Imaging of Intracranial Hemorrhage

Radiomics and Deep Features: Robust Classification of Brain Hemorrhages and Reproducibility Analysis Using a 3D Autoencoder Neural Network

This study evaluates the reproducibility of machine learning models that integrate radiomics and deep features (features extracted from a 3D autoencoder neural network) to classify various brain hemorrhages effectively. Using a dataset of 720 patients, we extracted 215 radiomics features (RFs) and 15,680 deep features (DFs) from CT brain images. With rigorous screening based on Intraclass Correlation Coefficient thresholds (>0.75), we identified 135 RFs and 1054 DFs for analysis. Feature selection techniques such as Boruta, Recursive Feature Elimination (RFE), XGBoost, and ExtraTreesClassifier were utilized alongside 11 classifiers, including AdaBoost, CatBoost, Decision Trees, LightGBM, Logistic Regression, Naive Bayes, Neural Networks, Random Forest, Support Vector Machines (SVM), and k-Nearest Neighbors (k-NN). Evaluation metrics included Area Under the Curve (AUC), Accuracy (ACC), Sensitivity (SEN), and F1-score. The model evaluation involved hyperparameter optimization, a 70:30 train-test split, and bootstrapping, further validated with the Wilcoxon signed-rank test and q-values. Notably, DFs showed higher accuracy. In the case of RFs, the Boruta + SVM combination emerged as the optimal model for AUC, ACC, and SEN, while XGBoost + Random Forest excelled in F1-score. Specifically, RFs achieved AUC, ACC, SEN, and F1-scores of 0.89, 0.85, 0.82, and 0.80, respectively. Among DFs, the ExtraTreesClassifier + Naive Bayes combination demonstrated remarkable performance, attaining an AUC of 0.96, ACC of 0.93, SEN of 0.92, and an F1-score of 0.92. Distinguished models in the RF category included SVM with Boruta, Logistic Regression with XGBoost, SVM with ExtraTreesClassifier, CatBoost with XGBoost, and Random Forest with XGBoost, each yielding significant q-values of 42. In the DFs realm, ExtraTreesClassifier + Naive Bayes, ExtraTreesClassifier + Random Forest, and Boruta + k-NN exhibited robustness, with 43, 43, and 41 significant q-values, respectively. This investigation underscores the potential of synergizing DFs with machine learning models to serve as valuable screening tools, thereby enhancing the interpretation of head CT scans for patients with brain hemorrhages.

Improved differentiation of cavernous malformation and acute intraparenchymal hemorrhage on CT using an AI algorithm

This study aimed to evaluate the utility of an artificial intelligence (AI) algorithm in differentiating between cerebral cavernous malformation (CCM) and acute intraparenchymal hemorrhage (AIH) on brain computed tomography (CT). A retrospective, multireader, randomized study was conducted to validate the performance of an AI algorithm in differentiating AIH from CCM on brain CT. CT images of CM and AIH (< 3 cm) were identified from the database. Six blinded reviewers, including two neuroradiologists, two radiology residents, and two emergency department physicians, evaluated CT images from 288 patients (CCM, n = 173; AIH, n = 115) with and without AI assistance, comparing diagnostic performance. Brain CT interpretation with AI assistance resulted in significantly higher diagnostic accuracy than without (86.92% vs. 79.86%, p < 0.001). Radiology residents and emergency department physicians showed significantly improved accuracy of CT interpretation with AI assistance than without (84.21% vs. 75.35%, 80.73% vs. 72.57%; respectively, p < 0.05). Neuroradiologists showed a trend of higher accuracy with AI assistance in the interpretation but lacked statistical significance (95.83% vs. 91.67%, p = 0.56). The use of an AI algorithm can enhance the differentiation of AIH from CCM in brain CT interpretation, particularly for nonexperts in neuroradiology.

Deep multiscale convolutional feature learning for intracranial hemorrhage classification and weakly supervised localization

Objective

This study evaluated the performance of attentional fusion model-based multiscale features in classifying intracerebral hemorrhage and the localization of bleeding focus based on weakly supervised target localization.

Methods

A publicly available dataset provided by the American College of Neuroradiology (ASNR) was used, consisting of 750,000 computed tomography (CT) scans of the brain, manually marked by radiologists for intracranial hemorrhage and five hemorrhage subtypes. A multiscale feature classification and weakly supervised localization framework based on an attentional fusion mechanism were applied, which could be annotated at the slice level and provided intracranial hemorrhage classification and hemorrhage focus localization.

Results

The designed framework achieved excellent performance for classification and localization. The area under the curve (AUC) for predicting bleeding was 0.973. High AUC values were observed for the five hemorrhage subtypes (epidural AUC = 0.891, subdural AUC = 0.991, subarachnoid AUC = 0.983, intraventricular AUC = 0.995, intraparenchymal AUC = 0.990). This model outperformed the average entry-level radiology trainee compared to previously reported data.

Conclusion

The designed method quickly and accurately detected intracerebral hemorrhage, classifying hemorrhage subtypes and locating bleeding points with image-level annotation alone. The results indicate that this framework can significantly reduce diagnostic time while improving the detection of intracerebral hemorrhage in emergencies. It can thus be integrated into the diagnostic radiology workflow in the future.

The effect of stent retriever mechanical thrombectomy combined with tirofiban in treating acute ischemic stroke

OBJECTIVE

To analyze the effectiveness of stent retriever mechanical thrombectomy combined with tirofiban in treating acute ischemic stroke.

METHODS

Markedly effective is defined as an SIS score of over 90, effective is indicated by an SIS score of between 50-90, and a score of below 50 suggests ineffective treatment results.

RESULTS

①The treatment's overall effectiveness in the observation group (91.30%) was significantly higher than that in the control group (75.56%) (p < 0.05). ②The vascular recanalization rate in the observation group (89.13%) was significantly higher than that in the control group (71.11%) (p < 0.05). ③The stent retrieval operation count (2.41 ± 0.23) was significantly lower in the observation group than in the control group (1.29 ± 0.16) (p < 0.05). ④ After treatment, the platelet aggregation rate (10.74 ± 3.95) and NIHSS scores (6.58 ± 1.04) were significantly lower, and the Barthel index (77.86 ± 7.21) was significantly higher in the observation group compared to the control group (26.47 ± 5.12, 7.75 ± 2.36, 68.12 ± 6.15) (p < 0.05). All platelet aggregation rate, NIHSS scores and Barthel Index showed significant improvement after treatment when compared to those before treatment (p < 0.05).

CONCLUSION

The combined application of stent retriever mechanical thrombectomy and tirofiban in acute ischemic stroke treatment shows promising effectiveness. Compared to stent retriever alone, tirofiban adjunctive therapy enhances vascular recanalization, reduces retrieval procedures, shortens treatment duration, inhibits platelet aggregation, and improves neurological function recovery, daily living activities, and prognosis. Moreover, it doesn't significantly increase symptom-related risks.

