Penumbra Detection With Oxygen Extraction Fraction Using Magnetic Susceptibility in Patients With Acute Ischemic Stroke

Prediction of prognosis in acute ischemic stroke after mechanical thrombectomy based on multimodal MRI radiomics and deep learning

Background

Acute ischemic stroke (AIS) is a major global health threat associated with high rates of disability and mortality, highlighting the need for early prognostic assessment to guide treatment. Currently, there are no reliable methods for the early prediction of poor prognosis in AIS, especially after mechanical thrombectomy. This study aimed to explore the value of radiomics and deep learning based on multimodal magnetic resonance imaging (MRI) in predicting poor prognosis in patients with AIS who underwent mechanical thrombectomy. This study aimed to provide a more accurate and comprehensive tool for stroke prognosis.

Methods

This study retrospectively analyzed the clinical data and multimodal MRI images of patients with stroke at admission. Logistic regression was employed to identify the risk factors associated with poor prognosis and to construct a clinical model. Radiomics features of the stroke-affected regions were extracted from the patients' baseline multimodal MRI images, and the optimal radiomics features were selected using a least absolute shrinkage and selection operator regression model combined with five-fold cross-validation. The radiomics score was calculated based on the feature weights, and machine learning techniques were applied using a logistic regression classifier to develop the radiomics model. In addition, a deep learning model was devised using ResNet101 and transfer learning. The clinical, radiomics, and deep learning models were integrated to establish a comprehensive multifactorial logistic regression model, termed the CRD (Clinic-Radiomics-Deep Learning) model. The performance of each model in predicting poor prognosis was assessed using receiver operating characteristic (ROC) curve analysis, with the optimal model visualized as a nomogram. A calibration curve was plotted to evaluate the accuracy of nomogram predictions.

Results

A total of 222 patients with AIS were enrolled in this study in a 7:3 ratio, with 155 patients in the training cohort and 67 in the validation cohort. Statistical analysis of clinical data from the training and validation cohorts identified two independent risk factors for poor prognosis: the National Institutes of Health Stroke Scale score at admission and the occurrence of intracerebral hemorrhage. Of the 1,197 radiomic features, 16 were selected to develop the radiomics model. Area under the ROC curve (AUC) analysis of specific indicators demonstrated varying performances across methods and cohorts. In the training cohort, the clinical, radiomics, deep learning, and integrated CRD models achieved AUC values of 0.762, 0.755, 0.689, and 0.834, respectively. In the validation cohort, the clinical model exhibited an AUC of 0.874, the radiomics model achieved an AUC of 0.805, the deep learning model attained an AUC of 0.757, and the CRD model outperformed all models, with an AUC of 0.908. Calibration curves indicated that the CRD model showed exceptional consistency and accuracy in predicting poor prognosis in patients with AIS. Decision curve analysis revealed that the CRD model offered the highest net benefit compared with the clinical, radiomics, and deep learning models.

Conclusion

The CRD model based on multimodal MRI demonstrated high diagnostic efficacy and reliability in predicting poor prognosis in patients with AIS who underwent mechanical thrombectomy. This model holds considerable potential for assisting clinicians with risk assessment and decision-making for patients experiencing ischemic stroke.

Potential Separation of Multiple System Atrophy and Parkinson's Disease by Susceptibility-derived Components

BACKGROUND

Substantial evidence emphasizes the dysregulation of iron homeostasis, demyelination and oxidative stress in the neurodegenerative process of multiple system atrophy (MSA) and Parkinson's disease (PD), although its clinical implications remain unclear. Recent MRI post-processing techniques leveraging magnetic susceptibility properties provide a noninvasive means to characterize iron, myelin content and oxygen metabolism alterations. This study aims to investigate subcortical alterations of susceptibility-derived metrics in these two synucleinopathies.

METHODS

A cohort comprising 180 patients (122 with PD and 58 with MSA) and 77 healthy controls (HCs) underwent clinical evaluation and multi-echo gradient echo MRI scans. Susceptibility source separation, susceptibility-based oxygen extraction fraction (OEF) mapping and semiautomatic subcortical nuclei segmentation were utilized to derive parametric values of deep gray matter in all subjects.

RESULTS

MSA patients showed markedly elevated paramagnetic susceptibility values in the putamen, globus pallidus (GP) and thalamus; increased diamagnetic susceptibility values in the putamen and dentate nucleus; and reduced OEF values across all nuclei compared with PD patients and HCs. Whereas PD exhibited increased positive susceptibility values in the substantia nigra and enhancing negative values in the GP, similar to MSA. Notably, age-related reductions in OEF were evident in HCs, which was altered by the MSA pathology. Paramagnetic susceptibility was correlated with disease severity. Moreover, the susceptibility-derived metrics of striatum and midbrain nuclei proved to be effective predictors to distinguish PD from MSA (AUC = 0.833).

