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Diffusion Kurtosis Imaging of Leptin Intervention in Early Hypoxic–Ischemic Brain Edema
Journal Pre-proofs Research Article Diffusion kurtosis imaging of leptin intervention in early hypoxic–ischemic brain edema Xiaoning He, Juan Xiao, Juan Tian, Honghai Chen, Jing Liu, Chao Yang PII: DOI: Reference:
S0306-4522(20)30095-6 https://doi.org/10.1016/j.neuroscience.2020.02.009 NSC 19517
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Neuroscience
Received Date: Revised Date: Accepted Date:
26 November 2019 30 January 2020 7 February 2020
Please cite this article as: X. He, J. Xiao, J. Tian, H. Chen, J. Liu, C. Yang, Diffusion kurtosis imaging of leptin intervention in early hypoxic–ischemic brain edema, Neuroscience (2020), doi: https://doi.org/10.1016/ j.neuroscience.2020.02.009
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Diffusion kurtosis imaging of leptin intervention in early hypoxic–ischemic brain edema
Xiaoning Hea, Juan Xiaoa, Juan Tiana, Honghai Chena, Jing Liub*, Chao Yanga*
a
Department of Radiology, The Second Affiliated Hospital of Dalian Medical University,
China (No. 467, Zhongshan Road, Shahekou District, Dalian, Liaoning Province) b
Dalian Medical University, China (No. 9, West section, South Lvshun Road, Dalian,
Liaoning Province) *Corresponding authors Chao Yang: [email protected] Jing Liu: [email protected] Xiaoning He: [email protected] Juan Xiao: [email protected] Juan Tian: [email protected] Honghai Chen: [email protected]
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Abbreviations: Diffusion kurtosis imaging (DKI) Hypoxic–ischemic encephalopathy (HIE) Neuron-specific enolase (NSE) Diffusion weighted imaging (DWI) Diffusion tensor imaging (DTI) S100 calcium-binding protein beta (S100β) Mean kurtosis (MK) Axial kurtosis (Ka) Radial kurtosis (Kr) Mean diffusion coefficient (MD) Axial diffusion coefficient (Da) Radial diffusion coefficient (Dr)
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Abstract The role of leptin in neuroprotection has recently been recognized. However, there are few reports on the use of imaging methods to dynamically evaluate the neuroprotection role of leptin. Diffusion kurtosis imaging (DKI), which is a method used to measure non-Gaussian water diffusion, can reflect the real water diffusion in brain tissues. In this study, a newborn piglet model was used to dynamically evaluate the leptin intervention in early hypoxic– ischemic brain edema via DKI. Thirty-two Yorkshire newborn piglets were divided into three groups: the hypoxic–ischemic encephalopathy (HIE) group, the leptin group, and the control group. DKI scanning was performed at time points of 3, 6, 9, 12, 16, and 24 h after hypoxic– ischemic exposure. After scanning, arterial blood was extracted from all piglets to measure NSE and S100β levels. Then, the brain was completely extracted for pathological examination. In the lesion areas, the MK, Ka, and Kr values in the leptin group were significantly lower than those in the HIE group, the MD, Da, and Dr values showed an opposite trend. The lesion areas in the leptin group were smaller than those of in the HIE group. In addition, the pathological results showed that less cell and organelle injury occurred in the leptin group. Our findings indicate that leptin can effectively reduce hypoxic–ischemic brain edema, and DKI can be more sensitive than conventional diffusivity metrics for visualizing the microstructural changes of HIE. This provides a new clue for the treatment and evaluation of HIE. Keywords: piglets, diffusion kurtosis imaging, hypoxic–ischemic encephalopathy
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Introduction Hypoxic–ischemic encephalopathy (HIE) is one of the main causes of neonatal death and paralysis. Cytotoxic brain edema is the most important pathological change in the early stages, thus, knowing how to reduce brain edema is essential for providing treatment (Douglas-Escobar and Weiss, 2015). Leptin is an active protein secreted by adipocytes, which can pass through the blood–brain barrier freely. Recent studies showed that leptin results in important neuroprotective effects (Harrison et al., 2019; Davis et al., 2014), but currently, there is no dynamic and non-invasive method to evaluate this effect. In diagnosing neonatal HIE, diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) can detect abnormal signals before a routine MRI (Kline-Fath et al., 2018). DWI and DTI assume a Gaussian distribution for water molecule diffusion in brain tissue, however, these models are too idealistic to reflect the actual diffusion of water molecule in brain tissue (Jensen and Helpern, 2010; Basser and Pierpaoli, 2011). As an extension of DTI, diffusion kurtosis imaging (DKI) is based on the non-Gaussian model of water molecule diffusion, which is more similar to real tissue water molecule diffusion and adopts multiple b values, making it more accurate in reflecting brain microstructure changes (Cheung et al., 2009). In a related report of ischemic stroke, DKI-related parameters in the lesion area demonstrated an inhomogeneous high signal, reflecting the heterogeneity of water molecule diffusion limitations caused by cytotoxic edema (Wang et al., 2017). Currently, few reports on the application of DKI in HIE exist. Piglets and humans share a high homology in gene sequence and chromosome structure and show various similar anatomical structures (Li et al., 2017). Moreover, animal models can be studied dynamically and pathological results can be obtained eventually. Therefore, a newborn piglet as a model can be used to better simulate neonatal HIE. The purpose of this study was to investigate the effects of leptin on hypoxic–ischemic brain edema via DKI. We hypothesized that the neuroprotective effect of leptin is accurately observed on DKI dynamically. Finally, we used serological and pathological results to verify the imaging 4
findings.
Material and methods Animal preparations A total of 35 (19 males, 16 females) newborn healthy Yorkshire piglets (three to five days old, weighing 2 ± 0.2 kg) were obtained from the Dalian Hua-qiao breeding swine herd. All piglets were randomly divided into three groups: HIE (n = 15; 8 males, 7 females), leptin (n = 15; 8 males, 7 females), and control (n = 5; 3 males, 2 females). Anesthesia was administered by inhaling isoflurane. The bilateral common carotid arteries were separated by a 5-cm longitudinal incision in the middle of the neck. In the HIE and leptin groups, the bilateral common carotid artery was ligated with 4-0 fine silk. The incisions were then stitched together. The piglets were placed into a closed hypoxic chamber with a mixture of 4% oxygen and 96% nitrogen at a flow rate of 2 L/min for 30 min. After surgery, the leptin group was intraperitoneally injected with leptin (4 mg/kg) (ProSpec Biotech company). Only the bilateral carotid artery dissection was performed in the control group. Gentamicin was administered three hours before and after surgery to prevent infection. Three pigs died during the process of hypoxia; therefore, the actual number of analyzed piglets in the HIE and leptin groups was 13 and 14, respectively. All animal experiments complied with the National Institutes of Health (NIH) guidelines and were approved by the Animal Care and Use Committee of the local institutions. Magnetic Resonance Imaging All MR imaging, including T1WI, T2WI, T2FLAIR, and DKI maps, was performed using a 3.0-T MRI scanner (GE Discovery MR750w) and 32-channel head coil. Coronal scanning was employed as the coronal position can better display the lesion and help obtain the pathological tissue. DKI scans were applied using single-shot echo planar imaging pulse sequence. The imaging parameters for DKI acquisition were as follows: TR/TE = 4500 5
ms/minimum, field of view (FOV) = 220×220 mm2, slice thickness/spacing = 3.0/0.5 mm, matrix = 128×128, NEX = 2, b values = 0, 1000, 2000 s/mm2 (diffusion encoding vectors along 20 directions for each non-zero b-value), total scanning time = 14 minutes 45 seconds. A wooden animal holder was used to secure the pig's head in the prone position. Under inhalation anesthesia, all groups received MR scanning at different time points of 3, 6, 9, 12, 16, and 24 h after hypoxic–ischemic exposure. Data processing All raw data were post-processed using the FuncTool on a GE AW4.7 workstation. DKI- and DTI-related parameter images could be obtained simultaneously. Parametric maps of the mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), mean diffusion coefficient (MD), axial diffusion coefficient (Da), and radial diffusion coefficient (Dr) were obtained. In the HIE and leptin groups, regions of interest (ROIs, area = 3 mm2) were placed in areas where the MK signals were obviously high and the MD was low. ROIs of the same size were placed on the corresponding areas of the control group. For lesions in the bilateral hemispheres, we placed ROIs on the side with the largest lesion range and the strongest signal. When placing ROIs, we aimed to avoid the edge of the lesion and the lateral ventricle. Three ROIs were placed in each lesion area and the average value was used (Fig 1). The percent changes of different metrics were computed as follows: [(lesion value-control value)/control value] × 100%. The lesion areas (cm2) were measured on the MK and MD maps at all time points using the ImageJ software (https://imagej.nih.gov/ij/). The maximum layer of each lesion was selected to measure its area; the mean value was obtained after three measurements. All ROIs and lesion areas were drawn by two experienced radiologists. The results were examined by a third radiologist.
