Burden of Ischemic and Hemorrhagic Stroke Across the US From 1990 to 2019.

Importance: Stroke is a leading cause of death and disability in the US. Accurate and updated measures of stroke burden are needed to guide public health policies. Objective: To present burden estimates of ischemic and hemorrhagic stroke in the US in 2019 and describe trends from 1990 to 2019 by age, sex, and geographic location. Design, Setting, and Participants: An in-depth cross-sectional analysis of the 2019 Global Burden of Disease study was conducted. The setting included the time period of 1990 to 2019 in the US. The study encompassed estimates for various types of strokes, including all strokes, ischemic strokes, intracerebral hemorrhages (ICHs), and subarachnoid hemorrhages (SAHs). The 2019 Global Burden of Disease results were released on October 20, 2020. Exposures: In this study, no particular exposure was specifically targeted. Main Outcomes and Measures: The primary focus of this analysis centered on both overall and age-standardized estimates, stroke incidence, prevalence, mortality, and DALYs per 100 000 individuals. Results: In 2019, the US recorded 7.09 million prevalent strokes (4.07 million women [57.4%]; 3.02 million men [42.6%]), with 5.87 million being ischemic strokes (82.7%). Prevalence also included 0.66 million ICHs and 0.85 million SAHs. Although the absolute numbers of stroke cases, mortality, and DALYs surged from 1990 to 2019, the age-standardized rates either declined or remained steady. Notably, hemorrhagic strokes manifested a substantial increase, especially in mortality, compared with ischemic strokes (incidence of ischemic stroke increased by 13% [95% uncertainty interval (UI), 14.2%-11.9%]; incidence of ICH increased by 39.8% [95% UI, 38.9%-39.7%]; incidence of SAH increased by 50.9% [95% UI, 49.2%-52.6%]). The downturn in stroke mortality plateaued in the recent decade. There was a discernible heterogeneity in stroke burden trends, with older adults (50-74 years) experiencing a decrease in incidence in coastal areas (decreases up to 3.9% in Vermont), in contrast to an uptick observed in younger demographics (15-49 years) in the South and Midwest US (with increases up to 8.4% in Minnesota). Conclusions and Relevance: In this cross-sectional study, the declining age-standardized stroke rates over the past 3 decades suggest progress in managing stroke-related outcomes. However, the increasing absolute burden of stroke, coupled with a notable rise in hemorrhagic stroke, suggests an evolving and substantial public health challenge in the US. Moreover, the significant disparities in stroke burden trends across different age groups and geographic locations underscore the necessity for region- and demography-specific interventions and policies to effectively mitigate the multifaceted and escalating burden of stroke in the country.

Cerebellar Microstructural Abnormalities in Obsessive-Compulsive Disorder (OCD): a Systematic Review of Diffusion Tensor Imaging Studies.

Previous neuroimaging studies have suggested that obsessive-compulsive disorder (OCD) is associated with altered resting-state functional connectivity of the cerebellum. In this study, we aimed to describe the most significant and reproducible microstructural abnormalities and cerebellar changes associated with obsessive-compulsive disorder (OCD) using diffusion tensor imaging (DTI) investigations. PubMed and EMBASE were searched for relevant studies using the PRISMA 2020 protocol. A total of 17 publications were chosen for data synthesis after screening titles and abstracts, full-text examination, and executing the inclusion criteria. The patterns of cerebellar white matter (WM) integrity loss, determined by fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) metrics, varied across studies and symptoms. Changes in fractional anisotropy (FA) values were described in six publications, which were decreased in four and increased in two studies. An increase in diffusivity parameters of the cerebellum (i.e., MD, RD, and AD) in OCD patients was reported in four studies. Alterations of the cerebellar connectivity with other brain areas were also detected in three studies. Heterogenous results were found in studies that investigated cerebellar microstructural abnormalities in correlation with symptom dimension or severity. OCD's complex phenomenology may be characterized by changes in cerebellar WM connectivity across wide networks, as shown by DTI studies on OCD patients in both children and adults. Classification features in machine learning and clinical tools for diagnosing OCD and determining the prognosis of the disorder might both benefit from using cerebellar DTI data.

