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Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a microaveraged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the microaveraged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in clinical settings and drug trials. Further prospective studies are needed to confirm its ability to improve patient care.
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BACKGROUND AND PURPOSE: Contrast staining is a common finding after endovascular treatment of acute ischemic stroke. It typically occurs in infarcted tissue and is considered an indicator of irreversible brain damage. Contrast staining in noninfarcted tissue has not been systematically investigated. We sought to assess the incidence, risk factors, and clinical significance of contrast staining in noninfarcted tissue after endovascular treatment. MATERIALS AND METHODS: We conducted a retrospective review of consecutive patients who underwent endovascular treatment for anterior circulation large-vessel occlusion acute ischemic stroke. Contrast staining, defined as new hyperdensity on CT after endovascular treatment, was categorized as either contrast staining in infarcted tissue if the stained region demonstrated restricted diffusion on follow-up MR imaging or contrast staining in noninfarcted tissue if the stained region demonstrated no restricted diffusion. Baseline differences between patients with and without contrast staining in noninfarcted tissue were compared. Logistic regression was used to identify independent associations for contrast staining in noninfarcted tissue after endovascular treatment. RESULTS: Among 194 patients who underwent endovascular treatment for large-vessel occlusion acute ischemic stroke and met the inclusion criteria, contrast staining in infarcted tissue was noted in 52/194 (26.8%) patients; contrast staining in noninfarcted tissue, in 26 (13.4%) patients. Both contrast staining in infarcted tissue and contrast staining in noninfarcted tissue were noted in 5.6% (11/194). Patients with contrast staining in noninfarcted tissue were found to have a higher likelihood of having an ASPECTS of 8-10, to be associated with contrast staining in infarcted tissue, and to achieve successful reperfusion compared with those without contrast staining in noninfarcted tissue. In contrast staining in noninfarcted tissue regions, the average attenuation was 40 HU, significantly lower than the contrast staining in infarcted tissue regions (53 HU). None of the patients with contrast staining in noninfarcted tissue had clinical worsening during their hospital stay. The median discharge mRS was significantly lower in patients with contrast staining in noninfarcted tissue than in those without (3 versus 4; P = .018). No independent predictors of contrast staining in noninfarcted tissue were found. CONCLUSIONS: Contrast staining can be seen outside the infarcted tissue after endovascular treatment of acute ischemic stroke, likely attributable to the reversible disruption of the BBB in ischemic but not infarcted tissue. While generally benign, understanding its characteristics is important because it may mimic pathologic conditions such as infarcted tissue and cerebral edema.
Subject(s)
Contrast Media , Endovascular Procedures , Ischemic Stroke , Humans , Male , Female , Aged , Ischemic Stroke/diagnostic imaging , Ischemic Stroke/surgery , Ischemic Stroke/therapy , Retrospective Studies , Middle Aged , Aged, 80 and over , Tomography, X-Ray Computed , Treatment Outcome , Risk Factors , Magnetic Resonance Imaging/methodsABSTRACT
Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an AI model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations, and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a micro-averaged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the micro-averaged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in various clinical settings and drug trials, with promising implications for person-level management.
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OBJECTIVE: Internal Jugular Vein Stenosis (IJVS) is hypothesized to play a role in the pathogenesis of diverse neurological diseases. We sought to evaluate differences in IJVS assessment between CT and MRI in a retrospective patient cohort. METHODS: We included consecutive patients who had both MRI of the brain and CT of the head and neck with contrast from 1 June 2021 to 30 June 2022 within the same admission. The degree of IJVS was categorized into five grades (0-IV). RESULTS: A total of 35 patients with a total of 70 internal jugular (IJ) veins were included in our analysis. There was fair intermodality agreement in stenosis grades (κ = 0.220, 95% C.I. = [0.029, 0.410]), though categorical stenosis grades were significantly discordant between imaging modalities, with higher grades more frequent in MRI (χ2 = 27.378, p = 0.002). On CT-based imaging, Grade III or IV stenoses were noted in 17/70 (24.2%) IJs, whereas on MRI-based imaging, Grade III or IV stenoses were found in 40/70 (57.1%) IJs. Among veins with Grade I-IV IJVS, MRI stenosis estimates were significantly higher than CT stenosis estimates (77.0%, 95% C.I. [35.9-55.2%] vs. 45.6%, 95% C.I. [35.9-55.2%], p < 0.001). CONCLUSION: MRI with contrast overestimates the degree of IJVS compared to CT with contrast. Consideration of this discrepancy should be considered in diagnosis and treatment planning in patients with potential IJVS-related symptoms.
