Faculty Bibliography

BACKGROUND AND PURPOSE/OBJECTIVE:Artificial intelligence (AI) models have shown promise in neuroradiology, yet their real-world generalizability remains uncertain, partly due to variability in imaging acquisition and protocols. We aimed to evaluate the impact of data source, scanner manufacturer, scan mode, slice thickness, and the AI models developed by participating teams on AI performance in this secondary analysis of the 2019 American Society of Functional Neuroradiology (ASFNR) AI Competition. MATERIALS AND METHODS/METHODS:We included 1,177 anonymized noncontrast head CT scans from five institutions. Four teams participated, developing models to detect acute ischemic stroke, intracranial hemorrhage, mass effect, and to assess age-appropriate normality. Generalized estimating equations (GEE) were used to evaluate the effects of the aforementioned variables on model performance, and collinearity diagnostics were applied to exclude redundant variables. RESULTS:Due to collinearity with scanner manufacturer, data source was excluded from the model. Across all tasks, the AI model employed significantly influenced performance. Scanner manufacturer was significantly associated with accuracy in detecting intracranial hemorrhage and acute ischemic stroke but not mass effect or age-based normality. Slice thickness significantly associated with detection of intracranial hemorrhage and mass effect, with thinner slices yielding higher accuracy, but showed no effect on ischemic stroke or normality assessments. Scan mode did not significantly influence performance for any task. CONCLUSION/CONCLUSIONS:This secondary analysis demonstrates that imaging acquisition and protocol variability may significantly affect AI model performance. Scanner manufacturer, slice thickness, and the developed AI model were significantly associated with model accuracy, whereas scan mode had no significant impact. Among these, the developed AI model consistently proved most influential, reflecting the importance of training data, model architecture, and preprocessing methods.

OBJECTIVES/OBJECTIVE:Anti-amyloid-beta immunotherapy requires frequent MRI screening for amyloid-related imaging abnormalities-hemorrhage subtype (ARIA-H), consisting of cerebral microbleeds (CMB) and/or superficial siderosis (SS), using gradient-recalled echo (GRE) or susceptibility-weighted imaging (SWI). Screening MRI sequences for ARIA-H may benefit from acceleration to maximize patient enrollment by increased throughput and reduced motion degradation. This study assessed the diagnostic performance of standard GRE and SWI to echo-planar imaging (EPI) accelerated substitutions for detecting CMB and SS. MATERIALS AND METHODS/METHODS:This retrospective single-center rater study included 50 patients, 25 with CMB and 25 patients without CMB (median age 77 y, IQR: 70 to 82 y; 30 of 50 female) who were imaged with FDG PET-3T MRI from April to July 2023. Standard GRE (90 s) and SWI (192 s) were compared with an EPI-accelerated GRE (aGRE; 13 s, 86% time reduction) and an EPI-accelerated SWI substitution (aSWI; 33 s, 83% time reduction). Three board-certified neuroradiologists independently reported CMB and SS (per ARIA-H monitoring guidelines), perceived image quality and motion for each sequence. There were 240 total assessments per rater (the 4 different sequences for the 50 patients plus 10 duplicated patients). Sensitivity, specificity, positive and negative predictive values, area under the curve (AUC), inter-rater and intrarater agreement were determined for each sequence and rater. RESULTS:The aggregate AUCs for the 4 individual sequences were excellent for detecting CMB (0.84 to 0.94) and SS (0.89 to 1.00) without statistical differences observed between standard and EPI-accelerated substitutions. Both aGRE and aSWI had high negative predictive values (96.5% to 100%). There were modest quantitative correlations between standard and accelerated sequences (0.606 and 0.391 for GRE and SWI, respectively), no differences in CMB count for aGRE (bias 0.01, P=0.895), but reduced CMB count with aSWI (bias -1.12, P=0.014). Inter-rater agreements were mildly reduced for both GRE versus aGRE (eg, 0.757 to 0.622 for CMB detection) and SWI versus aSWI (eg, 0.834 to 0.649 for SS detection). Perceived image quality for accelerated sequences was reduced, but with less motion observed with aSWI. CONCLUSIONS:The aGRE and aSWI sequences shorten scan times 86% and 83%, respectively, with similar diagnostic performance for ARIA-H screening, but reduced rater agreement and perceived image quality.

