Impact of an automated large vessel occlusion detection tool on clinical workflow and patient outcomes.

Purpose: Automated large vessel occlusion (LVO) tools allow for prompt identification of positive LVO cases, but little is known about their role in acute stroke triage when implemented in a real-world setting. The purpose of this study was to evaluate the automated LVO detection tool's impact on acute stroke workflow and clinical outcomes. Materials and methods: Consecutive patients with a computed tomography angiography (CTA) presenting with suspected acute ischemic stroke were compared before and after the implementation of an AI tool, RAPID LVO (RAPID 4.9, iSchemaView, Menlo Park, CA). Radiology CTA report turnaround times (TAT), door-to-treatment times, and the NIH stroke scale (NIHSS) after treatment were evaluated. Results: A total of 439 cases in the pre-AI group and 321 cases in the post-AI group were included, with 62 (14.12%) and 43 (13.40%) cases, respectively, receiving acute therapies. The AI tool demonstrated a sensitivity of 0.96, a specificity of 0.85, a negative predictive value of 0.99, and a positive predictive value of 0.53. Radiology CTA report TAT significantly improved post-AI (mean 30.58 min for pre-AI vs. 22 min for post-AI, p < 0.0005), notably at the resident level (p < 0.0003) but not at higher levels of expertise. There were no differences in door-to-treatment times, but the NIHSS at discharge was improved for the pre-AI group adjusted for confounders (parameter estimate = 3.97, p < 0.01). Conclusion: Implementation of an automated LVO detection tool improved radiology TAT but did not translate to improved stroke metrics and outcomes in a real-world setting.

Methamphetamine use increases the risk of cerebral small vessel disease in young patients with acute ischemic stroke.

Methamphetamine use causes spikes in blood pressure. Chronic hypertension is a major risk factor for cerebral small vessel disease (cSVD). The aim of this study is to investigate whether methamphetamine use increases the risk of cSVD. Consecutive patients with acute ischemic stroke at our medical center were screened for methamphetamine use and evidence of cSVD on MRI of the brain. Methamphetamine use was identified by self-reported history and/or positive urine drug screen. Propensity score matching was used to select non-methamphetamine controls. Sensitivity analysis was performed to assess the effect of methamphetamine use on cSVD. Among 1369 eligible patients, 61 (4.5%) were identified to have a history of methamphetamine use and/or positive urine drug screen. Compared with the non-methamphetamine group (n = 1306), the patients with methamphetamine abuse were significantly younger (54.5 ± 9.7 vs. 70.5 ± 12.4, p < 0.001), male (78.7% vs. 54.0%, p < 0.001) and White (78.7% vs. 50.4%, p < 0.001). Sensitivity analysis showed that methamphetamine use was associated with increased white matter hyperintensities, lacunes, and total burden of cSVD. The association was independent of age, sex, concomitant cocaine use, hyperlipidemia, acute hypertension, and stroke severity. Our findings suggest that methamphetamine use increases the risk of cSVD in young patients with acute ischemic stroke.

Autoimmune-mediated encephalitis and mimics: A neuroimaging review.

Autoimmune encephalitis is a category of autoantibody-mediated neurological disorders that often presents a diagnostic challenge due to its variable clinical and imaging findings. The purpose of this image-based review is to provide an overview of the major subtypes of autoimmune encephalitis and their associated autoantibodies, discuss their characteristic clinical and imaging features, and highlight several disease processes that may mimic imaging findings of autoimmune encephalitis. A literature search on autoimmune encephalitis was performed and publications from neuroradiology, neurology, and nuclear medicine literature were included. Cases from our institutional database that best exemplify major imaging features were presented.

Head-to-head comparison of commercial artificial intelligence solutions for detection of large vessel occlusion at a comprehensive stroke center.