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Fig 1. (New Fig 1) Schematic diagram of the placement of the lesion’s region of interest and lesion area measurement (HIE group at 3 h).
Serological examination After scanning, all piglets were placed on the operating table, the common carotid artery was exposed, and arterial blood was extracted from each group under anesthesia. After centrifugation, the concentrations of the serum neuronal marker neuron-specific enolase (NSE) and the astrocyte marker S100 calcium-binding protein beta (S100β) were detected by an ELISA (Dalian Kaifang Biotechnology Co., LTD). Histology After obtaining blood samples, the brain was extracted from the skull, and the lesion areas were selected with reference to the scan line (the vertical line at the base of the skull). Referring to the image scanning level, the corresponding areas of lesions in the HIE and leptin groups were sampled in the control group. For half of the piglets in each group randomly (leptin group number = 7, HIE group number = 7, control group number = 3), the brain tissue was cut into thick slices of 3 mm and placed in a 4% paraformaldehyde solution for 48 h, dehydrated, embedded with paraffin, stained with hematoxylin and eosin, and observed using an optical microscope. For the other half of the piglets (leptin group number = 7, HIE group number = 6, control group number = 2), the brain tissue was cut into specimens of 3 × 3 × 3 mm3, which were stained with uranyl acetate and citrate. The morphology and 7
structural changes of organelles in the diseased brain tissues were observed by transmission electron microscopy (TEM). Histological changes were evaluated by two experienced pathologists, and typical lesion areas were photographed. Statistical Analysis The SPSS 19.0 software (SPSS, Chicago, IL, USA) was used for all statistical analyses. All parameter values were tested for normality and homogeneity of variance, and the data were expressed as the mean ± standard deviation. Differences in parameter values among the different time points and between groups were calculated using a repeated measures ANOVA, the percent changes of different metrics within and between groups were compared using t-test. Comparisons between the lesion areas of the HIE and leptin group were made using the independent-samples t-test and group differences in NSE and S100β were compared with a one-way ANOVA. All multiple comparisons were performed using the post-hoc least significant difference method. P < 0.05 was set as the statistical significance threshold.
Results Changes in the DKI and DTI-derived variables between groups In this study, all piglets in the HIE and leptin groups presented with lesions in their subcortical area and periventricular white matter. The MK and MD maps (pseudocolor images) of the groups at different time points are presented in Fig. 1 and Fig. 2. Compared with the control group, from 3 to 24 h, the MK maps in the lesion areas demonstrated inhomogeneous high signals, and the MD maps showed relatively homogeneous low signals. The MK, Ka, Kr, MD, Da, and Dr values were significantly different between the HIE or leptin group and the control group (P-values, all <0.001).
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Fig. 2 MK, MD, and T2WI maps of the HIE group at different time points. The patchy lesion was located in the subcortical area and periventricular white matter of the bilateral cerebral hemispheres (white arrow). MK displayed an inhomogeneous high signal, whereas MD showed a relatively homogeneous low signal; T2W showed a fuzzy high signal.
Fig. 3 MK, MD, and T2WI maps of the leptin group at different time points. The dot-like lesion was located in the periventricular white matter of the bilateral cerebral hemispheres (white arrow). MK displayed an inhomogeneous high signal, whereas MD showed a relatively homogeneous low signal; T2W showed a fuzzy high signal.
At each time point, the values of the DKI-related parameters (MK, Ka, and Kr) in the 9
leptin group were significantly lower than those in the HIE group, whereas the DTI-related parameters (MD, Da, and Dr) displayed the opposite relationship (P < 0.001) (Table 1). Table 1. DKI- and DTI-derived variables between groups at different time points Time
Group
3h
HIE
6h
9h
12 h
16 h
24 h
MK
MD (μm2/ms)
Ka
Da (μm2/ms)
Kr
Dr (μm2/ ms)
1.26±0.15
1.22 ± 0.10
1.19 ± 0.06
1.22 ± 0.09
1.36 ± 0.09
1.06 ± 0.12
Leptin
0.99 ± 0.08
1.51 ± 0.09
0.83 ± 0.12
1.81 ± 0.22
1.09 ± 0.08
1.36 ± 0.12
Control
0.77 ± 0.02
1.97 ± 0.04
0.63 ± 0.03
2.37 ± 0.07
0.84 ± 0.02
1.78 ± 0.04
HIE
1.38 ± 0.10
1.03 ± 0.13
1.31 ± 0.07
1.14 ± 0.13
1.45 ± 0.07
0.95 ± 0.11
Leptin
1.01 ± 0.07
1.50 ± 0.11
0.81 ± 0.12
1.83 ± 0.24
1.13 ± 0.09
1.29 ± 0.12
Control
0.76 ± 0.01
1.98 ± 0.03
0.64 ± 0.02
2.38 ± 0.08
0.86 ± 0.01
1.77 ± 0.03
HIE
1.50 ± 0.08
0.96 ± 0.07
1.42 ± 0.06
1.03 ± 0.07
1.59 ± 0.06
0.90 ± 0.10
Leptin
1.03 ± 0.08
1.48 ± 0.11
0.84 ± 0.12
1.81 ± 0.24
1.13 ± 0.11
1.28 ± 0.14
Control
0.76 ± 0.02
1.96 ± 0.08
0.65 ± 0.03
2.35 ± 0.04
0.84 ± 0.03
1.80 ± 0.04
HIE
1.60 ± 0.14
0.92 ± 0.11
1.49 ± 0.10
0.98 ± 0.10
1.67 ± 0.21
0.83 ± 0.11
Leptin
1.09 ± 0.13
1.43 ± 0.11
0.91 ± 0.19
1.70 ± 0.36
1.18 ± 0.11
1.24 ± 0.12
Control
0.75 ± 0.02
1.99 ± 0.05
0.66 ± 0.02
2.36 ± 0.06
0.85 ± 0.02
1.79 ± 0.03
HIE
1.68 ± 0.11
0.88 ± 0.10
1.53 ± 0.07
0.95 ± 0.11
1.74 ± 0.08
0.80 ± 0.04
Leptin
1.16 ± 0.18
1.35 ± 0.17
1.04 ± 0.24
1.61 ± 0.37
1.27 ± 0.16
1.12 ± 0.13
Control
0.78 ± 0.02
1.95 ± 0.03
0.64 ± 0.02
2.35 ± 0.04
0.83 ± 0.02
1.77 ± 0.03
HIE
1.79 ± 0.12
0.81 ± 0.07
1.56 ± 0.07
0.92 ± 0.07
1.86 ± 0.08
0.76 ± 0.05
Leptin
1.20 ± 0.20
1.25 ± 0.22
1.06 ± 0.27
1.53 ± 0.45
1.30 ± 0.19
1.09 ± 0.13
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Control
0.75 ± 0.03
1.96 ± 0.04
P-value
<0.001
<0.001
P-value*
<0.001
P-value#
<0.001
0.63 ± 0.02
2.37 ± 0.03
0.86 ± 0.02
1.76 ± 0.04
<0.001
<0.001
<0.001
＜0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
P-value = Comparison between groups; P-value* = Among different time points; P-value# = interaction of time × group.
Percentage changes in different metrics In the HIE and leptin groups, the percent changes in the DKI-related variables (MK, Ka and Kr) were significantly higher than those of the DTI-related variables (MD, Da and Dr) at different time points (P < 0.05). In the HIE group, the relative magnitude of changes in the axial metrics (Ka and Da) were significantly higher than those in the radial metrics (Kr and Dr) (P < 0.05). The percent changes of leptin group were lower than that of HIE group (P < 0.05). (Fig. 3).
Fig. 4 Percentage changes in DKI- and DTI-derived variables in the lesions at different time points
3.3 The temporal evolution of the DKI- and DTI-derived variables In the HIE group, the MK, Ka, Kr, MD, Da, and Dr values gradually changed from 3 to 24 h in the lesion areas; however, the trend of change in the leptin group slowed down significantly (Fig. 4).