CONCLUSION

Susceptibility-derived metrics could detect pathological involvement distinct to each disease, offering significant potential for differentiating between MSA and PD in clinical settings.

Oxygen extraction fraction changes in ischemic tissue from 24-72 hours to 12 months after successful reperfusion

Oxygen Extraction Fraction (OEF) is a critical measure of a tissue's metabolic state post-ischemic stroke. This study investigated OEF changes in stroke-affected tissue compared to healthy tissue, post-reperfusion. OEF maps generated from gradient echo MRI images of 87 ischemic stroke patients at three time points after successful Endovascular Thrombectomy (EVT) were analysed in a prospective longitudinal multicentre study. Regions of interest (ROIs) delineating the infarct areas and corresponding mirror regions were drawn. The MR-derived OEF index values were obtained from the ROIs and compared using Wilcoxon signed rank tests. The cross-sectional comparison of OEF index values revealed lower values in the infarct areas than the corresponding contralateral areas at all three time points after successful EVT, presented as median (interquartile range) [24-72 hours: 20.84 (17.56-26.82)% vs 27.56 (23.22-31.87)%; 3 months: 27.37 (23.28-30.35)% vs 32.55 (28.00-35.81)%; 12 months: 24.38 (22.35-29.77)% vs 29.39 (25.86-34.04)%, p < 0.001 for all three time points]. Longitudinally, relative OEF index values increased gradually over time [24-72 hours: 0.81 (0.67-0.87); 3 months: 0.86 (0.79-0.95); 12 months: 0.88 (0.75-0.95)]. The findings revealed that following successful EVT, OEF in infarct tissue improves over time, indicating potential tissue recovery.Trial registration name and URL: Post-Reperfusion Pathophysiology in Acute Ischemic Stroke https://trialsearch.who.int/Trial2.aspx?TrialID=ACTRN12624000629538.

The expression changes endothelial and fibrinolytic biomarkers in acute ischemic stroke patients with OSA

OBJECTIVE

To assess the expression changes of serum fibrinogen, E-selectin, and tissue-type plasminogen activator (t-PA) in acute ischemic stroke (AIS) patients with varying degrees of obstructive sleep apnea syndrome (OSA), and evaluate their value in diagnosing AIS with OSA.

METHODS

Data were gathered from 80 patients with AIS who were admitted to the First Hospital of Jilin University between January 2023 and December 2023. Out of these, 60 patients completed the NIHSS Scale, ESS Scale, STOP-Bang Scale, and underwent polysomnography within a week of symptom onset. Based on the apnea-hypopnea index (AHI) score, patients were categorized into three groups: 15 in the non-exposed group (AHI < 5), 15 in the mildly exposed group (5 ≤ AHI ≤ 15), and 30 in the moderately to severely exposed group (AHI > 15). Serum levels of fibrinogen, E-selectin, and t-PA were determined using enzyme-linked immunosorbent assay.

RESULTS

Polysomnography results indicated AIS with OSA had an increased arousal index and oxygen desaturation index (P < 0.001). Additionally, serum levels of fibrinogen, E-selectin, and t-PA were markedly elevated in the moderately-severely exposed group compared to the non-exposed group (P < 0.001), and these levels positively correlated with the severity of OSA. ROC curves showed the sensitivities of serum of fibrinogen, E-selection, and t-PA was 84.4%, 80%, and 82.2%, respectively, and the specificities of 60%, 66.7%, and 66.7%, compared with that of PSG respectively.

CONCLUSION

The expression of serum fibrinogen, E-selectin, and t-PA is elevated in AIS with OSA and correlates with the severity of OSA.

Delta radiomics modeling based on CTP for predicting hemorrhagic transformation after intravenous thrombolysis in acute cerebral infarction: an 8-year retrospective pilot study

Objective

To explore the value of delta radiomics from cerebral CT perfusion (CTP) in predicting hemorrhagic transformation after intravenous thrombolysis for acute cerebral infarction (HT-ACI).

Methods

Clinical and imaging data of 419 patients with acute cerebral infarction who underwent CTP after treatment between November 2016 and August 2024 were retrospectively collected. Based on post-thrombolysis cranial CT or MRI results, patients were divided into the HT-ACI group (114 cases) and the non-HT-ACI group (305 cases). The dataset was split into a training set and a test set in a 7:3 ratio based on time nodes. In the training set, regions of interest (ROI) within the cerebral infarction area on CTP images were delineated using 3D slicer software, and delta radiomic features were extracted. Hemodynamic parameters such as cerebral blood volume (CBV), cerebral blood flow (CBF), and time to peak (TTP) were obtained using CTP techniques. These were combined with baseline patient data (e.g., age, sex, NIHSS score, medical history) to establish various models for predicting HT-ACI through multivariable logistic regression analysis. The predictive performance of the models was compared using DeLong curves, clinical net benefit was assessed using decision curves, and model predictions were validated using the XGboost algorithm. These results were then validated in the test set, and a nomogram and calibration curve were constructed for clinical application.

