmith Neonatal Neurological Examination (HNNE) at 30-32 weeks postmenstrual age (PMA, 'Early') and term equivalent age (TEA) in infants born <31 weeks PMA to predict cognitive outcomes at 12 months corrected age (CA).

METHODS

Prospective cohort study of 119 infants (73 males; median 28.4 weeks gestational age at birth) who underwent Early and TEA HNNE. At 12 months CA, 104 participants completed Bayley Scales of Infant and Toddler Development, 3rd Edition, (Bayley-III). Optimum cut-off points for each HNNE subscale were determined to establish diagnostic accuracy for predicting adverse cognitive outcomes on the Bayley-III Cognitive Composite Scale (≤85).

RESULTS

The best diagnostic accuracy for HNNE total score at 30-32 weeks PMA predicting cognitive impairment occurred at cut-off ≤16.7 (sensitivity (Se) = 71%, specificity (Sp) = 51%). The Abnormal Signs subscale demonstrated the best balance of sensitivity/specificity combination (Se = 71%, Sp = 71%; cut-off ≤1.5). For HNNE at TEA, the total score at cut-off ≤24.5 had Se = 71% and Sp = 47% for predicting cognitive impairment. The Tone Patterns subscale demonstrated the strongest diagnostic accuracy at TEA (Se = 71%, Sp = 63%; cut-off ≤3).

CONCLUSIONS

Early and TEA HNNE demonstrated moderate diagnostic accuracy for cognitive outcomes at 12-months CA in infants born <31 weeks gestational age.

CLINICAL TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry; Trial Registration Number: ACTRN12613000280707; web address of trial: http://www.ANZCTR.org.au/ACTRN12613000280707.aspx .

IMPACT

Early Hammersmith Neonatal Neurological Examination (HNNE) assessment at 30-32 weeks postmenstrual age has moderate diagnostic accuracy for cognitive outcomes at 12 months corrected age in infants born <31 weeks gestation. Early HNNE at 30-32 weeks has stronger predictive validity than HNNE at term equivalent age. Early HNNE may provide an early marker for risk-stratification to optimise the planning of post-discharge support and follow-up services for infants born preterm.

Neuroimaging at Term Equivalent Age: Is There Value for the Preterm Infant? A Narrative Summary

Advances in neuroimaging of the preterm infant have enhanced the ability to detect brain injury. This added information has been a blessing and a curse. Neuroimaging, particularly with magnetic resonance imaging, has provided greater insight into the patterns of injury and specific vulnerabilities. It has also provided a better understanding of the microscopic and functional impacts of subtle and significant injuries. While the ability to detect injury is important and irresistible, the evidence for how these injuries link to specific long-term outcomes is less clear. In addition, the impact on parents can be profound. This narrative summary will review the history and current state of brain imaging, focusing on magnetic resonance imaging in the preterm population and the current state of the evidence for how these patterns relate to long-term outcomes.

Early Diagnostics and Early Intervention in Neurodevelopmental Disorders-Age-Dependent Challenges and Opportunities

This review discusses early diagnostics and early intervention in developmental disorders in the light of brain development. The best instruments for early detection of cerebral palsy (CP) with or without intellectual disability are neonatal magnetic resonance imaging, general movements assessment at 2-4 months and from 2-4 months onwards, the Hammersmith Infant Neurological Examination and Standardized Infant NeuroDevelopmental Assessment. Early detection of autism spectrum disorders (ASD) is difficult; its first signs emerge at the end of the first year. Prediction with the Modified Checklist for Autism in Toddlers and Infant Toddler Checklist is possible to some extent and improves during the second year, especially in children at familial risk of ASD. Thus, prediction improves substantially when transient brain structures have been replaced by permanent circuitries. At around 3 months the cortical subplate has dissolved in primary motor and sensory cortices; around 12 months the cortical subplate in prefrontal and parieto-temporal cortices and cerebellar external granular layer have disappeared. This review stresses that families are pivotal in early intervention. It summarizes evidence on the effectiveness of early intervention in medically fragile neonates, infants at low to moderate risk, infants with or at high risk of CP and with or at high risk of ASD.

