Abilities of a Densitometric Analysis of Computed Tomography Images and Hemorrhagic Parameters to Predict Outcome Favorability in Patients With Intracerebral Hemorrhage

Formic acid induces hypertension-related hemorrhage in hSSAOTG in mice and human

Hypertension is a confirmed risk factor for cerebral hemorrhage in humans. Which endogenous factor directly induces hypertension-related hemorrhage is unclear. In this study, 42 hemorrhagic patients with hypertension and hyperlipidemia and 42 age-matched healthy controls were enrolled. The contents of serum semicarbazide-sensitive amine oxidase (SSAO) and formic acid (FC, FC is a final product of SSAO through the oxidation of endogenous formaldehyde, which results from the enzymatic oxidative deamination of the SSAO substrate, methylamine) were examined in the patients after stroke. Hemorrhagic areas were quantified by computer tomography. In the animal study, hemorrhagic degree was assessed by hemotoxylin & eosin or tissue hemoglobin kits. The relationship between FC and blood pressure/hemorrhagic degree was examined in wild-type mice and hSSAO^TG mice fed with high-fat diets or high-fat and -salt diets. The results showed that the levels of serum FC were positively correlated with blood pressure and hemorrhagic areas in hemorrhagic patients. Transfection of microRNA-134 could enhance SSAO expression in human vascular smooth muscle cells. Consistently, after treatment with high-fat and -salt diets, hSSAO^TG mice exhibited higher levels of miR134 and FC, higher blood pressure, and more severe hemorrhage than wild-type mice. Interestingly, folic acid reduced hypertension and hemorrhage in hSSAO^TG mice fed with high-fat diets. These findings suggest that FC is a crucial endogenous factor for hypertension and hemorrhage.

Intracranial Densitometry-Augmented Machine Learning Enhances the Prognostic Value of Brain CT in Pediatric Patients With Traumatic Brain Injury: A Retrospective Pilot Study

Background: The inter- and intrarater variability of conventional computed tomography (CT) classification systems for evaluating the extent of ischemic-edematous insult following traumatic brain injury (TBI) may hinder the robustness of TBI prognostic models. Objective: This study aimed to employ fully automated quantitative densitometric CT parameters and a cutting-edge machine learning algorithm to construct a robust prognostic model for pediatric TBI. Methods: Fifty-eight pediatric patients with TBI who underwent brain CT were retrospectively analyzed. Intracranial densitometric information was derived from the supratentorial region as a distribution representing the proportion of Hounsfield units. Furthermore, a machine learning-based prognostic model based on gradient boosting (i.e., CatBoost) was constructed with leave-one-out cross-validation. At discharge, the outcome was assessed dichotomously with the Glasgow Outcome Scale (favorability: 1-3 vs. 4-5). In-hospital mortality, length of stay (>1 week), and need for surgery were further evaluated as alternative TBI outcome measures. Results: Densitometric parameters indicating reduced brain density due to subtle global ischemic changes were significantly different among the TBI outcome groups, except for need for surgery. The skewed intracranial densitometry of the unfavorable outcome became more distinguishable in the follow-up CT within 48 h. The prognostic model augmented by intracranial densitometric information achieved adequate AUCs for various outcome measures [favorability = 0.83 (95% CI: 0.72-0.94), in-hospital mortality = 0.91 (95% CI: 0.82-1.00), length of stay = 0.83 (95% CI: 0.72-0.94), and need for surgery = 0.71 (95% CI: 0.56-0.86)], and this model showed enhanced performance compared to the conventional CRASH-CT model. Conclusion: Densitometric parameters indicative of global ischemic changes during the acute phase of TBI are predictive of a worse outcome in pediatric patients. The robustness and predictive capacity of conventional TBI prognostic models might be significantly enhanced by incorporating densitometric parameters and machine learning techniques.