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Fig. 5 The time course of MK and MD values between groups in the lesion areas
The lesion areas of HIE group and leptin group As presented in Fig. 5, the lesion areas of leptin group were smaller than those of HIE group at each time point, regardless of MK or MD maps (P < 0.05).
Fig. 6 The lesion areas of HIE group and leptin group at different time points.
Serological findings Compared with the control group, the serum concentrations of NSE and S100β in the HIE group were significantly increased (P < 0.05), conversely, the serum concentrations of NSE in the leptin group were significantly lower than those of the HIE group (P < 0.05). No 12
significant difference in S100β concentrations between the HIE and leptin groups (P > 0.05) existed. The serum concentrations of NSE and S100β in the groups at 24 h are presented in Table 2. Table 2. Serum concentrations of NSE and S100β in the groups at 24 h Group
NSE (μg/ L)
S100β (ng/ L)
HIE
149.34 ± 9.14
628.02 ± 22.14
Leptin
107.64 ± 4.84
610.66 ± 22.14
Control
111.21 ± 5.19
532.45 ± 30.77
P-value
<0.001
0.001
P-value*
0.16
0.001
P-value#
<0.001
0.84
P-value = Comparison between HIE and control groups; P-value* = Comparison between leptin and control groups; P-value# = Comparison between HIE and leptin groups
Histological findings The pathological images of each group are shown in Fig. 6 and Fig. 7. Light microscopy in the HIE group revealed loose tissue, pale cytoplasm, swelling of glial cells, nuclear condensation, formation of red neurons, and interstitial edema. In the leptin group, local cytoplasm pale, tissue loose, and irregular and sparse nucleus were noted. The electron microscopy images show that the chromatin in the control group was fine, granular, and evenly distributed; abundant organelles could be observed in the cytoplasm; the mitochondria were oval; and the mitochondrial cristae were well-developed. In the HIE group, mitochondrial swelling, mitochondrial ridge fracture, partial mitochondrial membrane rupture, and autophagosomes with phagocytosis wrapped in the inner cavity could be observed in part of the field of vision. Mitochondrial swelling was observed in the leptin 13
group, and spherical mitochondria were more common, with some mitochondria displaying a normal shape.
Fig. 7 Optical microscope photograph between the groups at 24 h. A: HIE group (HE 100×), B: Leptin group (HE 100×), C: Control group (HE 100×). A: Pale cytoplasm, enlarged intercellular space, glial cells swelling, formation of red neurons (the arrow). B: Local cytoplasm pale, tissue loose, and irregular and sparse nucleus (the arrow).
Fig. 8 TEM photograph between the groups at 24 h. A: Control group (80000×), B: HIE group (80000×), C: HIE group (50000×), D: Leptin group (25000×). B: Mitochondrial swelling, mitochondrial ridge fracture, partial mitochondrial membrane rupture (black arrow). C: Autophagosomes with phagocytosis wrapped in the inner cavity (red arrow). D: Mild Mitochondrial swelling (white arrow).
Discussion Recent study on the neuroprotective effects of leptin found that leptin can reduce hypoxic–ischemic brain injury by reducing brain edema, inhibiting apoptosis, and promoting 14
energy metabolism (Hu et al., 2019), which provides a new direction for the treatment of neonatal HIE. Compared with traditional dMRI techniques, DKI can truly detect the true diffusion of water molecule pathologically (Rudrapatna et al., 2014). In addition to the advantages of the imaging model, DKI also has multiple parametric maps, which makes it possible to accurately evaluate the effects of leptin on hypoxic–ischemic brain edema. Imaging revealed that the lesions were distributed in the subcortical area and periventricular white matter. This is because of the increased blood supply in the basal ganglia area at the early stages of hypoxia–ischemia, resulting in blood flow redistribution. Therefore, the lesions in the subcortical area and periventricular white matter occurred early. As the two most characteristic parameters, the MK images showed an inhomogeneous high signal, whereas the MD images presented a relatively homogeneous low signal in the lesion areas, indicating that DKI could reflect the diffusion heterogeneity of water molecules caused by cytotoxic edema after hypoxia–ischemia. Moreover, larger percent changes have been consistently reported for kurtosis metrics than for diffusivity metrics in ischemic stroke (Yin et al., 2018; Wang et al., 2018), indicating that DKI parameters are more sensitive for detecting microstructure changes in brain tissue. Notably, in the HIE group, the percentage changes were larger along the axial direction (Ka and Da) than along the radial direction (Kr and Dr), and the majority of lesions were located in the white matter tissue, which may indicate that the axon injury was more severe than the myelin injury. This is also the reason for the inhomogeneous hyperintensity in the MK images. Recent studies (Guo et al., 2016; Zhang et al., 2016) showed that axonal varicosity and endoplasmic reticulum changes lead to higher axial diffusion limitations after cytotoxic edema. From 3 to 24 h, in the HIE group, the MK, Ka, Kr, MD, Da, and Dr values gradually changed in the lesion areas, which indicates a progressive increase in cytotoxic edema. Spampinato et al. (2017) reported that the higher the MK value, the lower the MD value, indicating a poor prognosis. At each time point, the parameter values and lesion areas in the leptin group significantly differed from those in the HIE group, and the trend of change in the parameter values in the leptin group was relatively moderate, suggesting that the degree of 15
brain injury in the leptin group was relatively mild. This finding indicates that leptin could effectively reduce hypoxic–ischemic brain edema. Finally, the pathological results also showed that there was significantly less cell and organelle damage in the leptin group than in the HIE group. In addition, autophagosomes were observed in the HIE group, which contained damaged organelles, indicating that hypoxia–ischemia activated autophagy in nerve cells, leading to further injury of nerve cells, which is consistent with a previously reported finding (Koike et al., 2008). In addition, we observed that the lesion area of MK was significantly smaller than that of MD in both the HIE and leptin groups, consistent with the results of relevant studies on cerebral infarction (Yin et al., 2018; Zhang et al., 2016). DKI has proved to be more accurate in reflecting the diffusion of water molecules because of its non-Gaussian nature. The results indicated that MK may reflect the actual range of cytotoxic edema and the severity of brain damage; however, this requires more accurate histological confirmation. As sensitive markers of hypoxic–ischemic brain injury, NSE and S100β have become reliable indicators for the early diagnosis of HIE. These two substances exist in normal brain tissues and have low peripheral blood levels because of the blood–brain barrier (Elshorbagy et al., 2019). When hypoxia–ischemia occurs, the blood–brain barrier is damaged, resulting in increased concentrations of NSE and S100β in the peripheral blood. Studies have shown that serum concentrations of NSE and S100β are significantly correlated with disease severity (Hoshi et al., 2005). In our study, the HIE group showed significantly higher serum levels of NSE and S100β at 24 h compared with the control group. Meanwhile, the NSE concentration of the leptin group was significantly lower than that of the HIE group, suggesting that the leptin group presented with a mild brain injury, which is consistent with the imaging and pathological findings. Unfortunately, no significant difference in S100β concentration was observed between the leptin group and the HIE group, although the leptin group showed lower values. A possible reason for the lack of a significant difference is the small sample size. Leptin has been demonstrated to be involved in the organization and maturation of the 16
nervous system. Leptin therapy can increase the density of neurons (Zhang et al., 2007), reduce apoptosis caused by HIE (Kumral et al., 2012), and improve spatial memory (Feng and Jiang 2018). The results of our study are consistent with previous reports that indicate that leptin treatment can reduce hypoxic–ischemic encephalopathy. The mechanism by which leptin alleviates early brain edema has not been clarified. Current studies suggest that aquaporin plays an active role in the formation of brain edema, among which aquaporin 4 (AQP4) is widely distributed on the membrane at the junction of the brain parenchyma and fluid components (Di et al., 2016). Using gene silencing technology to reduce the expression of the AQP4 gene can effectively reduce cytotoxic brain edema (Yang et al., 2015), suggesting that AQP4 plays an important role in the formation of early cytotoxic brain edema. Therefore, in this study, leptin may inhibit the expression of AQP4 to reduce brain edema. However, this mechanism requires further study. This study exhibits several limitations. First, the number of cases was small, due to the pathological images at each time point were not obtained. Therefore, the degree of cytotoxic edema cannot be observed dynamically from the pathology findings. Secondly, the expression of AQP4 in brain tissues was not detected; therefore, the neuroprotective mechanism of leptin could not be confirmed. Our future work aims to address these deficiencies. In addition, a prior study (Chuhutin et al., 2017) has suggested caution in evaluating results using DKI indicators obtained via different fitting techniques and b-value; our study only used workstations to post-process DKI. DKI images processed using the GE Advantage Workstation have been widely used in clinical studies with reliable results (Xu et al., 2016; Li et al., 2019). Furthermore, Diffusional Kurtosis Estimator software (http://nitrc.org/projects/dke) based on the MATLAB platform has also been recognized (Tabesh et al., 2011). In the future, it will be necessary to use additional image post-processing tools to comprehensively evaluate the results.