Diagnostic performance of MRI radiomics for classification of Alzheimer's disease, mild cognitive impairment, and normal subjects: a systematic review and meta-analysis.

BACKGROUND: Alzheimer's disease (AD) is a debilitating neurodegenerative disease. Early diagnosis of AD and its precursor, mild cognitive impairment (MCI), is crucial for timely intervention and management. Radiomics involves extracting quantitative features from medical images and analyzing them using advanced computational algorithms. These characteristics have the potential to serve as biomarkers for disease classification, treatment response prediction, and patient stratification. Of note, Magnetic resonance imaging (MRI) radiomics showed a promising result for diagnosing and classifying AD, and MCI from normal subjects. Thus, we aimed to systematically evaluate the diagnostic performance of the MRI radiomics for this task. METHODS AND MATERIALS: A comprehensive search of the current literature was conducted using relevant keywords in PubMed/MEDLINE, Embase, Scopus, and Web of Science databases from inception to August 5, 2023. Original studies discussing the diagnostic performance of MRI radiomics for the classification of AD, MCI, and normal subjects were included. Method quality was evaluated with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and the Radiomics Quality Score (RQS) tools. RESULTS: We identified 13 studies that met the inclusion criteria, involving a total of 5448 participants. The overall quality of the included studies was moderate to high. The pooled sensitivity and specificity of MRI radiomics for differentiating AD from normal subjects were 0.92 (95% CI [0.85; 0.96]) and 0.91 (95% CI [0.85; 0.95]), respectively. The pooled sensitivity and specificity of MRI radiomics for differentiating MCI from normal subjects were 0.74 (95% CI [0.60; 0.85]) and 0.79 (95% CI [0.70; 0.86]), respectively. Also, the pooled sensitivity and specificity of MRI radiomics for differentiating AD from MCI were 0.73 (95% CI [0.64; 0.80]) and 0.79 (95% CI [0.64; 0.90]), respectively. CONCLUSION: MRI radiomics has promising diagnostic performance in differentiating AD, MCI, and normal subjects. It can potentially serve as a non-invasive and reliable tool for early diagnosis and classification of AD and MCI.

Radiomics: The New Promise for Differentiating Progression, Recurrence, Pseudoprogression, and Radionecrosis in Glioma and Glioblastoma Multiforme.

Glioma and glioblastoma multiform (GBM) remain among the most debilitating and life-threatening brain tumors. Despite advances in diagnosing approaches, patient follow-up after treatment (surgery and chemoradiation) is still challenging for differentiation between tumor progression/recurrence, pseudoprogression, and radionecrosis. Radiomics emerges as a promising tool in initial diagnosis, grading, and survival prediction in patients with glioma and can help differentiate these post-treatment scenarios. Preliminary published studies are promising about the role of radiomics in post-treatment glioma/GBM. However, this field faces significant challenges, including a lack of evidence-based solid data, scattering publication, heterogeneity of studies, and small sample sizes. The present review explores radiomics's capabilities in following patients with glioma/GBM status post-treatment and to differentiate tumor progression, recurrence, pseudoprogression, and radionecrosis.

Radiomics; A Potential Next "Omics" in Psychiatric Disorders; An Introduction.

Psychiatric disorders remain one of the most debilitating conditions; however, most patients are never diagnosed and do not seek treatment. Despite its massive burden on modern society and the health system, many hurdles prevent proper diagnosis and management of these disorders. The diagnosis is primarily based on clinical symptoms, and efforts to find appropriate biomarkers have not been practical. Through the past years, researchers have put a tremendous effort into finding biomarkers in "omics" fields: genomics, transcriptomics, proteomics, metabolomics, and epigenomics. This article reviews the evolving field of radiomics and its role in diagnosing psychiatric disorders as the sixth potential "omics." The first section of this paper elaborates on the definition of radiomics and its potential to provide a detailed structural study of the brain. Following that, we have provided the latest promising results of this novel approach in a broad range of psychiatric disorders. Radiomics fits well within the concept of psychoradiology. Besides volumetric analysis, radiomics takes advantage of many other features. This technique may open a new field in psychiatry for diagnosing and classifying psychiatric disorders and treatment response prediction in the era of precision and personalized medicine. The initial results are encouraging, but radiomics in psychiatry is still in its infancy. Despite the extensive burden of psychiatric disorders, there are very few published studies in this field, with small patient populations. The lack of prospective multi-centric studies and heterogeneity of studies in design are the significant barriers against the clinical adaptation of radiomics in psychoradiology.

Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas.

PURPOSE: The Response Assessment in Neuro-Oncology (RANO) criteria for lower-grade gliomas (LGGs) define tumor progression as ≥25% change in the T2/FLAIR signal area based on an operator's discretion of the perpendicular diameter of the largest tumor cross-section. Potential sources of error include acquisition inconsistency of 2D slices, operator selection variabilities in both representative tumor cross-section and measurement line locations, and the inability to quantify infiltrative tumor margins and satellite lesions. Our goal was to assess the accuracy and reproducibility of RANO in LG. MATERIALS AND METHODS: A total of 651 FLAIR MRIs from 63 participants with LGGs were retrospectively analyzed by three blinded attending physicians and three blinded resident trainees using RANO criteria, 2D visual assessment, and computer-assisted 3D volumetric assessment. RESULTS: RANO product measurements had poor-to-moderate inter-operator reproducibility (r2 = 0.28-0.82; coefficient of variance (CV) = 44-110%; mean percent difference (diff) = 0.4-46.8%) and moderate-to-excellent intra-operator reproducibility (r2 = 0.71-0.88; CV = 31-58%; diff = 0.3-23.9%). When compared to 2D visual ground truth, the accuracy of RANO compared to previous and baseline scans was 66.7% and 65.1%, with an area under the ROC curve (AUC) of 0.67 and 0.66, respectively. When comparing to volumetric ground truth, the accuracy of RANO compared to previous and baseline scans was 21.0% and 56.5%, with an AUC of 0.39 and 0.55, respectively. The median time delay at diagnosis was greater for false negative cases than for false positive cases for the RANO assessment compared to previous (2.05 > 0.50 years, p = 0.003) and baseline scans (1.08 > 0.50 years, p = 0.02). CONCLUSION: RANO-based assessment of LGGs has moderate reproducibility and poor accuracy when compared to either visual or volumetric ground truths.

Acute Necrotizing Encephalopathy in Adult Patients With COVID-19: A Systematic Review of Case Reports and Case Series.

BACKGROUND AND PURPOSE: Acute necrotizing encephalopathy (ANE) is a rare neurological disorder that is often associated with viral infections. Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a few COVID-19-associated ANE cases have been reported. Since very little is known about ANE, the present study aimed to determine the clinical, biochemical, and radiological characteristics of affected patients. METHODS: A search was conducted on PubMed, Scopus, Embase, and Web of Science databases for articles published up to August 30, 2022 using relevant keywords. Case reports and series in the English language that reported ANE in adult patients with COVID-19 confirmed by reverse transcription polymerase chain reaction were included in this study. Data on the demographic, clinical, laboratory, and radiological characteristics of patients were extracted and analyzed using the SPSS software (version 26). RESULTS: The study included 30 patients (18 males) with COVID-19 and ANE who were aged 49.87±18.68 years (mean±standard deviation). Fever was the most-prevalent symptom at presentation (66.7%). Elevated C-reactive protein was observed in the laboratory assessments of 13 patients. Computed tomography and magnetic resonance imaging were the most-common radiological modalities used for brain assessments. The most commonly prescribed medications were methylprednisolone (30%) and remdesivir (26.7%). Sixteen patients died prior to discharge. CONCLUSIONS: The diagnosis of COVID-19-associated ANE requires a thorough knowledge of the disease. Since the clinical presentations of ANE are neither sensitive nor specific, further laboratory and brain radiological evaluations will be needed to confirm the diagnosis. The suspicion of ANE should be raised among patients with COVID-19 who present with progressive neurological symptoms.

Radiomics Outperforms Clinical and Radiologic Signs in Predicting Spontaneous Basal Ganglia Hematoma Expansion: A Pilot Study.