Purpose: Despite the availability of commercial artificial intelligence (AI) tools for large vessel occlusion (LVO) detection, there is paucity of data comparing traditional machine learning and deep learning solutions in a real-world setting. The purpose of this study is to compare and validate the performance of two AI-based tools (RAPID LVO and CINA LVO) for LVO detection. Materials and methods: This was a retrospective, single center study performed at a comprehensive stroke center from December 2020 to June 2021. CT angiography (n = 263) for suspected stroke were evaluated for LVO. RAPID LVO is a traditional machine learning model which primarily relies on vessel density threshold assessment, while CINA LVO is an end-to-end deep learning tool implemented with multiple neural networks for detection and localization tasks. Reasons for errors were also recorded. Results: There were 29 positive and 224 negative LVO cases by ground truth assessment. RAPID LVO demonstrated an accuracy of 0.86, sensitivity of 0.90, specificity of 0.86, positive predictive value of 0.45, and negative predictive value of 0.98, while CINA demonstrated an accuracy of 0.96, sensitivity of 0.76, specificity of 0.98, positive predictive value of 0.85, and negative predictive value of 0.97. Conclusion: Both tools successfully detected most anterior circulation occlusions. RAPID LVO had higher sensitivity while CINA LVO had higher accuracy and specificity. Interestingly, both tools were able to detect some, but not all M2 MCA occlusions. This is the first study to compare traditional and deep learning LVO tools in the clinical setting.

Point-of-Care Brain MRI: Preliminary Results from a Single-Center Retrospective Study.

Background Point-of-care (POC) MRI is a bedside imaging technology with fewer than five units in clinical use in the United States and a paucity of scientific studies on clinical applications. Purpose To evaluate the clinical and operational impacts of deploying POC MRI in emergency department (ED) and intensive care unit (ICU) patient settings for bedside neuroimaging, including the turnaround time. Materials and Methods In this preliminary retrospective study, all patients in the ED and ICU at a single academic medical center who underwent noncontrast brain MRI from January 2021 to June 2021 were investigated to determine the number of patients who underwent bedside POC MRI. Turnaround time, examination limitations, relevant findings, and potential CT and fixed MRI findings were recorded for patients who underwent POC MRI. Descriptive statistics were used to describe clinical variables. The Mann-Whitney U test was used to compare the turnaround time between POC MRI and fixed MRI examinations. Results Of 638 noncontrast brain MRI examinations, 36 POC MRI examinations were performed in 35 patients (median age, 66 years [IQR, 57-77 years]; 21 women), with one patient undergoing two POC MRI examinations. Of the 36 POC MRI examinations, 13 (36%) occurred in the ED and 23 (64%) in the ICU. There were 12 of 36 (33%) POC MRI examinations interpreted as negative, 14 of 36 (39%) with clinically significant imaging findings, and 10 of 36 (28%) deemed nondiagnostic for reasons such as patient motion. Of 23 diagnostic POC MRI examinations with comparison CT available, three (13%) demonstrated acute infarctions not apparent on CT scans. Of seven diagnostic POC MRI examinations with subsequent fixed MRI examinations, two (29%) demonstrated missed versus interval subcentimeter infarctions, while the remaining demonstrated no change. The median turnaround time of POC MRI was 3.4 hours in the ED and 5.3 hours in the ICU. Conclusion Point-of-care (POC) MRI was performed rapidly in the emergency department and intensive care unit. A few POC MRI examinations demonstrated acute infarctions not apparent at standard-of-care CT examinations. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Anzai and Moy in this issue.

Validation of a Deep Learning Tool in the Detection of Intracranial Hemorrhage and Large Vessel Occlusion.