Subject(s)
Jugular Veins , Vascular Diseases , Humans , Constriction, Pathologic/diagnostic imaging , Constriction, Pathologic/pathology , Jugular Veins/diagnostic imaging , Jugular Veins/pathology , Retrospective Studies , Magnetic Resonance Imaging , Vascular Diseases/pathology , Tomography, X-Ray ComputedABSTRACT
Quantifying the risk of progression to Alzheimer's disease (AD) could help identify persons who could benefit from early interventions. We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 544, discovery cohort) and the National Alzheimer's Coordinating Center (NACC, n = 508, validation cohort), subdividing individuals with mild cognitive impairment (MCI) into risk groups based on cerebrospinal fluid amyloid-ß levels and identifying differential gray matter patterns. We then created models that fused neural networks with survival analysis, trained using non-parcellated T1-weighted brain MRIs from ADNI data, to predict the trajectories of MCI to AD conversion within the NACC cohort (integrated Brier score: 0.192 [discovery], and 0.108 [validation]). Using modern interpretability techniques, we verified that regions important for model prediction are classically associated with AD. We confirmed AD diagnosis labels using postmortem data. We conclude that our framework provides a strategy for risk-based stratification of individuals with MCI and for identifying regions key for disease prognosis.
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BACKGROUND: Challenging arterial anatomy may prevent timely endovascular treatment (EVT) of acute ischemic stroke (AIS) through a transfemoral approach prompting the use of alternative access routes. We determined the crossover rate from femoral to radial access during EVT of AIS due to large vessel occlusion and identified its radiological predictors and clinical outcomes. MATERIALS AND METHODS: Retrospective review of all AIS patients who underwent EVT at a single institution from January 2016 to March 2021 was performed. A primary and a secondary radial group depending on whether the radial approach was used primarily or secondary to failure of transfemoral approach were compared. RESULTS: A total of 358 consecutive AIS patients with large vessel occlusion underwent EVT. Radial approach was used primarily in 6 patients (primary radial [PR]) and secondarily in 16 patients (secondary radial [SR]). The rate of femoral to radial crossover was 4.7%. Type III arch and bovine arch configurations were the most common characteristic in the crossover group. Radial access was successful to secure intracranial access in all cases of PR and in 87% of crossover cases. There was no significant difference between the rates of successful reperfusion (53.3% SR, 83% PR, P = 0.20), National Institutes of Health Stroke Scale score on discharge (19 SR, 18 PR group, P = 0.90), or good outcome defined as modified Rankin Scale score 0-2 (13.3% SR, 33.3% PR, P = 0.29). CONCLUSIONS: A radial approach can be considered during EVT of AIS due to large vessel occlusion either primarily or secondarily with a lower threshold to switch from the femoral approach in cases of challenging anatomy.
Subject(s)
Brain Ischemia , Endovascular Procedures , Ischemic Stroke , Stroke , Humans , Stroke/diagnostic imaging , Stroke/surgery , Stroke/complications , Brain Ischemia/diagnostic imaging , Brain Ischemia/surgery , Brain Ischemia/complications , Ischemic Stroke/complications , Treatment Outcome , Thrombectomy , Retrospective StudiesABSTRACT
Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer's disease (AD) is the most common. New measures are needed to improve the diagnosis of individuals with cognitive impairment due to various etiologies. Here, we report a deep learning framework that accomplishes multiple diagnostic steps in successive fashion to identify persons with normal cognition (NC), mild cognitive impairment (MCI), AD, and non-AD dementias (nADD). We demonstrate a range of models capable of accepting flexible combinations of routinely collected clinical information, including demographics, medical history, neuropsychological testing, neuroimaging, and functional assessments. We then show that these frameworks compare favorably with the diagnostic accuracy of practicing neurologists and neuroradiologists. Lastly, we apply interpretability methods in computer vision to show that disease-specific patterns detected by our models track distinct patterns of degenerative changes throughout the brain and correspond closely with the presence of neuropathological lesions on autopsy. Our work demonstrates methodologies for validating computational predictions with established standards of medical diagnosis.
Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Deep Learning , Alzheimer Disease/diagnostic imaging , Alzheimer Disease/psychology , Cognitive Dysfunction/diagnosis , Cognitive Dysfunction/pathology , Disease Progression , Humans , Neuroimaging/methodsABSTRACT
BACKGROUND AND OBJECTIVES: Late neuropathologies of repetitive head impacts from contact sports can include chronic traumatic encephalopathy (CTE) and white matter degeneration. White matter hyperintensities (WMH) on fluid-attenuated inversion recovery (FLAIR) MRI scans are often viewed as microvascular disease from vascular risk, but might have unique underlying pathologies and risk factors in the setting of repetitive head impacts. We investigated the neuropathologic correlates of antemortem WMH in brain donors exposed to repetitive head impacts. The association between WMH and repetitive head impact exposure and informant-reported cognitive and daily function were tested. METHODS: This imaging-pathologic correlation study included symptomatic male decedents exposed to repetitive head impacts. Donors had antemortem FLAIR scans from medical records and were without evidence of CNS neoplasm, large vessel infarcts, hemorrhage, or encephalomalacia. WMH were quantified using log-transformed values for total lesion volume (TLV), calculated using the lesion prediction algorithm from the Lesion Segmentation Toolbox. Neuropathologic assessments included semiquantitative ratings of white matter rarefaction, cerebrovascular disease, hyperphosphorylated tau (p-tau) severity (CTE stage, dorsolateral frontal cortex), and ß-amyloid (Aß). Among football players, years of play was a proxy for repetitive head impact exposure. Retrospective informant-reported cognitive and daily function were assessed using the Cognitive Difficulties Scale (CDS) and Functional Activities Questionnaire (FAQ). Regression models controlled for demographics, diabetes, hypertension, and MRI resolution. Statistical significance was defined as p ≤ 0.05. RESULTS: The sample included 75 donors: 67 football players and 8 nonfootball contact sport athletes or military veterans. Dementia was the most common MRI indication (64%). Fifty-three (70.7%) had CTE at autopsy. Log TLV was associated with white matter rarefaction (odds ratio [OR] 2.32, 95% confidence interval [CI] 1.03, 5.24; p = 0.04), arteriolosclerosis (OR 2.38, 95% CI 1.02, 5.52; p = 0.04), CTE stage (OR 2.58, 95% CI 1.17, 5.71; p = 0.02), and dorsolateral frontal p-tau severity (OR 3.03, 95% CI 1.32, 6.97; p = 0.01). There was no association with Aß. More years of football play was associated with log TLV (unstandardized ß 0.04, 95% CI 0.01, 0.06; p = 0.01). Greater log TLV correlated with higher FAQ (unstandardized ß 4.94, 95% CI 0.42, 8.57; p = 0.03) and CDS scores (unstandardized ß 15.35, 95% CI -0.27, 30.97; p = 0.05). DISCUSSION: WMH might capture long-term white matter pathologies from repetitive head impacts, including those from white matter rarefaction and p-tau, in addition to microvascular disease. Prospective imaging-pathologic correlation studies are needed. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence of associations between FLAIR white matter hyperintensities and neuropathologic changes (white matter rarefaction, arteriolosclerosis, p-tau accumulation), years of American football play, and reported cognitive symptoms in symptomatic brain donors exposed to repetitive head impacts.