Prediction of the hematoma expansion (HE) of spontaneous basal ganglia hematoma (SBH) from the first non-contrast CT can result in better management, which has the potential of improving outcomes. This study has been designed to compare the performance of "Radiomics analysis," "radiology signs," and "clinical-laboratory data" for this task. We retrospectively reviewed the electronic medical records for clinical, demographic, and laboratory data in patients with SBH. CT images were reviewed for the presence of radiologic signs, including black-hole, blend, swirl, satellite, and island signs. Radiomic features from the SBH on the first brain CT were extracted, and the most predictive features were selected. Different machine learning models were developed based on clinical, laboratory, and radiology signs and selected Radiomic features to predict hematoma expansion (HE). The dataset used for this analysis included 116 patients with SBH. Among different models and different thresholds to define hematoma expansion (10%, 20%, 25%, 33%, 40%, and 50% volume enlargement thresholds), the Random Forest based on 10 selected Radiomic features achieved the best performance (for 25% hematoma enlargement) with an area under the curve (AUC) of 0.9 on the training dataset and 0.89 on the test dataset. The models based on clinical-laboratory and radiology signs had low performance (AUCs about 0.5-0.6).

ALK-positive histiocytosis involving the cavernous sinus: A deceptive radiologic mimic of meningioma.

Anaplastic lymphoma kinase (ALK)-positive histiocytosis is an uncommon condition, recently considered a separate condition from other histiocytosis by WHO 5th edition. It can involve intracranial structures. This manuscript describes a case of ALK-positive histiocytosis of the cavernous sinus, focusing on the radiologic and pathologic presentation of the entity. Our case had MRI manifestations mimicking meningioma, metastasis, and Langerhans histiocytosis. On CT imaging, benign osseous remodeling of the cavernous sinus was detected, which can be helpful in differentiating it from more common meningioma.

Prediction of in-hospital adverse clinical outcomes in patients with pulmonary thromboembolism, machine learning based models.

Background: Pulmonary thromboembolism (PE) is the third leading cause of cardiovascular events. The conventional modeling methods and severity risk scores lack multiple laboratories, paraclinical and imaging data. Data science and machine learning (ML) based prediction models may help better predict outcomes. Materials and methods: In this retrospective registry-based design, all consecutive hospitalized patients diagnosed with pulmonary thromboembolism (based on pulmonary CT angiography) from 2011 to 2019 were recruited. ML based algorithms [Gradient Boosting (GB) and Deep Learning (DL)] were applied and compared with logistic regression (LR) to predict hemodynamic instability and/or all-cause mortality. Results: A total number of 1,017 patients were finally enrolled in the study, including 465 women and 552 men. Overall incidence of study main endpoint was 9.6%, (7.2% in men and 12.4% in women; p-value = 0.05). The overall performance of the GB model is better than the other two models (AUC: 0.94 for GB vs. 0.88 and 0.90 for DL and LR models respectively). Based on GB model, lower O2 saturation and right ventricle dilation and dysfunction were among the strongest adverse event predictors. Conclusion: ML-based models have notable prediction ability in PE patients. These algorithms may help physicians to detect high-risk patients earlier and take appropriate preventive measures.

Magnetic Resonance Imaging (MRI) Findings in COVID-19 Associated Encephalitis.

We conducted this study to investigate the scope of the MRI neuroimaging manifestations in COVID-19-associated encephalitis. From January 2020 to September 2021, patients with clinical diagnosis of COVID-19-associated encephalitis, as well as concomitant abnormal imaging findings on brain MRI, were included. Two board-certified neuro-radiologists reviewed these selected brain MR images, and further discerned the abnormal imaging findings. 39 patients with the clinical diagnosis of encephalitis as well as abnormal MRI findings were included. Most (87%) of these patients were managed in ICU, and 79% had to be intubated-ventilated. 15 (38%) patients died from the disease, while the rest were discharged from the hospital. On MRI, FLAIR hyperintensities in the insular cortex were the most common finding, seen in 38% of the patients. Micro-hemorrhages on the SWI images were equally common, also seen in 38% patients. FLAIR hyperintensities in the medial temporal lobes were seen in 30%, while FLAIR hyperintensities in the posterior fossa were evident in 20%. FLAIR hyperintensities in basal ganglia and thalami were seen in 15%. Confluent FLAIR hyperintensities in deep and periventricular white matter, not explained by microvascular angiopathy, were detected in 7% of cases. Cortical-based FLAIR hyperintensities in 7%, and FLAIR hyperintensity in the splenium of the corpus callosum in 7% of patients. Finally, isolated FLAIR hyperintensity around the third ventricle was noted in 2% of patients.

