Genetic underpinnings of cerebral edema in acute brain injury: an opportunity for pathway discovery

Imaging biomarkers of cerebral edema automatically extracted from routine CT scans of large vessel occlusion strokes

BACKGROUND AND PURPOSE

Volumetric and densitometric biomarkers have been proposed to better quantify cerebral edema after stroke, but their relative performance has not been rigorously evaluated.

METHODS

Patients with large vessel occlusion stroke from three institutions were analyzed. An automated pipeline extracted brain, cerebrospinal fluid (CSF), and infarct volumes from serial CTs. Several biomarkers were measured: change in global CSF volume from baseline (ΔCSF); ratio of CSF volumes between hemispheres (CSF ratio); and relative density of infarct region compared with mirrored contralateral region (net water uptake [NWU]). These were compared to radiographic standards, midline shift and relative hemispheric volume (RHV) and malignant edema, defined as deterioration resulting in need for osmotic therapy, decompressive surgery, or death.

RESULTS

We analyzed 255 patients with 210 baseline CTs, 255 24-hour CTs, and 81 72-hour CTs. Of these, 35 (14%) developed malignant edema and 63 (27%) midline shift. CSF metrics could be calculated for 310 (92%), while NWU could only be obtained from 193 (57%). Peak midline shift was correlated with baseline CSF ratio (ρ = -.22) and with CSF ratio and ΔCSF at 24 hours (ρ = -.55/.63) and 72 hours (ρ = -.66/.69), but not with NWU (ρ = .15/.25). Similarly, CSF ratio was correlated with RHV (ρ = -.69/-.78), while NWU was not. Adjusting for age, National Institutes of Health Stroke Scale, tissue plasminogen activator treatment, and Alberta Stroke Program Early CT Score, CSF ratio (odds ratio [OR]: 1.95 per 0.1, 95% confidence interval [CI]: 1.52-2.59) and ΔCSF at 24 hours (OR: 1.87 per 10%, 95% CI: 1.47-2.49) were associated with malignant edema.

CONCLUSION

CSF volumetric biomarkers can be automatically measured from almost all routine CTs and correlate better with standard edema endpoints than net water uptake.

On Net Water Uptake in Posttraumatic Ischemia Foci

BACKGROUND

The influence of cerebral edema and resultant secondary complications on the clinical outcome of traumatic brain injury (TBI) is well known. Clinical studies of brain water homeostasis dynamics in TBI are limited, which determines the relevance of our work. The purpose is to study changes in brain water homeostasis after TBI of varying severity compared to corresponding cerebral microcirculation parameters.

MATERIALS

This non-randomized retrospective single-center study complies with the Helsinki Declaration for patient's studies. The study included 128 patients with posttraumatic ischemia (PCI) after moderate-to-severe TBI in the middle cerebral artery territory who were admitted to the hospital between July 2015 and February 2022. PCI was evaluated by perfusion computed tomography (CT), and brain edema was determined using net water uptake (NWU) on baseline CT images. The patients were allocated according to Marshall's classification. Multivariate linear regression models were performed to analyze data.

RESULTS

NWU in PCI areas were significantly higher than in patients with its absence (8.1% vs. 4.2%, accordingly; p < 0.001). In the multivariable regression analysis, the mean transit time increase was significantly and independently associated with higher NWU (R2 = 0.089, p < 0.01). In the PCI zone, cerebral blood flow, cerebral blood volume, and time to peak were not significantly associated with NWU values (p > 0.05). No significant differences were observed between the NWU values in PCI foci in different Marshall groups (p = 0.308).

CONCLUSION

Marshall's classification does not predict the progression of posttraumatic ischemia. The blood passage delays through the cerebral microvascular bed is associated with brain tissue water content increase in the PCI focus.

A Focal Impact Model of Traumatic Brain Injury in Xenopus Tadpoles Reveals Behavioral Alterations, Neuroinflammation, and an Astroglial Response

Traumatic Brain Injury (TBI) is a global driver of disability, and we currently lack effective therapies to promote neural repair and recovery. TBI is characterized by an initial insult, followed by a secondary injury cascade, including inflammation, excitotoxicity, and glial cellular response. This cascade incorporates molecular mechanisms that represent potential targets of therapeutic intervention. In this study, we investigate the response to focal impact injury to the optic tectum of Xenopus laevis tadpoles. This injury disrupts the blood-brain barrier, causing edema, and produces deficits in visually-driven behaviors which are resolved within one week. Within 3 h, injured brains show a dramatic transcriptional activation of inflammatory cytokines, upregulation of genes associated with inflammation, and recruitment of microglia to the injury site and surrounding tissue. Shortly afterward, astrocytes undergo morphological alterations and accumulate near the injury site, and these changes persist for at least 48 h following injury. Genes associated with astrocyte reactivity and neuroprotective functions also show elevated levels of expression following injury. Since our results demonstrate that the response to focal impact injury in Xenopus resembles the cellular alterations observed in rodents and other mammalian models, the Xenopus tadpole offers a new, scalable vertebrate model for TBI.