Purpose: Recently developed machine-learning algorithms have demonstrated strong performance in the detection of intracranial hemorrhage (ICH) and large vessel occlusion (LVO). However, their generalizability is often limited by geographic bias of studies. The aim of this study was to validate a commercially available deep learning-based tool in the detection of both ICH and LVO across multiple hospital sites and vendors throughout the U.S. Materials and Methods: This was a retrospective and multicenter study using anonymized data from two institutions. Eight hundred fourteen non-contrast CT cases and 378 CT angiography cases were analyzed to evaluate ICH and LVO, respectively. The tool's ability to detect and quantify ICH, LVO, and their various subtypes was assessed among multiple CT vendors and hospitals across the United States. Ground truth was based off imaging interpretations from two board-certified neuroradiologists. Results: There were 255 positive and 559 negative ICH cases. Accuracy was 95.6%, sensitivity was 91.4%, and specificity was 97.5% for the ICH tool. ICH was further stratified into the following subtypes: intraparenchymal, intraventricular, epidural/subdural, and subarachnoid with true positive rates of 92.9, 100, 94.3, and 89.9%, respectively. ICH true positive rates by volume [small (<5 mL), medium (5-25 mL), and large (>25 mL)] were 71.8, 100, and 100%, respectively. There were 156 positive and 222 negative LVO cases. The LVO tool demonstrated an accuracy of 98.1%, sensitivity of 98.1%, and specificity of 98.2%. A subset of 55 randomly selected cases were also assessed for LVO detection at various sites, including the distal internal carotid artery, middle cerebral artery M1 segment, proximal middle cerebral artery M2 segment, and distal middle cerebral artery M2 segment with an accuracy of 97.0%, sensitivity of 94.3%, and specificity of 97.4%. Conclusion: Deep learning tools can be effective in the detection of both ICH and LVO across a wide variety of hospital systems. While some limitations were identified, specifically in the detection of small ICH and distal M2 occlusion, this study highlights a deep learning tool that can assist radiologists in the detection of emergent findings in a variety of practice settings.

Development and external validation of a prognostic tool for COVID-19 critical disease.

BACKGROUND: The rapid spread of coronavirus disease 2019 (COVID-19) revealed significant constraints in critical care capacity. In anticipation of subsequent waves, reliable prediction of disease severity is essential for critical care capacity management and may enable earlier targeted interventions to improve patient outcomes. The purpose of this study is to develop and externally validate a prognostic model/clinical tool for predicting COVID-19 critical disease at presentation to medical care. METHODS: This is a retrospective study of a prognostic model for the prediction of COVID-19 critical disease where critical disease was defined as ICU admission, ventilation, and/or death. The derivation cohort was used to develop a multivariable logistic regression model. Covariates included patient comorbidities, presenting vital signs, and laboratory values. Model performance was assessed on the validation cohort by concordance statistics. The model was developed with consecutive patients with COVID-19 who presented to University of California Irvine Medical Center in Orange County, California. External validation was performed with a random sample of patients with COVID-19 at Emory Healthcare in Atlanta, Georgia. RESULTS: Of a total 3208 patients tested in the derivation cohort, 9% (299/3028) were positive for COVID-19. Clinical data including past medical history and presenting laboratory values were available for 29% (87/299) of patients (median age, 48 years [range, 21-88 years]; 64% [36/55] male). The most common comorbidities included obesity (37%, 31/87), hypertension (37%, 32/87), and diabetes (24%, 24/87). Critical disease was present in 24% (21/87). After backward stepwise selection, the following factors were associated with greatest increased risk of critical disease: number of comorbidities, body mass index, respiratory rate, white blood cell count, % lymphocytes, serum creatinine, lactate dehydrogenase, high sensitivity troponin I, ferritin, procalcitonin, and C-reactive protein. Of a total of 40 patients in the validation cohort (median age, 60 years [range, 27-88 years]; 55% [22/40] male), critical disease was present in 65% (26/40). Model discrimination in the validation cohort was high (concordance statistic: 0.94, 95% confidence interval 0.87-1.01). A web-based tool was developed to enable clinicians to input patient data and view likelihood of critical disease. CONCLUSIONS AND RELEVANCE: We present a model which accurately predicted COVID-19 critical disease risk using comorbidities and presenting vital signs and laboratory values, on derivation and validation cohorts from two different institutions. If further validated on additional cohorts of patients, this model/clinical tool may provide useful prognostication of critical care needs.

Impact of COVID-19 on Acute Stroke Presentation at a Comprehensive Stroke Center.

