MR imaging and outcome in neonatal HIBD models are correlated with sex: the value of diffusion tensor MR imaging and diffusion kurtosis MR imaging

ObjectiveHypoxic-ischemic encephalopathy can lead to lifelong morbidity and premature death in full-term newborns. Here, we aimed to determine the efficacy of diffusion kurtosis (DK) [mean kurtosis (MK)] and diffusion tensor (DT) [fractional anisotropy (FA), mean diffusion (MD), axial diffusion (AD), and radial diffusion (RD)] parameters for the early diagnosis of early brain histopathological changes and the prediction of neurodegenerative events in a full-term neonatal hypoxic-ischemic brain injury (HIBD) rat model.MethodsThe HIBD model was generated in postnatal day 7 Sprague-Dawley rats to assess the changes in DK and DT parameters in 10 specific brain structural regions involving the gray matter, white matter, and limbic system during acute (12 h) and subacute (3 d and 5 d) phases after hypoxic ischemia (HI), which were validated against histology. Sensory and cognitive parameters were assessed by the open field, novel object recognition, elevated plus maze, and CatWalk tests.ResultsRepeated-measures ANOVA revealed that specific brain structures showed similar trends to the lesion, and the temporal pattern of MK was substantially more varied than DT parameters, particularly in the deep gray matter. The change rate of MK in the acute phase (12 h) was significantly higher than that of DT parameters. We noted a delayed pseudo-normalization for MK. Additionally, MD, AD, and RD showed more pronounced differences between males and females after HI compared to MK, which was confirmed in behavioral tests. HI females exhibited anxiolytic hyperactivity-like baseline behavior, while the memory ability of HI males was affected in the novel object recognition test. CatWalk assessments revealed chronic deficits in limb gait parameters, particularly the left front paw and right hind paw, as well as poorer performance in HI males than HI females.ConclusionsOur results suggested that DK and DT parameters were complementary in the immature brain and provided great value in assessing early tissue microstructural changes and predicting long-term neurobehavioral deficits, highlighting their ability to detect both acute and long-term changes. Thus, the various diffusion coefficient parameters estimated by the DKI model are powerful tools for early HIBD diagnosis and prognosis assessment, thus providing an experimental and theoretical basis for clinical treatment

Application of TBSS-based machine learning models in the diagnosis of pediatric autism

ObjectiveTo explore the microstructural changes of white matter in children with pediatric autism by using diffusion kurtosis imaging (DKI), and evaluate whether the combination of tract-based spatial statistics (TBSS) and back-propagation neural network (BPNN)/support vector machine (SVM)/logistic regression (LR) was feasible for the classification of pediatric autism.MethodsDKI data were retrospectively collected from 32 children with autism and 27 healthy controls (HCs). Kurtosis fractional anisotropy (FAK), mean kurtosis (MK), axial kurtosis (KA), radial kurtosis (RK), fractional anisotropy (FA), axial diffusivity (DA), mean diffusivity (MD) and Radial diffusivity (DR) were generated by iQuant workstation. TBSS was used to detect the regions of parameters values abnormalities and for the comparison between these two groups. In addition, we also introduced the lateralization indices (LI) to study brain lateralization in children with pediatric autism, using TBSS for additional analysis. The parameters values of the differentiated regions from TBSS were then calculated for each participant and used as the features in SVM/BPNN/LR. All models were trained and tested with leave-one-out cross validation (LOOCV).ResultsCompared to the HCs group, the FAK, DA, and KA values of multi-fibers [such as the bilateral superior longitudinal fasciculus (SLF), corticospinal tract (CST) and anterior thalamic radiation (ATR)] were lower in pediatric autism group (p < 0.05, TFCE corrected). And we also found DA lateralization abnormality in Superior longitudinal fasciculus (SLF) (the LI in HCs group was higher than that in pediatric autism group). However, there were no significant differences in FA, MD, MK, DR, and KR values between HCs and pediatric autism group (P > 0.05, TFCE corrected). After performing LOOCV to train and test three model (SVM/BPNN/LR), we found the accuracy of BPNN (accuracy = 86.44%) was higher than that of LR (accuracy = 76.27%), but no different from SVM (RBF, accuracy = 81.36%; linear, accuracy = 84.75%).ConclusionOur proposed method combining TBSS findings with machine learning (LR/SVM/BPNN), was applicable in the classification of pediatric autism with high accuracy. Furthermore, the FAK, DA, and KA values and Lateralization index (LI) value could be used as neuroimaging biomarkers to discriminate the children with pediatric autism or not