Automatic segmentation of hemorrhagic transformation on follow-up non-contrast CT after acute ischemic stroke

Background

Hemorrhagic transformation (HT) following reperfusion therapies is a serious complication for patients with acute ischemic stroke. Segmentation and quantification of hemorrhage provides critical insights into patients' condition and aids in prognosis. This study aims to automatically segment hemorrhagic regions on follow-up non-contrast head CT (NCCT) for stroke patients treated with endovascular thrombectomy (EVT).

Methods

Patient data were collected from 10 stroke centers across two countries. We propose a semi-automated approach with adaptive thresholding methods, eliminating the need for extensive training data and reducing computational demands. We used Dice Similarity Coefficient (DSC) and Lin's Concordance Correlation Coefficient (Lin's CCC) to evaluate the performance of the algorithm.

Results

A total of 51 patients were included, with 28 Type 2 hemorrhagic infarction (HI2) cases and 23 parenchymal hematoma (PH) cases. The algorithm achieved a mean DSC of 0.66 ± 0.17. Notably, performance was superior for PH cases (mean DSC of 0.73 ± 0.14) compared to HI2 cases (mean DSC of 0.61 ± 0.18). Lin's CCC was 0.88 (95% CI 0.79-0.93), indicating a strong agreement between the algorithm's results and the ground truth. In addition, the algorithm demonstrated excellent processing time, with an average of 2.7 s for each patient case.

Conclusion

To our knowledge, this is the first study to perform automated segmentation of post-treatment hemorrhage for acute stroke patients and evaluate the performance based on the radiological severity of HT. This rapid and effective tool has the potential to assist with predicting prognosis in stroke patients with HT after EVT.

Automated volumetric evaluation of intracranial compartments and cerebrospinal fluid distribution on emergency trauma head CT scans to quantify mass effect

Background

Intracranial space is divided into three compartments by the falx cerebri and tentorium cerebelli. We assessed whether cerebrospinal fluid (CSF) distribution evaluated by a specifically developed deep-learning neural network (DLNN) could assist in quantifying mass effect.

Methods

Head trauma CT scans from a high-volume emergency department between 2018 and 2020 were retrospectively analyzed. Manual segmentations of intracranial compartments and CSF served as the ground truth to develop a DLNN model to automate the segmentation process. Dice Similarity Coefficient (DSC) was used to evaluate the segmentation performance. Supratentorial CSF Ratio was calculated by dividing the volume of CSF on the side with reduced CSF reserve by the volume of CSF on the opposite side.

Results

Two hundred and seventy-four patients (mean age, 61 years ± 18.6) after traumatic brain injury (TBI) who had an emergency head CT scan were included. The average DSC for training and validation datasets were respectively: 0.782 and 0.765. Lower DSC were observed in the segmentation of CSF, respectively 0.589, 0.615, and 0.572 for the right supratentorial, left supratentorial, and infratentorial CSF regions in the training dataset, and slightly lower values in the validation dataset, respectively 0.567, 0.574, and 0.556. Twenty-two patients (8%) had midline shift exceeding 5 mm, and 24 (8.8%) presented with high/mixed density lesion exceeding >25 ml. Fifty-five patients (20.1%) exhibited mass effect requiring neurosurgical treatment. They had lower supratentorial CSF volume and lower Supratentorial CSF Ratio (both p < 0.001). A Supratentorial CSF Ratio below 60% had a sensitivity of 74.5% and specificity of 87.7% (AUC 0.88, 95%CI 0.82-0.94) in identifying patients that require neurosurgical treatment for mass effect. On the other hand, patients with CSF constituting 10-20% of the intracranial space, with 80-90% of CSF specifically in the supratentorial compartment, and whose Supratentorial CSF Ratio exceeded 80% had minimal risk.

Conclusion

CSF distribution may be presented as quantifiable ratios that help to predict surgery in patients after TBI. Automated segmentation of intracranial compartments using the DLNN model demonstrates a potential of artificial intelligence in quantifying mass effect. Further validation of the described method is necessary to confirm its efficacy in triaging patients and identifying those who require neurosurgical treatment.

Concomitant radiosurgical and targeted oncological treatment improves the outcome of patients with brain metastases from gastrointestinal cancer

BACKGROUND

So far, only limited studies exist that evaluate patients with brain metastases (BM) from GI cancer and associated primary cancers who were treated by Gamma Knife Radiosurgery (GKRS) and concomitant immunotherapy (IT) or targeted therapy (TT).

METHODS

Survival after GKRS was compared to the general and specific Graded Prognostic Assessment (GPA) and Score Index for Radiosurgery (SIR). Further, the influence of age, sex, Karnofsky Performance Status Scale (KPS), extracranial metastases (ECM) status at BM diagnosis, number of BM, the Recursive Partitioning Analysis (RPA) classes, GKRS1 treatment mode and concomitant treatment with IT or TT on the survival after GKRS was analyzed. Moreover, complication rates after concomitant GKRS and mainly TT treatment are reported.

RESULTS

Multivariate Cox regression analysis revealed IT or TT at or after the first Gamma Knife Radiosurgery (GKRS1) treatment as the only significant predictor for overall survival after GKRS1, even after adjusting for sex, KPS group, age group, number of BM at GKRS1, RPA class, ECM status at BM diagnosis and GKRS treatment mode. Concomitant treatment with IT or TT did not increase the rate of adverse radiation effects. There was no significant difference in local BM progression after GKRS between patients who received IT or TT and patients without IT or TT.

CONCLUSION

Good local tumor control rates and low rates of side effects demonstrate the safety and efficacy of GKRS in patients with BM from GI cancers. The concomitant radiosurgical and targeted oncological treatment significantly improves the survival after GKRS without increasing the rate of adverse radiation effects. To provide local tumor control, radiosurgery remains of utmost importance in modern GI BM management.

Clinical applications of arterial spin labeling of the intracranial compartment in vascular anomalies-A case-based review

Arterial spin labeling (ASL) is a magnetic resonance perfusion technique that allows for quantification of cerebral blood flow (CBF) without the use of contrast or radiation. Several applications of ASL have been described in diagnosis of strokes and stroke mimics, intracranial tumors, and other conditions. Various vascular anomalies exhibit specific CBF patterns that correlate with different signal intensities on ASL. In this case-based review, we demonstrate the utility of ASL in diagnosis and surveillance of vascular anomalies in the intracranial compartment.

Detection of cerebral aneurysm and intracranial vertebral dissection using non-enhanced magnetic resonance imaging in emergency setting: Emphasis on magnitude image of susceptibility-weighted image

PURPOSE

To evaluate image features and diagnostic performance of susceptibility-weighted image (SWI) in detection of intracranial vertebral artery dissection (VAD) and unruptured intracranial aneurysm (UIA).