Background: COVID-19 has impacted healthcare in many ways, including presentation of acute stroke. Since time-sensitive thrombolysis is essential for reducing morbidity and mortality in acute stroke, any delays due to the pandemic can have serious consequences. Methods: We retrospectively reviewed the electronic medical records for patients presenting with acute ischemic stroke at a comprehensive stroke center in March-April 2020 (the early months of COVID-19) and compared to the same time period in 2019. Stroke metrics such as incidence, time to arrival, and immediate outcomes were assessed. Results: There were 48 acute ischemic strokes (of which 7 were transfers) in March-April 2020 compared to 64 (of which 12 were transfers) in 2019. The average last known well to arrival time (±SD) for stroke codes was 1,041 (±1682.1) min in 2020 and 554 (±604.9) min in 2019. Of the patients presenting directly to the ED with a known last known well time, 27.8% (10/36) presented in the first 4.5 h in 2020, in contrast to 40.5% (15/37) in 2019. Patients who died comprised 10.4% of the stroke cohort in 2020 (5/48) compared to 6.3% in 2019 (4/64). Conclusions: During the first 2 months of COVID-19, there were fewer overall stroke cases who presented to our hospital, and of these cases, there was delayed presentation in comparison to the same time period in 2019. Recognizing how stroke presentation may be affected by COVID-19 would allow for optimization of established stroke triage algorithms in order to ensure safe and timely delivery of stroke care during a pandemic.

Spot Sign in Secondary Intraventricular Hemorrhage Predicts Early Neurological Decline.

PURPOSE: The spot sign is associated with intracerebral hemorrhage (ICH) expansion and neurological decline. However, the relationship of the spot sign to secondary intraventricular hemorrhage (IVH) has not been well established. The presence of the spot sign in secondary IVH may provide information regarding neurologic outcome in a population with known poor prognosis. METHODS: A subset analysis was performed of patients with IVH from the Antihypertensive Treatment of Acute Cerebral Hemorrhage 2 (ATACH-II) study, a randomized clinical trial examining the effect of intensive blood pressure reduction on hematoma expansion. The presence of the spot sign was determined on CTA and IVH expansion was measured in the first 24 hours. The primary outcome measure was early neurological decline (END), defined as ≥ 2-point decrease in Glasgow Coma Scale (GCS) score or ≥ 4-point increase in NIH Stroke Scale (NIHSS). Secondary outcomes including various radiological and clinical factors were also measured. RESULTS: Of 57 patients included in this analysis, the spot sign was present in 17 (29.8%). The spot sign was a predictor of END in univariate (P < 0.005 for GCS and P = 0.04 for NIHSS) and multivariate analyses using GCS scores (OR=7.2, CI 1.6 - 32.5, P = 0.01). Median 90 day modified Rankin Scale (mRS) scores were significantly different between spot sign-positive and spot sign-negative groups (P = 0.02). CONCLUSIONS: The presence of the spot sign is associated with END in patients with secondary IVH. Identifying this radiologic feature could have important implications for triaging these patients to the appropriate level of care.

Central Nervous System Vasculopathies.

Various imaging techniques play a role in the diagnosis of CNS vasculopathies, which comprise a heterogeneous group of disorders, including various noninflammatory and inflammatory etiologies. Noninflammatory vasculopathies include entities such as CADASIL, Susac, moyamoya, fibromuscular dysplasia, vasculopathy of connective tissue disorders, and reversible vasoconstriction syndrome. Inflammatory vasculopathies include vasculitides of different vessel sizes, primary angiitis of the CNS, vasculitis of systemic disease, and vasculitis secondary to specific causes. Miscellaneous etiology includes cerebral amyloid angiopathy, which has noninflammatory and inflammatory subtypes. This article discusses important clinical and imaging findings used to distinguish these disorders.

Evaluation of neonatal brain myelination using the T1- and T2-weighted MRI ratio.