A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants

Survivors following very premature birth (i.e., ≤ 32 weeks gestational age) remain at high risk for neurodevelopmental impairments. Recent advances in deep learning techniques have made it possible to aid the early diagnosis and prognosis of neurodevelopmental deficits. Deep learning models typically require training on large datasets, and unfortunately, large neuroimaging datasets with clinical outcome annotations are typically limited, especially in neonates. Transfer learning represents an important step to solve the fundamental problem of insufficient training data in deep learning. In this work, we developed a multi-task, multi-stage deep transfer learning framework using the fusion of brain connectome and clinical data for early joint prediction of multiple abnormal neurodevelopmental (cognitive, language and motor) outcomes at 2 years corrected age in very preterm infants. The proposed framework maximizes the value of both available annotated and non-annotated data in model training by performing both supervised and unsupervised learning. We first pre-trained a deep neural network prototype in a supervised fashion using 884 older children and adult subjects, and then re-trained this prototype using 291 neonatal subjects without supervision. Finally, we fine-tuned and validated the pre-trained model using 33 preterm infants. Our proposed model identified very preterm infants at high-risk for cognitive, language, and motor deficits at 2 years corrected age with an area under the receiver operating characteristic curve of 0.86, 0.66 and 0.84, respectively. Employing such a deep learning model, once externally validated, may facilitate risk stratification at term-equivalent age for early identification of long-term neurodevelopmental deficits and targeted early interventions to improve clinical outcomes in very preterm infants.

Cerebral palsy after very preterm birth - an imaging perspective

Neonatal brain imaging undoubtedly can provide the most accurate information from which to determine whether cerebral palsy is likely to affect an individual infant born preterm. The sensitivity and specificity of that information is different between cranial ultrasound and MRI, depending on what approaches and sequences are used and the timing of the examinations. In this chapter we highlight the changing incidence of different patterns of brain injury in the preterm newborn and present a comparison of cranial ultrasound and MRI for predicting cerebral palsy in preterm infants affected by the commoner intracranial pathologies.

Prediction of childhood brain outcomes in infants born preterm using neonatal MRI and concurrent clinical biomarkers (PREBO-6): study protocol for a prospective cohort study

INTRODUCTION

Infants born very preterm are at risk of adverse neurodevelopmental outcomes, including cognitive deficits, motor impairments and cerebral palsy. Earlier identification enables targeted early interventions to be implemented with the aim of improving outcomes.

METHODS AND ANALYSIS

Protocol for 6-year follow-up of two cohorts of infants born <31 weeks gestational age (PPREMO: Prediction of Preterm Motor Outcomes; PREBO: Prediction of Preterm Brain Outcomes) and a small term-born reference sample in Brisbane, Australia. Both preterm cohorts underwent very early MRI and concurrent clinical assessment at 32 and 40 weeks postmenstrual age (PMA) and were followed up at 3, 12 and 24 months corrected age (CA). This study will perform MRI and electroencephalography (EEG). Primary outcomes include the Movement Assessment Battery for Children second edition and Full-Scale IQ score from the Wechsler Intelligence Scale for Children fifth edition (WISC-V). Secondary outcomes include the Gross Motor Function Classification System for children with cerebral palsy; executive function (Behavior Rating Inventory of Executive Function second edition, WISC-V Digit Span and Picture Span, Wisconsin Card Sorting Test 64 Card Version); attention (Test of Everyday Attention for Children second edition); language (Clinical Evaluation of Language Fundamentals fifth edition), academic achievement (Woodcock Johnson IV Tests of Achievement); mental health and quality of life (Development and Well-Being Assessment, Autism Spectrum Quotient-10 Items Child version and Child Health Utility-9D).

AIMS

Examine the ability of early neonatal MRI, EEG and concurrent clinical measures at 32 weeks PMA to predict motor, cognitive, language, academic achievement and mental health outcomes at 6 years CA.Determine if early brain abnormalities persist and are evident on brain MRI at 6 years CA and the relationship to EEG and concurrent motor, cognitive, language, academic achievement and mental health outcomes.

ETHICS AND DISSEMINATION

Ethical approval has been obtained from Human Research Ethics Committees at Children's Health Queensland (HREC/19/QCHQ/49800) and The University of Queensland (2019000426). Study findings will be presented at national and international conferences and published in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

ACTRN12619000155190p. WEB ADDRESS OF TRIAL: http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12619000155190p.

Predicting developmental outcomes in preterm infants: A simple white matter injury imaging rule

OBJECTIVE

To develop a simple imaging rule to predict neurodevelopmental outcomes at 4.5 years in a cohort of preterm neonates with white matter injury (WMI) based on lesion location and examine whether clinical variables enhance prediction.

