Early detection relationship of cerebral palsy markers using brain structure and general movements in infants born <32 weeks gestational age

Trends in brain MRI and CP association using deep learning

Cerebral palsy (CP) is a neurological disorder that dissipates body posture and impairs motor functions. It may lead to an intellectual disability and affect the quality of life. Early intervention is critical and challenging due to the uncooperative body movements of children, potential infant recovery, a lack of a single vision modality, and no specific contrast or slice-range selection and association. Early and timely CP identification and vulnerable brain MRI scan associations facilitate medications, supportive care, physical therapy, rehabilitation, and surgical interventions to alleviate symptoms and improve motor functions. The literature studies are limited in selecting appropriate contrast and utilizing contrastive coupling in CP investigation. After numerous experiments, we introduce deep learning models, namely SSeq-DL and SMS-DL, correspondingly trained on single-sequence and multiple brain MRIs. The introduced models are tailored with specialized attention mechanisms to learn susceptible brain trends associated with CP along the MRI slices, specialized parallel computing, and fusions at distinct network layer positions to significantly identify CP. The study successfully experimented with the appropriateness of single and coupled MRI scans, highlighting sensitive slices along the depth, model robustness, fusion of contrastive details at distinct levels, and capturing vulnerabilities. The findings of the SSeq-DL and SMSeq-DL models report lesion-vulnerable regions and covered slices trending in age range to assist radiologists in early rehabilitation.

A Simple MRI Score Predicts Pathological General Movements in Very Preterm Infants with Brain Injury-Retrospective Cohort Study

BACKGROUND/OBJECTIVES

Very preterm infants are at increased risk of brain injury and impaired brain development. The Total Abnormality Score and biometric parameters, such as biparietal width, interhemispheric distance and transcerebellar diameter, are simple measures to evaluate brain injury, development and growth using cerebral magnetic resonance imaging data at term-equivalent age. The aim of this study was to evaluate the association between the Total Abnormality Score and biometric parameters with general movements in very preterm infants with brain injury.

METHODS

This single-center retrospective cohort study included 70 very preterm infants (≤32 weeks' gestation and/or <1500 g birth weight) born between January 2017 and June 2021 in a level-three neonatal intensive care unit with brain injury-identified using cerebral magnetic resonance imaging data at term-equivalent age. General movements analysis was carried out at corrected age of 8-16 weeks. Binary logistic regression and Spearman correlation were used to examine the associations between the Total Abnormality Score and biometric parameters with general movements.

RESULTS

There was a significant association between the Total Abnormality Score and the absence of fidgety movements [OR: 1.19, 95% CI = 1.38-1.03] as well as a significant association between the transcerebellar diameter and fidgety movements (Spearman ρ = -0.269, p < 0.05).

CONCLUSIONS

Among very preterm infants with brain injury, the Total Abnormality Score can be used to predict the absence of fidgety movements and may be an easily accessible tool for identifying high-risk very preterm infants and planning early interventions accordingly.

The General Movement Optimality Score-Revised (GMOS-R) with Socioeconomically Stratified Percentile Ranks

Background: The general movement optimality score (GMOS) quantifies the details of general movements (GMs). We recently conducted psychometric analyses of the GMOS and developed a revised scoresheet. Consequently, the GMOS-Revised (GMOS-R) instrument necessitated validation using new percentile ranks. This study aimed to provide these percentile ranks for the GMOS-R and to investigate whether sex, preterm birth, or the infant's country of birth and residence affected the GMOS-R distribution. Methods: We applied the GMOS-R to an international sample of 1983 infants (32% female, 44% male, and 24% not disclosed), assessed in the extremely and very preterm period (10%), moderate (12%) and late (22%) preterm periods, at term (25%), and post-term age (31%). Data were grouped according to the World Bank's classification into lower- and upper-middle-income countries (LMICs and UMICs; 26%) or high-income countries (HICs; 74%), respectively. Results: We found that sex and preterm or term birth did not affect either GM classification or the GMOS-R, but the country of residence did. A lower median GMOS-R for infants with normal or poor-repertoire GMs from LMICs and UMICs compared with HICs suggests the use of specific percentile ranks for LMICs and UMICs vs. HICs. Conclusion: For clinical and scientific use, we provide a freely available GMOS-R scoring sheet, with percentile ranks reflecting socioeconomic stratification.

Predictive Value of Fidgety Movement Assessment and Magnetic Resonance Imaging for Cerebral Palsy in Infants

BACKGROUND

The early prediction of cerebral palsy (CP) could enable the follow-up of high-risk infants during the neuroplasticity period. This study aimed to explore the predictive value of fidgety movement assessment (FMA) and brain magnetic resonance imaging (MRI) for the development of CP in clinic rehabilitation setting.

METHODS

This retrospective observational study included infants who underwent FMA and brain MRI at age nine to 20 weeks at Children's Hospital, Zhejiang University School of Medicine, between March 2018 and September 2019. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy of FMA and MRI for predicting the development of CP were assessed.

RESULTS

A total of 258 infants (169 males, gestational age 37.4 ± 3.0 weeks, birth weight 2987.9 ± 757.1 g) were included. Fifteen children had CP after age two years. The diagnostic value of FMA and brain MRI combination showed 86.7% sensitivity (95% confidence interval [CI]: 58.4% to 97.7%), 98.4% specificity (95% CI: 95.6% to 99.5%), and 97.7% accuracy (95% CI: 95.0% to 99.1%); the combination diagnostic value also showed a significantly higher AUC for predicting CP after age two years than FMA alone (AUC: 0.981 vs 0.893, P = 0.013).