Results

In the training set, significant differences were observed between the two groups in NIHSS score, pre-illness usually use of anticoagulants, age, infarction size, ADC difference, CBF, and Delta radscore (P < 0.05). The combined model [AUC 0.878, OR 0.0217, 95%CI 0.835-0.913] demonstrated superior predictive performance compared to the clinical model [AUC 0.725, OR 0.0310, 95%CI 0.670-0.775] and the imaging model [AUC 0.818, OR 0.0259, 95%CI 0.769-0.861]. This was confirmed by the XGboost algorithm, and decision curves confirmed the higher clinical net benefit of the combined model. Similar results were validated in the test set, and a novel nomogram was constructed to simplify the prediction process for HT-ACI.

Conclusion

The combined model established based on delta radiomics from CTP may provide early insights into the hemodynamic status of acutely ischemic brain tissue, holding significant clinical importance for predicting HT-ACI. This method could offer a powerful imaging reference for clinical decision-making in patients with ACI, helping to reduce the risk of HT-ACI and improve patient outcomes.

Oxygen extraction fraction change in M1-M6 brain regions of patients with unilateral or bilateral middle cerebral artery occlusion

Cerebral blood flow (CBF) and oxygen extraction fraction (OEF) can be measured using arterial spin labeling (ASL) and quantitative susceptibility mapping (QSM) sequences, respectively. ASL and QSM sequences were performed on 13 healthy participants and 46 patients with unilateral or bilateral Middle cerebral artery (MCA) occlusion. M1-M3 and M4-M6 correspond to anterior, lateral, and posterior MCA territories within the insular ribbon and centrum semiovale, respectively. In patients with unilateral MCA occlusion, significant decreases in CBF were observed in the lesions in M1, M3, M5 and M6 regions, as well as in the contralateral M3 and M5 regions. The OEF of the lesion in the M1-M4 and M6 regions, and the contralateral M1-M3 regions were significantly higher. Additionally, the cerebral metabolic rate of oxygen (CMRO2) in the lesions of the M3 and M6 regions, and the contralateral M3 region, were significantly lower compared to the corresponding regions of healthy participants. For patients with bilateral MCA occlusion, the CMRO2 in the left M5 region and the right M3 and M6 regions were significantly lower than that in the corresponding regions of healthy participants. In conclusion, abnormal hemodynamics occur in the contralateral hemisphere of patients with unilateral MCA occlusion.

Prognostic value of multi-PLD ASL radiomics in acute ischemic stroke

Introduction

Early prognosis prediction of acute ischemic stroke (AIS) can support clinicians in choosing personalized treatment plans. The aim of this study is to develop a machine learning (ML) model that uses multiple post-labeling delay times (multi-PLD) arterial spin labeling (ASL) radiomics features to achieve early and precise prediction of AIS prognosis.

Methods

This study enrolled 102 AIS patients admitted between December 2020 and September 2024. Clinical data, such as age and baseline National Institutes of Health Stroke Scale (NIHSS) score, were collected. Radiomics features were extracted from cerebral blood flow (CBF) images acquired through multi-PLD ASL. Features were selected using least absolute shrinkage and selection operator regression, and three models were developed: a clinical model, a CBF radiomics model, and a combined model, employing eight ML algorithms. Model performance was assessed using receiver operating characteristic curves and decision curve analysis (DCA). Shapley Additive exPlanations was applied to interpret feature contributions.

Results

The combined model of extreme gradient boosting demonstrated superior predictive performance, achieving an area under the curve (AUC) of 0.876. Statistical analysis using the DeLong test revealed its significant outperformance compared to both the clinical model (AUC = 0.658, p < 0.001) and the CBF radiomics model (AUC = 0.755, p = 0.002). The robustness of all models was confirmed through permutation testing. Furthermore, DCA underscored the clinical utility of the combined model. The prognostic prediction of AIS was notably influenced by the baseline NIHSS score, age, as well as texture and shape features of CBF.

Conclusion

The integration of clinical data and multi-PLD ASL radiomics features in a model offers a secure and dependable approach for predicting the prognosis of AIS, particularly beneficial for patients with contraindications to contrast agents. This model aids clinicians in devising individualized treatment plans, ultimately enhancing patient prognosis.

Association between iron content in grey matter nuclei and functional outcome in patients with acute ischaemic stroke: A quantitative susceptibility mapping study

BACKGROUND AND PURPOSE

This study aimed to investigate the association between iron content in grey matter (GM) nuclei and functional outcome in acute ischaemic stroke (AIS) patients utilizing quantitative susceptibility mapping.

