Natural Language Processing of Radiology Reports to Detect Complications of Ischemic Stroke.

BACKGROUND: Abstraction of critical data from unstructured radiologic reports using natural language processing (NLP) is a powerful tool to automate the detection of important clinical features and enhance research efforts. We present a set of NLP approaches to identify critical findings in patients with acute ischemic stroke from radiology reports of computed tomography (CT) and magnetic resonance imaging (MRI). METHODS: We trained machine learning classifiers to identify categorical outcomes of edema, midline shift (MLS), hemorrhagic transformation, and parenchymal hematoma, as well as rule-based systems (RBS) to identify intraventricular hemorrhage (IVH) and continuous MLS measurements within CT/MRI reports. Using a derivation cohort of 2289 reports from 550 individuals with acute middle cerebral artery territory ischemic strokes, we externally validated our models on reports from a separate institution as well as from patients with ischemic strokes in any vascular territory. RESULTS: In all data sets, a deep neural network with pretrained biomedical word embeddings (BioClinicalBERT) achieved the highest discrimination performance for binary prediction of edema (area under precision recall curve [AUPRC] > 0.94), MLS (AUPRC > 0.98), hemorrhagic conversion (AUPRC > 0.89), and parenchymal hematoma (AUPRC > 0.76). BioClinicalBERT outperformed lasso regression (p < 0.001) for all outcomes except parenchymal hematoma (p = 0.755). Tailored RBS for IVH and continuous MLS outperformed BioClinicalBERT (p < 0.001) and linear regression, respectively (p < 0.001). CONCLUSIONS: Our study demonstrates robust performance and external validity of a core NLP tool kit for identifying both categorical and continuous outcomes of ischemic stroke from unstructured radiographic text data. Medically tailored NLP methods have multiple important big data applications, including scalable electronic phenotyping, augmentation of clinical risk prediction models, and facilitation of automatic alert systems in the hospital setting.

Implementation of Institutional Triaging Algorithms Decreases Head and Neck MDCT Use in Blunt Trauma.

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.

Role of cervical spine MRI in the setting of negative cervical spine CT in blunt trauma: Critical additional information in the setting of clinical findings suggestive of occult injury.

BACKGROUND AND PURPOSE: Cervical spine injury is common in the setting of blunt trauma and there is consensus that cervical spine CT (CSCT) is the image modality of choice for initial evaluation for blunt trauma related injuries of the cervical spine. However, there is disagreement in the literature with regards to further evaluation of blunt trauma patients with cervical spine MRI (CSMRI) after negative CSCT when there is persistent clinical concern for occult trauma related injury. The purpose of this study is to examine the utility of CSMRI for detection of occult injury in blunt trauma patients after negative CSCT. MATERIALS AND METHODS: We reviewed records for 7,301 patients admitted for blunt trauma (November 2007-December 2013) and identified 259 who underwent CSMRI after a negative CSCT. These CSMRIs were reviewed to determine the number and type of significant CT occult injuries identified and clinical indications that led to CSMRI acquisition. RESULTS AND CONCLUSIONS: CSMRI detected significant injuries following negative CSCT in 31% (81/259) of patients. There were 15 cord contusions/infarcts, 9 bone contusions/fractures, 7 spinal canal hemorrhages and 66 soft tissue injuries. Upper extremity neurological deficit had greatest positive predictive value (PPV) for detection of CT-occult injury on CSMRI of 43% (23/53), followed by equivocal CSCT findings (38%, 18/47), presence of extra-cervical injuries (34%, 20/58), midline cervical tenderness (20%, 17/85), and isolated lower extremity neurological deficit (0%, 0/16). CSMRI is recommended following negative CSCT in the evaluation of blunt cervical spine trauma when appropriate clinical concerns are present.

Nonhomogeneous Gadolinium Retention in the Cerebral Cortex after Intravenous Administration of Gadolinium-based Contrast Agent in Rats and Humans.