MATERIALS AND METHODS

From January 2015 to December 2021, symptomatic patients who underwent 3.0 T MR SWI were recruited. For study group, transfemoral cerebral angiography-proven lesions were included, while 1:1 matched control group with MR angiography were included. Image features of SWI were evaluated. Diagnostic performance and interobserver agreements were calculated for detecting VAD with stenosis and UIA greater than 7 mm.

RESULTS

Total of 110 patients (mean age: 60.92 years, female: 60/110) were included. In the study group (N = 55), 21 patients (38.2%) had VAD, while 34 patients (61.8%) had UIA. For SWI-detectable VAD, larger parent artery (PA)-dilatation ratio was observed (1.36 vs. 1.84, p = 0.034). For SWI-detectable UIA, larger PA-dome ratio (1.32 vs. 1.90, p = 0.020) and larger PA-height ratio (1.25 vs. 1.77, p = 0.005) were observed. The diagnostic performance and kappa values for VAD with stenosis were as follow: sensitivity: 91.7 (95% CI: 61.5-99.8); specificity: 93.9 (95% CI: 87.2-97.7); к: 0.80. The diagnostic performance for UIA larger than 7 mm were as follow: sensitivity: 87.5 (95% CI: 47.4-99.7); specificity: 95.1 (95% CI: 88.9-98.4); к: 0.73.

CONCLUSION

SWI-detectable lesions were VAD with larger PA-dilatation ratio, and UIA with larger PA-dome ratio, and PA-height ratio. SWI was able to accurately detect VAD with stenosis and UIA larger than 7 mm with substantial interobserver agreements.

Advantages of computed tomography-based navigation in clipping distal anterior cerebral artery aneurysms: a retrospective cohort study

Background

The occurrence rate of distal anterior cerebral artery (DACA) aneurysms is relatively low, primarily due to their deep-seated location, which makes surgical clamping challenging. The objective of this study was to investigate the efficacy and safety of computed tomography (CT) navigation-assisted clipping of DACA aneurysms compared to traditional clipping without navigation.

Methods

A retrospective cohort study involving retrospective data collection was performed. The retrospective analysis was conducted on 139 patients with ruptured DACA aneurysms who underwent clipping. From January 2013 to November 2021, 164 patients were retrieved at the Department of Neurosurgery, Renmin Hospital of Wuhan University. The inclusion criteria were patients diagnosed with DACA aneurysms via CT angiography (CTA) or digital subtraction angiography (DSA), those with complete clinical data, and those who underwent craniotomy for aneurysm clipping. Meanwhile, the exclusion criteria were as follows: aneurysm recurrence, traumatic brain injury or surgery history, blood disorders or recent anticoagulant use, and severe organ dysfunction. Data on gender, age, Hunt-Hess grade, Fisher grade, modified Rankin Scale (mRS) score, aneurysm location, hospitalization time, aneurysm found time (the duration from incision to aneurysm discovery), and intraoperative bleeding volume were collected from medical records and neurosurgical databases. Patients were followed up in the clinic or by telephone in May 2022. All patients were divided into a navigation group or a traditional group for statistical analysis.

Results

No statistically significant differences were observed in age, sex, Fisher grade, Hunt-Hess grade, hospitalization time, or aneurysm site between the navigation group and traditional group (P>0.05). Intraoperative blood loss was lower in the navigation group than in the traditional group {370 [280-460] vs. 430 [310-610] mL, P=0.045}. Patients in the traditional group had a shorter aneurysm found time than did those in the navigation group {49 [42-53] vs. 79 [63-84] min, P<0.001}. There was no significant difference in the mRS score at hospital discharge (P=0.336) or follow-up (P=0.157) between the two groups.

Conclusions

CT neuronavigation-assisted microsurgery for clipping DACA aneurysms may improve surgical accuracy, shorten the time to locate aneurysms, and reduce intraoperative blood loss. Although no significant difference in prognosis was observed, this technique shows promise as a safe and effective alternative to traditional clipping without navigation.

Decreasing false-positive detection of intracranial hemorrhage (ICH) using RAPID ICH 3

INTRODUCTION

The prompt detection of intracranial hemorrhage (ICH) on a non-contrast head CT (NCCT) is critical for the appropriate triage of patients, particularly in high volume/high acuity settings. Several automated ICH detection tools have been introduced; however, at present, most suffer from suboptimal specificity leading to false-positive notifications.

METHODS

NCCT scans from 4 large databases were evaluated for the presence of an ICH (IPH, IVH, SAH or SDH) of >0.4 ml using fully-automated RAPID ICH 3.0 as compared to consensus detection from at least two neuroradiology experts. Scans were excluded for (1) severe CT artifacts, (2) prior neurosurgical procedures, or (3) recent intravenous contrast. ICH detection accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and positive and negative likelihood ratios by were determined.

RESULTS

A total of 881 studies were included. The automated software correctly identified 453/463 ICH-positive cases and 416/418 ICH-negative cases, resulting in a sensitivity of 97.84% and specificity 99.52%, positive predictive value 99.56%, and negative predictive value 97.65% for ICH detection. The positive and negative likelihood ratios for ICH detection were similarly favorable at 204.49 and 0.02 respectively. Mean processing time was <40 seconds.

CONCLUSIONS

In this large data set of nearly 900 patients, the automated software demonstrated high sensitivity and specificity for ICH detection, with rare false-positives.

Performance of RAPID noncontrast CT stroke platform in large vessel occlusion and intracranial hemorrhage detection

Background

Noncontrast CT (NCCT) is used to evaluate for intracerebral hemorrhage (ICH) and ischemia in acute ischemic stroke (AIS). Large vessel occlusions (LVOs) are a major cause of AIS, but challenging to detect on NCCT.

Aims

The purpose of this study is to evaluate an AI software called RAPID NCCT Stroke (RAPID, iSchemaView, Menlo Park, CA) for ICH and LVO detection compared to expert readers.

Methods

In this IRB approved retrospective, multicenter study, stand-alone performance of the software was assessed based on the consensus of 3 neuroradiologists and sensitivity and specificity were determined. The platform's performance was then compared to interpretation by readers comprised of eight general radiologists (GR) and three neuroradiologists (NR) in detecting ICH and hyperdense vessel sign (HVS) indicating LVO.

Results

A total of 244 cases were included. Of the 244, 115 were LVOs and 26 were ICHs. One hundred three cases did not have LVO nor ICH. Stand-alone performance of the software demonstrated sensitivities and specificities of 96.2 and 99.5% for ICH and 63.5 and 95.1% for LVO detection. Compared to all 11 readers and eight GR readers only respectively, the software demonstrated superiority, achieving significantly higher sensitivities (63.5% versus 43.6%, p < 0.0001 and 63.5% versus 40.9%, p = 0.001).

Conclusion

The RAPID NCCT Stroke platform demonstrates superior performance to radiologists for detecting LVO from a NCCT. Use of this software platform could lead to earlier LVO detection and expedited transfer of these patients to a thrombectomy capable center.