METHODS

Forty AIS patients and 40 age-, sex- and education-matched healthy controls underwent quantitative susceptibility mapping to assess susceptibility values, which are positively correlated with iron content, in the caudate nucleus, putamen, globus pallidus, thalamus, red nucleus and substantia nigra. The nuclei on the contralateral side were measured in AIS patients to minimize confounding due to oedema or haemorrhage. Functional outcome was determined by the modified Rankin Scale (mRS) score at 3 months after stroke. Poor outcome was defined as mRS >2, whilst a good outcome was defined as ≤2.

RESULTS

Susceptibility values were significantly higher in most contralateral GM nuclei in AIS patients than in the corresponding left or right nuclei in healthy controls. AIS patients with poor outcome showed significantly lower susceptibility value than those with good outcome in the contralateral caudate nucleus, but no significant differences were observed in other GM nuclei. Binary logistic regression analysis revealed a significant association between the susceptibility value of the contralateral caudate nucleus and poor outcome after adjustment for confounders (adjusted odds ratio 0.692, 95% confidence interval 0.486-0.986, p = 0.042). Receiver operating characteristic curve analysis showed an acceptable ability of the susceptibility value of the contralateral caudate nucleus to predict poor outcome (area under the curve 0.740, p = 0.013).

CONCLUSIONS

Lower iron content in the contralateral caudate nucleus was associated with poor functional outcome in AIS patients.

Oxygen Extraction Fraction Mapping on Admission Magnetic Resonance Imaging May Predict Recovery of Hyperacute Ischemic Brain Lesions After Successful Thrombectomy: A Retrospective Observational Study

BACKGROUND

In acute stroke, diffusion-weighted imaging (DWI) is used to assess the ischemic core. Dynamic-susceptibility contrast perfusion magnetic resonance imaging allows an estimation of the oxygen extraction fraction (OEF), but the outcome of DWI lesions with increased OEF postrecanalization is unclear. This study investigated the impact of OEF on the fate of DWI lesions in patients achieving recanalization after thrombectomy.

METHODS

This was a retrospective analysis of the HIBISCUS-STROKE cohort (Cohort of Patients to Identify Biological and Imaging Markers of Cardiovascular Outcomes in Stroke; NCT: 03149705), a single-center observational study that prospectively enrolled patients who underwent magnetic resonance imaging triage for thrombectomy and a day-6 T2-fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging. Automated postprocessing of admission dynamic-susceptibility contrast perfusion magnetic resonance imaging generated OEF maps. At visual analysis, the OEF status within DWI lesions was assessed in comparison to the contralateral side and correlated with volume changes (difference of ischemic lesion between admission DWI and registered day-6 T2-FLAIR). At voxel-based analysis, recovered DWI regions (lesions present on the admission DWI but absent on the registered day-6 T2-FLAIR) and nonrecovered regions were segmented to extract semiquantitative OEF values.

RESULTS

Of the participants enrolled from 2016 to 2022, 134 of 321 (41.7%) were included (median age, 71.0 years; 58.2% male; median baseline National Institutes of Health Scale score, 15.0). At visual analysis, 46 of 134 (34.3%) patients had increased OEF within DWI lesions. These patients were more likely to show a reduction in ischemic lesion volumes compared with those without increased OEF (median change, -4.0 versus 4.8 mL; P<0.0001). Multivariable analysis indicated that increased OEF within DWI lesions was associated with a reduction in ischemic lesion volumes from admission DWI to day-6 T2-FLAIR (odds ratio, 0.68 [95% CI, 0.49-0.87]; P=0.008). At voxel-based analysis, recovered DWI regions had increased OEF, while nonrecovered regions had decreased OEF (median, 126.9% versus -27.0%; P<0.0001).

CONCLUSIONS

Increased OEF within hyperacute DWI lesions was associated with ischemic lesion recovery between admission DWI and day-6 T2-FLAIR in patients achieving recanalization after thrombectomy.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT03149705.

Prognostic value of multi-PLD ASL-based cerebral perfusion ASPECTS in acute ischemic stroke

Introduction

We aimed to verify the application value of the Alberta Stroke Program Early CT Score (ASPECTS) based on multiple post-labeling delay (multi-PLD) arterial spin labeling (ASL) for outcome assessment in acute ischemic stroke (AIS) patients.

Method

The endpoint was modified Rankin scale score at 90 days (90-day mRS). Patients were divided into the good outcome (0-2) and poor outcome (3-6) groups. The independent samples t-test, Mann-Whitney U-test, and χ2-test were used to compare clinical and imaging parameters between groups. We used partial correlation analysis to evaluate the relationships between ASPECTS and outcomes. Multivariate logistic regression analysis was used to examine potential independent prognostic indicators. The receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of the independent prognostic indicators in predicting outcomes.

