Differentiation of the Infarct Core from Ischemic Penumbra within the First 4.5 Hours, Using Diffusion Tensor Imaging-Derived Metrics: A Rat Model

Anisotropy component of DTI reveals long-term neuroinflammation following repetitive mild traumatic brain injury in rats

BACKGROUND

This study aimed to investigate the long-term effects of repetitive mild traumatic brain injury (rmTBI) with varying inter-injury intervals by measuring diffusion tensor metrics, including mean diffusivity (MD), fractional anisotropy (FA), and diffusion magnitude (L) and pure anisotropy (q).

METHODS

Eighteen rats were randomly divided into three groups: short-interval rmTBI (n = 6), long-interval rmTBI (n = 6), and sham controls (n = 6). MD, FA, L, and q values were analyzed from longitudinal diffusion tensor imaging at days 50 and 90 after rmTBI. Immunohistochemical staining against neurons, astrocytes, microglia, and myelin was performed. Analysis of variance, Pearson correlation coefficient, and simple linear regression model were used.

RESULTS

At day 50 post-rmTBI, lower cortical FA and q values were shown in the short-interval group (p ≤ 0.038). In contrast, higher FA and q values were shown for the long-interval group (p ≤ 0.039) in the corpus callosum. In the ipsilesional external capsule and internal capsule, no significant changes were found in FA, while lower L and q values were shown in the short-interval group (p ≤ 0.028) at day 90. The q values in the external capsule and internal capsule were negatively correlated with the number of microglial cells and the total number of astroglial cells (p ≤ 0.035).

CONCLUSION

Tensor scalar measurements, such as L and q values, are sensitive to exacerbated chronic injury induced by rmTBI with shorter inter-injury intervals and reflect long-term astrogliosis induced by the cumulative injury.

RELEVANCE STATEMENT

Tensor scalar measurements, including L and q values, are potential DTI metrics for detecting long-term and subtle injury following rmTBI; in particular, q values may be used for quantifying remote white matter (WM) changes following rmTBI.

KEY POINTS

The alteration of L and q values was demonstrated after chronic repetitive mild traumatic brain injury. Changing q values were observed in the impact site and remote WM. The lower q values in the remote WM were associated with astrogliosis.

Ischemia-reperfusion injury in a salvaged penumbra: Longitudinal high-tesla perfusion magnetic resonance imaging in a rat model

INTRODUCTION

Although ischemia-reperfusion (I/R) injury varies between cortical and subcortical regions, its effects on specific regions remain unclear. In this study, we used various magnetic resonance imaging (MRI) techniques to examine the spatiotemporal dynamics of I/R injury within the salvaged ischemic penumbra (IP) and reperfused ischemic core (IC) of a rodent model, with the aim of enhancing therapeutic strategies by elucidating these dynamics.

MATERIALS AND METHODS

A total of 17 Sprague-Dawley rats were subjected to 1 h of transient middle cerebral artery occlusion with a suture model. MRI, including diffusion tensor imaging (DTI), T2-weighted imaging, perfusion-weighted imaging, and T1 mapping, was conducted at multiple time points for up to 5 days during the I/R phases. The spatiotemporal dynamics of blood-brain barrier (BBB) modifications were characterized through changes in T1 within the IP and IC regions and compared with mean diffusivity (MD), T2, and cerebral blood flow.

RESULTS

During the I/R phases, the MD of the IC initially decreased, normalized after recanalization, decreased again at 24 h, and peaked on day 5. By contrast, the IP remained relatively stable. Both the IP and IC exhibited hyperperfusion, with the IP reaching its peak at 24 h, followed by resolution, whereas hyperperfusion was maintained in the IC until day 5. Despite hyperperfusion, the IP maintained an intact BBB, whereas the IC experienced persistent BBB leakage. At 24 h, the IC exhibited an increase in the T2 signal, corresponding to regions exhibiting BBB disruption at 5 days.