PURPOSE: To validate the T1- and T2-weighted (T1w/T2w) MRI ratio technique in evaluating myelin in the neonatal brain. MATERIALS AND METHODS: T1w and T2w MR images of 10 term neonates with normal-appearing brain parenchyma were obtained from a single 1.5 Tesla MRI and retrospectively analyzed. T1w/T2w ratio images were created with a postprocessing pipeline and qualitatively compared with standard clinical sequences (T1w, T2w, and apparent diffusion coefficient [ADC]). Quantitative assessment was also performed to assess the ratio technique in detecting areas of known myelination (e.g., posterior limb of the internal capsule) and very low myelination (e.g., optic radiations) using linear regression analysis and the Michelson Contrast equation, a measure of luminance contrast intensity. RESULTS: The ratio image provided qualitative improvements in the ability to visualize regional variation in myelin content of neonates. Linear regression analysis demonstrated a significant inverse relationship between the ratio intensity values and ADC values in the posterior limb of the internal capsule and the optic radiations (R2 = 0.96 and P < 0.001). The Michelson Contrast equation showed that contrast differences between these two regions for the ratio images were 1.6 times higher than T1w, 2.6 times higher than T2w, and 1.8 times higher than ADC (all P < 0.001). Finally, the ratio improved visualization of the corticospinal tract, one of the earliest myelinated pathways. CONCLUSION: The T1w/T2w ratio accentuates contrast between myelinated and less myelinated structures and may enhance our diagnostic ability to detect myelination patterns in the neonatal brain. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage2 J. MAGN. RESON. IMAGING 2017;46:690-696.

Hypofractionated radiation therapy versus standard fractionated radiation therapy with concurrent temozolomide in elderly patients with newly diagnosed glioblastoma.

PURPOSE: Adjuvant hypofractionated radiation therapy (HRT) for elderly patients with newly diagnosed glioblastoma (GBM) is a reasonable option compared with standard fractionation radiation therapy (SFRT). Outcomes in patients receiving HRT in the presence of temozolomide (TMZ) compared with SFRT with TMZ are unclear. We examined HRT for GBM with TMZ in comparison to SFRT with TMZ. METHODS AND MATERIALS: We conducted a retrospective analysis of patients ≥60 years of age with newly diagnosed GBM who received SFRT or HRT from 1994 to 2014 in the postoperative setting. Inclusion criteria included SFRT (60 Gy/30 fractions or 59.4 Gy/33 fractions) versus HRT (40 Gy/15 fractions). RESULTS: In this cohort, 158 patients were treated with SFRT versus 26 with HRT. Median survival in patients receiving SFRT compared with HRT was 430 and 475 days (P = .550), respectively. Ninety-five percent of the SFRT patients received TMZ versus 100% of those treated with HRT. Patients receiving HRT were older (median, 72 vs 66 years). All HRT patients were treated with the intensity modulated radiation therapy (IMRT) technique versus SFRT, in which 57% had IMRT. Multivariate Cox regression showed decreased overall survival (OS) associated with patient age >70 (hazard ratio [HR], 1.84), lower Karnofsky performance status (HR, 5.25), biopsy versus surgical resection (HR, 4.18), radiation therapy planning technique 3- or 2-dimensional planning versus IMRT (HR, 1.91; HR, 3.40, respectively). Analysis restricted to patients receiving IMRT-based planning showed no difference in OS between HRT and SFRT. For patients receiving TMZ, there was no survival difference between those treated with HRT and those treated with SFRT. CONCLUSIONS: Elderly GBM patients receiving HRT and those receiving SFRT had similar OS. Subset analysis patients receiving concurrent TMZ showed no difference in OS between the HRT and SFRT groups.

A Modern Radiotherapy Series of Survival in Hispanic Patients with Glioblastoma.

BACKGROUND: Studies have shown racial differences in cancer outcomes. We investigate whether survival differences existed in Hispanic patients with glioblastoma (GBM) compared with other ethnicities from our modern radiotherapy series, because no study to date has focused on outcomes in this group after radiation therapy. METHODS: We retrospectively evaluated 428 patients diagnosed with GBM from 1996 to 2014 at our institution, divided into 4 groups based on self-report: white, black, Hispanic, and Asian/Indian. The primary outcome was overall survival. We analyzed differences in prognostic factors among the whole cohort compared with the Hispanic cohort alone. RESULTS: Baseline characteristics of the 4 racial groups were comparable. With a median follow-up of 387 days, no survival differences were seen by Kaplan-Meier analysis. Median overall survival for Hispanic patients was 355 days versus 450 days for the entire cohort. Factors significant for patient outcomes in the entire cohort differed slightly from those specific to Hispanic patients. Low Karnofsky Performance Status was significant on multivariate analysis in the whole population, but not in Hispanic patients. Extent of resection, recursive partitioning analysis class, and radiation therapy total dose were significant on multivariate analysis in both the whole population and Hispanic patients. CONCLUSIONS: We found that Hispanic patients with GBM had no difference in survival compared with other ethnicities in our cohort. Differences exist in factors associated with outcomes on single and multivariate analysis for Hispanic patients with GBM compared with the entire cohort. Additional studies focusing on Hispanic patients will aid in more personalized treatment approaches in this group.