Subject(s)
White Matter , Brain/diagnostic imaging , Brain/pathology , Humans , Magnetic Resonance Imaging , Male , Prospective Studies , Retrospective Studies , White Matter/diagnostic imaging , White Matter/pathologyABSTRACT
BACKGROUND: Chronic traumatic encephalopathy (CTE), a neurodegenerative tauopathy, cannot currently be diagnosed during life. Atrophy patterns on magnetic resonance imaging could be an effective in vivo biomarker of CTE, but have not been characterized. Mechanisms of neurodegeneration in CTE are unknown. Here, we characterized macrostructural magnetic resonance imaging features of brain donors with autopsy-confirmed CTE. The association between hyperphosphorylated tau (p-tau) and atrophy on magnetic resonance imaging was examined. METHODS: Magnetic resonance imaging scans were obtained by medical record requests for 55 deceased symptomatic men with autopsy-confirmed CTE and 31 men (n = 11 deceased) with normal cognition at the time of the scan, all >60 years Three neuroradiologists visually rated regional atrophy and microvascular disease (0 [none]-4 [severe]), microbleeds, and cavum septum pellucidum presence. Neuropathologists rated tau severity and atrophy at autopsy using semi-quantitative scales. RESULTS: Compared to unimpaired males, donors with CTE (45/55=stage III/IV) had greater atrophy of the orbital-frontal (mean diff.=1.29), dorsolateral frontal (mean diff.=1.31), superior frontal (mean diff.=1.05), anterior temporal (mean diff.=1.57), and medial temporal lobes (mean diff.=1.60), and larger lateral (mean diff.=1.72) and third (mean diff.=0.80) ventricles, controlling for age at scan (ps<0.05). There were no effects for posterior atrophy or microvascular disease. Donors with CTE had increased odds of a cavum septum pellucidum (OR = 6.7, p < 0.05). Among donors with CTE, greater tau severity across 14 regions corresponded to greater atrophy on magnetic resonance imaging (beta = 0.68, p < 0.01). CONCLUSIONS: These findings support frontal-temporal atrophy as a magnetic resonance imaging finding of CTE and show p-tau accumulation is associated with atrophy in CTE.
Subject(s)
Chronic Traumatic Encephalopathy , Atrophy/pathology , Autopsy , Brain/metabolism , Chronic Traumatic Encephalopathy/pathology , Humans , Magnetic Resonance Imaging/methods , Male , tau Proteins/metabolismABSTRACT
BACKGROUND: Generative adversarial networks (GAN) can produce images of improved quality but their ability to augment image-based classification is not fully explored. We evaluated if a modified GAN can learn from magnetic resonance imaging (MRI) scans of multiple magnetic field strengths to enhance Alzheimer's disease (AD) classification performance. METHODS: T1-weighted brain MRI scans from 151 participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI), who underwent both 1.5-Tesla (1.5-T) and 3-Tesla imaging at the same time were selected to construct a GAN model. This model was trained along with a three-dimensional fully convolutional network (FCN) using the generated images (3T*) as inputs to predict AD status. Quality of the generated images was evaluated using signal to noise ratio (SNR), Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) and Natural Image Quality Evaluator (NIQE). Cases from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL, n = 107) and the National Alzheimer's Coordinating Center (NACC, n = 565) were used for model validation. RESULTS: The 3T*-based FCN classifier performed better than the FCN model trained using the 1.5-T scans. Specifically, the mean area under curve increased from 0.907 to 0.932, from 0.934 to 0.940, and from 0.870 to 0.907 on the ADNI test, AIBL, and NACC datasets, respectively. Additionally, we found that the mean quality of the generated (3T*) images was consistently higher than the 1.5-T images, as measured using SNR, BRISQUE, and NIQE on the validation datasets. CONCLUSION: This study demonstrates a proof of principle that GAN frameworks can be constructed to augment AD classification performance and improve image quality.