CONCLUSIONS

Hyperperfusion and BBB impairment have distinct patterns in the IP and IC. Quantitative T1 mapping may serve as a supplementary tool for the early detection of malignant hyperemia accompanied by BBB leakage, aiding in precise interventions after recanalization. These findings underscore the value of MRI markers in monitoring ischemia-specific regions and customizing therapeutic strategies to improve patient outcomes.

Estimating the volume of penumbra in rodents using DTI and stack-based ensemble machine learning framework

BACKGROUND

This study investigates the potential of diffusion tensor imaging (DTI) in identifying penumbral volume (PV) compared to the standard gadolinium-required perfusion-diffusion mismatch (PDM), utilizing a stack-based ensemble machine learning (ML) approach with enhanced explainability.

METHODS

Sixteen male rats were subjected to middle cerebral artery occlusion. The penumbra was identified using PDM at 30 and 90 min after occlusion. We used 11 DTI-derived metrics and 14 distance-based features to train five voxel-wise ML models. The model predictions were integrated using stack-based ensemble techniques. ML-estimated and PDM-defined PVs were compared to evaluate model performance through volume similarity assessment, the Pearson correlation analysis, and Bland-Altman analysis. Feature importance was determined for explainability.

RESULTS

In the test rats, the ML-estimated median PV was 106.4 mL (interquartile range 44.6-157.3 mL), whereas the PDM-defined median PV was 102.0 mL (52.1-144.9 mL). These PVs had a volume similarity of 0.88 (0.79-0.96), a Pearson correlation coefficient of 0.93 (p < 0.001), and a Bland-Altman bias of 2.5 mL (2.4% of the mean PDM-defined PV), with 95% limits of agreement ranging from -44.9 to 49.9 mL. Among the features used for PV prediction, the mean diffusivity was the most important feature.

CONCLUSIONS

Our study confirmed that PV can be estimated using DTI metrics with a stack-based ensemble ML approach, yielding results comparable to the volume defined by the standard PDM. The model explainability enhanced its clinical relevance. Human studies are warranted to validate our findings.

RELEVANCE STATEMENT

The proposed DTI-based ML model can estimate PV without the need for contrast agent administration, offering a valuable option for patients with kidney dysfunction. It also can serve as an alternative if perfusion map interpretation fails in the clinical setting.

KEY POINTS

• Penumbral volume can be estimated by DTI combined with stack-based ensemble ML. • Mean diffusivity was the most important feature used for predicting penumbral volume. • The proposed approach can be beneficial for patients with kidney dysfunction.

A prospective reappraisal of motor outcome prediction in patients with acute stroke by using atlas-based diffusion tensor imaging biomarkers

BACKGROUND

Diffusion tensor imaging (DTI) biomarkers can be used to quantify microstructural changes in the cerebral white matter (WM) following injury.

OBJECTIVES

This prospective single-center study aimed to evaluate whether atlas-based DTI-derived metrics obtained within 1 week after stroke can predict the motor outcome at 3 months.

METHODS

Forty patients with small acute stroke (2-7 days after onset) involving the corticospinal tract were included. Each patient underwent magnetic resonance imaging (MRI) within 1 week and at 3 months after stroke, and the changes based on DTI-derived metrics were compared by performing WM tract atlas-based quantitative analysis.

RESULTS

A total of 40 patients were included, with median age 63.5 years and a majority of males (72.5%). Patients were classified into good-prognosis group (mRS 0-2, n = 27) and poor-prognosis group (mRS 3-5, n = 13) by outcome. The median (25th-75th percentile) of MD (0.7 (0.6-0.7) vs. 0.7 (0.7-0.8); p = 0.049) and AD (0.6 (0.5, 0.7) vs. 0.7 (0.6, 0.8); p = 0.023) ratios within 1 week were significantly lower in the poor-prognosis group compared to the good-prognosis group. The ROC curve of the combined DTI-derived metrics model showed comparable Youden index (65.5% vs. 58.4%-65.4%) and higher specificity (96.3% vs. 69.2%-88.5%) compared to clinical indexes. The area under the ROC curve of the combined DTI-derived metrics model is comparable to those of the clinical indexes (all p > 0.1) and higher than those of the individual DTI-derived metrics parameters.