Magnetic resonance imaging features of presumed intracerebral hemorrhages in dogs show a significant association between apparent diffusion coefficient peripheral layer and estimated bleeding age and commonly exhibit a T2 blackout effect

In humans, intracranial hematomas commonly exhibit a T2 blackout effect (BOE) with diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) maps. Published descriptions of comparable findings in dogs with intracerebral hemorrhages are lacking. Aims of this retrospective observational study were to describe the appearance of presumed intracerebral hemorrhages (PICHs) in DWI regardless of the underlying etiology and presence of T2 blackout effect (T2 BOE) in dogs and to test potential associations with DWI and ADC findings versus the estimated age of the hemorrhage. Magnetic resonance imaging studies of dogs with presumed PICHs based on the combined evaluation of T2*W gradient echo and/or susceptibility-weighted imaging, T1W and T2W images were enrolled. The age of the hemorrhage was estimated according to published criteria based on T1W and T2W sequences. The association between the age of the hemorrhage and the appearance of each finding (stratified or mixed), their signal intensities in DWI/ADC and the presence of the T2 BOE, was evaluated. A total of 35 PICHs were included: 13 of them were stratified and 22 had a mixed aspect. Only the ADC appearance of the peripheral layer in stratified PICHs was significantly associated with estimated age of the hemorrhage (p = .033), being hypointense in all hyperacute cases and hypo-/isointense in acute cases. The T2 BOE was present in 29/35 PICHs. The DWI sequences showed limited utility to date PICHs in this study population. As in humans, the T2 BOE was commonly seen in DWI and ADC maps of dogs with PICHs.

A Review on the Use of Imaging Biomarkers in Oncology Clinical Trials: Quality Assurance Strategies for Technical Validation

Imaging biomarkers (IBs) have been proposed in medical literature that exploit images in a quantitative way, going beyond the visual assessment by an imaging physician. These IBs can be used in the diagnosis, prognosis, and response assessment of several pathologies and are very often used for patient management pathways. In this respect, IBs to be used in clinical practice and clinical trials have a requirement to be precise, accurate, and reproducible. Due to limitations in imaging technology, an error can be associated with their value when considering the entire imaging chain, from data acquisition to data reconstruction and subsequent analysis. From this point of view, the use of IBs in clinical trials requires a broadening of the concept of quality assurance and this can be a challenge for the responsible medical physics experts (MPEs). Within this manuscript, we describe the concept of an IB, examine some examples of IBs currently employed in clinical practice/clinical trials and analyze the procedure that should be carried out to achieve better accuracy and reproducibility in their use. We anticipate that this narrative review, written by the components of the EFOMP working group on "the role of the MPEs in clinical trials"-imaging sub-group, can represent a valid reference material for MPEs approaching the subject.

Coexistence of ipsilateral acute-on-chronic subdural hematoma and acute extradural hematoma: A case report

Chronic subdural hematomas are typically observed in elderly patients receiving antithrombotic and/or anticoagulant therapy. In contrast, acute subdural and extradural hematomas are often observed in young people with traumatic brain injury. The coexistence of ipsilateral chronic subdural and extradural hematomas is rare. Depending on the Glasgow Coma Scale and neuroimaging findings, early surgical intervention is mandatory, as seen in our patient. Early surgical evacuation of a traumatic extradural and chronic subdural hematoma should be done. Also, antithrombotic drug use can lead to chronic subdural hematoma.

Resource utilization in management of spontaneous intracerebral hemorrhage without systemic risk factors. Does early surgical decompression matter?

BACKGROUND

Even though different subtypes of spontaneous ICH are frequently linked to a poor prognosis, their causes, pathological features, and prognoses vary. Atypical intracerebral hemorrhage is the subtype of spontaneous ICH that usually occurs due to an underlying localized vascular lesion. It is unrelated to systemic vascular risk factors, mostly affects children and young adults and is associated with a relatively good outcome. This fact should be considered when planning the evaluation and treatment. Investigating the cause of this subtype is fundamental to providing optimal management. However, if resources do not allow completing the investigations, the cause will be more difficult to discover. Treatment decisions will be made under stress to save the patient's life, especially with rapidly deteriorating patients.

METHODS

We described three cases of spontaneous ICH without systemic risk factors where the bleeding source could not be determined before surgery due to a lack of resources, preventing preoperative vascular investigation. Knowing that the atypical ICH has a distinct identity, regarding etiology and prognosis, encouraged the surgeons to resort to early surgical decompression as an alternative plan. We reviewed the literature searching for supporting evidence.

RESULTS

The results of treatment of the presented cases were satisfactory. The lack of reported similar cases was brought to light by a literature analysis that sought to provide backing for the proposed management strategy. In the end, we supplied two graphic organizers to help readers remember the different types and treatment of hemorrhagic stroke.

CONCLUSION

There isn't enough evidence to show that there are other ways to treat atypical intracerebral haemorrhage when resources are limited. The presented cases highlight the importance of decisionmaking in resource-constrained situations when patient outcomes can be improved.

Alzheimer Disease and Related Cognitive Impairment in Older Adults: A Narrative Review of Screening, Prevention, and Management for Manual Therapy Providers

Objective

The aim of this narrative review was to review literature relevant to manual therapists about cognitive impairment, together with screening, potential treatment, and prevention modalities.

Methods

A literature search of AMED (Allied and Complementary Medicine Database), CINAHL (Cumulative Index of Nursing and Allied Health Literature), PubMed, and MEDLINE was conducted with the search terms "cognitive decline," "cognitive impairment," "screening," and "prevention." We reviewed current screening practices, including functional exams, imaging, and laboratory testing. We reviewed current potential preventive measures and treatments being implemented in practice.

Results

We selected 49 resources for this narrative summary. The Montreal Cognitive Assessment and Mini-Mental State Exam are recommended screening tools. Imaging and laboratory testing are not recommended in screening for cognitive decline. Promotion of healthy, active living through physical and mental activities may assist with prevention of cognitive decline.

Conclusion

Cognitive decline affects a large proportion of the US population. Recognizing signs and symptoms of this condition starts with individuals, caretakers, family members, and health care providers. Health care providers should utilize the most appropriate screening tools to assess the presence of cognitive conditions.

Primary and secondary non-traumatic intra-cerebral haemorrhage: MRI findings

Intracranial haemorrhage (ICH) accounts for 10-30% of strokes, being the form with the worst prognosis. The causes of cerebral haemorrhage can be both primary, mainly hypertensive and amyloid angiopathy, and secondary, such as tumours or vascular lesions. Identifying the aetiology of bleeding is essential since it determines the treatment to be performed and the patient's prognosis. The main objective of this review is to review the main magnetic resonance imaging (MRI) findings of the primary and secondary causes of ICH, focusing on those radiological signs that help guide bleeding due to primary angiopathy or secondary to an underlying lesion. The indications for MRI in the event of non-traumatic intracranial haemorrhage will also be reviewed.