Subject(s)
Alzheimer Disease , Alzheimer Disease/diagnostic imaging , Australia , Brain/diagnostic imaging , Humans , Magnetic Resonance Imaging , NeuroimagingABSTRACT
Background Multidetector CT (MDCT) enables rapid and accurate diagnosis of head and neck (HN) injuries in patients with blunt trauma (BT). However, MDCT is overused, and appropriate selection of patients for imaging could improve workflow. Purpose To investigate the effect of implementing clinical triaging algorithms on use of MDCT in the HN in patients who have sustained BT. Materials and Methods In this retrospective study, patients aged 15 years or older with BT admitted between October 28, 2007, and December 31, 2013, were included. Patients were divided into pre- and postalgorithm groups. The institutional trauma registry and picture archiving and communication system reports were reviewed to determine which patients underwent MDCT of the head, MDCT of the cervical spine (CS), and MDCT angiography of the HN at admission and whether these examinations yielded positive results. Injury Severity Score, Acute Physiology and Chronic Health Evaluation II score (only those patients in the intensive care unit), length of hospital stay (LOS), length of intensive care unit stay (ICULOS), and mortality were obtained from the trauma registry. Results A total of 8999 patients (mean age, 45 years ± 20 [standard deviation]; age range, 15-101 years; 6027 male) were included in this study. A lower percentage of the postalgorithm group versus the prealgorithm group underwent MDCT of the head (55.8% [2774 of 4969 patients]; 95% CI: 54.4, 57.2 vs 64.2% [2589 of 4030 patients]; 95% CI: 62.8, 65.7; P < .001) and CS (49.4% [2452 of 4969 patients]; 95% CI: 48.0, 50.7 vs 60.5% [2438 of 4030 patients]; 95% CI: 59.0, 62.0; P < .001) but not MDCT angiography of the HN (9.7% [480 of 4969 patients]; 95% CI: 8.9, 10.5 vs 9.8% [393 of 4030 patients]; 95% CI: 8.9, 10.7; P > .99). Pre- versus postalgorithm groups did not differ in LOS (mean, 4.8 days ± 7.1 vs 4.5 days ± 7.1, respectively; P = .42), ICULOS (mean, 4.6 days ± 6.6 vs 4.8 days ± 6.7, respectively; P > .99), or mortality (2.9% [118 of 4030 patients]; 95% CI: 2.5, 3.5; vs 2.8% [141 of 4969 patients]; 95% CI: 2.4, 3.3; respectively; P > .99). Conclusion Implementation of a clinical triaging algorithm resulted in decreased use of multidetector CT of the head and cervical spine in patients who experienced blunt trauma, without increased adverse outcomes. © RSNA, 2021 See also the editorial by Munera and Martin in this issue.
Subject(s)
Craniocerebral Trauma/diagnostic imaging , Multidetector Computed Tomography/statistics & numerical data , Neck Injuries/diagnostic imaging , Triage/methods , Wounds, Nonpenetrating/diagnostic imaging , APACHE , Adolescent , Adult , Aged , Aged, 80 and over , Algorithms , Craniocerebral Trauma/mortality , Female , Humans , Injury Severity Score , Length of Stay/statistics & numerical data , Male , Middle Aged , Neck Injuries/mortality , Patient Selection , Retrospective Studies , Wounds, Nonpenetrating/mortalityABSTRACT
BACKGROUND: Spinal aneurysms (SA) are rare neurovascular pathologies with an unclear natural history and management strategy. We review the clinical and radiologic manifestations, management, and outcome of patients who presented with spinal subarachnoid hemorrhage (SAH) secondary to ruptured spinal aneurysms over a 10-year period. We provide a literature review about this condition and its management. METHODS: All patients diagnosed with nontraumatic spinal SAH were collected from a single-center prospectively maintained database of patients with SAH between January 2010 and January 2020. Patients diagnosed with spinal aneurysms were reviewed. For each patient, demographic data, clinical presentation, imaging findings, management strategies, and outcomes are reviewed and discussed. RESULTS: Between January 2010 and January 2020, ten patients were diagnosed with nontraumatic spinal SAH (3 patients presented with isolated spinal SAH and 7 patients with concomitant spinal and posterior fossa SAH). Among those, 4 patients were found to have a spinal aneurysm as the cause of SAH. The aneurysms were located in the cervical regions in 3 patients (75%) and at the thoracic level in 1 patient. Two aneurysms (50%) involved the anterior spinal artery, and 2 aneurysms (50%) involved a radiculomedullary artery. One aneurysm was a flow-related aneurysm of the anterior spinal artery in the setting of bilateral vertebral artery occlusion and was treated by surgical clipping with good outcome. Three aneurysms were idiopathic pseudoaneurysms with a negative diagnostic evaluation for secondary causes. These pseudoaneurysms were treated conservatively; 2 patients did well and 1 patient passed away from severe intracranial vasospasm. Two aneurysms resolved on diagnostic angiogram, and 1 aneurysm was absent on initial angiogram and appeared on follow-up diagnostic imaging 3 months later. CONCLUSIONS: Spinal aneurysms are rare neurovascular pathologies that should be considered in the setting of spinal and/or posterior fossa subarachnoid hemorrhage. Conservative treatment may be a potential safe alternative to interventional treatment. Before the initiation of surgical or endovascular treatment, spinal angiography should be repeated because of the potential for spontaneous resolution.
