Apparent diffusion coefficient histogram analysis of neonatal hypoxic-ischemic encephalopathy

Amide proton transfer and apparent diffusion coefficient analysis reveal susceptibility of brain regions to neonatal hypoxic-ischemic encephalopathy

Purpose

To identify brain regions affected by Hypoxic-Ischemic Encephalopathy (HIE) in neonates using Amide Proton Transfer (APT) imaging and Apparent Diffusion Coefficient (ADC).

Materials and methods

Twenty neonates were divided into HIE and control groups. All neonates were undergoing MRI, including APT and DWI. Imaging analysis was performed using SPM12. The independent-samples t-test was used to analyze the difference in APTw values and ADC values between the mild HIE neonates and the control group. The receiver operating characteristic (ROC) curves were established to assess the diagnostic values of APTw and ADC values in different brain regions for HIE. Pearson's correlation analysis was used to analyze the correlation between APTw values and ADC values for each region.

Results

APTw values were significantly higher in 26 regions of the HIE group. ADC values were lower in the right anterior temporal lobe and higher in bilateral Subthalamic nucleus in HIE. The APTw values of 22 regions showed very high area under the curve (AUC), whereas the AUC of ADC values in right anterior temporal lobe and right subthalamic nucleus were both 0.802. Notably, the right anterior temporal lobe exhibited significant differences in both APTw and ADC values between the HIE and control groups, additionally, APTw value was significant positive correlated with ADC values in right anterior temporal lobe.

Conclusion

APTw and ADC are effective in detecting HIE, with APTw being more sensitive. The right anterior temporal lobe is particularly affected by HIE, with significant changes in APTw and ADC values and a positive correlation between them. This suggests that temporal lobe damage may be critical in the long-term neurological consequences of HIE.

Volumetric apparent diffusion coefficient histogram analysis in term neonatal asphyxia treated with hypothermia

OBJECTIVES

Our aim is to estimate the long-term neurological sequelae and prognosis in term neonatal asphyxia treated with hypothermia via volumetric apparent diffusion coefficient (ADC) map histogram analysis (HA).

METHODS

Brain MRI studies of 83 term neonates with asphyxia who received whole-body hypothermia treatment and examined between postnatal (PN) fourth and sixth days were retrospectively re-evaluated by 2 radiologists. Volumetric HA was performed for the areas frequently affected in deep and superficial asphyxia (thalamus, lentiform nucleus, posterior limb of internal capsule, corpus callosum forceps major, and perirolandic cortex-subcortical white matter) on ADC map. The quantitative ADC values were obtained separately for each region. Qualitative-visual (conventional) MRI findings were also re-evaluated. Neonates were examined neurodevelopmentally according to the Revised Brunet-Lezine scale. The distinguishability of long-term neurodevelopmental outcomes was statistically investigated.

RESULTS

With HA, the adverse neurodevelopmental outcomes could only be distinguished from mild-moderated impairment and normal development at the thalamus with 10th percentile ADC (P = .02 and P = .03, respectively) and ADCmin (P = .03 and P = .04, respectively). Also with the conventional MRI findings, adverse outcome could be distinguished from mild-moderated impairment (P = .04) and normal development (P = .04) via cytotoxic oedema of the thalamus, corpus striatum, and diffuse cerebral cortical.

CONCLUSION

The long-term adverse neurodevelopmental outcomes in newborns with asphyxia who received whole-body hypothermia treatment can be estimated similarly with volumetric ADC-HA and the conventional assessment of the ADC map.

ADVANCES IN KNOWLEDGE

This study compares early MRI ADC-HA with neurological sequelae in term newborns with asphyxia who received whole-body hypothermia treatment. We could not find any significant difference in predicting adverse neurological sequelae between the visual-qualitative evaluation of the ADC map and HA.

Microstructural Alterations in Projection and Association Fibers in Neonatal Hypoxia-Ischemia

BACKGROUND

Diffusion MRI (dMRI) is known to be sensitive to hypoxic-ischemic encephalopathy (HIE). However, existing dMRI studies used simple diffusion tensor metrics and focused only on a few selected cerebral regions, which cannot provide a comprehensive picture of microstructural injury.

PURPOSE

To systematically characterize the microstructural alterations in mild, moderate, and severe HIE neonates compared to healthy neonates with advanced dMRI using region of interest (ROI), tract, and fixel-based analyses.

STUDY TYPE

Prospective.