CONCLUSIONS

Atlas-based DTI-derived metrics at acute stage provide objective information for prognosis prediction of patients with ischemic or lacunar stroke.

Synthetic Adrenocorticotropic Peptides Modulate the Expression Pattern of Immune Genes in Rat Brain following the Early Post-Stroke Period

Ischemic stroke is an acute local decrease in cerebral blood flow due to a thrombus or embolus. Of particular importance is the study of the genetic systems that determine the mechanisms underlying the formation and maintenance of a therapeutic window (a time interval of up to 6 h after a stroke) when effective treatment can be provided. Here, we used a transient middle cerebral artery occlusion (tMCAO) model in rats to study two synthetic derivatives of adrenocorticotropic hormone (ACTH). The first was ACTH(4-7)PGP, which is known as Semax. It is actively used as a neuroprotective drug. The second was the ACTH(6-9)PGP peptide, which is elucidated as a prospective agent only. Using RNA-Seq analysis, we revealed hundreds of ischemia-related differentially expressed genes (DEGs), as well as 131 and 322 DEGs related to the first and second peptide at 4.5 h after tMCAO, respectively, in dorsolateral areas of the frontal cortex of rats. Furthermore, we showed that both Semax and ACTH(6-9)PGP can partially prevent changes in the immune- and neurosignaling-related gene expression profiles disturbed by the action of ischemia at 4.5 h after tMCAO. However, their different actions with regard to predominantly immune-related genes were also revealed. This study gives insight into how the transcriptome depends on the variation in the structure of the related peptides, and it is valuable from the standpoint of the development of measures for early post-stroke therapy.

Altered diffusivity of the subarachnoid cisterns in the rat brain following neurological disorders

BACKGROUND

Although changes in diffusion characteristics of the brain parenchyma in neurological disorders are widely studied and used in clinical practice, the change in diffusivity in the cerebrospinal fluid (CSF) system is rarely reported. In this study, free water diffusion in the subarachnoid cisterns and ventricles of the rat brain was examined using diffusion magnetic resonance imaging (MRI), and the effects of neurological disorders on diffusivity in CSF system were investigated.

METHODS

Diffusion MRI and T₂-weighted images were obtained in the intact rats, 24 h after ischemic stroke, and 50 days after mild traumatic brain injury (mTBI). We conducted the assessment of diffusivity in the rat brain in the subarachnoid cisterns around the midbrain, as well as the lateral ventricles. One-way ANOVA and Kruskal-Wallis test were used to evaluate the change in mean diffusivity (MD) and MD histogram, respectively, in CSF system following different neurological disease.

RESULTS

A significant decrease in the mean MD value of the subarachnoid cisterns was observed in the stroke rats compared with the intact and mTBI rats (p < 0.005). In addition, the skewness (p < 0.002), maximum MD (p < 0.002), and MD percentiles (p < 0.002) in the stroke rats differed significantly from those in the intact and mTBI rats. By contrast, no difference was observed in the mean MD value of the lateral ventricles among three groups of rats. We proposed that the assessment of the subarachnoid cisterns, rather than the lateral ventricles, in the rat brain would be useful in providing diffusion information in the CSF system.

CONCLUSIONS

Alterations in MD parameters of the subarachnoid cisterns after stroke provide evidence that brain injury may alter the characteristics of free water diffusion not only in the brain parenchyma but also in the CSF system.