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 ∙ 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 ∙ g-1 ± 0.04 in piriform cortex, 0.24 µg ∙ g-1 ± 0.04 in dentate gyrus, 0.17 µg ∙ g-1 ± 0.04 in hippocampus) and subcortical structures (0.47 µg ∙ g-1 ± 0.10 in facial nucleus, 0.39 µg ∙ g-1 ± 0.10 in choroid plexus, 0.29 µg ∙ g-1 ± 0.05 in caudate-putamen, 0.26 µg ∙ g-1 ± 0.05 in reticular nucleus of the thalamus, 0.24 µg ∙ g-1 ± 0.04 in vestibular nucleus) and significantly greater than that in the cerebellum (0.17 µg ∙ g-1 ± 0.03, P = .01) and white matter tracts (anterior commissure: 0.05 µg ∙ g-1 ± 0.01, P = .002; corpus callosum: 0.05 µg ∙ g-1 ± 0.02, P = .001; cranial nerve: 0.02 µg ∙ 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.

MRI-detected spinal disc degenerative changes in athletes participating in the Rio de Janeiro 2016 Summer Olympics games.

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.

Posterior Reversible Encephalopathy Syndrome in Patients with Coronavirus Disease 2019: Two Cases and A Review of The Literature.

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.

Cerebral Venous Sinus Thromboses in Patients with SARS-CoV-2 Infection: Three Cases and a Review of the Literature.

INTRODUCTION: Early studies suggest that acute cerebrovascular events may be common in patients with coronavirus disease 2019 (COVID-19) and may be associated with a high mortality rate. Most cerebrovascular events described have been ischemic strokes, but both intracerebral hemorrhage and rarely cerebral venous sinus thrombosis (CVST) have also been reported. The diagnosis of CVST can be elusive, with wide-ranging and nonspecific presenting symptoms that can include headache or altered sensorium alone. OBJECTIVE: To describe the presentation, barriers to diagnosis, treatment, and outcome of CVST in patients with COVID-19. METHODS: We abstracted data on all patients diagnosed with CVST and COVID-19 from March 1 to August 9, 2020 at Boston Medical Center. Subsequently, we reviewed the literature and extracted all published cases of CVST in patients with COVID-19 from January 1, 2020 through August 9, 2020 and included all studies with case descriptions. RESULTS: We describe the clinical features and management of CVST in 3 women with COVID-19 who developed CVST days to months after initial COVID-19 symptoms. Two patients presented with encephalopathy and without focal neurologic deficits, while one presented with visual symptoms. All patients were treated with intravenous hydration and anticoagulation. None suffered hemorrhagic complications, and all were discharged home. We identified 12 other patients with CVST in the setting of COVID-19 via literature search. There was a female predominance (54.5%), most patients presented with altered sensorium (54.5%), and there was a high mortality rate (36.4%). CONCLUSIONS: During this pandemic, clinicians should maintain a high index of suspicion for CVST in patients with a recent history of COVID-19 presenting with non-specific neurological symptoms such as headache to provide expedient management and prevent complications. The limited data suggests that CVST in COVID-19 is more prevalent in females and may be associated with high mortality.

Imaging of Intracranial Infections.

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.

Differentiating Between Healthy Control Participants and Those with Mild Cognitive Impairment Using Volumetric MRI Data.

OBJECTIVE: To determine whether volumetric measures of the hippocampus, entorhinal cortex, and other cortical measures can differentiate between cognitively normal individuals and subjects with mild cognitive impairment (MCI). METHOD: Magnetic resonance imaging (MRI) data from 46 cognitively normal subjects and 50 subjects with MCI as part of the Boston University Alzheimer's Disease Center research registry and the Alzheimer's Disease Neuroimaging Initiative were used in this cross-sectional study. Cortical, subcortical, and hippocampal subfield volumes were generated from each subject's MRI data using FreeSurfer v6.0. Nominal logistic regression models containing these variables were used to identify subjects as control or MCI. RESULTS: A model containing regions of interest (superior temporal cortex, caudal anterior cingulate, pars opercularis, subiculum, precentral cortex, caudal middle frontal cortex, rostral middle frontal cortex, pars orbitalis, middle temporal cortex, insula, banks of the superior temporal sulcus, parasubiculum, paracentral lobule) fit the data best (R2 = .7310, whole model test chi-square = 97.16, p < .0001). CONCLUSIONS: MRI data correctly classified most subjects using measures of selected medial temporal lobe structures in combination with those from other cortical areas, yielding an overall classification accuracy of 93.75%. These findings support the notion that, while volumes of medial temporal lobe regions differ between cognitively normal and MCI subjects, differences that can be used to distinguish between these two populations are present elsewhere in the brain.

Retained executive abilities in mild cognitive impairment are associated with increased white matter network connectivity.