Conclusions 17
This controlled study showed that leptin can significantly relieve cytotoxic brain edema and exhibits a high value in the treatment of HIE. DKI, a very sensitive imaging technique to cytotoxic brain edema, with the advantage of being a more realistic imaging model, containing multiple b values and parameters, can more comprehensively and sensitively reflect the changes of brain tissue microstructure. Overall, DKI has a broad application prospect in clinical work as a dynamic and non-invasive method that can accurately evaluate HIE and its therapeutic effect.
Acknowledgements: Chao Yang and Jing Liu designed the study; Xiaoning He, Juan Xiao and Honghai Chen conducted the experiments, Juan Tian performed the statistical analysis; Xiaoning He wrote the manuscript. Declarations of interest: None Research involving Human Participants and/or Animals: The animal experiments complied with the NIH guidelines and were approved by the Animal Care and Use Committee of Dalian Medical University. Funding: This study was supported by the National Natural Science Foundation of China [grant number 81771663] and the Natural Science Foundation of Liaoning Province [grant number 20170540237].
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References Basser PJ, Pierpaoli C (2011) Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson 213:560-570. Cheung MM, Hui ES, Chan KC, Helpern JA, Qi L, Wu EX (2009) Does diffusion kurtosis imaging lead to better neural tissue characterization? A rodent brain maturation study. Neuroimage 45:386-392. Chuhutin A, Hansen B, Jespersen SN (2017) Precision and accuracy of diffusion kurtosis estimation and the influence of b-value selection. NMR Biomed 30:e3777. Davis C, Mudd J, Hawkins M (2014) Neuroprotective effects of leptin in the context of obesity and metabolic disorders. Neurobiol Dis 72:61-71. Di BB, Malik VA, Begum S, Jablonowski L, Gómez-González GB, Neumann ID, Rupprecht R (2016) Fluoxetine requires the endfeet protein aquaporin-4 to enhance plasticity of astrocyte processes. Front Cell Neurosci 10:8. Douglas-Escobar M, Weiss MD (2015) Hypoxic-ischemic encephalopathy: A review for the clinician. JAMA Pediatr 169:397-403. Elshorbagy HH, Barseem NF, Elsadek AE, Al-shokary AH, Maksoud YH, Abdulsamea SE, Talaat IM, Suliman HA, et al. (2019) The study of serum neuron-specific enolase and S100 calcium-binding protein B in pediatric diabetic ketoacidosis. J Clin Res Pediatr Endocrinol. Feng EC, Jiang L (2018) Effects of leptin on neurocognitive and motor functions in juvenile rats in a preterm brain damage model. Mol Med Rep 18:4095-4102. Guo YL, Li SJ, Zhang ZP, Shen ZW, Zhang GS, Yan G, Wang YT, Rao HB, et al. (2016) Parameters of diffusional kurtosis imaging for the diagnosis of acute cerebral infarction in different brain regions. Exp Ther Med 12:933-938. 19
Harrison L, Schriever SC, Feuchtinger A, Kyriakou E, Baumann P, Pfuhlmann K, Messias AC, Walch A, et al. (2019) Fluorescent blood–brain barrier tracing shows intact leptin transport in obese mice. Int J Obes 43:1305. Hoshi T, Kitagawa K, Yamagami H, Furukado S, Hougaku H, Hori M (2005) Relations of serum high-sensitivity C-reactive protein and interleukin-6 levels with silent brain infarction. Stroke 36:768-772. Hu S, Cheng D, Peng D, Tan J, Huang Y, Chen C (2019) Leptin attenuates cerebral ischemic injury in rats by modulating the mitochondrial electron transport chain via the mitochondrial STAT3 pathway. Brain Behav 9:e01200. Jensen JH, Helpern JA (2010) MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR Biomed 23:698-710. Kumral A, Yesilirmak DC, Sozmen S, Ergur BU, Tugyan K, Ozbal S, Guclu S, Duman N, et al. (2012) Effect of leptin treatment on neonatal hypoxic-ischemic brain injury. J Matern Fetal Neonatal Med 25:141-146. Kline-Fath BM, Horn PS, Yuan W, Merhar S, Venkatesan C, Thomas CW, Schapiro MB (2018) Conventional MRI scan and DTI imaging show more severe brain injury in neonates with hypoxic-ischemic encephalopathy and seizures. Early Hum Dev 122:8-14. Koike M，Shibata M，Tadakoshi M, Gotoh K, Komatsu M, Waguri S, Kawahara N, Kuida K, et al. (2008) Inhibition of autophagy prevents hippocampal pyramidal neuron death after hypoxic-ischemic injury. Am J Pathol 172:454-469. Li C, Lan C, Zhang X, Yin L, Hao X, Tian J, Lin L, Sun H, et al. (2019) Evaluation of Diffusional Kurtosis Imaging in Sub-acute Ischemic Stroke: Comparison with Rehabilitation Treatment Effect. Cell Transplant 28:1053-1061. Li M, Chen L, Tian S, Lin Y, Tang Q, Zhou X, Li D, Yeung CK, et al. (2017) Comprehensive variation discovery and recovery of missing sequence in the pig genome 20
using multiple de novo assemblies. Genome Res 27:865-874. Rudrapatna SU, Wieloch T, Beirup K, Ruscher K, Mol W, Yanev P, Leemans A, van der Toorn A, et al. (2014) Can diffusion kurtosis imaging improve the sensitivity and specificity of detecting microstructural alterations in brain tissue chronically after experimental stroke? Comparisons with diffusion tensor imaging and histology. Neuroimage 97:363-373. Spampinato MV, Chan C, Jensen JH, Helpern JA, Bonilha L, Kautz SA, Nietert PJ, Feng W (2017) Diffusional kurtosis imaging and motor outcome in acute ischemic stroke. AJNR 38:1328-1334. Tabesh A, Jensen JH, Ardekani BA, Helpern JA (2011) Estimation of tensors and tensor-derived measures in diffusional kurtosis imaging. Magn Reson Med 65:823-836. Wang E, Wu Y, Cheung JS, Zhou IY, Igarashi T, Zhang X, Sun PZ (2017) pH imaging reveals worsened tissue acidification in diffusion kurtosis lesion than the kurtosis/diffusion lesion mismatch in an animal model of acute stroke. J Cereb Blood Flow Metab 37:3325-3333. Wang ML, Yu MM, Yang DX, Liu YL, Wei XE, Li WB (2018) Longitudinal microstructural changes in traumatic brain injury in rats: a diffusional kurtosis imaging, histology, and behavior study. AJNR 39:1650-1656. Xu S, Ye D, Lian T, Cai J, Xiao Z, Huang Y, Chen X, Zhang Z (2016) Assessment of severity of leukoaraiosis: a diffusional kurtosis imaging study. Clin Imaging 40:732-738. Yang C, Liu Z, Li H, Zhai F, Liu J, Bian J (2015) Aquaporin-4 knockdown ameliorates hypoxic-ischemic cerebral edema in newborn piglets. IUBMB Life, 2015, 67:182-190. Yin J, Sun H, Wang Z, Ni H, Shen W, Sun PZ (2018) Diffusion kurtosis imaging of acute infarction: comparison with routine diffusion and follow-up MR imaging. Radiology 287:651-657. 21
Zhang F, Wang S, Signore AP, Chen J (2007) Neuroprotective effects of leptin against ischemic injury induced by oxygen-glucose deprivation and transient cerebral ischemia. Stroke 38:2329-2336. Zhang S, Yao Y, Shi J, Tang X, Zhao L, Zhu W (2016) The temporal evolution of diffusional kurtosis imaging in an experimental middle cerebral artery occlusion (MCAO) model. Magn Reson Imaging 34:889-895.
Highlights
Leptin effectively reduces hypoxic-ischemic cerebral edema in newborn piglets.