Prior knowledge-based precise diagnosis of blend sign from head computed tomography

Introduction

Automated diagnosis of intracranial hemorrhage on head computed tomography (CT) plays a decisive role in clinical management. This paper presents a prior knowledge-based precise diagnosis of blend sign network from head CT scans.

Method

We employ the object detection task as an auxiliary task in addition to the classification task, which could incorporate the hemorrhage location as prior knowledge into the detection framework. The auxiliary task could help the model pay more attention to the regions with hemorrhage, which is beneficial for distinguishing the blend sign. Furthermore, we propose a self-knowledge distillation strategy to deal with inaccuracy annotations.

Results

In the experiment, we retrospectively collected 1749 anonymous non-contrast head CT scans from the First Affiliated Hospital of China Medical University. The dataset contains three categories: no intracranial hemorrhage (non-ICH), normal intracranial hemorrhage (normal ICH), and blend sign. The experimental results demonstrate that our method performs better than other methods.

Discussion

Our method has the potential to assist less-experienced head CT interpreters, reduce radiologists' workload, and improve efficiency in natural clinical settings.

Intracranial Hemorrhage Detection Using Parallel Deep Convolutional Models and Boosting Mechanism

Intracranial hemorrhage (ICH) can lead to death or disability, which requires immediate action from radiologists. Due to the heavy workload, less experienced staff, and the complexity of subtle hemorrhages, a more intelligent and automated system is necessary to detect ICH. In literature, many artificial-intelligence-based methods are proposed. However, they are less accurate for ICH detection and subtype classification. Therefore, in this paper, we present a new methodology to improve the detection and subtype classification of ICH based on two parallel paths and a boosting technique. The first path employs the architecture of ResNet101-V2 to extract potential features from windowed slices, whereas Inception-V4 captures significant spatial information in the second path. Afterwards, the detection and subtype classification of ICH is performed by the light gradient boosting machine (LGBM) using the outputs of ResNet101-V2 and Inception-V4. Thus, the combined solution, known as ResNet101-V2, Inception-V4, and LGBM (Res-Inc-LGBM), is trained and tested over the brain computed tomography (CT) scans of CQ500 and Radiological Society of North America (RSNA) datasets. The experimental results state that the proposed solution efficiently obtains 97.7% accuracy, 96.5% sensitivity, and 97.4% F1 score using the RSNA dataset. Moreover, the proposed Res-Inc-LGBM outperforms the standard benchmarks for the detection and subtype classification of ICH regarding the accuracy, sensitivity, and F1 score. The results prove the significance of the proposed solution for its real-time application.

Comparison of image quality between a novel mobile CT scanner and current generation stationary CT scanners

PURPOSE

Point-of-care imaging with mobile CT scanners offers several advantages, provided that the image quality is satisfactory. Our aim was to compare image quality of a novel mobile CT to stationary scanners for patients in a neurosurgical intensive care unit (ICU).

METHODS

From November 2020 to April 2021, all patients above 18 years of age examined by a mobile CT scanner at a neurosurgical ICU were included if they also had a stationary head CT examination during the same hospitalization. Quantitative image quality parameters included attenuation and noise in six predefined regions of interest, as well as contrast-to-noise ratio between gray and white matter. Subjective image quality was rated on a 4-garde scale, by four radiologists blinded to scanner parameters.

RESULTS

Fifty patients were included in the final study population. Radiation dose and image attenuation values were similar for mobCT and stationary CTs. There was a small statistically significant difference in subjective quality rating between mobCT and stationary CT images. Two radiologists favored the stationary CT images, one was neutral, and one favored mobCT images. For overall image quality, 14% of mobCT images were rated grade 1 (poor image quality) compared to 8% for stationary CT images.

CONCLUSION

Point-of-care brain CT imaging was successfully performed on clinical neurosurgical ICU patients with small reduction in image quality, predominantly affecting the posterior fossa, compared to high-end stationary CT scanners.

Hypoperfusion Intensity Ratio Is Correlated With the Risk of Parenchymal Hematoma After Endovascular Stroke Treatment

BACKGROUND

Parenchymal hematoma (PH) is a major complication after endovascular treatment (EVT) for ischemic stroke. The hypoperfusion intensity ratio (HIR) represents a perfusion parameter reflecting arterial collateralization and cerebral microperfusion in ischemic brain tissue. We hypothesized that HIR correlates with the risk of PH after EVT.

METHODS

Retrospective multicenter cohort study of patients with large vessel occlusion who underwent EVT between 2013 and 2021 at one of the 2 comprehensive stroke centers (University Medical Center Hamburg-Eppendorf, Germany and Stanford University School of Medicine, CA). HIR was automatically calculated on computed tomography perfusion studies as the ratio of brain volume with time-to-max (Tmax) delay >10 s over volume with Tmax >6 s. Reperfusion hemorrhages were assessed according to the Heidelberg Bleeding Classification. Primary outcome was PH occurrence (PH+) or absence (PH-) on follow-up imaging. Secondary outcome was good clinical outcome defined as a 90-day modified Rankin Scale score of 0 to 2.

RESULTS

A total of 624 patients met the inclusion criteria. We observed PH in 91 (14.6%) patients after EVT. PH+ patients had higher HIR on admission compared with PH- patients (median, 0.6 versus 0.4; P<0.001). In multivariable regression, higher admission blood glucose (adjusted odds ratio [aOR], 1.08 [95% CI, 1.04-1.13]; P<0.001), extensive baseline infarct defined as Alberta Stroke Program Early CT Score ≤5 (aOR, 2.48 [1.37-4.42]; P=0.002), and higher HIR (aOR, 1.22 [1.09-1.38]; P<0.001) were independent determinants of PH after EVT. Both higher HIR (aOR, 0.83 [0.75-0.92]; P<0.001) and PH on follow-up imaging (aOR, 0.39 [0.18-0.80]; P=0.013) were independently associated with lower odds of achieving good clinical outcome.

CONCLUSIONS

Poorer (higher) HIR on admission perfusion imaging was strongly associated with PH occurrence after EVT. HIR as a surrogate for cerebral microperfusion might reflect tissue vulnerability for reperfusion hemorrhages. This automated and quickly available perfusion parameter might help to assess the need for intensive medical care after EVT.

Hemorrhagic stroke: Uncommon complication of diabetic ketoacidosis in pediatric patients

Diabetic ketoacidosis (DKA) is a well-known complication of type 1 diabetes mellitus. Diabetic ketoacidosis predisposes patients into devastating neurological complications. The most common neurologic complication is cerebral edema. Stroke either ischemic or hemorrhagic are uncommon complications of DKA with worse patient's outcome. Hemorrhagic stroke can manifest as subarachnoid or intraparenchymal hemorrhage. We present a 14-year-girl presented with DKA and complicated with both subarachnoid and intraparenchymal hemorrhages. Owing to early diagnosis and prompt treatment the patient had good outcome.