Application of diffusion kurtosis imaging in neonatal brain development

BackgroundDeviations from the regular pattern of growth and development could lead to early childhood diseases, suggesting the importance of evaluating early brain development. Through this study, we aimed to explore the changing patterns of white matter and gray matter during neonatal brain development using diffusion kurtosis imaging (DKI).Materials and methodsIn total, 42 full-term neonates (within 28 days of birth) underwent conventional brain magnetic resonance imaging (MRI) and DKI. The DKI metrics (including kurtosis parameters and diffusion parameters) of white matter and deep gray matter were measured. DKI metrics from the different regions of interest (ROIs) were evaluated using the Kruskal–Wallis test and Bonferroni method. Spearman rank correlation analysis of the DKI metrics was conducted, and the age at the time of brain MRI acquisition was calculated. The subjects were divided into three groups according to their age at the time of brain MRI acquisition: the first group, neonates aged ≤7 days; the second group, neonates aged 8–14 days; and the third group, neonates aged 15–28 days. The rate of change in DKI metrics relative to the first group was computed.ResultsThe mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), and fractional anisotropy (FA) values showed positive correlations, whereas mean diffusion (MD), axial diffusion (Da), and radial diffusion (Dr) values showed negative correlations with the age at the time of brain MRI acquisition. The absolute correlation coefficients between MK values of almost all ROIs (except genu of the corpus callosum and frontal white matter) and the age at the time of brain MRI acquisition were greater than other metrics. The kurtosis parameters and FA values of central white matter were significantly higher than that of peripheral white matter, whereas the MD and Dr values were significantly lower than that of peripheral white matter. The MK value of the posterior limb of the internal capsule was the highest among the white matter areas. The FA value of the splenium of the corpus callosum was significantly higher than that of the other white matter areas. The kurtosis parameters and FA values of globus pallidus and thalamus were significantly higher than those of the caudate nucleus and putamen, whereas the Da and Dr values of globus pallidus and thalamus were significantly lower than those of the caudate nucleus and putamen. The relative change rates of kurtosis parameters and FA values of all ROIs were greater than those of MD, Da, and Dr values. The amplitude of MK values of almost all ROIs (except for the genu of the corpus callosum and central white matter of the centrum semiovale level) was greater than that of other metrics. The relative change rates of the Kr values of most ROIs were greater than those of the Ka value, and the relative change rates of the Dr values of most ROIs were greater than those of the Da value.ConclusionDKI parameters showed potential advantages in detecting the changes in brain microstructure during neonatal brain development

Predicting neurodevelopmental outcomes in extremely preterm neonates with low-grade germinal matrix-intraventricular hemorrhage using synthetic MRI