Automated Measurement of Net Water Uptake From Baseline and Follow-Up CTs in Patients With Large Vessel Occlusion Stroke

Quantifying the extent and evolution of cerebral edema developing after stroke is an important but challenging goal. Lesional net water uptake (NWU) is a promising CT-based biomarker of edema, but its measurement requires manually delineating infarcted tissue and mirrored regions in the contralateral hemisphere. We implement an imaging pipeline capable of automatically segmenting the infarct region and calculating NWU from both baseline and follow-up CTs of large-vessel occlusion (LVO) patients. Infarct core is extracted from CT perfusion images using a deconvolution algorithm while infarcts on follow-up CTs were segmented from non-contrast CT (NCCT) using a deep-learning algorithm. These infarct masks were flipped along the brain midline to generate mirrored regions in the contralateral hemisphere of NCCT; NWU was calculated as one minus the ratio of densities between regions, removing voxels segmented as CSF and with HU outside thresholds of 20-80 (normal hemisphere and baseline CT) and 0-40 (infarct region on follow-up). Automated results were compared with those obtained using manually-drawn infarcts and an ASPECTS region-of-interest based method that samples densities within the infarct and normal hemisphere, using intraclass correlation coefficient (ρ). This was tested on serial CTs from 55 patients with anterior circulation LVO (including 66 follow-up CTs). Baseline NWU using automated core was 4.3% (IQR 2.6-7.3) and correlated with manual measurement (ρ = 0.80, p < 0.0001) and ASPECTS (r = -0.60, p = 0.0001). Automatically segmented infarct volumes (median 110-ml) correlated to manually-drawn volumes (ρ = 0.96, p < 0.0001) with median Dice similarity coefficient of 0.83 (IQR 0.72-0.90). Automated NWU was 24.6% (IQR 20-27) and highly correlated to NWU from manually-drawn infarcts (ρ = 0.98) and the sampling-based method (ρ = 0.68, both p < 0.0001). We conclude that this automated imaging pipeline is able to accurately quantify region of infarction and NWU from serial CTs and could be leveraged to study the evolution and impact of edema in large cohorts of stroke patients.

Early complementary acupuncture improves the clinical prognosis of traumatic brain edema: A randomized controlled trial

BACKGROUND

Traumatic brain edema occurs commonly brain injury, and most manifests as pericontusional edema of brain contusions. On the basis of evidence-based medicine, apart from recommending craniotomy and mannitol, there are few particularly effective measures to prevent and treat traumatic brain edema. It is uncertain whether an early complementary acupuncture treatment would improve long-term outcomes of patients with traumatic brain edema. The aim of this study is to assess the efficacy and the safety of early complementary acupuncture for patients with traumatic brain edema.

METHODS

This study is an actively accruing, single-center, single-blinded, 2-arm, randomized controlled trial. Patients with traumatic brain injury, a Glasgow Coma Scale score of 6∼12, and brain edema on computed tomography scan will be divided into 2 groups on the basis of stratified block randomization. All patients will receive conventional treatment, and the study group will undergo additional acupuncture therapy (start within 72 hours after the injury) once a day for 28 days. The primary outcome is the dichotomized Glasgow Outcome Score at 6 months and 12 months after injury, and the secondary outcomes are the Glasgow Coma Scale, the volume of traumatic brain edema, the serum levels of C-reactive protein and interleukin-6, and the Modified Barthel Index.

DISCUSSION

This study will provide data regarding the efficacy of early complementary acupuncture for traumatic brain edema. If the study yields positive results, its findings may offer insights into a valuable complementary option of acupuncture for traumatic brain edema that could provide pilot evidence for large, randomized, controlled trials.Trial registration: This trial has been published in the Chinese Clinical Trial Register, http://www.chictr.org.cn/edit.aspx?pid=141208&htm=4 (Identifier: ChiCTR2100053794, registered on December 3, 2021).

Accelerating Prediction of Malignant Cerebral Edema After Ischemic Stroke with Automated Image Analysis and Explainable Neural Networks

BACKGROUND

Malignant cerebral edema is a devastating complication of stroke, resulting in deterioration and death if hemicraniectomy is not performed prior to herniation. Current approaches for predicting this relatively rare complication often require advanced imaging and still suffer from suboptimal performance. We performed a pilot study to evaluate whether neural networks incorporating data extracted from routine computed tomography (CT) imaging could enhance prediction of edema in a large diverse stroke cohort.

METHODS

An automated imaging pipeline retrospectively extracted volumetric data, including cerebrospinal fluid (CSF) volumes and the hemispheric CSF volume ratio, from baseline and 24 h CT scans performed in participants of an international stroke cohort study. Fully connected and long short-term memory (LSTM) neural networks were trained using serial clinical and imaging data to predict those who would require hemicraniectomy or die with midline shift. The performance of these models was tested, in comparison with regression models and the Enhanced Detection of Edema in Malignant Anterior Circulation Stroke (EDEMA) score, using cross-validation to construct precision-recall curves.

RESULTS

Twenty of 598 patients developed malignant edema (12 required surgery, 8 died). The regression model provided 95% recall but only 32% precision (area under the precision-recall curve [AUPRC] 0.74), similar to the EDEMA score (precision 28%, AUPRC 0.66). The fully connected network did not perform better (precision 33%, AUPRC 0.71), but the LSTM model provided 100% recall and 87% precision (AUPRC 0.97) in the overall cohort and the subgroup with a National Institutes of Health Stroke Scale (NIHSS) score ≥ 8 (p = 0.0001 vs. regression and fully connected models). Features providing the most predictive importance were the hemispheric CSF ratio and NIHSS score measured at 24 h.

CONCLUSIONS

An LSTM neural network incorporating volumetric data extracted from routine CT scans identified all cases of malignant cerebral edema by 24 h after stroke, with significantly fewer false positives than a fully connected neural network, regression model, and the validated EDEMA score. This preliminary work requires prospective validation but provides proof of principle that a deep learning framework could assist in selecting patients for surgery prior to deterioration.