Results

Fifty-five AIS patients were included. The good outcome group had a lower baseline National Institutes of Health Stroke Scale (NIHSS; Z = -3.413, P < 0.001) and infarct core volume (ICV; Z = -3.114, P = 0.002) as well as higher cerebral blood flow (CBF)-ASPECTS (Z = -3.835, P < 0.001) and cerebral blood volume (CBV)-ASPECTS (Z = -4.099, P < 0.001). Higher CBF-ASPECTS (r = -0.459, P = 0.001), and CBV-ASPECTS (r = -0.502, P < 0.001) were associated with a lower 90-day mRS. The baseline NIHSS, CBF-ASPECTS, and CBV-ASPECTS were identified as independent prognostic indicators. The AUCs of the baseline NIHSS, CBF-ASPECTS, and CBV-ASPECTS were 83.3, 87.4, and 89.9%, respectively. Combining NIHSS with CBF-ASPECTS and CBV-ASPECTS, the AUC significantly improved to 96.3%. The combined three factors showed a significant difference compared to the baseline NIHSS (Z = 2.039, P = 0.041) and CBF-ASPECTS (Z = 2.099, P = 0.036), but no difference with CBV-ASPECTS (Z = 1.176, P = 0.239).

Conclusions

The ASPECTS based on multi-PLD ASL is a valuable tool for identifying independent prognostic indicators and assessing clinical outcomes in AIS patients. The baseline NIHSS, combined with CBF-ASPECTS and CBV-ASPECTS, enhances the predictive efficacy of clinical outcomes in AIS patients. The CBV-ASPECTS alone can offer comparable predictive efficacy to the combination.

Iron accumulation/overload and Alzheimer's disease risk factors in the precuneus region: A comprehensive narrative review

Alzheimer's disease (AD) is a neurodegenerative disease that is characterized by amyloid plaques, neurofibrillary tangles, and neuronal loss. Early cerebral and body iron dysregulation and accumulation interact with AD pathology, particularly in the precuneus, a crucial functional hub in cognitive functions. Quantitative susceptibility mapping (QSM), a novel post-processing approach, provides insights into tissue iron levels and cerebral oxygen metabolism and reveals abnormal iron accumulation early in AD. Increased iron deposition in the precuneus can lead to oxidative stress, neuroinflammation, and accelerated neurodegeneration. Metabolic disorders (diabetes, non-alcoholic fatty liver disease (NAFLD), and obesity), genetic factors, and small vessel pathology contribute to abnormal iron accumulation in the precuneus. Therefore, in line with the growing body of literature in the precuneus region of patients with AD, QSM as a neuroimaging method could serve as a non-invasive biomarker to track disease progression, complement other imaging modalities, and aid in early AD diagnosis and monitoring.

Clinical value of thromboelastography in predicting the risk of recurrence of acute ischemic stroke

Background

Thromboelastography (TEG) can objectively reflect the formation, development and rupture process of thrombosis in patients, but there are limited data on whether TEG can be used as a predictive tool for recurrence in patients with acute ischemic stroke.

Objective

To explore the TEG risk of recurrence in patients with acute ischemic stroke predictive value.

Methods

A total of 441 patients with acute ischemic stroke who met the research criteria in the First Affiliated Hospital of Henan University of Traditional Chinese Medicine from January 2020 to December 2021 were selected as the research objects. TEG was measured in all patients, and the main parameters of TEG (R value, indicating coagulation reaction time; K value and Angle, the rate of blood clot formation; MA value, indicating the maximum amplitude). The primary outcome of this study was ischemic stroke recurrence. Recurrent events included cerebral infarction, cerebral hemorrhage, TIA, and were determined by combining imaging events and clinical events. Logistic regression analysis was used to explore the influencing factors of recurrence in patients with acute ischemic stroke.

Results

Fifty-six patients (12.7%) had recurrence. Multivariate Logistic regression analysis showed that: Age [OR = 1.078, 95%CI(1.024, 1.135)], triglyceride [OR = 1.541, 95%CI(1.033, 2.298)], glycosylated hemoglobin [OR = 1.401, 95%CI(1.097, 1.790)], history of hypertension [OR = 16.046, p < 0.05], 95%CI(4.726, 54.489), R value [OR = 0.533, 95%CI(0.351, 0.809)], MA value [OR = 1.399, 95%CI(1.004, 1.949)] were independent influencing factors for hemorrhagic transformation in patients with acute ischemic stroke.

Conclusion

TEG has some value in predicting recurrence in patients with acute ischemic stroke, and the MA value in TEG [AUC = 0.806 (95%CI:0.747-0.867), with a sensitivity of 78.6% and a specificity of 70.4%], predicted the most significant efficiency of AIS recurrence.

Ischemic perfusion radiomics: assessing neurological impairment in acute ischemic stroke

Introduction

Accurate neurological impairment assessment is crucial for the clinical treatment and prognosis of patients with acute ischemic stroke (AIS). However, the original perfusion parameters lack the deep information for characterizing neurological impairment, leading to difficulty in accurate assessment. Given the advantages of radiomics technology in feature representation, this technology should provide more information for characterizing neurological impairment. Therefore, with its rigorous methodology, this study offers practical implications for clinical diagnosis by exploring the role of ischemic perfusion radiomics features in assessing the degree of neurological impairment.