DKI provides more detailed microstructural data of hypoxic/ischemic brain edema.
DKI serves as a model for measuring non-gaussian water diffusion.
DKI dynamically evaluated the neuroprotective effects of leptin.
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S0306-4522(20)30095-6 https://doi.org/10.1016/j.neuroscience.2020.02.009 NSC 19517
To appear in:
Neuroscience
Received Date: Revised Date: Accepted Date:
26 November 2019 30 January 2020 7 February 2020
Please cite this article as: X. He, J. Xiao, J. Tian, H. Chen, J. Liu, C. Yang, Diffusion kurtosis imaging of leptin intervention in early hypoxic–ischemic brain edema, Neuroscience (2020), doi: https://doi.org/10.1016/ j.neuroscience.2020.02.009
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Diffusion kurtosis imaging of leptin intervention in early hypoxic–ischemic brain edema
Xiaoning Hea, Juan Xiaoa, Juan Tiana, Honghai Chena, Jing Liub*, Chao Yanga*
a
Department of Radiology, The Second Affiliated Hospital of Dalian Medical University,
China (No. 467, Zhongshan Road, Shahekou District, Dalian, Liaoning Province) b
Dalian Medical University, China (No. 9, West section, South Lvshun Road, Dalian,
Liaoning Province) *Corresponding authors Chao Yang: [email protected] Jing Liu: [email protected] Xiaoning He: [email protected] Juan Xiao: [email protected] Juan Tian: [email protected] Honghai Chen: [email protected]
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Abbreviations: Diffusion kurtosis imaging (DKI) Hypoxic–ischemic encephalopathy (HIE) Neuron-specific enolase (NSE) Diffusion weighted imaging (DWI) Diffusion tensor imaging (DTI) S100 calcium-binding protein beta (S100β) Mean kurtosis (MK) Axial kurtosis (Ka) Radial kurtosis (Kr) Mean diffusion coefficient (MD) Axial diffusion coefficient (Da) Radial diffusion coefficient (Dr)
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Abstract The role of leptin in neuroprotection has recently been recognized. However, there are few reports on the use of imaging methods to dynamically evaluate the neuroprotection role of leptin. Diffusion kurtosis imaging (DKI), which is a method used to measure non-Gaussian water diffusion, can reflect the real water diffusion in brain tissues. In this study, a newborn piglet model was used to dynamically evaluate the leptin intervention in early hypoxic– ischemic brain edema via DKI. Thirty-two Yorkshire newborn piglets were divided into three groups: the hypoxic–ischemic encephalopathy (HIE) group, the leptin group, and the control group. DKI scanning was performed at time points of 3, 6, 9, 12, 16, and 24 h after hypoxic– ischemic exposure. After scanning, arterial blood was extracted from all piglets to measure NSE and S100β levels. Then, the brain was completely extracted for pathological examination. In the lesion areas, the MK, Ka, and Kr values in the leptin group were significantly lower than those in the HIE group, the MD, Da, and Dr values showed an opposite trend. The lesion areas in the leptin group were smaller than those of in the HIE group. In addition, the pathological results showed that less cell and organelle injury occurred in the leptin group. Our findings indicate that leptin can effectively reduce hypoxic–ischemic brain edema, and DKI can be more sensitive than conventional diffusivity metrics for visualizing the microstructural changes of HIE. This provides a new clue for the treatment and evaluation of HIE. Keywords: piglets, diffusion kurtosis imaging, hypoxic–ischemic encephalopathy
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Introduction Hypoxic–ischemic encephalopathy (HIE) is one of the main causes of neonatal death and paralysis. Cytotoxic brain edema is the most important pathological change in the early stages, thus, knowing how to reduce brain edema is essential for providing treatment (Douglas-Escobar and Weiss, 2015). Leptin is an active protein secreted by adipocytes, which can pass through the blood–brain barrier freely. Recent studies showed that leptin results in important neuroprotective effects (Harrison et al., 2019; Davis et al., 2014), but currently, there is no dynamic and non-invasive method to evaluate this effect. In diagnosing neonatal HIE, diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) can detect abnormal signals before a routine MRI (Kline-Fath et al., 2018). DWI and DTI assume a Gaussian distribution for water molecule diffusion in brain tissue, however, these models are too idealistic to reflect the actual diffusion of water molecule in brain tissue (Jensen and Helpern, 2010; Basser and Pierpaoli, 2011). As an extension of DTI, diffusion kurtosis imaging (DKI) is based on the non-Gaussian model of water molecule diffusion, which is more similar to real tissue water molecule diffusion and adopts multiple b values, making it more accurate in reflecting brain microstructure changes (Cheung et al., 2009). In a related report of ischemic stroke, DKI-related parameters in the lesion area demonstrated an inhomogeneous high signal, reflecting the heterogeneity of water molecule diffusion limitations caused by cytotoxic edema (Wang et al., 2017). Currently, few reports on the application of DKI in HIE exist. Piglets and humans share a high homology in gene sequence and chromosome structure and show various similar anatomical structures (Li et al., 2017). Moreover, animal models can be studied dynamically and pathological results can be obtained eventually. Therefore, a newborn piglet as a model can be used to better simulate neonatal HIE. The purpose of this study was to investigate the effects of leptin on hypoxic–ischemic brain edema via DKI. We hypothesized that the neuroprotective effect of leptin is accurately observed on DKI dynamically. Finally, we used serological and pathological results to verify the imaging 4
findings.
Material and methods Animal preparations A total of 35 (19 males, 16 females) newborn healthy Yorkshire piglets (three to five days old, weighing 2 ± 0.2 kg) were obtained from the Dalian Hua-qiao breeding swine herd. All piglets were randomly divided into three groups: HIE (n = 15; 8 males, 7 females), leptin (n = 15; 8 males, 7 females), and control (n = 5; 3 males, 2 females). Anesthesia was administered by inhaling isoflurane. The bilateral common carotid arteries were separated by a 5-cm longitudinal incision in the middle of the neck. In the HIE and leptin groups, the bilateral common carotid artery was ligated with 4-0 fine silk. The incisions were then stitched together. The piglets were placed into a closed hypoxic chamber with a mixture of 4% oxygen and 96% nitrogen at a flow rate of 2 L/min for 30 min. After surgery, the leptin group was intraperitoneally injected with leptin (4 mg/kg) (ProSpec Biotech company). Only the bilateral carotid artery dissection was performed in the control group. Gentamicin was administered three hours before and after surgery to prevent infection. Three pigs died during the process of hypoxia; therefore, the actual number of analyzed piglets in the HIE and leptin groups was 13 and 14, respectively. All animal experiments complied with the National Institutes of Health (NIH) guidelines and were approved by the Animal Care and Use Committee of the local institutions. Magnetic Resonance Imaging All MR imaging, including T1WI, T2WI, T2FLAIR, and DKI maps, was performed using a 3.0-T MRI scanner (GE Discovery MR750w) and 32-channel head coil. Coronal scanning was employed as the coronal position can better display the lesion and help obtain the pathological tissue. DKI scans were applied using single-shot echo planar imaging pulse sequence. The imaging parameters for DKI acquisition were as follows: TR/TE = 4500 5
ms/minimum, field of view (FOV) = 220×220 mm2, slice thickness/spacing = 3.0/0.5 mm, matrix = 128×128, NEX = 2, b values = 0, 1000, 2000 s/mm2 (diffusion encoding vectors along 20 directions for each non-zero b-value), total scanning time = 14 minutes 45 seconds. A wooden animal holder was used to secure the pig's head in the prone position. Under inhalation anesthesia, all groups received MR scanning at different time points of 3, 6, 9, 12, 16, and 24 h after hypoxic–ischemic exposure. Data processing All raw data were post-processed using the FuncTool on a GE AW4.7 workstation. DKI- and DTI-related parameter images could be obtained simultaneously. Parametric maps of the mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), mean diffusion coefficient (MD), axial diffusion coefficient (Da), and radial diffusion coefficient (Dr) were obtained. In the HIE and leptin groups, regions of interest (ROIs, area = 3 mm2) were placed in areas where the MK signals were obviously high and the MD was low. ROIs of the same size were placed on the corresponding areas of the control group. For lesions in the bilateral hemispheres, we placed ROIs on the side with the largest lesion range and the strongest signal. When placing ROIs, we aimed to avoid the edge of the lesion and the lateral ventricle. Three ROIs were placed in each lesion area and the average value was used (Fig 1). The percent changes of different metrics were computed as follows: [(lesion value-control value)/control value] × 100%. The lesion areas (cm2) were measured on the MK and MD maps at all time points using the ImageJ software (https://imagej.nih.gov/ij/). The maximum layer of each lesion was selected to measure its area; the mean value was obtained after three measurements. All ROIs and lesion areas were drawn by two experienced radiologists. The results were examined by a third radiologist.