Early neuroimaging and ultrastructural correlates of injury outcome after neonatal hypoxic-ischaemia

Hypoxic ischaemia encephalopathy is the major cause of brain injury in new-borns. However, to date, useful biomarkers which may be used to early predict neurodevelopmental impairment for proper commencement of hypothermia therapy is still lacking. This study aimed to determine whether the early neuroimaging characteristics and ultrastructural correlates were associated with different injury progressions and brain damage severity outcomes after neonatal hypoxic ischaemia. Longitudinal 7 T MRI was performed within 6 h, 24 h and 7 days after hypoxic ischaemia in rat pups. The brain damage outcome at 7 days post-hypoxic ischaemia assessed using histopathology and MRI were classified as mild, moderate and severe. We found there was a spectrum of different brain damage severity outcomes after the same duration of hypoxic ischaemia. The severity of brain damage determined using MRI correlated well with that assessed by histopathology. Quantitative MRI characteristics denoting water diffusivity in the tissue showed significant differences in the apparent diffusion coefficient deficit volume and deficit ratios within 6 h, at 24 h and 7 days after hypoxic ischaemia among the 3 different outcome groups. The susceptible brain areas to hypoxic ischaemia were revealed by the temporal changes in regional apparent diffusion coefficient values among three outcome groups. Within 6 h post-hypoxic ischaemia, a larger apparent diffusion coefficient deficit volume and deficit ratios and lower apparent diffusion coefficient values were highly associated with adverse brain damage outcome. In the apparent diffusion coefficient deficit areas detected early after hypoxic ischaemia which were highly associated with severe damage outcome, transmission electron microscopy revealed fragmented nuclei; swollen rough endoplasmic reticulum and degenerating mitochondria in the cortex and prominent myelin loss and axon detraction in the white matter. Taken together, different apparent diffusion coefficient patterns obtained early after hypoxic ischaemia are highly associated with different injury progression leading to different brain damage severity outcomes, suggesting the apparent diffusion coefficient characteristics may be applicable to early identify the high-risk neonates for hypothermia therapy.

Machine learning-based segmentation of ischemic penumbra by using diffusion tensor metrics in a rat model

Background

Recent trials have shown promise in intra-arterial thrombectomy after the first 6–24 h of stroke onset. Quick and precise identification of the salvageable tissue is essential for successful stroke management. In this study, we examined the feasibility of machine learning (ML) approaches for differentiating the ischemic penumbra (IP) from the infarct core (IC) by using diffusion tensor imaging (DTI)-derived metrics.

Methods

Fourteen male rats subjected to permanent middle cerebral artery occlusion (pMCAO) were included in this study. Using a 7 T magnetic resonance imaging, DTI metrics such as fractional anisotropy, pure anisotropy, diffusion magnitude, mean diffusivity (MD), axial diffusivity, and radial diffusivity were derived. The MD and relative cerebral blood flow maps were coregistered to define the IP and IC at 0.5 h after pMCAO. A 2-level classifier was proposed based on DTI-derived metrics to classify stroke hemispheres into the IP, IC, and normal tissue (NT). The classification performance was evaluated using leave-one-out cross validation.

Results

The IC and non-IC can be accurately segmented by the proposed 2-level classifier with an area under the receiver operating characteristic curve (AUC) between 0.99 and 1.00, and with accuracies between 96.3 and 96.7%. For the training dataset, the non-IC can be further classified into the IP and NT with an AUC between 0.96 and 0.98, and with accuracies between 95.0 and 95.9%. For the testing dataset, the classification accuracy for IC and non-IC was 96.0 ± 2.3% whereas for IP and NT, it was 80.1 ± 8.0%. Overall, we achieved the accuracy of 88.1 ± 6.7% for classifying three tissue subtypes (IP, IC, and NT) in the stroke hemisphere and the estimated lesion volumes were not significantly different from those of the ground truth (p = .56, .94, and .78, respectively).