PURPOSE: To describe structural network differences in individuals with mild cognitive impairment (MCI) with high versus low executive abilities, as reflected by measures of white matter connectivity using diffusion tensor imaging (DTI). MATERIALS AND METHODS: This was a retrospective, cross-sectional study. Of the 128 participants from the Alzheimer's Disease Neuroimaging Initiative database who had both a DTI scan as well as a diagnosis of MCI, we used an executive function score to classify the top 15 scoring patients as high executive ability, and the bottom-scoring 16 patients as low executive ability. Using a regions-of-interest-based analysis, we constructed networks and calculated graph theory measures on the constructed networks. We used automated tractography in order to compare differences in major white matter tracts. RESULTS: The high executive ability group yielded greater network size, density and clustering coefficient. The high executive ability group reflected greater fractional anisotropy bilaterally in the inferior and superior longitudinal fasciculi. CONCLUSIONS: The network measures of the high executive ability group demonstrated greater white matter integrity. This suggests that white matter reserve may confer greater protection of executive abilities. Loss of this reserve may lead to greater impairment in the progression to Alzheimer's disease dementia. KEY POINTS: • The MCI high executive ability group yielded a larger network. • The MCI high executive ability group had greater FA in numerous tracts. • White matter reserve may confer greater protection of executive abilities. • Loss of executive reserve may lead to greater impairment in AD dementia.

Functional brain networks involved in decision-making under certain and uncertain conditions.

PURPOSE: The aim of this study was to describe imaging markers of decision-making under uncertain conditions in normal individuals, in order to provide baseline activity to compare to impaired decision-making in pathological states. METHODS: In this cross-sectional study, 19 healthy subjects ages 18-35 completed a novel decision-making card-matching task using a Phillips T3 Scanner and a 32-channel head coil. Functional data were collected in six functional runs. In one condition of the task, the participant was certain of the rule to apply to match the cards; in the other condition, the participant was uncertain. We performed cluster-based comparison of the two conditions using FSL fMRI Expert Analysis Tool and network-based analysis using MATLAB. RESULTS: The uncertain > certain comparison yielded three clusters-a midline cluster that extended through the midbrain, the thalamus, bilateral prefrontal cortex, the striatum, and bilateral parietal/occipital clusters. The certain > uncertain comparison yielded bilateral clusters in the insula, parietal and temporal lobe, as well as a medial frontal cluster. A larger, more connected functional network was found in the uncertain condition. CONCLUSION: The involvement of the insula, parietal cortex, temporal cortex, ventromedial prefrontal cortex, and orbitofrontal cortex of the certain condition reinforces the notion that certainty is inherently rewarding. For the uncertain condition, the involvement of the prefrontal cortex, parietal cortex, striatum, thalamus, amygdala, and hippocampal involvement was expected, as these are areas involved in resolving uncertainty and rule updating. The involvement of occipital cortical involvement and midbrain involvement may be attributed to increased visual attention and increased motor control.

Radiological imaging features of the basal ganglia that may predict progression to hemicraniectomy in large territory middle cerebral artery infarct.

PURPOSE: Predicting which patients are at risk for hemicraniectomy can be helpful for triage and can help preserve neurologic function if detected early. We evaluated basal ganglia imaging predictors for early hemicraniectomy in patients with large territory anterior circulation infarct. METHODS: This retrospective study evaluated patients with ischemic infarct admitted from January 2005 to July 2011. Patients with malignant cerebral edema refractory to medical therapy or with herniating signs such as depressed level of consciousness, anisocoria, and contralateral leg weakness were triaged to hemicraniectomy. Admission images were reviewed for presence of caudate, lentiform nucleus (putamen and globus pallidus), or basal ganglia (caudate + lentiform nucleus) infarction. RESULTS: Thirty-one patients with large territory MCA infarct, 10 (32%), underwent hemicraniectomy. Infarction of the caudate nucleus (9/10 vs 6/21, p = 0.002) or basal ganglia (5/10 vs 2/21, p = 0.02) predicted progression to hemicraniectomy. Infarction of the lentiform nucleus only did not predict progression to hemicraniectomy. Sensitivity for patients who did and did not have hemicraniectomy were 50% (5/10) and 90.5% (19/21). For caudate nucleus and caudate plus lentiform nucleus infarcts, the crude- and age-adjusted odds of progression to hemicraniectomy were 9.5 (1.4-64.3) and 6.6 (0.78-55.4), respectively. CONCLUSION: Infarction of the caudate nucleus or basal ganglia correlated with patients progressing to hemicraniectomy. Infarction of the lentiform nucleus alone did not.