POPULATION

A total of 42 neonates (24 males and 18 females).

FIELD STRENGTH/SEQUENCE

3-T, diffusion-weighted echo-planar imaging.

ASSESSMENT

Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), fiber density (FD), fiber cross-section (FC), and fiber density and cross-section (FDC) were calculated in 40 ROIs and 6 tracts. Fixel-based analysis was performed to assess group differences in individual fiber components within a voxel (fixel).

STATISTICAL TESTS

One-way analysis of covariance (ANCOVA) to compare dMRI metrics among severe/moderate/mild HIE and control groups and general linear model for fixel-wise group differences (age, sex, and body weight as covariates). Adjusted P value < 0.05 was considered statistically significant.

RESULTS

For severe HIE, ROI-based analysis revealed widespread regions, including the deep nuclei and white matter with reduced FA, while in moderate injury, only FC was decreased around the posterior watershed zones. Tract-based analysis demonstrated significantly reduced FA, FD, and FC in the right inferior fronto-occipital fasciculus (IFOF), right inferior longitudinal fasciculus (ILF), and splenium of corpus callosum (SCC) in moderate HIE, and in right IFOF and left anterior thalamic radiation (ATR) in mild HIE. Correspondingly, we found altered fixels in the right middle-posterior IFOF and ILF, and in the central-to-right part of SCC in moderate HIE.

DATA CONCLUSION

For severe HIE, extensive microstructural injury was identified. For moderate-mild HIE, association fiber injury in posterior watershed area with a rightward lateralization was found.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 3.

Age-related topographic map of magnetic resonance diffusion metrics in neonatal brains

Accelerated maturation of brain parenchyma close to term-equivalent age leads to rapid changes in diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) metrics of neonatal brains, which can complicate the evaluation and interpretation of these scans. In this study, we characterized the topography of age-related evolution of diffusion metrics in neonatal brains. We included 565 neonates who had MRI between 0 and 3 months of age, with no structural or signal abnormality-including 162 who had DTI scans. We analyzed the age-related changes of apparent diffusion coefficient (ADC) values throughout brain and DTI metrics (fractional anisotropy [FA] and mean diffusivity [MD]) along white matter (WM) tracts. Rate of change in ADC, FA, and MD values across 5 mm cubic voxels was calculated. There was significant reduction of ADC and MD values and increase of FA with increasing gestational age (GA) throughout neonates' brain, with the highest temporal rates in subcortical WM, corticospinal tract, cerebellar WM, and vermis. GA at birth had significant effect on ADC values in convexity cortex and corpus callosum as well as FA/MD values in corpus callosum, after correcting for GA at scan. We developed online interactive atlases depicting age-specific normative values of ADC (ages 34-46 weeks), and FA/MD (35-41 weeks). Our results show a rapid decrease in diffusivity metrics of cerebral/cerebellar WM and vermis in the first few weeks of neonatal age, likely attributable to myelination. In addition, prematurity and low GA at birth may result in lasting delay in corpus callosum myelination and cerebral cortex cellularity.

Whole-volume ADC histogram of the brain as an image biomarker in evaluating disease severity of neonatal hypoxic-ischemic encephalopathy

Purpose

To examine the diagnostic significance of the apparent diffusion coefficient (ADC) histogram in quantifying neonatal hypoxic ischemic encephalopathy (HIE).

Methods

An analysis was conducted on the MRI data of 90 HIE patients, 49 in the moderate-to-severe group, and the other in the mild group. The 3D Slicer software was adopted to delineate the whole brain region as the region of interest, and 22 ADC histogram parameters were obtained. The interobserver consistency of the two radiologists was assessed by the interclass correlation coefficient (ICC). The difference in parameters (ICC > 0.80) between the two groups was compared by performing the independent sample t-test or the Mann–Whitney U test. In addition, an investigation was conducted on the correlation between parameters and the neonatal behavioral neurological assessment (NBNA) score. The ROC curve was adopted to assess the efficacy of the respective significant parameters. Furthermore, the binary logistic regression was employed to screen out the independent risk factors for determining the severity of HIE.