Subcortical signal alteration of corticospinal tracts. A radiologic manifestation of ARIA: A case report.

Patients with Alzheimer's disease who have been given monoclonal antibodies targeting amyloid-ß (Aß) (eg, gantenerumab, donanemab, lecanemab, and aducanumab) for scientific purposes may have a spectrum of imaging findings known as amyloid-related imaging abnormalities (ARIA), shown on brain magnetic resonance imaging (MRI) scans. These neuroimaging abnormalities are caused by antibody-mediated destruction of accumulated Aß aggregates in cerebral blood vessels and brain parenchyma. ARIA may demonstrate as brain edema or sulcal effusion (ARIA-E) or as hemosiderin deposits caused by brain parenchymal or pial hemorrhage (ARIA-H). The current study explores 2 cases with interval development of FLAIR hyper signal intensity along the bilateral corticospinal tracts in the motor cortex/precentral gyri after treatment by aducanumab. We believe this manifestation is a subtype of ARIA-A that has not been explored earlier. Our first case was a 72-year-old woman with a history of HTN and kidney transplant (polycystic kidney) who presented with mild cognitive impairment with clinical findings consistent with early Alzheimer's disease. After receiving 3 doses of aducunumab and experiencing cognition improvement, she underwent a brain MRI because of dizziness and vertigo. The brain MRI demonstrated new FLAIR hyper signal intensity in subcortical regions of precentral gyri (motor cortex) symmetrically as well as trace subarachnoid hemorrhage at the vertex compatible with ARIA-E and ARIA-H. Our second case was an 85-year-old woman with a history of small lymphocytic leukemia which was treated 20 years earlier. After orthopedic surgery 2 years ago, she developed dementia with anterograde amnesia. Since then, Aricept and Namenda have been started, but there have been no improvements in her subjective condition. The initial Amyloid PET/MR imaging showed diffuse cerebral Amyloid deposition. After tolerating 6 doses of aducanumab a safety MRI revealed new bilateral symmetric FLAIR hyper signal intensity in the subcortical motor cortex. Results of our study suggest that the subcortical corticospinal tract is another hotspot for ARIA findings. Hence, these regions might be an unknown site for both the action and adverse effects of aducanumab on amyloid plaques with secondary inflammation. In addition, radiologists must take this phenomenon into the account, and be cognizant that the FLAIR hyper signal intensities should not be misinterpreted as motor neuron disease (eg, amyotrophic lateral sclerosis).

Radiomics for differentiation of the posterior fossa pilocytic astrocytoma versus hemangioblastomas in adults. A pilot study.

PURPOSE: Both pilocytic astrocytoma (PA) and hemangioblastoma (HB) are common primary neoplasms of the posterior fossa with similar radiological manifestations. This study was conducted to evaluate the role of Radiomics in differentiating these two conditions in adults. MATERIALS AND METHODS: After a retrospective search of our institutional imaging archive, adult patients with a known diagnosis of PA or HB were included. We reviewed each patient's most recent preoperative brain magnetic resonance imaging (MRI). The solid enhancing nodule of each lesion on post-contrast T1 sequence was manually segmented. Multiple Radiomics features were then extracted from each nodule using the Pyradiomics library. Subsequently, the most predictive features were identified by feature selection models. Following this, different machine learning (ML) models were constructed based on these selected features to classify lesions as PA or HB. Finally, we evaluated the performance of each model by leave-one-out cross-validation. RESULTS: With inclusion and exclusion criteria, 34 enhancing PA nodules and 39 HB nodules were selected. A total of 115 features were extracted from each enhancing nodule. Twelve characteristics were detected as most predictive of histopathological diagnosis. Among various ML models, the neural network had the best performance in differentiating these two conditions with an AUC of 0.9 and an accuracy of 82%. CONCLUSIONS: In this retrospective study, Radiomics MRI techniques demonstrated high performance in distinguishing adult posterior fossa PA from HB. Future development of Radiomics models may advance presurgical diagnosis of these two conditions when added to routine clinical practice and thus improve patient management.