Methods

This study employs a meticulous methodology, starting with generating perfusion parameter maps through Dynamic Susceptibility Contrast-Perfusion Weighted Imaging (DSC-PWI) and determining ischemic regions based on these maps and a set threshold. Radiomics features are then extracted from the ischemic regions, and the t-test and least absolute shrinkage and selection operator (Lasso) algorithms are used to select the relevant features. Finally, the selected radiomics features and machine learning techniques are used to assess the degree of neurological impairment in AIS patients.

Results

The results show that the proposed method outperforms the original perfusion parameters, radiomics features of the infarct and hypoxic regions, and their combinations, achieving an accuracy of 0.926, sensitivity of 0.923, specificity of 0.929, PPV of 0.923, NPV of 0.929, and AUC of 0.923, respectively.

Conclusion

The proposed method effectively assesses the degree of neurological impairment in AIS patients, providing an objective auxiliary assessment tool for clinical diagnosis.

The rate-pressure product combined model within 24 h on admission predicts the 30-day mortality rate in conservatively treated patients with intracerebral hemorrhage

Background and objectives

Recently, some literature has proposed new indicators such as rate-pressure product, platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, etc. However, there has been no literature that has utilized these new indicators to establish a predictive model for assessing the risk of mortality in patients within 24 h on admission. Therefore, this study aims to build a predictive model that can rapidly assess the likelihood of mortality in patients within 24 h of admission.

Methods

The datasets used in this study are available from the corresponding author upon reasonable request. Patients were randomly assigned to the training or validation cohort based on a ratio of 7:3, which was implemented as internal validations for the final predictive models. In the training set, least absolute shrinkage and selection operator (LASSO) regression was employed to select predictive factors, followed by both univariate and subsequent multivariate analysis. The predictive ability was assessed by the area under the receiver operating characteristic (ROC) curve.

Results

A total of 428 patients were included in our research. The final model included 4 independent predictors (Glasgow Coma Scale, hematoma volume, rate-pressure product, c-reactive protein) and was developed as a simple-to-use nomogram. The training set and internal validation set model's C-index are 0.933 and 0.954, demonstrating moderate predictive ability with regard to risks of mortality. Compared to ICH score (AUC: 0.910 and 0.925), the net reclassification index (NRI) is 0.298 (CI = -0.105 to 0.701, p: 0.147) and integrated discrimination improvement (IDI) is 0.089 (CI = -0.049 to 0.228, p: 0.209). Our model is equally excellent as the classic ICH score model.

Conclusion

We developed a model with four independent risk factors to predict the mortality of ICH patients. Our predictive model is effective in assessing the risk of mortality in patients within 24 h on admission, which might be worth considering in clinical settings after further external validation.

Cortical oxygen extraction fraction using quantitative BOLD MRI and cerebral blood flow during vasodilation

Introduction: We aimed to demonstrate non-invasive measurements of regional oxygen extraction fraction (OEF) from quantitative BOLD MRI modeling at baseline and after pharmacological vasodilation. We hypothesized that OEF decreases in response to vasodilation with acetazolamide (ACZ) in healthy conditions, reflecting compensation in regions with increased cerebral blood flow (CBF), while cerebral metabolic rate of oxygen (CMRO2) remained unchanged. We also aimed to assess the relationship between OEF and perfusion in the default mode network (DMN) regions that have shown associations with vascular risk factors and cerebrovascular reactivity in different neurological conditions. Material and methods: Eight healthy subjects (47 ± 13 years, 6 female) were scanned on a 3 T scanner with a 32-channel head coil before and after administration of 15 mg/kg ACZ as a pharmacological vasodilator. The MR imaging acquisition protocols included: 1) A Gradient Echo Slice Excitation Profile Imaging Asymmetric Spin Echo scan to quantify OEF, deoxygenated blood volume, and reversible transverse relaxation rate (R2 ') and 2) a multi-post labeling delay arterial spin labeling scan to measure CBF. To assess changes in each parameter due to vasodilation, two-way t-tests were performed for all pairs (baseline versus vasodilation) in the DMN brain regions with Bonferroni correction for multiple comparisons. The relationships between CBF versus OEF and CBF versus R2' were analyzed and compared across DMN regions using linear, mixed-effect models. Results: During vasodilation, CBF significantly increased in the medial frontal cortex (P = 0.004 ), posterior cingulate gyrus (pCG) (P = 0.004 ), precuneus cortex (PCun) (P = 0.004 ), and occipital pole (P = 0.001 ). Concurrently, a significant decrease in OEF was observed only in the pCG (8.8%, P = 0.003 ) and PCun (8.7 % , P = 0.001 ). CMRO2 showed a trend of increased values after vasodilation, but these differences were not significant after correction for multiple comparisons. Although R2' showed a slightly decreasing trend, no statistically significant changes were found in any regions in response to ACZ. The CBF response to ACZ exhibited a stronger negative correlation with OEF (β = - 0.104 ± 0.027 ; t = - 3.852 , P < 0.001 ), than with R2' (β = - 0.016 ± 0.006 ; t = - 2.692 , P = 0.008 ). Conclusion: Quantitative BOLD modeling can reliably measure OEF across multiple physiological conditions and captures vascular changes with higher sensitivity than R2' values. The inverse correlation between OEF and CBF across regions in DMN, suggests that these two measurements, in response to ACZ vasodilation, are reliable indicators of tissue health in this healthy cohort.