Conclusions

Our method achieved comparable results to the conventional approach using perfusion–diffusion mismatch. We suggest that a single DTI sequence along with ML algorithms is capable of dichotomizing ischemic tissue into the IC and IP.

Behavioral and Structural Effects of Single and Repeat Closed-Head Injury

BACKGROUND AND PURPOSE

The effects of multiple head impacts, even without detectable primary injury, on subsequent behavioral impairment and structural abnormality is yet well explored. Our aim was to uncover the dynamic changes and long-term effects of single and repetitive head injury without focal contusion on tissue microstructure and macrostructure.

MATERIALS AND METHODS

We introduced a repetitive closed-head injury rodent model (n = 70) without parenchymal lesions. We performed a longitudinal MR imaging study during a 50-day study period (T₂-weighted imaging, susceptibility-weighted imaging, and diffusion tensor imaging) as well as sequential behavioral assessment. Immunohistochemical staining for astrogliosis was examined in a subgroup of animals. Paired and independent t tests were used to evaluate the outcome change after injury and the cumulative effects of impact load, respectively.

RESULTS

There was no gross morphologic evidence for head injury such as skull fracture, contusion, or hemorrhage on micro-CT and MR imaging. A significant decrease of white matter fractional anisotropy from day 21 on and an increase of gray matter fractional anisotropy from day 35 on were observed. Smaller mean cortical volume in the double-injury group was shown at day 50 compared with sham and single injury (P < .05). Behavioral deficits (P < .05) in neurologic outcome, balance, and locomotor activity were also aggravated after double injury. Histologic analysis showed astrogliosis 24 hours after injury, which persisted throughout the study period.

CONCLUSIONS

There are measurable and dynamic changes in microstructure, cortical volume, behavior, and histopathology after both single and double injury, with more severe effects seen after double injury. This work bridges cross-sectional evidence from human subject and pathologic studies using animal models with a multi-time point, longitudinal research paradigm.

Diffusion Tensor-Derived Properties of Benign Oligemia, True "at Risk" Penumbra, and Infarct Core during the First Three Hours of Stroke Onset: A Rat Model

Objective

The aim of this study was to investigate diffusion tensor (DT) imaging-derived properties of benign oligemia, true “at risk” penumbra (TP), and the infarct core (IC) during the first 3 hours of stroke onset.

Materials and Methods

The study was approved by the local animal care and use committee. DT imaging data were obtained from 14 rats after permanent middle cerebral artery occlusion (pMCAO) using a 7T magnetic resonance scanner (Bruker) in room air. Relative cerebral blood flow and apparent diffusion coefficient (ADC) maps were generated to define oligemia, TP, IC, and normal tissue (NT) every 30 minutes up to 3 hours. Relative fractional anisotropy (rFA), pure anisotropy (rq), diffusion magnitude (rL), ADC (rADC), axial diffusivity (rAD), and radial diffusivity (rRD) values were derived by comparison with the contralateral normal brain.

Results

The mean volume of oligemia was 24.7 ± 14.1 mm³, that of TP was 81.3 ± 62.6 mm³, and that of IC was 123.0 ± 85.2 mm³ at 30 minutes after pMCAO. rFA showed an initial paradoxical 10% increase in IC and TP, and declined afterward. The rq, rL, rADC, rAD, and rRD showed an initial discrepant decrease in IC (from −24% to −36%) as compared with TP (from −7% to −13%). Significant differences (p < 0.05) in metrics, except rFA, were found between tissue subtypes in the first 2.5 hours. The rq demonstrated the best overall performance in discriminating TP from IC (accuracy = 92.6%, area under curve = 0.93) and the optimal cutoff value was −33.90%. The metric values for oligemia and NT remained similar at all time points.

Conclusion

Benign oligemia is small and remains microstructurally normal under pMCAO. TP and IC show a distinct evolution of DT-derived properties within the first 3 hours of stroke onset, and are thus potentially useful in predicting the fate of ischemic brain.