Results

The ADCmean, ADCmin, ADCmax,10th−70th, 90th percentile of ADC values of the moderate-to-severe group were smaller than those of the mild group, while the group's variance, skewness, kurtosis, heterogeneity, and mode-value were higher than those of the mild group (P < 0.05). All the mentioned parameters, the ADCmean, ADCmin, and 10th−70th and 90th percentile of ADC displayed positive correlations with the NBNA score, mode-value and ADCmax displayed no correlations with the NBNA score, the rest showed negative correlations with the NBNA score (P < 0.05). The area under the curve (AUC) of variance was the largest (AUC = 0.977; cut-off 972.5, sensitivity 95.1%; specificity 87.8%). According to the logistic regression analysis, skewness, kurtosis, variance, and heterogeneity were independent risk factors for determining the severity of HIE (OR > 1, P < 0.05).

Conclusions

The ADC histogram contributes to the HIE diagnosis and is capable of indicating the diffusion information of the brain objectively and quantitatively. It refers to a vital method for assessing the severity of HIE.

Machine Learning Models on ADC Features to Assess Brain Changes of Children With Pierre Robin Sequence

In order to evaluate brain changes in young children with Pierre Robin sequence (PRs) using machine learning based on apparent diffusion coefficient (ADC) features, we retrospectively enrolled a total of 60 cases (42 in the training dataset and 18 in the testing dataset) which included 30 PRs and 30 controls from the Children's Hospital Affiliated to the Nanjing Medical University from January 2017–December 2019. There were 21 and nine PRs cases in each dataset, with the remainder belonging to the control group in the same age range. A total of 105 ADC features were extracted from magnetic resonance imaging (MRI) data. Features were pruned using least absolute shrinkage and selection operator (LASSO) regression and seven ADC features were developed as the optimal signatures for training machine learning models. Support vector machine (SVM) achieved an area under the receiver operating characteristic curve (AUC) of 0.99 for the training set and 0.85 for the testing set. The AUC of the multivariable logistic regression (MLR) and the AdaBoost for the training and validation dataset were 0.98/0.84 and 0.94/0.69, respectively. Based on the ADC features, the two groups of cases (i.e., the PRs group and the control group) could be well-distinguished by the machine learning models, indicating that there is a significant difference in brain development between children with PRs and normal controls.

Multi-Slice Radiomic Analysis of Apparent Diffusion Coefficient Metrics Improves Evaluation of Brain Alterations in Neonates With Congenital Heart Diseases

Apparent diffusion coefficients (ADC) can provide phenotypic information of brain lesions, which can aid the diagnosis of brain alterations in neonates with congenital heart diseases (CHDs). However, the corresponding clinical significance of quantitative descriptors of brain tissue remains to be elucidated. By using ADC metrics and texture features, this study aimed to investigate the diagnostic value of single-slice and multi-slice measurements for assessing brain alterations in neonates with CHDs. ADC images were acquired from 60 neonates with echocardiographically confirmed non-cyanotic CHDs and 22 healthy controls (HCs) treated at Children's Hospital of Nanjing Medical University from 2012 to 2016. ADC metrics and texture features for both single and multiple slices of the whole brain were extracted and analyzed to the gestational age. The diagnostic performance of ADC metrics for CHDs was evaluated by using analysis of covariance and receiver operating characteristic. For both the CHD and HC groups, ADC metrics were inversely correlated with the gestational age in single and multi-slice measurements (P < 0.05). Histogram metrics were significant for identifying CHDs (P < 0.05), while textural features were insignificant. Multi-slice ADC (P < 0.01) exhibited greater diagnostic performance for CHDs than single-slice ADC (P < 0.05). These findings indicate that radiomic analysis based on ADC metrics can objectively provide more quantitative information regarding brain development in neonates with CHDs. ADC metrics for the whole brain may be more clinically significant in identifying atypical brain development in these patients. Of note, these results suggest that multi-slice ADC can achieve better diagnostic performance for CHD than single-slice.

Comparison of brain microstructure after prenatal spina bifida repair by either laparotomy-assisted fetoscopic or open approach

OBJECTIVE

To compare prenatal and postnatal brain microstructure between infants that underwent fetoscopic myelomeningocele (MMC) repair and those that had open-hysterotomy repair.