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Fig 1. (New Fig 1) Schematic diagram of the placement of the lesion’s region of interest and lesion area measurement (HIE group at 3 h).
Serological examination After scanning, all piglets were placed on the operating table, the common carotid artery was exposed, and arterial blood was extracted from each group under anesthesia. After centrifugation, the concentrations of the serum neuronal marker neuron-specific enolase (NSE) and the astrocyte marker S100 calcium-binding protein beta (S100β) were detected by an ELISA (Dalian Kaifang Biotechnology Co., LTD). Histology After obtaining blood samples, the brain was extracted from the skull, and the lesion areas were selected with reference to the scan line (the vertical line at the base of the skull). Referring to the image scanning level, the corresponding areas of lesions in the HIE and leptin groups were sampled in the control group. For half of the piglets in each group randomly (leptin group number = 7, HIE group number = 7, control group number = 3), the brain tissue was cut into thick slices of 3 mm and placed in a 4% paraformaldehyde solution for 48 h, dehydrated, embedded with paraffin, stained with hematoxylin and eosin, and observed using an optical microscope. For the other half of the piglets (leptin group number = 7, HIE group number = 6, control group number = 2), the brain tissue was cut into specimens of 3 × 3 × 3 mm3, which were stained with uranyl acetate and citrate. The morphology and 7
structural changes of organelles in the diseased brain tissues were observed by transmission electron microscopy (TEM). Histological changes were evaluated by two experienced pathologists, and typical lesion areas were photographed. Statistical Analysis The SPSS 19.0 software (SPSS, Chicago, IL, USA) was used for all statistical analyses. All parameter values were tested for normality and homogeneity of variance, and the data were expressed as the mean ± standard deviation. Differences in parameter values among the different time points and between groups were calculated using a repeated measures ANOVA, the percent changes of different metrics within and between groups were compared using t-test. Comparisons between the lesion areas of the HIE and leptin group were made using the independent-samples t-test and group differences in NSE and S100β were compared with a one-way ANOVA. All multiple comparisons were performed using the post-hoc least significant difference method. P < 0.05 was set as the statistical significance threshold.
Results Changes in the DKI and DTI-derived variables between groups In this study, all piglets in the HIE and leptin groups presented with lesions in their subcortical area and periventricular white matter. The MK and MD maps (pseudocolor images) of the groups at different time points are presented in Fig. 1 and Fig. 2. Compared with the control group, from 3 to 24 h, the MK maps in the lesion areas demonstrated inhomogeneous high signals, and the MD maps showed relatively homogeneous low signals. The MK, Ka, Kr, MD, Da, and Dr values were significantly different between the HIE or leptin group and the control group (P-values, all <0.001).
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Fig. 2 MK, MD, and T2WI maps of the HIE group at different time points. The patchy lesion was located in the subcortical area and periventricular white matter of the bilateral cerebral hemispheres (white arrow). MK displayed an inhomogeneous high signal, whereas MD showed a relatively homogeneous low signal; T2W showed a fuzzy high signal.
Fig. 3 MK, MD, and T2WI maps of the leptin group at different time points. The dot-like lesion was located in the periventricular white matter of the bilateral cerebral hemispheres (white arrow). MK displayed an inhomogeneous high signal, whereas MD showed a relatively homogeneous low signal; T2W showed a fuzzy high signal.
At each time point, the values of the DKI-related parameters (MK, Ka, and Kr) in the 9
leptin group were significantly lower than those in the HIE group, whereas the DTI-related parameters (MD, Da, and Dr) displayed the opposite relationship (P < 0.001) (Table 1). Table 1. DKI- and DTI-derived variables between groups at different time points Time
Group
3h
HIE
6h
9h
12 h
16 h
24 h
MK
MD (μm2/ms)
Ka
Da (μm2/ms)
Kr
Dr (μm2/ ms)
1.26±0.15
1.22 ± 0.10
1.19 ± 0.06
1.22 ± 0.09
1.36 ± 0.09
1.06 ± 0.12
Leptin
0.99 ± 0.08
1.51 ± 0.09
0.83 ± 0.12
1.81 ± 0.22
1.09 ± 0.08
1.36 ± 0.12
Control
0.77 ± 0.02
1.97 ± 0.04
0.63 ± 0.03
2.37 ± 0.07
0.84 ± 0.02
1.78 ± 0.04
HIE
1.38 ± 0.10
1.03 ± 0.13
1.31 ± 0.07
1.14 ± 0.13
1.45 ± 0.07
0.95 ± 0.11
Leptin
1.01 ± 0.07
1.50 ± 0.11
0.81 ± 0.12
1.83 ± 0.24
1.13 ± 0.09
1.29 ± 0.12
Control
0.76 ± 0.01
1.98 ± 0.03
0.64 ± 0.02
2.38 ± 0.08
0.86 ± 0.01
1.77 ± 0.03
HIE
1.50 ± 0.08
0.96 ± 0.07
1.42 ± 0.06
1.03 ± 0.07
1.59 ± 0.06
0.90 ± 0.10
Leptin
1.03 ± 0.08
1.48 ± 0.11
0.84 ± 0.12
1.81 ± 0.24
1.13 ± 0.11
1.28 ± 0.14
Control
0.76 ± 0.02
1.96 ± 0.08
0.65 ± 0.03
2.35 ± 0.04
0.84 ± 0.03
1.80 ± 0.04
HIE
1.60 ± 0.14
0.92 ± 0.11
1.49 ± 0.10
0.98 ± 0.10
1.67 ± 0.21
0.83 ± 0.11
Leptin
1.09 ± 0.13
1.43 ± 0.11
0.91 ± 0.19
1.70 ± 0.36
1.18 ± 0.11
1.24 ± 0.12
Control
0.75 ± 0.02
1.99 ± 0.05
0.66 ± 0.02
2.36 ± 0.06
0.85 ± 0.02
1.79 ± 0.03
HIE
1.68 ± 0.11
0.88 ± 0.10
1.53 ± 0.07
0.95 ± 0.11
1.74 ± 0.08
0.80 ± 0.04
Leptin
1.16 ± 0.18
1.35 ± 0.17
1.04 ± 0.24
1.61 ± 0.37
1.27 ± 0.16
1.12 ± 0.13
Control
0.78 ± 0.02
1.95 ± 0.03
0.64 ± 0.02
2.35 ± 0.04
0.83 ± 0.02
1.77 ± 0.03
HIE
1.79 ± 0.12
0.81 ± 0.07
1.56 ± 0.07
0.92 ± 0.07
1.86 ± 0.08
0.76 ± 0.05
Leptin
1.20 ± 0.20
1.25 ± 0.22
1.06 ± 0.27
1.53 ± 0.45
1.30 ± 0.19
1.09 ± 0.13
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Control
0.75 ± 0.03
1.96 ± 0.04
P-value
<0.001
<0.001
P-value*
<0.001
P-value#
<0.001
0.63 ± 0.02
2.37 ± 0.03
0.86 ± 0.02
1.76 ± 0.04
<0.001
<0.001
<0.001
＜0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
P-value = Comparison between groups; P-value* = Among different time points; P-value# = interaction of time × group.
Percentage changes in different metrics In the HIE and leptin groups, the percent changes in the DKI-related variables (MK, Ka and Kr) were significantly higher than those of the DTI-related variables (MD, Da and Dr) at different time points (P < 0.05). In the HIE group, the relative magnitude of changes in the axial metrics (Ka and Da) were significantly higher than those in the radial metrics (Kr and Dr) (P < 0.05). The percent changes of leptin group were lower than that of HIE group (P < 0.05). (Fig. 3).
Fig. 4 Percentage changes in DKI- and DTI-derived variables in the lesions at different time points
3.3 The temporal evolution of the DKI- and DTI-derived variables In the HIE group, the MK, Ka, Kr, MD, Da, and Dr values gradually changed from 3 to 24 h in the lesion areas; however, the trend of change in the leptin group slowed down significantly (Fig. 4).