ObjectivesThis study aims to assess the predictive capability of synthetic MRI in assessing neurodevelopmental outcomes for extremely preterm neonates with low-grade Germinal Matrix-Intraventricular Hemorrhage (GMH-IVH). The study also investigates the potential enhancement of predictive performance by combining relaxation times from different brain regions.Materials and methodsIn this prospective study, 80 extremely preterm neonates with GMH-IVH underwent synthetic MRI around 38 weeks, between January 2020 and June 2022. Neurodevelopmental assessments at 18 months of corrected age categorized the infants into two groups: those without disability (n = 40) and those with disability (n = 40), with cognitive and motor outcome scores recorded. T1, T2 relaxation times, and Proton Density (PD) values were measured in different brain regions. Logistic regression analysis was utilized to correlate MRI values with neurodevelopmental outcome scores. Synthetic MRI metrics linked to disability were identified, and combined models with independent predictors were established. The predictability of synthetic MRI metrics in different brain regions and their combinations were evaluated and compared with internal validation using bootstrap resampling.ResultsElevated T1 and T2 relaxation times in the frontal white matter (FWM) and caudate were significantly associated with disability (p < 0.05). The T1-FWM, T1-Caudate, T2-FWM, and T2-Caudate models exhibited overall predictive performance with AUC values of 0.751, 0.695, 0.856, and 0.872, respectively. Combining these models into T1-FWM + T1-Caudate + T2-FWM + T2-Caudate resulted in an improved AUC of 0.955, surpassing individual models (p < 0.05). Bootstrap resampling confirmed the validity of the models.ConclusionSynthetic MRI proves effective in early predicting adverse outcomes in extremely preterm infants with GMH-IVH. The combination of T1-FWM + T1-Caudate + T2-FWM + T2-Caudate further enhances predictive accuracy, offering valuable insights for early intervention strategies

Thermal performance of finned-tube thermoacoustic heat exchangers in oscillatory flow conditions

Heat exchangers play a key role in the overall performance of thermoacoustic devices. Due to the complex nature of oscillatory flows, the underlying mechanism of heat transfer in oscillatory flows is still not fully understood. This work investigates the effect of fin length and fin spacing on the thermal performance of finned-tube heat exchangers. The heat transfer rate between two finned-tube heat exchangers arranged side-by-side in an oscillatory flow was measured over a range of testing conditions. The results are presented in terms of heat transfer coefficient and heat transfer effectiveness. Comparisons are made between experimental results of this work and a number of models, such as, the Time-Average Steady-Flow Equivalent (TASFE) model, the Root Mean Square Reynolds Number (RMS-Re) model and the boundary layer conduction model, as well as several empirical correlations in literature. A new empirical correlation is proposed to be used for the prediction of thermal performance for finned-tube heat exchangers in oscillatory flows. The uncertainties associated with the measurement of heat flux are estimated

Photometry and Spectroscopy of KS Ursae Majoris during Superoutburst

We report photometric and spectroscopic observations of the SU UMa-type dwarf novae, KS Ursae Majoris, during its 2003 February superoutburst. Modulations with a period of $0.07017\pm0.00021$ day, which is 3.3% larger than the orbital period, have been found during the superoutburst and may be positive superhumps. A maximum trough-to-peak amplitude of around 0.3 magnitude is determined for this superhump. The spectra show broad, absorption-line profiles. The lines display blue and red troughs which alternate in depth. The radial velocity curve of the absorption wings of H$\beta$ has an amplitude of $40\pm11$ km s$^{-1}$ and a phase offset of $0.12\pm0.03$. The $\gamma$ velocity of the binary is $3\pm9$ km s$^{-1}$ and varies on an order of 50 km s$^{-1}$ from day to day. From another clear evidence for a precessing eccentric disk, we obtain a solution to an eccentric outer disk consistent with theoretical works, which demonstrates the validity of the relation between superhumps and tidal effects. The inner part of the disk is also eccentric as evidenced by asymmetric and symmetric wings in the lines. Therefore, the whole disk is eccentric and the variation of $\gamma$ velocity and the evolutionary asymmetric line profiles could be criterions for an precessing eccentric accretion disk.Comment: 12 pages, 8 figures, accpeted for publication in A

Evaluation of white matter microstructural alterations in premature infants with necrotizing enterocolitis