Causes and Risk Factors of Pediatric Spontaneous Intracranial Hemorrhage—A Systematic Review

Previous studies suggest that the most common cause of spontaneous intracerebral hemorrhage in children and adolescents is arteriovenous malformations (AVMs). However, an update containing recently published data on pediatric spontaneous intracranial hemorrhages is lacking. The aim of this study is to systematically analyze the published data on the etiologies and risk factors of pediatric spontaneous intracranial hemorrhage. This systematic review was performed in compliance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A search in PubMed, Embase, Scopus, Web of Science and Cochrane Library was conducted aiming for articles published in year 2000 and later, containing data on etiology and risk factors of spontaneous intracranial hemorrhages in unselected cohorts of patients aged between 1 month and 18 years. As a result, forty studies were eligible for data extraction and final analysis. These included 7931 children and adolescents with 4009 reported etiologies and risk factors. A marked variety of reported etiologies and risk factors among studies was observed. Vascular etiologies were the most frequently reported cause of pediatric spontaneous intracranial hemorrhages (n = 1727, 43.08% of all identified etiologies or risk factors), with AVMs being the most common vascular cause (n = 1226, 70.99% of all vascular causes). Hematological and systemic causes, brain tumors, intracranial infections and cardiac causes were less commonly encountered risk factors and etiologies.

Fatal intracranial hemorrhage as the presenting sign of acute promyelocytic leukemia: A case report

Intracranial hemorrhage (ICH) can be a devastating medical event with numerous potential etiologies. In young people under age 40, ruptured vascular malformation is the most common cause of ICH. Without critical review of imaging and laboratory findings and clinical suspicion beyond vascular malformation, alternative etiologies of hemorrhage may be overlooked in the younger age group. Here we present a case of a 22-year-old male presenting with large ICH originally thought secondary to ruptured vascular malformation. After careful review of all imaging and laboratory findings, the patient was found to have hemorrhage secondary to acute promyelocytic leukemia (APL). Though ICH proved fatal in this case, early treatment of acute leukemia with appropriate chemotherapeutic agents and correction of coagulopathy could be life saving for patients with less severe intracranial injury.

A Case Report of Diabetic Striatopathy: An Approach to Diagnosis Based on Clinical and Radiological Findings

Diabetic striatopathy (DS) is an acute hyperkinetic movement disorder characterized by hemiballismus-hemichorea (HBHC) due to nonketotic hyperglycemia. DS manifests a fascinating interplay between endocrinopathy (diabetes), striatal (putamen, caudate nucleus, globus pallidus) pathology, and a dramatic neurological movement disorder, HBHC. The striking hyperintensity on imaging modalities such as computed axial tomography (CT) scan of the brain and T1-weighted magnetic resonance imaging (MRI) of the brain can mislead the clinician to an erroneous diagnosis of a cerebral hemorrhage and/or ischemic infarct, especially in an acute setting. We present an acute case of DS and outline the natural history, semiology, typical radiological findings, and therapeutic options. With careful and thoughtful analysis, an accurate diagnosis can be exacted, sparing the patient unnecessary anxiety and medical costs.

Overview of Traumatic Brain Injury in American Football Athletes

OBJECTIVE

The aim of this review is to provide a summary of the epidemiology, clinical presentation, pathophysiology, and treatment of traumatic brain injury in collision athletes, particularly those participating in American football.

DATA SOURCES

A literature search was conducted using the PubMed/MEDLINE and Google Scholar databases for publications between 1990 and 2019. The following search phrases were used: "concussion," "professional athletes," "collision athletes," "mild traumatic brain injury," "severe traumatic brain injury," "management of concussion," "management of severe traumatic brain injury," and "chronic traumatic encephalopathy." Publications that did not present epidemiology, clinical presentation, pathophysiology, radiological evaluation, or management were omitted. Classic articles as per senior author recommendations were retrieved through reference review.

RESULTS

The results of the literature review yielded 147 references: 21 articles discussing epidemiology, 16 discussing clinical presentation, 34 discussing etiology and pathophysiology, 10 discussing radiological evaluation, 34 articles for on-field management, and 32 articles for medical and surgical management.

CONCLUSION

Traumatic brain injuries are frequent in professional collision athletes, and more severe injuries can have devastating and lasting consequences. Although sport-related concussions are well studied in professional American football, there is limited literature on the epidemiology and management of severe traumatic brain injuries. This article reviews the epidemiology, as well as the current practices in sideline evaluation, acute management, and surgical treatment of concussions and severe traumatic brain injury in professional collision athletes. Return-to-play decisions should be based on individual patient symptoms and recovery.

How to dose-stage large or high-risk brain metastases: an alternative two-fraction radiosurgical treatment approach

OBJECTIVE

The authors sought to evaluate clinical outcome in patients with large, high-risk brain metastases (BMs) treated with different dose strategies by use of two-fraction dose-staged Gamma Knife radiosurgery (GKRS).

METHODS

A retrospective analysis was performed with data from 142 patients from two centers who had been treated with two-fraction dose-staged GKRS between June 2015 and January 2020. Depending on the changes in marginal dose between the first (GKRS1) and second (GKRS2) GKRS treatments, the study population was divided into three treatment groups: dose escalation, dose maintenance, and dose de-escalation.

RESULTS

The 142 study patients underwent two-fraction dose-staged GKRS treatments for 166 large, high-risk BMs. The median tumor volume of 7.4 cm3 decreased significantly from GKRS1 to GKRS2 (4.4 cm3; p < 0.001), and to the last follow-up (1.8 cm3; p < 0.001). These significant differences in BM volume reduction were achieved in all three treatment groups. However, differences according to the primary tumor histology were apparent: while dose maintenance seemed to be the most effective treatment strategy for BMs from lung cancer or melanoma, dose escalation was the most beneficial treatment option for BMs from breast, gastrointestinal, or genitourinary cancer. Of note, the vast majority of patients who underwent dose-staged BM treatment did not show any significant postradiosurgical complications.

CONCLUSIONS

In patients with large, high-risk BMs, dose-staged GKRS treatment represents an effective local treatment method with acceptable complication risks. Different dose-strategy options are available that may be chosen according to the primary tumor histology and treatment volume but may also be tailored to the findings at GKRS2.