Subject(s)
Aneurysm, Ruptured/therapy , Conservative Treatment/methods , Disease Management , Neurosurgical Procedures/methods , Spinal Cord/blood supply , Subarachnoid Hemorrhage/therapy , Adult , Aged , Aneurysm, Ruptured/diagnostic imaging , Female , Humans , Male , Middle Aged , Spinal Cord/diagnostic imaging , Subarachnoid Hemorrhage/diagnostic imaging , Vertebral Artery/diagnostic imaging , Vertebral Artery/surgeryABSTRACT
INTRODUCTION: Encephalopathy is a common complication of coronavirus disease 2019. Although the encephalopathy is idiopathic in many cases, there are several published reports of patients with posterior reversible encephalopathy syndrome in the setting of coronavirus disease 2019. OBJECTIVE: To describe the diverse presentations, risk factors, and outcomes of posterior reversible encephalopathy syndrome in patients with coronavirus disease 2019. METHODS: We assessed patients with coronavirus disease 2019 and a diagnosis of posterior reversible encephalopathy syndrome at our institution from April 1 to June 24, 2020. We performed a literature search to capture all known published cases of posterior reversible encephalopathy syndrome in patients with coronavirus disease 2019. RESULTS: There were 2 cases of posterior reversible encephalopathy syndrome in the setting of coronavirus 2019 at our institution during a 3-month period. One patient was treated with anakinra, an interleukin-1 inhibitor that may disrupt endothelial function. The second patient had an underlying human immunodeficiency virus infection. We found 13 total cases in our literature search, which reported modest blood pressure fluctuations and a range of risk factors for posterior reversible encephalopathy syndrome. One patient was treated with tocilizumab, an interleukin-6 inhibitor that may have effects on endothelial function. All patients had an improvement in their neurological symptoms. Interval imaging, when available, showed radiographic improvement of brain lesions. CONCLUSIONS: Risk factors for posterior reversible encephalopathy syndrome in patients with coronavirus disease 2019 may include underlying infection or immunomodulatory agents with endothelial effects in conjunction with modest blood pressure fluctuations. We found that the neurological prognosis for posterior reversible encephalopathy syndrome in the setting of coronavirus disease 2019 infection is favorable. Recognition of posterior reversible encephalopathy syndrome in this patient population is critical for prognostication and initiation of treatment, which may include cessation of potential offending agents and tight blood pressure control.
