A multitask deep learning approach for pulmonary embolism detection and identification

Pulmonary embolism (PE) is a blood clot traveling to the lungs and is associated with substantial morbidity and mortality. Therefore, rapid diagnoses and treatments are essential. Chest computed tomographic pulmonary angiogram (CTPA) is the gold standard for PE diagnoses. Deep learning can enhance the radiologists’workflow by identifying PE using CTPA, which helps to prioritize important cases and hasten the diagnoses for at-risk patients. In this study, we propose a two-phase multitask learning method that can recognize the presence of PE and its properties such as the position, whether acute or chronic, and the corresponding right-to-left ventricle diameter (RV/LV) ratio, thereby reducing false-negative diagnoses. Trained on the RSNA-STR Pulmonary Embolism CT Dataset, our model demonstrates promising PE detection performances on the hold-out test set with the window-level AUROC achieving 0.93 and the sensitivity being 0.86 with a specificity of 0.85, which is competitive with the radiologists’sensitivities ranging from 0.67 to 0.87 with specificities of 0.89–0.99. In addition, our model provides interpretability through attention weight heatmaps and gradient-weighted class activation mapping (Grad-CAM). Our proposed deep learning model could predict PE existence and other properties of existing cases, which could be applied to practical assistance for PE diagnosis

A Low-cost Biofeedback Tool for Automated Assessments of Upper Extremity Function in Stroke Patients

Studies report up to 85% of stroke survivors experience upper extremity (UE) hemiparesis1 and 78% fail to achieve the average UE function for their age, even after 3 months of treatment2. Limited access to outpatient rehabilitation for these survivors worsens the issue; in Texas, 71% of rural counties lack rehabilitation clinics for stroke patients. To mitigate issues involving healthcare accessibility, research has been undertaken to automate scoring of the Fugl-Meyer assessment, the standard stroke rehabilitation scale describing upper extremity motor function, to alleviate physician burden and inform physical therapists of disabilities. We aim to demonstrate the feasibility of using a single handheld camera for motion detection and machine learning methods to score gross and fine upper extremity motor skills with accuracies comparable to traditional methods involving complex recording equipment. Investigators recorded Fugl-Meyer assessments performed by consenting stroke patients (N=45) presenting with acute or subacute weakness or unilateral hemiplegia resulting from ischemic or hemorrhagic stroke. Two deep-learning motion detection algorithms extracted xy-positional coordinates of body joints and hand joints from the study activity videos. We developed and tested the predictive ability of four machine learning models, eXtreme Gradient Boosting (XGBoost), a convolutional neural network (CNN), recurrent neural network (RNN), and dilated CNN, and compared the results with scores provided by a licensed occupational therapist. The item-wise prediction accuracies are 0.838∓0.214, 0.764∓0.155, 0.807∓0.165, 0.827∓0.162 for each model listed above, respectively. Strong correlation between model prediction and total Fugl-Meyer scores are seen when analyzed by patient or group-wise; correlation coefficients average 0.89 and range between 0.83 and 0.951. This novel method demonstrates potential to conduct telehealth rehabilitation evaluations with low-cost and pre-existing technologies. This system should reduce physician and therapist burden and improve accessibility to healthcare rehabilitation among geographically isolated and patient population living with disabilities. References: 1. Levin, M. F., Kleim, J. A., & Wolf, S. L. (2009). What do motor “recovery” and “compensation” mean in patients following stroke? Neurorehabilitation and Neural Repair, 23(4), 313–319. 2. Mayo, N. E., Wood-Dauphinee, S., Ahmed, S., Gordon, C., Higgins, J., McEwen, S., & Salbach, N. (1999). Disablement following stroke. Disability and Rehabilitation, 21(5-6), 258–268

The 10th Biennial Hatter Cardiovascular Institute workshop: cellular protection—evaluating new directions in the setting of myocardial infarction, ischaemic stroke, and cardio-oncology

Due to its poor capacity for regeneration, the heart is particularly sensitive to the loss of contractile cardiomyocytes. The onslaught of damage caused by ischaemia and reperfusion, occurring during an acute myocardial infarction and the subsequent reperfusion therapy, can wipe out upwards of a billion cardiomyocytes. A similar program of cell death can cause the irreversible loss of neurons in ischaemic stroke. Similar pathways of lethal cell injury can contribute to other pathologies such as left ventricular dysfunction and heart failure caused by cancer therapy. Consequently, strategies designed to protect the heart from lethal cell injury have the potential to be applicable across all three pathologies. The investigators meeting at the 10th Hatter Cardiovascular Institute workshop examined the parallels between ST-segment elevation myocardial infarction (STEMI), ischaemic stroke, and other pathologies that cause the loss of cardiomyocytes including cancer therapeutic cardiotoxicity. They examined the prospects for protection by remote ischaemic conditioning (RIC) in each scenario, and evaluated impasses and novel opportunities for cellular protection, with the future landscape for RIC in the clinical setting to be determined by the outcome of the large ERIC-PPCI/CONDI2 study. It was agreed that the way forward must include measures to improve experimental methodologies, such that they better reflect the clinical scenario and to judiciously select combinations of therapies targeting specific pathways of cellular death and injury