BACKGROUND AND PURPOSE/OBJECTIVE:Artificial intelligence models in radiology are frequently developed and validated using data sets from a single institution and are rarely tested on independent, external data sets, raising questions about their generalizability and applicability in clinical practice. The American Society of Functional Neuroradiology (ASFNR) organized a multicenter artificial intelligence competition to evaluate the proficiency of developed models in identifying various pathologies on NCCT, assessing age-based normality and estimating medical urgency. MATERIALS AND METHODS/METHODS:In total, 1201 anonymized, full-head NCCT clinical scans from 5 institutions were pooled to form the data set. The data set encompassed studies with normal findings as well as those with pathologies, including acute ischemic stroke, intracranial hemorrhage, traumatic brain injury, and mass effect (detection of these, task 1). NCCTs were also assessed to determine if findings were consistent with expected brain changes for the patient's age (task 2: age-based normality assessment) and to identify any abnormalities requiring immediate medical attention (task 3: evaluation of findings for urgent intervention). Five neuroradiologists labeled each NCCT, with consensus interpretations serving as the ground truth. The competition was announced online, inviting academic institutions and companies. Independent central analysis assessed the performance of each model. Accuracy, sensitivity, specificity, positive and negative predictive values, and receiver operating characteristic (ROC) curves were generated for each artificial intelligence model, along with the area under the ROC curve. RESULTS:Four teams processed 1177 studies. The median age of patients was 62 years, with an interquartile range of 33 years. Nineteen teams from various academic institutions registered for the competition. Of these, 4 teams submitted their final results. No commercial entities participated in the competition. For task 1, areas under the ROC curve ranged from 0.49 to 0.59. For task 2, two teams completed the task with area under the ROC curve values of 0.57 and 0.52. For task 3, teams had little-to-no agreement with the ground truth. CONCLUSIONS:To assess the performance of artificial intelligence models in real-world clinical scenarios, we analyzed their performance in the ASFNR Artificial Intelligence Competition. The first ASFNR Competition underscored the gap between expectation and reality; and the models largely fell short in their assessments. As the integration of artificial intelligence tools into clinical workflows increases, neuroradiologists must carefully recognize the capabilities, constraints, and consistency of these technologies. Before institutions adopt these algorithms, thorough validation is essential to ensure acceptable levels of performance in clinical settings.

BACKGROUND:Acute neurological manifestation is a common complication of acute Coronavirus Disease 2019 (COVID-19) disease. This retrospective cohort study investigated the 3-year outcomes of patients with and without significant neurological manifestations during initial COVID-19 hospitalization. METHODS AND FINDINGS/RESULTS:Patients hospitalized for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection between 03/01/2020 and 4/16/2020 in the Montefiore Health System in the Bronx, an epicenter of the early pandemic, were included. Follow-up data was captured up to 01/23/2023 (3 years post-COVID-19). This cohort consisted of 414 patients with COVID-19 with significant neurological manifestations and 1,199 propensity-matched patients (for age and COVID-19 severity score) with COVID-19 without neurological manifestations. Neurological involvement during the acute phase included acute stroke, new or recrudescent seizures, anatomic brain lesions, presence of altered mentation with evidence for impaired cognition or arousal, and neuro-COVID-19 complex (headache, anosmia, ageusia, chemesthesis, vertigo, presyncope, paresthesias, cranial nerve abnormalities, ataxia, dysautonomia, and skeletal muscle injury with normal orientation and arousal signs). There were no significant group differences in female sex composition (44.93% versus 48.21%, p = 0.249), ICU and IMV status, white, not Hispanic (6.52% versus 7.84%, p = 0.380), and Hispanic (33.57% versus 38.20%, p = 0.093), except black non-Hispanic (42.51% versus 36.03%, p = 0.019). Primary outcomes were mortality, stroke, heart attack, major adverse cardiovascular events (MACE), reinfection, and hospital readmission post-discharge. Secondary outcomes were neuroimaging findings (hemorrhage, active and prior stroke, mass effect, microhemorrhages, white matter changes, microvascular disease (MVD), and volume loss). More patients in the neurological cohort were discharged to acute rehabilitation (10.39% versus 3.34%, p < 0.001) or skilled nursing facilities (35.75% versus 25.35%, p < 0.001) and fewer to home (50.24% versus 66.64%, p < 0.001) than matched controls. Incidence of readmission for any reason (65.70% versus 60.72%, p = 0.036), stroke (6.28% versus 2.34%, p < 0.001), and MACE (20.53% versus 16.51%, p = 0.032) was higher in the neurological cohort post-discharge. Per Kaplan-Meier univariate survival curve analysis, such patients in the neurological cohort were more likely to die post-discharge compared to controls (hazard ratio: 2.346, (95% confidence interval (CI) [1.586, 3.470]; p < 0.001)). Across both cohorts, the major causes of death post-discharge were heart disease (13.79% neurological, 15.38% control), sepsis (8.63%, 17.58%), influenza and pneumonia (13.79%, 9.89%), COVID-19 (10.34%, 7.69%), and acute respiratory distress syndrome (ARDS) (10.34%, 6.59%). Factors associated with mortality after leaving the hospital involved the neurological cohort (odds ratio (OR): 1.802 (95% CI [1.237, 2.608]; p = 0.002)), discharge disposition (OR: 1.508 (95% CI [1.276, 1.775]; p < 0.001)), congestive heart failure (OR: 2.281 (95% CI [1.429, 3.593]; p < 0.001)), higher COVID-19 severity score (OR: 1.177 (95% CI [1.062, 1.304]; p = 0.002)), and older age (OR: 1.027 (95% CI [1.010, 1.044]; p = 0.002)). There were no group differences in radiological findings, except that the neurological cohort showed significantly more age-adjusted brain volume loss (p = 0.045) than controls. The study's patient cohort was limited to patients infected with COVID-19 during the first wave of the pandemic, when hospitals were overburdened, vaccines were not yet available, and treatments were limited. Patient profiles might differ when interrogating subsequent waves. CONCLUSIONS:Patients with COVID-19 with neurological manifestations had worse long-term outcomes compared to matched controls. These findings raise awareness and the need for closer monitoring and timely interventions for patients with COVID-19 with neurological manifestations, as their disease course involving initial neurological manifestations is associated with enhanced morbidity and mortality.