Imaging spectrum of amyloid-related imaging abnormalities associated with aducanumab immunotherapy.

Alzheimer's Disease (AD) is a leading cause of morbidity. Management of AD has traditionally been aimed at symptom relief rather than disease modification. Recently, AD research has begun to shift focus towards disease-modifying therapies that can alter the progression of AD. In this context, a class of immunotherapy agents known as monoclonal antibodies target diverse cerebral amyloid-beta (Aß) epitopes to inhibit disease progression. Aducanumab was authorized by the US Food and Drug Administration (FDA) to treat AD on June 7, 2021. Aducanumab has shown promising clinical and biomarker efficacy but is associated with amyloid-related imaging abnormalities (ARIA). Neuroradiologists play a critical role in diagnosing ARIA, necessitating familiarity with this condition. This pictorial review will appraise the radiologic presentation of ARIA in patients on aducanumab.

Radiological and Clinical Findings of Non-bifurcating Carotid Artery With Aberrant Course: A Case Report and Review of the Literature.

A non-bifurcating carotid artery is a rare variation in the carotid circulation. Here we present a rare case of a non-bifurcating carotid artery with an aberrant course of the internal carotid artery incidentally discovered in a patient who presented to the trauma center after a fall. To our knowledge, this is the first reported case of a non-bifurcating carotid artery with an aberrant course of the internal carotid artery. The embryonic mechanisms of this variation and the available literature regarding this condition are also reviewed. Knowing this variation is necessary before considering vascular intervention of the neck and ear surgery to avoid vascular injury and complications.

Cerebral Venous Sinus Thrombosis following Ventriculoperitoneal Shunting for Idiopathic Intracranial Hypertension.

A 30-year-old woman with idiopathic intracranial hypertension experienced worsening headaches and decreasing vision in her left eye. She underwent an uncomplicated ventriculoperitoneal shunt procedure but the following day was found to have cerebral venous sinus thrombosis. Treatment included venous sinus thrombectomy and anticoagulation. She had a favourable clinical outcome. Extensive evaluation including testing for thrombophilia was unremarkable. Potential causes for this rare association are discussed.

Cerebellar Microstructural Abnormalities in Parkinson's Disease: a Systematic Review of Diffusion Tensor Imaging Studies.

Diffusion tensor imaging (DTI) is now having a strong momentum in research to evaluate the neural fibers of the CNS. This technique can study white matter (WM) microstructure in neurodegenerative disorders, including Parkinson's disease (PD). Previous neuroimaging studies have suggested cerebellar involvement in the pathogenesis of PD, and these cerebellum alterations can correlate with PD symptoms and stages. Using the PRISMA 2020 framework, PubMed and EMBASE were searched to retrieve relevant articles. Our search revealed 472 articles. After screening titles and abstracts, and full-text review, and implementing the inclusion criteria, 68 papers were selected for synthesis. Reviewing the selected studies revealed that the patterns of reduction in cerebellum WM integrity, assessed by fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity measures can differ symptoms and stages of PD. Cerebellar diffusion tensor imaging (DTI) changes in PD patients with "postural instability and gait difficulty" are significantly different from "tremor dominant" PD patients. Freezing of the gate is strongly related to cerebellar involvement depicted by DTI. The "reduced cognition," "visual disturbances," "sleep disorders," "depression," and "olfactory dysfunction" are not related to cerebellum microstructural changes on DTI, while "impulsive-compulsive behavior" can be linked to cerebellar WM alteration. Finally, higher PD stages and longer disease duration are associated with cerebellum white matter alteration depicted by DTI. Depiction of cerebellar white matter involvement in PD is feasible by DTI. There is an association with disease duration and severity and several clinical presentations with DTI findings. This clinical-imaging association may eventually improve disease management.