Stochastic process for white matter injury detection in preterm neonates

Development and Validation of a Dynamic Nomogram to Predict the Risk of Neonatal White Matter Damage

Purpose

White matter damage (WMD) was defined as the appearance of rough and uneven echo enhancement in the white matter around the ventricle. The aim of this study was to develop and validate a risk prediction model for neonatal WMD.

Materials and Methods

We collected data for 1,733 infants hospitalized at the Department of Neonatology at The First Affiliated Hospital of Zhengzhou University from 2017 to 2020. Infants were randomly assigned to training (n = 1,216) or validation (n = 517) cohorts at a ratio of 7:3. Multivariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to establish a risk prediction model and web-based risk calculator based on the training cohort data. The predictive accuracy of the model was verified in the validation cohort.

Results

We identified four variables as independent risk factors for brain WMD in neonates by multivariate logistic regression and LASSO analysis, including gestational age, fetal distress, prelabor rupture of membranes, and use of corticosteroids. These were used to establish a risk prediction nomogram and web-based calculator (https://caowenjun.shinyapps.io/dynnomapp/). The C-index of the training and validation sets was 0.898 (95% confidence interval: 0.8745-0.9215) and 0.887 (95% confidence interval: 0.8478-0.9262), respectively. Decision tree analysis showed that the model was highly effective in the threshold range of 1-61%. The sensitivity and specificity of the model were 82.5 and 81.7%, respectively, and the cutoff value was 0.099.

Conclusion

This is the first study describing the use of a nomogram and web-based calculator to predict the risk of WMD in neonates. The web-based calculator increases the applicability of the predictive model and is a convenient tool for doctors at primary hospitals and outpatient clinics, family doctors, and even parents to identify high-risk births early on and implementing appropriate interventions while avoiding excessive treatment of low-risk patients.

Can you see what I see? Assessing brain maturation and injury in preterm and term neonates

This scientific commentary refers to ‘Modelling brain development to detect white matter injury in term and preterm born neonates’ by O’Muircheartaigh et al. (doi: 10.1093/brain/awz412).

Quantitative Analysis of Punctate White Matter Lesions in Neonates Using Quantitative Susceptibility Mapping and R2* Relaxation

BACKGROUND AND PURPOSE

It is difficult to distinguish punctate white matter lesions from focal hemorrhagic lesions in neonates on conventional MR imaging because both kinds of lesions show increased signal intensity on T1-weighted images and, frequently, decreased signal intensity on T2-weighted images. Our aim was to distinguish punctate white matter lesions and focal hemorrhagic lesions using quantitative measures.

MATERIALS AND METHODS

In the current study, we acquired multiecho gradient recalled-echo MR imaging data from 24 neonates with hypoxic-ischemic encephalopathy and postprocessed them as R2* relaxation maps and quantitative susceptibility maps. Seven subjects who were found to have multifocal punctate white matter lesions and/or focal hemorrhagic lesions on R2* maps were included (mean gestational age at birth, 33 ± 4.28 weeks; mean gestational age at scanning, 38 ± 2 weeks). Manually drawing ROIs on R2* maps, we measured R2* and magnetic susceptibility values of the lesions, along with white matter regions within the corpus callosum as healthy comparison tissue.

RESULTS

R2* and magnetic susceptibility values were both found to easily distinguish punctate white matter lesions, focal hemorrhagic lesions, and healthy white matter tissue from each other (P < .05), with a large Hedge g. R2* and magnetic susceptibility values were significantly increased in focal hemorrhagic lesions compared with punctate white matter lesions and healthy white matter tissue. Punctate white matter lesions were also found to have significantly increased values over healthy white matter tissue.

CONCLUSIONS

R2* and quantitative susceptibility maps can be used to help clinicians distinguish and measure focal hemorrhages, punctate white matter lesions, and healthy white matter tissue.