INTRODUCTION/BACKGROUND:Pilocytic astrocytoma, a World Health Organization grade 1 tumor, is the most common brain tumor in children between 5 and 14 years of age and the second most common in children younger than 5 and older than 14. Although classical to the cerebellum and hypothalamic regions, it can also arise in the spinal cord. Larotrectinib, a selective inhibitor of tropomyosin receptor kinase, has been effective in pediatric tumors with NTRK fusion mutations in children as young as 1-month-old. CASE/METHODS:We share the case of a 9-month-old boy who presented with a 4-month history of regression of his milestones and severe constipation who was found to have a large spinal pilocytic astrocytoma with multiple intracranial periventricular lesions.

Neuroborreliosis can manifest with cranial nerve (CN) palsies, commonly CN VII. Rarely have isolated or multiple palsies been reported. We describe a case of a young female from a Lyme endemic region who presented with bilateral CN VI palsies and a dilated right pupil, possibly a partial CN III palsy. She later developed CN VII palsy and bilateral enhancement of multiple cranial nerves on neuroimaging. She was diagnosed with Lyme disease by serological testing, with gradual improvement on antibiotics. Our case illustrates that neuroborreliosis can present as any or multiple CN palsies, and should be considered particularly in endemic areas.

The development of multiple sclerosis (MS) is multifactorial. Elevated levels of vitamin D may lower the risk and reduce relapses by immunomodulatory mechanisms. Conversely, vitamin D-dependent rickets (VDDR), an inheritable form of rickets secondary to impairment in vitamin D synthesis or action, may increase MS risk. This has been described in three patients with VDDR type 1A. Here, we present a patient with VDDR type 2 - unclear if type 2A or 2B based on historical genetic testing - who subsequently developed MS. She presented with 8 weeks of binocular horizontal diplopia and was found to have 8 prism dioptres of esotropia in primary gaze and a mild limitation of abduction in both eyes. Radiological workup was consistent with MS demyelination. She was started on solumedrol infusions, with full resolution of the esotropia and abduction deficits. She has since been transitioned to ocrelizumab with vitamin D supplementation and has not had a relapse to date. It is important to consider MS in patients genetically predisposed to low vitamin D levels or functional impairment, as with VDDR. Vitamin D supplementation can achieve remission in some forms of VDDR, and its role in MS prevention in these patients should be considered. In patients with type 2A or 2B VDDR, who have impairment in receptor function, additional treatment modalities require investigation. Lastly, demyelination is a rare cause of bilateral cranial nerve 6 palsy. This case illustrates the importance of considering MS in cranial nerve palsies, particularly in patients with vitamin D deficiencies or functional impairment.

The coronavirus disease 2019 (COVID -19) pandemic caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) has affected almost every country in the world, resulting in severe morbidity, mortality and economic hardship, and altering the landscape of healthcare forever. Although primarily a pulmonary illness, it can affect multiple organ systems throughout the body, sometimes with devastating complications and long-term sequelae. As we move into the second year of this pandemic, a better understanding of the pathophysiology of the virus and the varied imaging findings of COVID-19 in the involved organs is crucial to better manage this complex multi-organ disease and to help improve overall survival. This manuscript provides a comprehensive overview of the pathophysiology of the virus along with a detailed and systematic imaging review of the extra-thoracic manifestation of COVID-19 with the exception of unique cardiothoracic features associated with multisystem inflammatory syndrome in children (MIS-C). In Part I, extra-thoracic manifestations of COVID-19 in the abdomen in adults and features of MIS-C will be reviewed. In Part II, manifestations of COVID-19 in the musculoskeletal, central nervous and vascular systems will be reviewed.