METHODS

Sixty-eight preterm neonates born 24-32 weeks' gestation (median 27.7 weeks) were diagnosed with WMI on early brain MRI scans (median 32.3 weeks). 3D T1-weighted images of 60 neonates with 4.5-year outcomes were reformatted and aligned to the posterior commissure-eye plane and WMI was classified by location: anterior or posterior-only to the midventricle line on the reformatted axial plane. Adverse outcomes at 4.5 years were defined as Wechsler Preschool and Primary Scale of Intelligence full-scale IQ <85, cerebral palsy, or Movement Assessment Battery for Children, second edition percentile <5. The prediction of adverse outcome by WMI location, intraventricular hemorrhage (IVH), bronchopulmonary dysplasia (BPD), and retinopathy of prematurity (ROP) was assessed using multivariable logistic regression.

RESULTS

Six children had adverse cognitive outcomes and 17 had adverse motor outcomes. WMI location predicted cognitive outcomes in 90% (area under receiver operating characteristic curve [AUC] 0.80) and motor outcomes in 85% (AUC 0.75). Adding IVH, BPD, and ROP to the model enhances the predictive strength for cognitive and motor outcomes (AUC 0.83 and 0.88, respectively). Rule performance was confirmed in an independent cohort of children with WMI.

CONCLUSIONS

WMI on early MRI can be classified by location to predict preschool age outcomes in children born preterm. The predictive value of this WMI classification is enhanced by considering clinical factors apparent by term-equivalent age.

Animal models of developmental motor disorders: parallels to human motor dysfunction in cerebral palsy

Cerebral palsy (CP) is the most common motor disability in children. Much of the previous research on CP has focused on reducing the severity of brain injuries, whereas very few researchers have investigated the cause and amelioration of motor symptoms. This research focus has had an impact on the choice of animal models. Many of the commonly used animal models do not display a prominent CP-like motor phenotype. In general, rodent models show anatomically severe injuries in the central nervous system (CNS) in response to insults associated with CP, including hypoxia, ischemia, and neuroinflammation. Unfortunately, most rodent models do not display a prominent motor phenotype that includes the hallmarks of spasticity (muscle stiffness and hyperreflexia) and weakness. To study motor dysfunction related to developmental injuries, a larger animal model is needed, such as rabbit, pig, or nonhuman primate. In this work, we describe and compare various animal models of CP and their potential for translation to the human condition.

Early prediction of unilateral cerebral palsy in infants with asymmetric perinatal brain injury - Model development and internal validation

BACKGROUND

Early diagnosis of unilateral cerebral palsy is important after asymmetric perinatal brain injury (APBI). Our objective is to estimate the risk of unilateral cerebral palsy (UCP) in infants with APBI during the first months of life using neuroimaging and clinical assessment.

PATIENTS AND METHODS

Prognostic multivariable prediction modeling study including 52 infants (27 males), median gestational age 39.3 weeks with APBI from Sweden (n = 33) and the Netherlands (n = 19).

INCLUSION CRITERIA

(1) neonatal MRI within one month after term equivalent age (TEA), (2) Hand Assessment for Infants (HAI) between 3.5 and 4.5 months of (corrected) age. UCP was diagnosed ≥24 months of age. Firth regression with cross-validation was used to construct and internally validate the model to estimate the risk for UCP based on the predictors corticospinal tract (CST) and basal ganglia/thalamus (BGT) involvement, contralesional HAI Each hand sum score (EaHS), gestational age and sex.

RESULTS

UCP was diagnosed in 18 infants (35%). Infants who developed UCP more often had involvement of the CST and BGT on neonatal MRI and had lower contralesional HAI EaHS compared to those who did not develop UCP. The final model showed excellent accuracy for UCP prediction between 3.5 and 4.5 months (area under the curve, AUC = 0.980; 95% CI 0.95-1.00).

CONCLUSIONS

Combining neonatal MRI, the HAI, gestational age and sex accurately identify the prognostic risk of UCP at 3.5-4.5 months in infants with APBI.

The complex aetiology of cerebral palsy

Cerebral palsy (CP) is the most prevalent, severe and costly motor disability of childhood. Consequently, CP is a public health priority for prevention, but its aetiology has proved complex. In this Review, we summarize the evidence for a decline in the birth prevalence of CP in some high-income nations, describe the epidemiological evidence for risk factors, such as preterm delivery and fetal growth restriction, genetics, pregnancy infection and other exposures, and discuss the success achieved so far in prevention through the use of magnesium sulfate in preterm labour and therapeutic hypothermia for birth-asphyxiated infants. We also consider the complexities of disentangling prenatal and perinatal influences, and of establishing subtypes of the disorder, with a view to accelerating the translation of evidence into the development of strategies for the prevention of CP.