A fast segmentation-free fully automated approach to white matter injury detection in preterm infants

White matter injury (WMI) is the most prevalent brain injury in the preterm neonate leading to developmental deficits. However, detecting WMI in magnetic resonance (MR) images of preterm neonate brains using traditional WM segmentation-based methods is difficult mainly due to lack of reliable preterm neonate brain atlases to guide segmentation. Hence, we propose a segmentation-free, fast, unsupervised, atlas-free WMI detection method. We detect the ventricles as blobs using a fast linear maximally stable extremal regions algorithm. A reference contour equidistant from the blobs and the brain-background boundary is used to identify tissue adjacent to the blobs. Assuming normal distribution of the gray-value intensity of this tissue, the outlier intensities in the entire brain region are identified as potential WMI candidates. Thereafter, false positives are discriminated using appropriate heuristics. Experiments using an expert-annotated dataset show that the proposed method runs 20 times faster than our earlier work which relied on time-consuming segmentation of the WM region, without compromising WMI detection accuracy. Graphical Abstract Key Steps of Segmentation-free WMI Detection.

Effect of T helper cell 1/T helper cell 2 balance and nuclear factor-κB on white matter injury in premature neonates

Incidence of white matter injury (WMI), which is featured as softening of white matter tissues, has recently increased. Previous studies have demonstrated a close correlation between T helper cell 1 and T helper cell 2 (Th1/Th2) imbalance and nuclear factor‑κB (NF‑κB) with brain disease. Their role in premature WMI, however, remains to be illustrated. Serum samples were collected from 60 premature WMI neonates, plus another control group of 60 premature babies without WMI. Patients were further divided into mild, moderate and severe WMI groups. Reverse transcription quantitative polymerase chain reaction was used to test mRNA expression levels of Th1/Th2 cytokines, including interleukin 2 (IL)‑2, tumor necrosis factor‑α (TNF‑α), IL‑4, IL‑10 and nuclear factor (NF)‑κB, whilst their serum levels were measured by ELISA. Their correlation with disease occurrence and progression were further analysed, to illustrate the effect of Th1/Th2 balance and NF‑κB on pathology of premature WMI. Serum levels of IL‑4 and IL‑10 were significantly decreased in premature WMI babies, whilst IL‑2, TNF‑α and NF‑κB were upregulated (P<0.05 vs. control group). With aggravated disease, IL‑4 and IL‑10 expression was further decreased while IL‑2, TNF‑α and NF‑κB were increased (P<0.05 vs. mild WMI group). Th1 cytokines IL‑2 and TNF‑α and NF‑κB were negatively correlated with Th2 cytokines IL‑4 and IL‑10. Disease severity was positively correlated with IL‑2, TNF‑α and NF‑κB expression, and was negatively correlated with IL‑4 and IL‑10 (P<0.05). Th1/Th2 imbalance and NF‑κB upregulation were observed in WMI pathogenesis, with elevated secretion of Th1 cytokines and decreased Th2 cytokines, suggesting that Th1/Th2 imbalance and NF‑κB upregulation may be a potential indicator for the early diagnosis and treatment of WMI pathogenesis and progression.

Harnessing Neuroimaging Capability in Pediatric Stroke: Proceedings of the Stroke Imaging Laboratory for Children Workshop

On June 5, 2015 the International Pediatric Stroke Study and the Stroke Imaging Laboratory for Children cohosted a unique workshop focused on developing neuroimaging research in pediatric stroke. Pediatric neurologists, neuroradiologists, interventional neuroradiologists, physicists, nurse practitioners, neuropsychologists, and imaging research scientists from around the world attended this one-day meeting. Our objectives were to (1) establish a group of experts to collaborate in advancing pediatric neuroimaging for stroke, (2) develop consensus clinical and research magnetic resonance imaging protocols for pediatric stroke patients, and (3) develop imaging-based research strategies in pediatric ischemic stroke. This article provides a summary of the meeting proceedings focusing on identified challenges and solutions and outcomes from the meeting. Further details on the workshop contents and outcomes are provided in three additional articles in the current issue of Pediatric Neurology.