Subject(s)
Betacoronavirus/pathogenicity , Coronavirus Infections/virology , Endothelium, Vascular/virology , Pneumonia, Viral/virology , Posterior Leukoencephalopathy Syndrome/virology , Blood Pressure , COVID-19 , Coinfection , Coronavirus Infections/diagnosis , Coronavirus Infections/immunology , Coronavirus Infections/physiopathology , Endothelium, Vascular/physiopathology , Female , HIV Infections/immunology , HIV Infections/physiopathology , HIV Infections/virology , Host-Pathogen Interactions , Humans , Immunosuppressive Agents/adverse effects , Middle Aged , Pandemics , Pneumonia, Viral/diagnosis , Pneumonia, Viral/immunology , Pneumonia, Viral/physiopathology , Posterior Leukoencephalopathy Syndrome/diagnosis , Posterior Leukoencephalopathy Syndrome/immunology , Posterior Leukoencephalopathy Syndrome/physiopathology , Prognosis , Risk Factors , SARS-CoV-2ABSTRACT
Perihematomal edema (PHE) surrounding intracerebral hemorrhage (ICH) may contribute to disease-associated morbidity. Before quantifying PHE's effects on morbidity, a fast, accurate, and reproducible method for measuring PHE volume is needed. The aim of this study is to demonstrate the use of a semiautomated dual clustering segmentation algorithm to generate PHE volumetrics on noncontrast computed tomography (CT) of the head and compare this technique to physicians' manual calculations.This is a single-center, retrospective imaging study that included head CTs performed from January 2008 to December 2014 on 154 patients with ICH. Subjectsâ≥â18 years old who were admitted to the hospital with spontaneous ICH were included. Included subjects had head CTs performed upon admission and within 6 to 24âhours. Two neurologists, 2 neuroradiologists, and a computer program all calculated hemorrhage and PHE volumes. Inter-rater correlation was evaluated using 2 statistical methods: intraclass correlations (ICCs) and limits of agreement (LOA). Additionally, correlation between volumes was separately evaluated using Pearson correlation coefficient.There was an excellent correlation between measurements performed by neurologists and neuroradiologists using ABC/2 for ICH (0.93) and PHE (0.78). There was a good correlation between measurements performed by neurologists using ABC/2 and the volume measurements generated by the algorithm for ICH (0.69) and PHE (0.70). There was a fair correlation between measurements performed by neuroradiologists using ABC/2 and volume measurements generated by the algorithm for ICH (0.47) and good correlation for PHE (0.73).Although the ABC/2 method for measuring PHE is quick and practical, algorithms that do not assume ellipsoidal shape may be more accurate.
Subject(s)
Algorithms , Brain Edema/complications , Brain Edema/diagnostic imaging , Cerebral Hemorrhage/complications , Cerebral Hemorrhage/diagnostic imaging , Hematoma/complications , Hematoma/diagnostic imaging , Tomography, X-Ray Computed , Adult , Humans , Retrospective StudiesABSTRACT
OBJECTIVE: To describe the frequency and the distribution of degenerative disc disease (DDD) detected in athletes who underwent spine MRI in the 2016 Summer Olympic Games in Rio de Janeiro. METHODS: Data on spine MRI examinations from the 2016 Summer Olympics were retrospectively analyzed. We assessed the frequency of DDD of the cervical (Cs), thoracic (Ts), and lumbar (Ls) spine using Pfirrmann's classification. Grade II and III were considered as mild, grade IV as moderate, and grade V as severe disc degeneration. Data were analyzed according to the location of the degenerative disc, type of sport, age-groups, and gender of the athletes. RESULTS: One hundred out of 11,274 athletes underwent 108 spine MRI's (21 C, 6 T, and 81 L) (53% Females (F), 47% Males (M)). The frequency of DDD was 40% (42% F, 58% M) over the entire spine (28% mild, 9% moderate and 3% severe). There were 58% (12%F, 88%M) of the cervical spine discs that showed some degree of degeneration (44% mild, 13.5% moderate and 1% severe). Athletics, Boxing, and Swimming were the sports most affected by DDD in the Cs. There were 12.5% of the thoracic discs that showed some degree of degeneration, all were mild DDD and were exclusively seen in female athletes. There were 39% (53% F, 47% M) of the lumbar discs with DDD (26% mild, 9% moderate, and 4% severe). CONCLUSION: Athletes who underwent spine MRI during the 2016 Summer Olympic Games show a high frequency of DDD of cervical and lumbar spines. Recognition of these conditions is important to develop training techniques that may minimize the development of degenerative pathology of the spine.