Normal saline as a natural intravascular contrast agent for dynamic perfusion-weighted MRI of the brain: Proof of concept at 1.5T.

PURPOSE: Gadolinium-based contrast agents have associated risks. Normal saline (NS) is a nontoxic sodium chloride water solution that can significantly increase the magnetic resonance imaging (MRI) relaxation times of blood via transient hemodilution (THD). The purpose of this pilot study was to test in vivo in the head the potential of normal saline as a safer, exogenous perfusion contrast agent. MATERIALS AND METHODS: This Health Insurance Portability and Accountability Act (HIPAA)-compliant prospective study was approved by the local Institutional Review Board (IRB): 12 patients were scanned with T1 -weighted inversion recovery turbo spin echo pulse sequence at 1.5T. The dynamic inversion recovery pulse sequence was run before, during, and after the NS injection for up to 5 minutes: 100 ml of NS was power-injected via antecubital veins at 3-4 ml/s. Images were processed to map maximum enhancement area-under-the-curve, time-to-peak, and mean-transit-time. These maps were used to identify the areas showing significant NS injection-related signal and to generate enhancement time curves. Hardware and pulse sequence stability were studied via phantom experimentation. Main features of the time curves were tested against theoretical modeling of THD signal effects using inversion recovery pulse sequences. Pearson correlation coefficient (R) mapping was used to differentiate genuine THD effects from motion confounders and noise. RESULTS: The scans of 8 out of 12 patients showed NS injection-related effects that correlate in magnitude with tissue type (gray matter ∼15% and white matter ∼3%). Motion artifacts prevented ascertaining NS signal effects in the remaining four patients. Positive and negative time curves were observed in vivo and this dual THD signal polarity was also observed in the theoretical simulations. R-histograms that were approximately constant in the range 0.1 < |R| < 0.8 and leading to correlation fractions of Fcorr (|R| > 0.5) = 0.45 and 0.59 were found to represent scans with genuine THD signal effects. CONCLUSION: A measurable perfusion effect in brain tissue was demonstrated in vivo using NS as an injectable intravascular contrast agent. J. Magn. Reson. Imaging 2016;44:1580-1591.

Association between cervical spine and skull-base fractures and blunt cerebrovascular injury.

INTRODUCTION: Blunt cerebrovascular injuries (BCVI) are associated with high morbidity and mortality and can lead to neurological deficits. The established criteria for patients undergoing CT angiography (CTA) for BCVI are broad, and can expose patients to radiation unnecessarily. This study aimed to examine the prevalence of BCVI in patients on CTA and determine presentations associated with the highest rates of BCVI. MATERIALS AND METHODS: With IRB approval, patients were selected for CTA screening for BCVI according to a predefined set of criteria at our hospital between 2007 and 2010. Patients were identified from our institution's trauma database. CTAs were retrospectively reviewed for BCVI including vasospasm and dissection. Electronic medical records were reviewed for clinical presentation and hospital course. RESULTS: Of 432 patients, vasospasm (n = 10) and/or dissection (n = 36) were found in 46 patients (10.6%). BCVI was associated with cervical spine and/or skull-base fracture in 40/46 patients (87%, P < 0.0001). Significant correlations were seen between dissection and fracture in 31/36 patients (86.2%, p < 0.0001) and between BCVI and both neurological deficits and fractures (27/44, P < 0.0001). CONCLUSION: BCVI was significantly associated with cervical and/or skullbase fractures and neurological deficits with coexistent fractures. Patients with these injuries should be prioritized for rapid CTA evaluation for BCVI. KEY POINTS: • CTA screening is important to identify patients with underlying BCVI • Cervical spine and/or skullbase fractures were significantly associated with BCVI • BCVI may occur in up to 11% of patients with blunt trauma injuries.

Differential Assessment of Internal Jugular Vein Stenosis in Patients Undergoing CT and MRI with Contrast.

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.

Contrast Staining in Noninfarcted Tissue after Endovascular Treatment of Acute Ischemic Stroke.

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.

AI-based differential diagnosis of dementia etiologies on multimodal data.

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.

AI-based differential diagnosis of dementia etiologies on multimodal data.

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.