CONCLUSIONS

The diagnostic value of FMA and brain MRI combination during infancy showed a high predictive value for CP development in clinical rehabilitation setting.

Early markers of neurodevelopmental disorders based on general movements for very preterm infants: study protocol for a multicentre prospective cohort study in a clinical setting in China

INTRODUCTION

Very preterm (VPT) infants may experience varying degrees of neurodevelopmental challenges. Lack of early markers for neurodevelopmental disorders may delay referral to early interventions. The detailed General Movements Assessment (GMA) could help us to identify early markers for VPT infants at risk of atypical neurodevelopmental clinical phenotype in the very early stage of life as soon as possible. Preterm infants with high risk of atypical neurodevelopmental outcomes will have the best possible start to life if early precise intervention in critical developmental windows is allowed.

METHODS AND ANALYSIS

This is a nationwide, multicentric prospective cohort study that will recruit 577 infants born <32 weeks of age. This study will determine the diagnostic value of the developmental trajectory of general movements (GMs) at writhing and fidgety age with qualitative assessment for different atypical developmental outcomes at 2 years evaluated by the Griffiths Development Scales-Chinese. The difference in the General Movement Optimality Score (GMOS) will be used to distinguish normal (N), poor repertoire (PR) and cramped sychronised (CS) GMs. We plan to build the percentile rank of GMOS (median, 10th, 25th, 75th and 90th percentile rank) in N, PR and CS of each global GM category and analyse the relationship between GMOS in writhing movements and Motor Optimality Score (MOS) in fidgety movements based on the detailed GMA. We explore the subcategories of the GMOS list, and MOS list that may identify specific early markers that help us to identify and predict different clinical phenotypes and functional outcomes in VPT infants.

ETHICS AND DISSEMINATION

The central ethical approval has been confirmed from the Research Ethical Board of Children's Hospital of Fudan University (ref approval no. 2022(029)) and the local ethical approval has been also obtained by the corresponding ethics committees of the recruitment sites. Critical analysis of the study results will contribute to providing a basis for hierarchical management and precise intervention for preterm infants in very early life.

TRIAL REGISTRATION NUMBER

ChiCTR2200064521.

Predicting the brain age of children with cerebral palsy using a two-dimensional convolutional neural networks prediction model without gray and white matter segmentation

Background

Abnormal brain development is common in children with cerebral palsy (CP), but there are no recent reports on the actual brain age of children with CP.

Objective

Our objective is to use the brain age prediction model to explore the law of brain development in children with CP.

Methods

A two-dimensional convolutional neural networks brain age prediction model was designed without segmenting the white and gray matter. Training and testing brain age prediction model using magnetic resonance images of healthy people in a public database. The brain age of children with CP aged 5-27 years old was predicted.

Results

The training dataset mean absolute error (MAE) = 1.85, r = 0.99; test dataset MAE = 3.98, r = 0.95. The brain age gap estimation (BrainAGE) of the 5- to 27-year-old patients with CP was generally higher than that of healthy peers (p < 0.0001). The BrainAGE of male patients with CP was higher than that of female patients (p < 0.05). The BrainAGE of patients with bilateral spastic CP was higher than those with unilateral spastic CP (p < 0.05).

Conclusion

A two-dimensional convolutional neural networks brain age prediction model allows for brain age prediction using routine hospital T1-weighted head MRI without segmenting the white and gray matter of the brain. At the same time, these findings suggest that brain aging occurs in patients with CP after brain damage. Female patients with CP are more likely to return to their original brain development trajectory than male patients after brain injury. In patients with spastic CP, brain aging is more serious in those with bilateral cerebral hemisphere injury than in those with unilateral cerebral hemisphere injury.

Inter- and intra-observer reliability of the "Assessment of Motor Repertoire- 3 to 5 Months" based on video recordings of infants with Prader-Willi syndrome

Background

The “Assessment of Motor Repertoire—3 to 5 Months”, which is a part of Prechtl's General Movements Assessment (GMA), has been gradually applied to infants with genetic metabolic disorders. However, there have been no studies on the application of the GMA for infants with Prader-Willi syndrome (PWS).

Aims

The purpose of this study was to determine the inter- and intra-observer reliability of the assessment tool in a population of infants with PWS.

Study design

This was a reliability and agreement study.

Subjects

This was a cross-sectional study with15 infants with PWS born at an average gestational age of 38 weeks.

Outcome measures

Standardized video recordings of 15 infants with PWS (corrected ages of 3 to 5 months) were independently assessed by three observers. Kappa and ICC statistics were applied in inter- and intra- observer reliability analyses.

Results

The overall reliability ICC values of the “Motor Optimality Score” (MOS) ranged from 0.84 to 0.98, and the pairwise agreement ranged between 0.86 and 0.95 for inter- observe reliability. In addition, ICC values for the MOS ranged between 0.95 and 0.98 for tester agreement in intra-observer reliability.

Complete agreement reliability (100%) was achieved in the subcategories of “Fidgety Movements” and “Movement Character” for the inter- and intra-observer reliability. Moderate to high inter- and intra-observer reliability were found in the subcategories of “Repertoire of Co-Existent Other Movements”, “Quality of Other Movements” and “Posture”, with kappa values ranging between 0.63 and 1.00.

Conclusion

There were high levels of inter-and intra-observer agreement in the “Assessment of Motor Repertoire—3 to 5 Months” for infants with PWS. It is possible to carry out standardized quantitative assessments of the motor performance of infants with PWS.