METHODS

This was a longitudinal retrospective cohort study of 57 fetuses that met the Management of Myelomeningocele Study (MOMS) trial criteria and underwent prenatal MMC repair, by a fetoscopic (n = 27) or open-hysterotomy (n = 30) approach, at 21.4-25.9 weeks' gestation. Fetoscopic repair was performed under CO₂ insufflation, according to our protocol. Diffusion-weighted magnetic resonance imaging (MRI) was performed before surgery in 30 cases (14 fetoscopic and 16 open), at 6 weeks postsurgery in 48 cases (24 fetoscopic and 24 open) and within the first year after birth in 23 infants (five fetoscopic and 18 open). Apparent diffusion coefficient (ADC) values from the basal ganglia, frontal, occipital and parietal lobes, mesencephalon and genu as well as splenium of the corpus callosum were calculated. ADC values at each of the three timepoints (presurgery, 6 weeks postsurgery and postnatally) and the percentage change in the ADC values between the timepoints were compared between the fetoscopic-repair and open-repair groups. ADC values at 6 weeks after surgery in the two prenatally repaired groups were compared with those in a control group of eight healthy fetuses that underwent MRI at a similar gestational age (GA). Comparison of ADC values was performed using the Student's t-test for independent samples (or Mann-Whitney U-test if non-normally distributed) and multivariate general linear model analysis, adjusting for GA or age at MRI and mean ventricular width.

RESULTS

There were no differences in GA at surgery or GA/postnatal age at MRI between the groups. No significant differences were observed in ADC values in any of the brain areas assessed between the open-repair and fetoscopic-repair groups at 6 weeks after surgery and in the first year after birth. No differences were detected in the ADC values of the studied areas between the control and prenatally repaired groups, except for significantly increased ADC values in the genu of the corpus callosum in the open-hysterotomy and fetoscopic-repair groups. Additionally, there were no differences between the two prenatally repaired groups in the percentage change in ADC values at any of the time intervals analyzed.

CONCLUSIONS

Fetoscopic MMC repair has no detectable effect on brain microstructure when compared to babies repaired using an open-hysterotomy technique. CO₂ insufflation of the uterine cavity during fetoscopy does not seem to have any isolated deleterious effects on fetal brain microstructure. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Predicting the nodal status in gastric cancers: The role of apparent diffusion coefficient histogram characteristic analysis

PURPOSE

To explore the application of histogram analysis in preoperative T and N staging of gastric cancers, with a focus on characteristic parameters of apparent diffusion coefficient (ADC) maps.

MATERIALS AND METHODS

Eighty-seven patients with gastric cancers underwent diffusion weighted magnetic resonance imaging (b=0, 1000s/mm²), which generated ADC maps. Whole-volume histogram analysis was performed on ADC maps and 7 characteristic parameters were obtained. All those patients underwent surgery and postoperative pathologic T and N stages were determined.

RESULTS

Four parameters, including skew, kurtosis, s-sD_av and sample number, showed significant differences among gastric cancers at different T and N stages. Most parameters correlated with T and N stages significantly and worked in differentiating gastric cancers at different T or N stages. Especially skew yielded a sensitivity of 0.758, a specificity of 0.810, and an area under the curve (AUC) of 0.802 for differentiating gastric cancers with and without lymph node metastasis (P<0.001). All the parameters, except AUC_low, showed good or excellent inter-observer agreement with intra-class correlation coefficients ranging from 0.710 to 0.991.

CONCLUSION

Characteristic parameters derived from whole-volume ADC histogram analysis could help assessing preoperative T and N stages of gastric cancers.

Apparent diffusion coefficient histogram shape analysis for monitoring early response in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy

Background

To explore the role of apparent diffusion coefficient (ADC) histogram shape related parameters in early assessment of treatment response during the concurrent chemo-radiotherapy (CCRT) course of advanced cervical cancers.

Methods

This prospective study was approved by the local ethics committee and informed consent was obtained from all patients. Thirty-two patients with advanced cervical squamous cell carcinomas underwent diffusion weighted magnetic resonance imaging (b values, 0 and 800 s/mm²) before CCRT, at the end of 2nd and 4th week during CCRT and immediately after CCRT completion. Whole lesion ADC histogram analysis generated several histogram shape related parameters including skewness, kurtosis, s-sD_av, width, standard deviation, as well as first-order entropy and second-order entropies. The averaged ADC histograms of 32 patients were generated to visually observe dynamic changes of the histogram shape following CCRT.

Results

All parameters except width and standard deviation showed significant changes during CCRT (all P < 0.05), and their variation trends fell into four different patterns. Skewness and kurtosis both showed high early decline rate (43.10 %, 48.29 %) at the end of 2nd week of CCRT. All entropies kept decreasing significantly since 2 weeks after CCRT initiated. The shape of averaged ADC histogram also changed obviously following CCRT.

Conclusions

ADC histogram shape analysis held the potential in monitoring early tumor response in patients with advanced cervical cancers undergoing CCRT.