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Fig. 5 The time course of MK and MD values between groups in the lesion areas
The lesion areas of HIE group and leptin group As presented in Fig. 5, the lesion areas of leptin group were smaller than those of HIE group at each time point, regardless of MK or MD maps (P < 0.05).
Fig. 6 The lesion areas of HIE group and leptin group at different time points.
Serological findings Compared with the control group, the serum concentrations of NSE and S100β in the HIE group were significantly increased (P < 0.05), conversely, the serum concentrations of NSE in the leptin group were significantly lower than those of the HIE group (P < 0.05). No 12
significant difference in S100β concentrations between the HIE and leptin groups (P > 0.05) existed. The serum concentrations of NSE and S100β in the groups at 24 h are presented in Table 2. Table 2. Serum concentrations of NSE and S100β in the groups at 24 h Group
NSE (μg/ L)
S100β (ng/ L)
HIE
149.34 ± 9.14
628.02 ± 22.14
Leptin
107.64 ± 4.84
610.66 ± 22.14
Control
111.21 ± 5.19
532.45 ± 30.77
P-value
<0.001
0.001
P-value*
0.16
0.001
P-value#
<0.001
0.84
P-value = Comparison between HIE and control groups; P-value* = Comparison between leptin and control groups; P-value# = Comparison between HIE and leptin groups
Histological findings The pathological images of each group are shown in Fig. 6 and Fig. 7. Light microscopy in the HIE group revealed loose tissue, pale cytoplasm, swelling of glial cells, nuclear condensation, formation of red neurons, and interstitial edema. In the leptin group, local cytoplasm pale, tissue loose, and irregular and sparse nucleus were noted. The electron microscopy images show that the chromatin in the control group was fine, granular, and evenly distributed; abundant organelles could be observed in the cytoplasm; the mitochondria were oval; and the mitochondrial cristae were well-developed. In the HIE group, mitochondrial swelling, mitochondrial ridge fracture, partial mitochondrial membrane rupture, and autophagosomes with phagocytosis wrapped in the inner cavity could be observed in part of the field of vision. Mitochondrial swelling was observed in the leptin 13
group, and spherical mitochondria were more common, with some mitochondria displaying a normal shape.
Fig. 7 Optical microscope photograph between the groups at 24 h. A: HIE group (HE 100×), B: Leptin group (HE 100×), C: Control group (HE 100×). A: Pale cytoplasm, enlarged intercellular space, glial cells swelling, formation of red neurons (the arrow). B: Local cytoplasm pale, tissue loose, and irregular and sparse nucleus (the arrow).
Fig. 8 TEM photograph between the groups at 24 h. A: Control group (80000×), B: HIE group (80000×), C: HIE group (50000×), D: Leptin group (25000×). B: Mitochondrial swelling, mitochondrial ridge fracture, partial mitochondrial membrane rupture (black arrow). C: Autophagosomes with phagocytosis wrapped in the inner cavity (red arrow). D: Mild Mitochondrial swelling (white arrow).
Discussion Recent study on the neuroprotective effects of leptin found that leptin can reduce hypoxic–ischemic brain injury by reducing brain edema, inhibiting apoptosis, and promoting 14
energy metabolism (Hu et al., 2019), which provides a new direction for the treatment of neonatal HIE. Compared with traditional dMRI techniques, DKI can truly detect the true diffusion of water molecule pathologically (Rudrapatna et al., 2014). In addition to the advantages of the imaging model, DKI also has multiple parametric maps, which makes it possible to accurately evaluate the effects of leptin on hypoxic–ischemic brain edema. Imaging revealed that the lesions were distributed in the subcortical area and periventricular white matter. This is because of the increased blood supply in the basal ganglia area at the early stages of hypoxia–ischemia, resulting in blood flow redistribution. Therefore, the lesions in the subcortical area and periventricular white matter occurred early. As the two most characteristic parameters, the MK images showed an inhomogeneous high signal, whereas the MD images presented a relatively homogeneous low signal in the lesion areas, indicating that DKI could reflect the diffusion heterogeneity of water molecules caused by cytotoxic edema after hypoxia–ischemia. Moreover, larger percent changes have been consistently reported for kurtosis metrics than for diffusivity metrics in ischemic stroke (Yin et al., 2018; Wang et al., 2018), indicating that DKI parameters are more sensitive for detecting microstructure changes in brain tissue. Notably, in the HIE group, the percentage changes were larger along the axial direction (Ka and Da) than along the radial direction (Kr and Dr), and the majority of lesions were located in the white matter tissue, which may indicate that the axon injury was more severe than the myelin injury. This is also the reason for the inhomogeneous hyperintensity in the MK images. Recent studies (Guo et al., 2016; Zhang et al., 2016) showed that axonal varicosity and endoplasmic reticulum changes lead to higher axial diffusion limitations after cytotoxic edema. From 3 to 24 h, in the HIE group, the MK, Ka, Kr, MD, Da, and Dr values gradually changed in the lesion areas, which indicates a progressive increase in cytotoxic edema. Spampinato et al. (2017) reported that the higher the MK value, the lower the MD value, indicating a poor prognosis. At each time point, the parameter values and lesion areas in the leptin group significantly differed from those in the HIE group, and the trend of change in the parameter values in the leptin group was relatively moderate, suggesting that the degree of 15
brain injury in the leptin group was relatively mild. This finding indicates that leptin could effectively reduce hypoxic–ischemic brain edema. Finally, the pathological results also showed that there was significantly less cell and organelle damage in the leptin group than in the HIE group. In addition, autophagosomes were observed in the HIE group, which contained damaged organelles, indicating that hypoxia–ischemia activated autophagy in nerve cells, leading to further injury of nerve cells, which is consistent with a previously reported finding (Koike et al., 2008). In addition, we observed that the lesion area of MK was significantly smaller than that of MD in both the HIE and leptin groups, consistent with the results of relevant studies on cerebral infarction (Yin et al., 2018; Zhang et al., 2016). DKI has proved to be more accurate in reflecting the diffusion of water molecules because of its non-Gaussian nature. The results indicated that MK may reflect the actual range of cytotoxic edema and the severity of brain damage; however, this requires more accurate histological confirmation. As sensitive markers of hypoxic–ischemic brain injury, NSE and S100β have become reliable indicators for the early diagnosis of HIE. These two substances exist in normal brain tissues and have low peripheral blood levels because of the blood–brain barrier (Elshorbagy et al., 2019). When hypoxia–ischemia occurs, the blood–brain barrier is damaged, resulting in increased concentrations of NSE and S100β in the peripheral blood. Studies have shown that serum concentrations of NSE and S100β are significantly correlated with disease severity (Hoshi et al., 2005). In our study, the HIE group showed significantly higher serum levels of NSE and S100β at 24 h compared with the control group. Meanwhile, the NSE concentration of the leptin group was significantly lower than that of the HIE group, suggesting that the leptin group presented with a mild brain injury, which is consistent with the imaging and pathological findings. Unfortunately, no significant difference in S100β concentration was observed between the leptin group and the HIE group, although the leptin group showed lower values. A possible reason for the lack of a significant difference is the small sample size. Leptin has been demonstrated to be involved in the organization and maturation of the 16
nervous system. Leptin therapy can increase the density of neurons (Zhang et al., 2007), reduce apoptosis caused by HIE (Kumral et al., 2012), and improve spatial memory (Feng and Jiang 2018). The results of our study are consistent with previous reports that indicate that leptin treatment can reduce hypoxic–ischemic encephalopathy. The mechanism by which leptin alleviates early brain edema has not been clarified. Current studies suggest that aquaporin plays an active role in the formation of brain edema, among which aquaporin 4 (AQP4) is widely distributed on the membrane at the junction of the brain parenchyma and fluid components (Di et al., 2016). Using gene silencing technology to reduce the expression of the AQP4 gene can effectively reduce cytotoxic brain edema (Yang et al., 2015), suggesting that AQP4 plays an important role in the formation of early cytotoxic brain edema. Therefore, in this study, leptin may inhibit the expression of AQP4 to reduce brain edema. However, this mechanism requires further study. This study exhibits several limitations. First, the number of cases was small, due to the pathological images at each time point were not obtained. Therefore, the degree of cytotoxic edema cannot be observed dynamically from the pathology findings. Secondly, the expression of AQP4 in brain tissues was not detected; therefore, the neuroprotective mechanism of leptin could not be confirmed. Our future work aims to address these deficiencies. In addition, a prior study (Chuhutin et al., 2017) has suggested caution in evaluating results using DKI indicators obtained via different fitting techniques and b-value; our study only used workstations to post-process DKI. DKI images processed using the GE Advantage Workstation have been widely used in clinical studies with reliable results (Xu et al., 2016; Li et al., 2019). Furthermore, Diffusional Kurtosis Estimator software (http://nitrc.org/projects/dke) based on the MATLAB platform has also been recognized (Tabesh et al., 2011). In the future, it will be necessary to use additional image post-processing tools to comprehensively evaluate the results.