Subject(s)
Athletic Injuries/diagnostic imaging , Athletic Injuries/epidemiology , Intervertebral Disc Degeneration/diagnostic imaging , Intervertebral Disc Degeneration/epidemiology , Magnetic Resonance Imaging/methods , Sports , Adult , Athletes , Brazil/epidemiology , Cervical Vertebrae/diagnostic imaging , Female , Humans , Lumbar Vertebrae/diagnostic imaging , Male , Retrospective Studies , Thoracic Vertebrae/diagnostic imaging , Young AdultABSTRACT
Background Gadolinium retention after repeated gadolinium-based contrast agent (GBCA) exposure has been reported in subcortical gray matter. However, gadolinium retention in the cerebral cortex has not been systematically investigated. Purpose To determine whether and where gadolinium is retained in rat and human cerebral cortex. Materials and Methods The cerebral cortex in Sprague-Dawley rats treated with gadopentetate dimeglumine (three doses over 4 weeks; cumulative gadolinium dose, 7.2 mmol per kilogram of body weight; n = 6) or saline (n = 6) was examined with antemortem MRI. Two human donors with repeated GBCA exposure (three and 15 doses; 1 and 5 months after exposure), including gadopentetate dimeglumine, and two GBCA-naive donors were also evaluated. Elemental brain maps (gadolinium, phosphorus, zinc, copper, iron) for rat and human brains were constructed by using laser ablation inductively coupled plasma mass spectrometry. Results Gadopentetate dimeglumine-treated rats showed region-, subregion-, and layer-specific gadolinium retention in the neocortex (anterior cingulate cortex: mean gadolinium concentration, 0.28 µg â g-1 ± 0.04 [standard error of the mean]) that was comparable (P > .05) to retention in the allocortex (mean gadolinium concentration, 0.33 µg â g-1 ± 0.04 in piriform cortex, 0.24 µg â g-1 ± 0.04 in dentate gyrus, 0.17 µg â g-1 ± 0.04 in hippocampus) and subcortical structures (0.47 µg â g-1 ± 0.10 in facial nucleus, 0.39 µg â g-1 ± 0.10 in choroid plexus, 0.29 µg â g-1 ± 0.05 in caudate-putamen, 0.26 µg â g-1 ± 0.05 in reticular nucleus of the thalamus, 0.24 µg â g-1 ± 0.04 in vestibular nucleus) and significantly greater than that in the cerebellum (0.17 µg â g-1 ± 0.03, P = .01) and white matter tracts (anterior commissure: 0.05 µg â g-1 ± 0.01, P = .002; corpus callosum: 0.05 µg â g-1 ± 0.02, P = .001; cranial nerve: 0.02 µg â g-1 ± 0.01, P = .004). Retained gadolinium colocalized with parenchymal iron. T1-weighted MRI signal intensification was not observed. Gadolinium retention was detected in the cerebral cortex, pia mater, and pia-ensheathed leptomeningeal vessels in two GBCA-exposed human brains but not in two GBCA-naive human brains. Conclusion Repeated gadopentetate dimeglumine exposure is associated with gadolinium retention in specific regions, subregions, and layers of cerebral cortex that are critical for higher cognition, affect, and behavior regulation, sensorimotor coordination, and executive function. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Kanal in this issue.
Subject(s)
Cerebral Cortex/metabolism , Contrast Media/pharmacokinetics , Gadolinium DTPA/pharmacokinetics , Administration, Intravenous , Adult , Animals , Contrast Media/administration & dosage , Female , Gadolinium DTPA/administration & dosage , Humans , Male , Mass Spectrometry/methods , Middle Aged , Models, Animal , Rats , Rats, Sprague-DawleyABSTRACT
Central nervous system (CNS) infections are a major source of morbidity and mortality despite the remarkable progress in prevention and treatment of infectious disease. Because of the difficulty of direct tissue sampling, imaging plays a crucial role in detecting, diagnosing, and monitoring the therapeutic response of CNS infections. An accurate diagnosis in CNS infections is especially rewarding, given the availability of potential effective antimicrobials.Bacterial, viral, fungal, and parasitic infections may affect the brain and/or its meningeal coverings, and can be characterized by a variety of radiological patterns that help narrow the differential diagnoses and eventually tailor the optimal management.This review addresses the typical imaging findings of intracranial infectious diseases in both immunocompetent and immunocompromised patients.