A joint convolutional-recurrent neural network with an attention mechanism for detecting intracranial hemorrhage on noncontrast head CT

To investigate the performance of a joint convolutional neural networks-recurrent neural networks (CNN-RNN) using an attention mechanism in identifying and classifying intracranial hemorrhage (ICH) on a large multi-center dataset; to test its performance in a prospective independent sample consisting of consecutive real-world patients. All consecutive patients who underwent emergency non-contrast-enhanced head CT in five different centers were retrospectively gathered. Five neuroradiologists created the ground-truth labels. The development dataset was divided into the training and validation set. After the development phase, we integrated the deep learning model into an independent center’s PACS environment for over six months for assessing the performance in a real clinical setting. Three radiologists created the ground-truth labels of the testing set with a majority voting. A total of 55,179 head CT scans of 48,070 patients, 28,253 men (58.77%), with a mean age of 53.84 ± 17.64 years (range 18–89) were enrolled in the study. The validation sample comprised 5211 head CT scans, with 991 being annotated as ICH-positive. The model's binary accuracy, sensitivity, and specificity on the validation set were 99.41%, 99.70%, and 98.91, respectively. During the prospective implementation, the model yielded an accuracy of 96.02% on 452 head CT scans with an average prediction time of 45 ± 8 s. The joint CNN-RNN model with an attention mechanism yielded excellent diagnostic accuracy in assessing ICH and its subtypes on a large-scale sample. The model was seamlessly integrated into the radiology workflow. Though slightly decreased performance, it provided decisions on the sample of consecutive real-world patients within a minute.

Endovascular Management of Intracranial Dural AVFs: Principles

Intracranial dural AVFs are abnormal communications between arteries that supply the dura mater and draining cortical veins or venous sinuses. They are believed to form as a response to venous insults such as thrombosis, trauma, or infection. Classification and management are dependent on the presence of drainage/reflux into cortical veins because such drainage markedly elevates the risk of hemorrhage or venous congestion, resulting in neurologic deficits. AVFs with tolerable symptoms and benign drainage patterns can be managed conservatively. Intolerable symptoms, presentation with hemorrhage/neurologic deficits, or aggressive drainage patterns are indications for intervention. Treatment options include microsurgical disconnection, endovascular transarterial embolization, transvenous embolization, or a combination. This is the first in a series of 3 articles on endovascular management of intracranial dural AVFs, in which we outline the principles and outcomes of endovascular treatment.

Volumetric accuracy of different imaging modalities in acute intracerebral hemorrhage

Background

Follow-up imaging in intracerebral hemorrhage is not standardized and radiologists rely on different imaging modalities to determine hematoma growth. This study assesses the volumetric accuracy of different imaging modalities (MRI, CT angiography, postcontrast CT) to measure hematoma size.

Methods

28 patients with acute spontaneous intracerebral hemorrhage referred to a tertiary stroke center were retrospectively included between 2018 and 2019. Inclusion criteria were (1) spontaneous intracerebral hemorrhage (supra- or infratentorial), (2) noncontrast CT imaging performed on admission, (3) follow-up imaging (CT angiography, postcontrast CT, MRI), and (4) absence of hematoma expansion confirmed by a third cranial image within 6 days. Two independent raters manually measured hematoma volume by drawing a region of interest on axial slices of admission noncontrast CT scans as well as on follow-up imaging (CT angiography, postcontrast CT, MRI) using a semi-automated segmentation tool (Visage image viewer; version 7.1.10). Results were compared using Bland–Altman plots.

Results

Mean admission hematoma volume was 18.79 ± 19.86 cc. All interrater and intrarater intraclass correlation coefficients were excellent (1; IQR 0.98–1.00). In comparison to hematoma volume on admission noncontrast CT volumetric measurements were most accurate in patients who received postcontrast CT (bias of − 2.47%, SD 4.67: n = 10), while CT angiography often underestimated hemorrhage volumes (bias of 31.91%, SD 45.54; n = 20). In MRI sequences intracerebral hemorrhage volumes were overestimated in T2* (bias of − 64.37%, SD 21.65; n = 10). FLAIR (bias of 6.05%, SD 35.45; n = 13) and DWI (bias of-14.6%, SD 31.93; n = 12) over- and underestimated hemorrhagic volumes.

Conclusions

Volumetric measurements were most accurate in postcontrast CT while CT angiography and MRI sequences often substantially over- or underestimated hemorrhage volumes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-022-00735-3.

1.5 Tesla Magnetic Resonance Imaging Features of Canine Intracranial Intra-axial Hematomas

The differentiation of solitary intra-axial hematomas from hemorrhagic neoplasms based on their magnetic resonance imaging (MRI) features is challenging. The treatment and prognosis for these two disease entities are vastly different and distinction between them is often based on MRI findings alone. The aim of this study was to describe the 1.5 tesla MRI features of canine intra-axial hematomas and correlate these findings with the evolution of hemorrhages described in human brains. Retrospective evaluation of patient details, clinical signs, and MRI findings of dogs with intra-axial hematomas that were histopathologically confirmed or determined via repeat MRI study and/or resolution of neurological signs. Ten dogs met the inclusion criteria. All 10 hematoma lesions were determined to be 2–7 days in age. On MRI, all 10 hemorrhagic lesions were comprised of two distinct regions; a relatively thin T1-weighted (T1W), T2-weighted (T2W) and gradient echo (GRE) hypointense (9/10) peripheral border region and a large central region that was heterogenous but predominantly T1W, T2W and GRE hyperintense (8/10). The peripheral border region was complete in its integrity in all 10 cases on T2W and GRE sequences. Contrast enhancement was present in (6/10) hematoma lesions and was always peripheral in nature with no evidence of central enhancement associated with any of the lesions. An intra-axial hematoma should be suspected in solitary hemorrhagic space occupying lesions that have a complete hypointense peripheral rim, elicit a peripheral contrast enhancement pattern, and display the expected temporal pattern of hematoma evolution.

Transfer Learning of the ResNet-18 and DenseNet-121 Model Used to Diagnose Intracranial Hemorrhage in CT Scanning

OBJECTIVE

The aim of the study was to verify the ability of the deep learning model to identify five subtypes and normal images in non-contrast enhancement CT of intracranial hemorrhage.

METHODS

A total of 351 patients (39 patients in the normal group, 312 patients in the intracranial hemorrhage group) who underwent intracranial hemorrhage noncontrast enhanced CT were selected, obtaining 2768 images in total (514 images for the normal group, 398 images for the epidural hemorrhage group, 501 images for the subdural hemorrhage group, 497 images for the intraventricular hemorrhage group, 415 images for the cerebral parenchymal hemorrhage group, and 443 images for the subarachnoid hemorrhage group). Based on the diagnostic reports of two radiologists with more than 10 years of experience, the ResNet-18 and DenseNet-121 deep learning models were selected. Transfer learning was used. 80% of the data was used for training models, 10% was used for validating model performance against overfitting, and the last 10% was used for the final evaluation of the model. Assessment indicators included accuracy, sensitivity, specificity, and AUC values.

RESULTS

The overall accuracy of ResNet-18 and DenseNet-121 models was obtained as 89.64% and 82.5%, respectively. The sensitivity and specificity of identifying five subtypes and normal images were above 0.80. The sensitivity of the DenseNet-121 model to recognize intraventricular hemorrhage and cerebral parenchymal hemorrhage was lower than 0.80, 0.73, and 0.76, respectively. The AUC values of the two deep learning models were found to be above 0.9.