Changes in the gray and white matter of patients with ischemic-edematous insults after traumatic brain injury

OBJECTIVE

Gray matter (GM) and white matter (WM) are vulnerable to ischemic-edematous insults after traumatic brain injury (TBI). The extent of secondary insult after brain injury is quantifiable using quantitative CT analysis. One conventional quantitative CT measure, the gray-white matter ratio (GWR), and a more recently proposed densitometric analysis are used to assess the extent of these insults. However, the prognostic capacity of the GWR in patients with TBI has not yet been validated. This study aims to test the prognostic value of the GWR and evaluate the alternative parameters derived from the densitometric analysis acquired during the acute phase of TBI. In addition, the prognostic ability of the conventional TBI prognostic models (i.e., IMPACT [International Mission for Prognosis and Analysis of Clinical Trials in TBI] and CRASH [Corticosteroid Randomisation After Significant Head Injury] models) were compared to that of the quantitative CT measures.

METHODS

Three hundred patients with TBI of varying ages (92 pediatric, 94 adult, and 114 geriatric patients) and admitted between 2008 and 2013 were included in this retrospective cohort study. The normality of the density of the deep GM and whole WM was evaluated as the proportion of CT pixels with Hounsfield unit values of 31-35 for GM and 26-30 for WM on CT images of the entire supratentorial brain. The outcome was evaluated using the Glasgow Outcome Scale (GOS) at discharge (GOS score ≤ 3, n = 100).

RESULTS

Lower proportions of normal densities in the deep GM and whole WM indicated worse outcomes. The proportion of normal WM exhibited a significant prognostic capacity (area under the curve [AUC] = 0.844). The association between the outcome and the normality of the WM density was significant in adult (AUC = 0.792), pediatric (AUC = 0.814), and geriatric (AUC = 0.885) patients. In pediatric patients, the normality of the overall density and the density of the GM were indicative of the outcome (AUC = 0.751). The average GWR was not associated with the outcome (AUC = 0.511). IMPACT and CRASH models showed adequate and reliable performance in the pediatric and geriatric groups but not in the adult group. The highest overall predictive performance was achieved by the densitometry-augmented IMPACT model (AUC = 0.881).

CONCLUSIONS

Both deep GM and WM are susceptible to ischemic-edematous insults during the early phase of TBI. The extent of the secondary injury was better evaluated by analyzing the normality of the deep GM and WM rather than by calculating the GWR.

Excellent accuracy of ABC/2 volume formula compared to computer-assisted volumetric analysis of subdural hematomas

Background

Subdural hematoma (SDH) is a common disease associated with high morbidity, which is becoming more prominent due to the increasing incidence. Decision for a surgical evacuation is made depending on the clinical appearance and the volume of SDH, wherefore it is important to have a simple ‘bedside’ method to measure and compare the volume of SDH.

Objective

The aim of the study was to verify the accuracy of the simplified ABC/2 volumetric formula to determine a valuable tool for the clinical practice.

Methods

Preoperative CT-scans of 83 patients with SDHs were used for the computer-assisted volumetric measurement via BrainLab® as well as the ABC/2 volumetric measurement. A = largest length (anterior to posterior) of the SDH; B = maximum width (lateral to midline) 90° to A; C = maximum height (coronal plane or multiplication of slices) of the hematoma. These measurements were performed by two independent clinicians in a blinded fashion. Both volumes were compared by linear regression analysis of Pearson and Bland-Altman regression analysis.

Results

Among 100 SDHs, 53% were under an 47% were over 100cm³ showing a well distribution of the hematoma sizes. There was an excellent correlation between computer-assisted volumetric measurement and ABC/2 (R² = 0.947, p<0.0001) and no undesirable deviation and trend were detected (p = 0.101; p = 0.777). A 95% tolerance region of the ratios of both methods was [0.805–1.201].

Conclusion

The ABC/2 method is a simple and fast bedside formula for the measurement of SDH volume in a timely manner without limited access through simple adaption, which may replace the computer-assisted volumetric measurement in the clinical and research area. Reason for the good accuracy seems to be the spherical form of SDH, which has a similarity to a half ellipsoid.