Assessing white matter microstructural changes in idiopathic normal pressure hydrocephalus using voxel-based R2* relaxometry analysis

Background

R2* relaxometry and quantitative susceptibility mapping can be combined to distinguish between microstructural changes and iron deposition in white matter. Here, we aimed to explore microstructural changes in the white matter associated with clinical presentations such as cognitive impairment in patients with idiopathic normal-pressure hydrocephalus (iNPH) using R2* relaxometry analysis in combination with quantitative susceptibility mapping.

Methods

We evaluated 16 patients clinically diagnosed with possible or probable iNPH and 18 matched healthy controls (HC) who were chosen based on similarity in age and sex. R2* and quantitative susceptibility mapping were compared using voxel-wise and atlas-based one-way analysis of covariance (ANCOVA). Finally, partial correlation analyses were performed to assess the relationship between R2* and clinical presentations.

Results

R2* was lower in some white matter regions, including the bilateral superior longitudinal fascicle and sagittal stratum, in the iNPH group compared to the HC group. The voxel-based quantitative susceptibility mapping results did not differ between the groups. The atlas-based group comparisons yielded negative mean susceptibility values in almost all brain regions, indicating no clear paramagnetic iron deposition in the white matter of any subject. R2* and cognitive performance scores between the left superior longitudinal fasciculus (SLF) and right sagittal stratum (SS) were positively correlated. In addition to that, R2* and gait disturbance scores between left SS were negatively correlated.

Conclusion

Our analysis highlights the microstructural changes without iron deposition in the SLF and SS, and their association with cognitive impairment and gait disturbance in patients with iNPH.

Quantitative Evaluation of Oxygen Extraction Fraction Changes in the Monkey Brain during Acute Stroke by Using Quantitative Susceptibility Mapping

BACKGROUND

The oxygen extraction fraction (OEF) indicates the brain's oxygen consumption and can be estimated by using the quantitative susceptibility mapping (QSM) MRI technique. Recent studies have suggested that OEF alteration following stroke is associated with the viability of at-risk tissue. In the present study, the temporal evolution of OEF in the monkey brain during acute stroke was investigated using QSM.

METHODS

Ischemic stroke was induced in adult rhesus monkeys (n = 8) with permanent middle cerebral artery occlusion (pMCAO) by using an interventional approach. Diffusion-, T2-, and T2*-weighted images were conducted on day 0, day 2, and day 4 post-stroke using a clinical 3T scanner. Progressive changes in magnetic susceptibility and OEF, along with their correlations with the transverse relaxation rates and diffusion indices, were examined.

RESULTS

The magnetic susceptibility and OEF in injured gray matter of the brain significantly increased during the hyperacute phase, and then decreased significantly on day 2 and day 4. Moreover, the temporal changes of OEF in gray matter were moderately correlated with mean diffusivity (MD) (r = 0.52; p = 0.046) from day 0 to day 4. Magnetic susceptibility in white matter progressively increased (from negative values to near zero) during acute stroke, and significant increases were seen on day 2 (p = 0.08) and day 4 (p = 0.003) when white matter was significantly degenerated. However, significant reduction of OEF in white matter was not seen until day 4 post-stroke.

CONCLUSION

The preliminary results demonstrate that QSM-derived OEF is a robust approach to examine the progressive changes of gray matter in the ischemic brain from the hyperacute phase to the subacute phase of stroke. The changes of OEF in gray matter were more prominent than those in white matter following stroke insult. The findings suggest that QSM-derived OEF may provide complementary information for understanding the neuropathology of the brain tissue following stroke and predicting stroke outcomes.

The diagnostic value of quantitative parameters on dual-layer detector-based spectral CT in identifying ischaemic stroke

Objective

To investigate the diagnostic value of quantitative parameters of spectral computed tomography (CT) in ischaemic stroke areas.

Methods

The medical records of 57 patients with acute ischaemic stroke (AIS) who underwent plain computed tomography (CT) head scans, CT angiography (CTA), and CT perfusion (CTP) were retrospectively reviewed. The ischaemic areas (including the core infarct area and penumbra) and non-ischaemic areas in each patient were quantitatively analyzed using F-STROKE software. Two independent readers measured the corresponding values of the spectroscopic quantitative parameters (effective atomic number [Zeff value], iodine density value, and iodine-no-water value) in the ischaemic area and contralateral normal area alone. The differences in spectroscopic quantitative parameters between the two groups were compared, and their diagnostic efficacy was obtained.