CONCLUSION

The deep learning model can accurately identify the five subtypes of intracranial hemorrhage and normal images, and it can be used as a new tool for clinical diagnosis in the future.

Temporal changes in extra-axial brain hematoma's signal intensity in magnetic resonance images of trauma patients: A preliminary, technical study

INTRODUCTION

Dating the exact or estimated time of trauma is an important issue facing forensic medicine. Several clinical and radiological methods were used to achieve this purpose. In the recent study, we aimed to track the changes in the signal intensity of the extra-axial brain hematoma using magnetic resonance imaging (MRI) conventional sequences as well as diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC).

MATERIALS AND METHODS

Considering inclusion and exclusion criteria, all patients with blunt head trauma were involved. After proper management., stabilization, and resuscitation, the participants were assessed using conventional sequences of MRI and DWI twenty-four hours, forty-eight hours, and three weeks after the injury. Temporal changes of signal intensity were compared by Wilcoxon ranged test.

RESULTS

Sixteen patients sustaining blunt head trauma were included in this study. The study showed that during the time, diffusion restriction could be seen in an extraaxial hematoma. At the first 24 hours, the signal of hematoma was void in 87.5% of DWI and 100% of ADC. On the second day, they were hypo-signal in 75% of DWI and 100% 0f ADCs, and after three weeks, 100% of cases were hyper-signal in DWI and hypo-signal ADCs.

CONCLUSION

This preliminary study has shown that the DWI can be used to detect and track the extra-axial hematoma. The signal intensity was void during the first twentyfour hours, although it became hypo-signal after 48 hours. Of note, the diffusion restriction is noted after three weeks.

Magnetic Resonance Imaging in Neurocritically Ill Patients: Who Fails and How?

OBJECTIVES

Performing magnetic resonance imaging (MRI) in neurocritically ill patients is challenging because it often requires sedation and withholding care in the neurological intensive care unit. This study investigated the incidence of and reasons for failed or complicated MRI (MRI-FC) in such patients.

METHODS

A consecutive series of 218 neurocritically ill patients who underwent brain MRI were retrospectively evaluated. Failed or complicated MRI included failure to obtain all ordered sequences, unscheduled sedative administration, decrease in oxygen saturation to less than 90%, hypotension (≥40-mm Hg decrease and/or use of inotropic agents), and cardiac or respiratory arrest.

RESULTS

Failed or complicated MRI occurred in 66 patients (30.3%) and included failure to obtain MRI sequences (n = 13), unscheduled use of sedatives (n = 62), oxygen desaturation (n = 9), and hypotension (n = 6). Cardiac or respiratory arrest did not occur. Use of sedative agents while in intensive care (P < 0.01), high Acute Physiology and Chronic Health Evaluation II score (P = 0.031), and low Glasgow Coma Scale score on admission (P = 0.047) were associated with MRI-FC. Scan times were longer (P = 0.004) and Glasgow Coma Scale (P < 0.001) and Richmond Agitation Sedation Scale (P = 0.003) scores were lower (P = 0.004) after imaging in patients with MRI-FC. Previous use of sedative agents was independently associated with MRI-FC (adjusted odds ratio = 3.57, 95% confidence interval = 1.78 to 7.24, P < 0.001).

CONCLUSIONS

Failed or complicated MRI was common and was associated with the use of sedative agents, severity of illness, and lower level of consciousness. Studies to ensure effective and safe performance of MRI in neurocritically ill patients are needed.

Current approaches and advances in the imaging of stroke

A stroke occurs when the blood flow to the brain is suddenly interrupted, depriving brain cells of oxygen and glucose and leading to further cell death. Neuroimaging techniques, such as computed tomography and magnetic resonance imaging, have greatly improved our ability to visualise brain structures and are routinely used to diagnose the affected vascular region of a stroke patient's brain and to inform decisions about clinical care. Currently, these multimodal imaging techniques are the backbone of the clinical management of stroke patients and have immensely improved our ability to visualise brain structures. Here, we review recent developments in the field of neuroimaging and discuss how different imaging techniques are used in the diagnosis, prognosis and treatment of stroke.

Summary: Stroke imaging has undergone seismic shifts in the past decade. Although magnetic resonance imaging (MRI) is superior to computed tomography in providing vital information, further research on MRI is still required to bring its full potential into clinical practice.

Hemorrhagic Transformation After Ischemic Stroke: Mechanisms and Management

Symptomatic hemorrhagic transformation (HT) is one of the complications most likely to lead to death in patients with acute ischemic stroke. HT after acute ischemic stroke is diagnosed when certain areas of cerebral infarction appear as cerebral hemorrhage on radiological images. Its mechanisms are usually explained by disruption of the blood-brain barrier and reperfusion injury that causes leakage of peripheral blood cells. In ischemic infarction, HT may be a natural progression of acute ischemic stroke and can be facilitated or enhanced by reperfusion therapy. Therefore, to balance risks and benefits, HT occurrence in acute stroke settings is an important factor to be considered by physicians to determine whether recanalization therapy should be performed. This review aims to illustrate the pathophysiological mechanisms of HT, outline most HT-related factors after reperfusion therapy, and describe prevention strategies for the occurrence and enlargement of HT, such as blood pressure control. Finally, we propose a promising therapeutic approach based on biological research studies that would help clinicians treat such catastrophic complications.

Diabetes mellitus and hypertensive cerebral hemorrhage

Diabetes mellitus is an increasingly common public health problem and affects the population health. In many studies, DM is very often in a close correlation with many cardiovascular diseases and brain hemorrhage in general. The aim of the paper was to determine whether the presence of diabetes mellitus has influence on the occurrence of cerebral hemorrhage. Material and methods: The study included 61 patients diagnosed with hypertensive intracerebral hematoma in the hemispheres of the brain. Results: The prevalence of diabetes in the group of survivors of intracerebral hemorrhage was 26.67%, while in the group of subjects in whom the disease ended lethally diabetes had an insignificantly higher prevalence of 43.75% (Chi-square: 1.61df = 1, p = 0.21). Analysis of the prevalence of diabetes regarding the mobility of the respondents showed that there were no respondents with diabetes in the group of patients who could function independently, while there were 7 (24.14%) respondents with diabetes in the group who required help or aid for accomplishing their daily activities, and 5 (50%) in the group of respondents who were completely dependent on someone else in performing the everyday functioning. Statistical analysis showed these differences as insufficient to be statistically confirmed as significant (Fisher exact test, p = 0.105). Conclusion: In patients who have had cerebral hemorrhage with lethal outcome diabetes mellitus is a very common phenomenon, as well as in patients who have survived but subsequently have decreased mobility. But these differences are not statistically significant. Measures for reduction of the incidence of diabetes mellitus are needed. These measures include early detection of the disease, treatment and prevention of disability.