Conclusions 17
This controlled study showed that leptin can significantly relieve cytotoxic brain edema and exhibits a high value in the treatment of HIE. DKI, a very sensitive imaging technique to cytotoxic brain edema, with the advantage of being a more realistic imaging model, containing multiple b values and parameters, can more comprehensively and sensitively reflect the changes of brain tissue microstructure. Overall, DKI has a broad application prospect in clinical work as a dynamic and non-invasive method that can accurately evaluate HIE and its therapeutic effect.
Acknowledgements: Chao Yang and Jing Liu designed the study; Xiaoning He, Juan Xiao and Honghai Chen conducted the experiments, Juan Tian performed the statistical analysis; Xiaoning He wrote the manuscript. Declarations of interest: None Research involving Human Participants and/or Animals: The animal experiments complied with the NIH guidelines and were approved by the Animal Care and Use Committee of Dalian Medical University. Funding: This study was supported by the National Natural Science Foundation of China [grant number 81771663] and the Natural Science Foundation of Liaoning Province [grant number 20170540237].
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References Basser PJ, Pierpaoli C (2011) Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson 213:560-570. Cheung MM, Hui ES, Chan KC, Helpern JA, Qi L, Wu EX (2009) Does diffusion kurtosis imaging lead to better neural tissue characterization? A rodent brain maturation study. Neuroimage 45:386-392. Chuhutin A, Hansen B, Jespersen SN (2017) Precision and accuracy of diffusion kurtosis estimation and the influence of b-value selection. NMR Biomed 30:e3777. Davis C, Mudd J, Hawkins M (2014) Neuroprotective effects of leptin in the context of obesity and metabolic disorders. Neurobiol Dis 72:61-71. Di BB, Malik VA, Begum S, Jablonowski L, Gómez-González GB, Neumann ID, Rupprecht R (2016) Fluoxetine requires the endfeet protein aquaporin-4 to enhance plasticity of astrocyte processes. Front Cell Neurosci 10:8. Douglas-Escobar M, Weiss MD (2015) Hypoxic-ischemic encephalopathy: A review for the clinician. JAMA Pediatr 169:397-403. Elshorbagy HH, Barseem NF, Elsadek AE, Al-shokary AH, Maksoud YH, Abdulsamea SE, Talaat IM, Suliman HA, et al. (2019) The study of serum neuron-specific enolase and S100 calcium-binding protein B in pediatric diabetic ketoacidosis. J Clin Res Pediatr Endocrinol. Feng EC, Jiang L (2018) Effects of leptin on neurocognitive and motor functions in juvenile rats in a preterm brain damage model. Mol Med Rep 18:4095-4102. Guo YL, Li SJ, Zhang ZP, Shen ZW, Zhang GS, Yan G, Wang YT, Rao HB, et al. (2016) Parameters of diffusional kurtosis imaging for the diagnosis of acute cerebral infarction in different brain regions. Exp Ther Med 12:933-938. 19
Harrison L, Schriever SC, Feuchtinger A, Kyriakou E, Baumann P, Pfuhlmann K, Messias AC, Walch A, et al. (2019) Fluorescent blood–brain barrier tracing shows intact leptin transport in obese mice. Int J Obes 43:1305. Hoshi T, Kitagawa K, Yamagami H, Furukado S, Hougaku H, Hori M (2005) Relations of serum high-sensitivity C-reactive protein and interleukin-6 levels with silent brain infarction. Stroke 36:768-772. Hu S, Cheng D, Peng D, Tan J, Huang Y, Chen C (2019) Leptin attenuates cerebral ischemic injury in rats by modulating the mitochondrial electron transport chain via the mitochondrial STAT3 pathway. Brain Behav 9:e01200. Jensen JH, Helpern JA (2010) MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR Biomed 23:698-710. Kumral A, Yesilirmak DC, Sozmen S, Ergur BU, Tugyan K, Ozbal S, Guclu S, Duman N, et al. (2012) Effect of leptin treatment on neonatal hypoxic-ischemic brain injury. J Matern Fetal Neonatal Med 25:141-146. Kline-Fath BM, Horn PS, Yuan W, Merhar S, Venkatesan C, Thomas CW, Schapiro MB (2018) Conventional MRI scan and DTI imaging show more severe brain injury in neonates with hypoxic-ischemic encephalopathy and seizures. Early Hum Dev 122:8-14. Koike M，Shibata M，Tadakoshi M, Gotoh K, Komatsu M, Waguri S, Kawahara N, Kuida K, et al. (2008) Inhibition of autophagy prevents hippocampal pyramidal neuron death after hypoxic-ischemic injury. Am J Pathol 172:454-469. Li C, Lan C, Zhang X, Yin L, Hao X, Tian J, Lin L, Sun H, et al. (2019) Evaluation of Diffusional Kurtosis Imaging in Sub-acute Ischemic Stroke: Comparison with Rehabilitation Treatment Effect. Cell Transplant 28:1053-1061. Li M, Chen L, Tian S, Lin Y, Tang Q, Zhou X, Li D, Yeung CK, et al. (2017) Comprehensive variation discovery and recovery of missing sequence in the pig genome 20
using multiple de novo assemblies. Genome Res 27:865-874. Rudrapatna SU, Wieloch T, Beirup K, Ruscher K, Mol W, Yanev P, Leemans A, van der Toorn A, et al. (2014) Can diffusion kurtosis imaging improve the sensitivity and specificity of detecting microstructural alterations in brain tissue chronically after experimental stroke? Comparisons with diffusion tensor imaging and histology. Neuroimage 97:363-373. Spampinato MV, Chan C, Jensen JH, Helpern JA, Bonilha L, Kautz SA, Nietert PJ, Feng W (2017) Diffusional kurtosis imaging and motor outcome in acute ischemic stroke. AJNR 38:1328-1334. Tabesh A, Jensen JH, Ardekani BA, Helpern JA (2011) Estimation of tensors and tensor-derived measures in diffusional kurtosis imaging. Magn Reson Med 65:823-836. Wang E, Wu Y, Cheung JS, Zhou IY, Igarashi T, Zhang X, Sun PZ (2017) pH imaging reveals worsened tissue acidification in diffusion kurtosis lesion than the kurtosis/diffusion lesion mismatch in an animal model of acute stroke. J Cereb Blood Flow Metab 37:3325-3333. Wang ML, Yu MM, Yang DX, Liu YL, Wei XE, Li WB (2018) Longitudinal microstructural changes in traumatic brain injury in rats: a diffusional kurtosis imaging, histology, and behavior study. AJNR 39:1650-1656. Xu S, Ye D, Lian T, Cai J, Xiao Z, Huang Y, Chen X, Zhang Z (2016) Assessment of severity of leukoaraiosis: a diffusional kurtosis imaging study. Clin Imaging 40:732-738. Yang C, Liu Z, Li H, Zhai F, Liu J, Bian J (2015) Aquaporin-4 knockdown ameliorates hypoxic-ischemic cerebral edema in newborn piglets. IUBMB Life, 2015, 67:182-190. Yin J, Sun H, Wang Z, Ni H, Shen W, Sun PZ (2018) Diffusion kurtosis imaging of acute infarction: comparison with routine diffusion and follow-up MR imaging. Radiology 287:651-657. 21
Zhang F, Wang S, Signore AP, Chen J (2007) Neuroprotective effects of leptin against ischemic injury induced by oxygen-glucose deprivation and transient cerebral ischemia. Stroke 38:2329-2336. Zhang S, Yao Y, Shi J, Tang X, Zhao L, Zhu W (2016) The temporal evolution of diffusional kurtosis imaging in an experimental middle cerebral artery occlusion (MCAO) model. Magn Reson Imaging 34:889-895.
Highlights
Leptin effectively reduces hypoxic-ischemic cerebral edema in newborn piglets.
DKI provides more detailed microstructural data of hypoxic/ischemic brain edema.
DKI serves as a model for measuring non-gaussian water diffusion.
DKI dynamically evaluated the neuroprotective effects of leptin.
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