Results

The Zeff, iodine-no-water value, and iodine density value of the ischaemic area all showed significant lower than those of non-ischaemic tissue (P < 0.001). For differentiating the ischaemic area from non-ischaemic tissue, the area under the curve (AUC) of the Zeff value reached 0.869 (cut-off value: 7.385; sensitivity: 93.0%; specificity: 70.2%), the AUC of the iodine density value reached 0.932 (cut-off value: 0.235; sensitivity: 91.2%; specificity: 82.5%), and the AUC of the iodine-no-water value reached 0.922 (cut-off value: 0.205; sensitivity: 96.5%; specificity: 78.9%).

Conclusion

The study showed the spectral CT would be a potential novel rapid method for identifying AIS. The spectral CT quantitative parameters (Zeff, iodine density values, and iodine-no-water values) can effectively differentiate the ischaemic area from non-ischaemic tissue in stroke patients.

Test-retest analysis of cerebral oxygen extraction estimates in healthy volunteers: comparison of methods based on quantitative susceptibility mapping and dynamic susceptibility contrast magnetic resonance imaging

Background

Estimation of the oxygen extraction fraction (OEF) by quantitative susceptibility mapping (QSM) magnetic resonance imaging (MRI) is promising but requires systematic evaluation. Extraction of OEF-related information from the tissue residue function in dynamic susceptibility contrast MRI (DSC-MRI) has also been proposed. In this study, whole-brain OEF repeatability was investigated, as well as the relationships between QSM-based OEF and DSC-MRI-based parameters, i.e., mean transit time (MTT) and an oxygen extraction index, referred to as apparent OEF (AOEF).

Method

Test-retest data were obtained from 20 healthy volunteers at 3 T. QSM maps were reconstructed from 3D gradient-echo MRI phase data, using morphology-enabled dipole inversion. DSC-MRI was accomplished using gradient-echo MRI at a temporal resolution of 1.24 s.

Results

The whole-brain QSM-based OEF was (40.4±4.8) % and, in combination with a previously published cerebral blood flow (CBF) estimate, this corresponds to a cerebral metabolic rate of oxygen level of CMRO2 = 3.36 ml O2/min/100 g. The intra-class correlation coefficient [ICC(2,1)] for OEF test-retest data was 0.73. The MTT-versus-OEF and AOEF-versus-OEF relationships showed correlation coefficients of 0.61 (p = 0.004) and 0.52 (p = 0.019), respectively.

Discussion

QSM-based OEF showed a convincing absolute level and good test-retest results in terms of the ICC. Moderate to good correlations between QSM-based OEF and DSC-MRI-based parameters were observed. The present results constitute an indicator of the level of robustness that can be achieved without applying extraordinary resources in terms of MRI equipment, imaging protocol, QSM reconstruction, and OEF analysis.

Quantitative susceptibility mapping as an imaging biomarker for Alzheimer’s disease: The expectations and limitations

Alzheimer’s disease (AD) is the most common type of dementia and a distressing diagnosis for individuals and caregivers. Researchers and clinical trials have mainly focused on β-amyloid plaques, which are hypothesized to be one of the most important factors for neurodegeneration in AD. Meanwhile, recent clinicopathological and radiological studies have shown closer associations of tau pathology rather than β-amyloid pathology with the onset and progression of Alzheimer’s symptoms. Toward a biological definition of biomarker-based research framework for AD, the 2018 National Institute on Aging–Alzheimer’s Association working group has updated the ATN classification system for stratifying disease status in accordance with relevant pathological biomarker profiles, such as cerebral β-amyloid deposition, hyperphosphorylated tau, and neurodegeneration. In addition, altered iron metabolism has been considered to interact with abnormal proteins related to AD pathology thorough generating oxidative stress, as some prior histochemical and histopathological studies supported this iron-mediated pathomechanism. Quantitative susceptibility mapping (QSM) has recently become more popular as a non-invasive magnetic resonance technique to quantify local tissue susceptibility with high spatial resolution, which is sensitive to the presence of iron. The association of cerebral susceptibility values with other pathological biomarkers for AD has been investigated using various QSM techniques; however, direct evidence of these associations remains elusive. In this review, we first briefly describe the principles of QSM. Second, we focus on a large variety of QSM applications, ranging from common applications, such as cerebral iron deposition, to more recent applications, such as the assessment of impaired myelination, quantification of venous oxygen saturation, and measurement of blood– brain barrier function in clinical settings for AD. Third, we mention the relationships among QSM, established biomarkers, and cognitive performance in AD. Finally, we discuss the role of QSM as an imaging biomarker as well as the expectations and limitations of clinically useful diagnostic and therapeutic implications for AD.