Background: Preterm infants with necrotizing enterocolitis (NEC) are at high risk of adverse neurodevelopmental outcomes. The aim of this study was to explore the value of diffusion tensor imaging (DTI) combined with serum C-reactive protein (CRP) and procalcitonin (PCT) in evaluating alterations of white matter (WM) microstructure in preterm infants with NEC. Methods: A retrospective cross-sectional study was conducted in which all participants were consecutively enrolled at The Third Affiliated Hospital of Zhengzhou University from June 2017 and October 2021. Data from 30 preterm infants with NEC [mean gestational age at birth 31.41±1.15 weeks; mean age at magnetic resonance imaging (MRI) 37.53±3.08 weeks] and 40 healthy preterm infants with no NEC were recorded (mean gestational age at birth 32.27±2.09 weeks; mean age at MRI 37.15±3.23 weeks). WM was used to obtain the fractional anisotropy (FA) and mean diffusivity (MD) values of the regions of interest (ROIs). Additionally, serum levels of CRP and PCT were determined. Spearman correlation analysis was performed between the WM-derived parameters, CRP level, and the PCT serum index. Results: Preterm infants with NEC had reduced FA values and elevated MD values in WM regions [posterior limbs of the internal capsule (PLIC), lentiform nucleus (LN), frontal white matter (FWM)] compared to the control group (P<0.05). Additionally, the FA of the PLIC was negatively correlated with serum CRP (r=−0.846; P<0.05) and PCT (r=−0.843; P<0.05). Meanwhile, the MD of PLIC was positively correlated with serum CRP (r=0.743; P<0.05) and PCT (r=0.743; P<0.05, respectively). The area under the curve (AUC) of FA and MD combined with CRP and PCT in the diagnosis of WM microstructure alterations with NEC was 0.968, representing a considerable improvement in predicted efficacy over single indicators, including FA [AUC: 0.938; 95% confidence interval (CI): 0.840–0.950], MD (AUC: 0.807; 95% CI: 0.722–0.838), CRP (AUC: 0.867; 95% CI: 0.822–0.889), and PCT (AUC: 0.706; 95% CI: 0.701–0.758). Conclusions: WM can noninvasively and quantitatively assess the WM microstructure alterations in preterm infants with NEC. WM combined with serum CRP and PCT demonstrated superior performance in detecting and evaluating WM microstructure alterations in preterm infants with NEC

The value of synthetic MRI in detecting the brain changes and hearing impairment of children with sensorineural hearing loss

IntroductionSensorineural hearing loss (SNHL) can arise from a diverse range of congenital and acquired factors. Detecting it early is pivotal for nurturing speech, language, and cognitive development in children with SNHL. In our study, we utilized synthetic magnetic resonance imaging (SyMRI) to assess alterations in both gray and white matter within the brains of children affected by SNHL.MethodsThe study encompassed both children diagnosed with SNHL and a control group of children with normal hearing {1.5-month-olds (n = 52) and 3-month-olds (n = 78)}. Participants were categorized based on their auditory brainstem response (ABR) threshold, delineated into normal, mild, moderate, and severe subgroups.Clinical parameters were included and assessed the correlation with SNHL. Quantitative analysis of brain morphology was conducted using SyMRI scans, yielding data on brain segmentation and relaxation time.Through both univariate and multivariate analyses, independent factors predictive of SNHL were identified. The efficacy of the prediction model was evaluated using receiver operating characteristic (ROC) curves, with visualization facilitated through the utilization of a nomogram. It's important to note that due to the constraints of our research, we worked with a relatively small sample size.ResultsNeonatal hyperbilirubinemia (NH) and children with inner ear malformation (IEM) were associated with the onset of SNHL both at 1.5 and 3-month groups. At 3-month group, the moderate and severe subgroups exhibited elevated quantitative T1 values in the inferior colliculus (IC), lateral lemniscus (LL), and middle cerebellar peduncle (MCP) compared to the normal group. Additionally, WMV, WMF, MYF, and MYV were significantly reduced relative to the normal group. Additionally, SNHL-children with IEM had high T1 values in IC, and LL and reduced WMV, WMF, MYV and MYF values as compared with SNHL-children without IEM at 3-month group. LL-T1 and WMF were independent risk factors associated with SNHL. Consequently, a prediction model was devised based on LL-T1 and WMF. ROC for training set, validation set and external set were 0.865, 0.806, and 0.736, respectively.ConclusionThe integration of T1 quantitative values and brain volume segmentation offers a valuable tool for tracking brain development in children affected by SNHL and assessing the progression of the condition's severity