Risk Factors for Pediatric Ischemic Stroke and Intracranial Hemorrhage: A National Electronic Health Record Based Study

BACKGROUND: Stroke is an important cause of morbidity in pediatrics. Large studies are needed to better understand the epidemiology, pathogenesis and risk factors associated with pediatric stroke. Large administrative datasets can provide information on risk factors in perinatal and childhood stroke at low cost. The aim of this hypothesis-generating study was to use a large administrative dataset to assess for prevalence and odds-ratios of rare exposures associated with pediatric stroke. METHODS: The data for patients aged 0-18 with a diagnosis of either ischemic stroke or intracranial hemorrhage were extracted from the Cerner Health Facts EMR Database from 2000 to 2018. Prevalence of various possible risk factors for pediatric and adult stroke was assessed using ICD 9 and 10 codes. Odds ratios were calculated using a control group of patients without stroke. RESULTS: CONCLUSION: This is the largest retrospective study of pediatric stroke of its kind from hospitals across the US in both academic and non-academic clinical settings. Much of our data was consistent with prior studies. ICD codes for tobacco exposure, hyperlipidemia, diabetes, and hypertension all had high odds ratios for stroke in children, which suggest a relationship between these conditions and pediatric stroke. However, ascertainment bias is a major concern with electronic health record-based studies. More focused study is needed into the role of these exposures into the pathogenesis of pediatric stroke

A National, Electronic Health Record-Based Study of Perinatal Hemorrhagic and Ischemic Stroke

BACKGROUND: Perinatal stroke occurs in approximately 1 in 1100 live births. Large electronic health record (EHR) data can provide information on exposures associated with perinatal stroke in a larger number of patients than is achievable through traditional clinical studies. The objective of this study is to assess prevalence and odds ratios of known and theorized comorbidities with perinatal ischemic and hemorrhagic stroke. METHODS: The data for patients aged 0-28 days with a diagnosis of either ischemic or hemorrhagic stroke were extracted from the Cerner Health Facts Electronic Medical Record (EMR) database. Incidence of birth demographics and perinatal complications were recorded. Odds ratios were calculated against a control group. RESULTS: A total of 535 (63%) neonates were identified with ischemic stroke and 312 (37%) with hemorrhagic stroke. The most common exposures for ischemic stroke were sepsis (n = 82, 15.33%), hypoxic injury (n = 61, 11.4%), and prematurity (n = 49, 9.16%). The most common comorbidities for hemorrhagic stroke were prematurity (n = 81, 26%) and sepsis (n = 63, 20%). No perinatal ischemic stroke patients had diagnosis codes for cytomegalovirus disease. Procedure and diagnosis codes related to critical illness, including intubation and resuscitation, were prominent in both hemorrhagic (n = 46, 15%) and ischemic stroke (n = 45, 8%). CONCLUSION: This electronic health record-based study of perinatal stroke, the largest of its kind, demonstrated a wide variety of comorbid conditions with ischemic and hemorrhagic stroke. Sepsis, prematurity, and hypoxic injury are associated with perinatal hemorrhagic and ischemic stroke, though prevalence varies between types. Much of our data were similar to prior studies, which lends validity to the electronic health record database in studying perinatal stroke

Peripheral Blood Monocytes as a Therapeutic Target for Marrow Stromal Cells in Stroke Patients

BACKGROUND: Systemic administration of marrow stromal cells METHODS: Peripheral blood from stroke patients was collected at 5-7 days ( RESULTS: Our results show that there is a higher release of IFN-γ and IL-10 from monocytes isolated from peripheral blood at day 5-7 after stroke compared with monocytes from healthy controls. In trans-well co-cultures of MSCs and monocytes isolated from stroke patients, we found statistically significant increased levels of IL-4 and MCP-1, and decreased levels of IL-6, IL-1β, and TNF-α. Addition of MSCs to monocytes increased the secretions of Fractalkine, IL-6, and MCP-1, while the secretions of TNF-α decreased, as compared to the secretions from monocytes alone. When MSCs were added to monocytes from stroke patients, they decreased the levels of IL-1β, and increased the levels of IL-10 significantly more as compared to when they were added to monocytes from control patients. CONCLUSION: The systemic circulation of stroke patients may differentially interact with MSCs to release soluble factors integral to their paracrine mechanisms of benefit. Our study finds that the effect of MSCs on Mϕ is different on those derived from stroke patients blood as compared to healthy controls. These findings suggest immunomodulation of peripheral immune cells as a therapeutic target for MSCs in patients with acute stroke

An Interpretable Framework to Identify Responsive Subgroups From Clinical Trials Regarding Treatment Effects: Application to Treatment of Intracerebral Hemorrhage

Randomized Clinical trials (RCT) suffer from a high failure rate which could be caused by heterogeneous responses to treatment. Despite many models being developed to estimate heterogeneous treatment effects (HTE), there remains a lack of interpretable methods to identify responsive subgroups. This work aims to develop a framework to identify subgroups based on treatment effects that prioritize model interpretability. The proposed framework leverages an ensemble uplift tree method to generate descriptive decision rules that separate samples given estimated responses to the treatment. Subsequently, we select a complementary set of these decision rules and rank them using a sparse linear model. To address the trial\u27s limited sample size problem, we proposed a data augmentation strategy by borrowing control patients from external studies and generating synthetic data. We apply the proposed framework to a failed randomized clinical trial for investigating an intracerebral hemorrhage therapy plan. The Qini-scores show that the proposed data augmentation strategy plan can boost the model\u27s performance and the framework achieves greater interpretability by selecting complementary descriptive rules without compromising estimation quality. Our model derives clinically meaningful subgroups. Specifically, we find those patients with Diastolic Blood Pressure≥70 mm hg and Systolic Blood Pressuresubgroups, our framework can contribute to developing personalized treatment strategies for patients more efficiently

Recent progress in translational research on neurovascular and neurodegenerative disorders

The already established and widely used intravenous application of recombinant tissue plasminogen activator as a re-opening strategy for acute vessel occlusion in ischemic stroke was recently added by mechanical thrombectomy, representing a fundamental progress in evidence-based medicine to improve the patient’s outcome. This has been paralleled by a swift increase in our understanding of pathomechanisms underlying many neurovascular diseases and most prevalent forms of dementia. Taken together, these current advances offer the potential to overcome almost two decades of marginally successful translational research on stroke and dementia, thereby spurring the entire field of translational neuroscience. Moreover, they may also pave the way for the renaissance of classical neuroprotective paradigms. This review reports and summarizes some of the most interesting and promising recent achievements in neurovascular and dementia research. It highlights sessions from the 9th International Symposium on Neuroprotection and Neurorepair that have been discussed from April 19th to 22nd in Leipzig, Germany. To acknowledge the emerging culture of interdisciplinary collaboration and research, special emphasis is given on translational stories ranging from fundamental research on neurode- and -regeneration to late stage translational or early stage clinical investigations

Necrostatin-1 Reduces Histopathology and Improves Functional Outcome after Controlled Cortical Impact in Mice

Necroptosis is a newly identified type of programmed necrosis initiated by the activation of tumor necrosis factor alpha (TNF?)/Fas. Necrostatin-1 is a specific inhibitor of necroptosis that reduces ischemic tissue damage in experimental stroke models. We previously reported decreased tissue damage and improved functional outcome after controlled cortical impact (CCI) in mice deficient in TNF? and Fas. Hence, we hypothesized that necrostatin-1 would reduce histopathology and improve functional outcome after CCI in mice. Compared with vehicle-/inactive analog-treated controls, mice administered necrostatin-1 before CCI had decreased propidium iodide-positive cells in the injured cortex and dentate gyrus (6 h), decreased brain tissue damage (days 14, 35), improved motor (days 1 to 7), and Morris water maze performance (days 8 to 14) after CCI. Improved spatial memory was observed even when drug was administered 15 mins after CCI. Necrostatin-1 treatment did not reduce caspase-3-positive cells in the dentate gyrus or cortex, consistent with a known caspase-independent mechanism of necrostatin-1. However, necrostatin-1 reduced brain neutrophil influx and microglial activation at 48 h, suggesting a novel anti-inflammatory effect in traumatic brain injury (TBI). The data suggest that necroptosis plays a significant role in the pathogenesis of cell death and functional outcome after TBI and that necrostatin-1 may have therapeutic potential for patients with TBI