Timing of Adjuvant Radiotherapy in Glioblastoma Patients: A Single-Institution Experience With More Than 400 Patients.

BACKGROUND: The standard of care for patients with newly diagnosed glioblastoma (GBM) is maximal safe resection followed by adjuvant radiation therapy (RT) and temozolomide (TMZ). OBJECTIVE: To investigate whether the timing of adjuvant RT after surgery affected outcome in patients with GBM. METHODS: We retrospectively reviewed all patients with a diagnosis of GBM at our institution. A total of 447 patients were included in our analysis. Patients were divided into 3 equal groups based on the interval between surgery and RT. The primary outcome was overall survival (OS). RESULTS: Patients who began RT less than 21 days after surgery tended to be older, have a lower a Karnofsky Performance Status score, and higher recursive partitioning analysis class. These patients were more likely to have undergone biopsy only and received 3-dimensional conformal RT or 2-dimensional RT. The median OS for patients who started RT less than 21 days after surgery, between 21 and 32 days after surgery, and more than 32 days after surgery was 374, 465, and 478 days, respectively (P = .004). On multivariate Cox regression analysis, Karnofsky Performance Status score lower than 70, undergoing biopsy only, recursive partitioning analysis classes IV and V/VI, use of less than 36 Gy RT, and lack of TMZ chemotherapy were predictors of worse OS. The interval between surgery and RT was not significantly associated with OS on multivariate analysis. CONCLUSION: Patients who begin RT less than 21 days after surgery tend to have worse prognostic factors than those who begin RT later. When accounting for significant covariates, the effect of timing between surgery and RT is not significant.

Opioids in the hypothalamic paraventricular nucleus stimulate ethanol intake.

BACKGROUND: Specialized hypothalamic systems that increase food intake might also increase ethanol intake. To test this possibility, morphine and receptor-specific opioid agonists were microinjected in the paraventricular nucleus (PVN) of rats that had learned to drink ethanol. To cross-validate the results, naloxone methiodide (m-naloxone), an opioid antagonist, was microinjected with the expectation that it would have the opposite effect of morphine and the specific opioid agonists. METHODS: Sprague-Dawley rats were trained, without sugar, to drink 4 or 7% ethanol and were then implanted with chronic brain cannulas aimed at the PVN. After recovery, those drinking 7% ethanol, with food and water available, were injected with 2 doses each of morphine or m-naloxone. To test for receptor specificity, 2 doses each of the mu-receptor agonist [D-Ala(2),N-Me-Phe(4),Gly(5)-ol]-Enkephalin (DAMGO), delta-receptor agonist D-Ala-Gly-Phe-Met-NH2 (DALA), or kappa-receptor agonist U-50,488H were injected. DAMGO was also tested in rats drinking 4% ethanol without food or water available. As an anatomical control for drug reflux, injections were made 2 mm dorsal to the PVN. RESULTS: A main result was a significant increase in ethanol intake induced by PVN injection of morphine. The opposite effect was produced by m-naloxone. The effects of morphine and m-naloxone were exclusively on intake of ethanol, even though food and water were freely available. In the analysis with specific receptor agonists, PVN injection of the delta-agonist DALA significantly increased 7% ethanol intake without affecting food or water intake. This is in contrast to the kappa-agonist U-50,488H, which decreased ethanol intake, and the mu-agonist DAMGO, which had no effect on ethanol intake in the presence or absence of food and water. In the anatomical control location 2 mm dorsal to the PVN, no drug caused any significant changes in ethanol, food, or water intake, providing evidence that the active site was close to the cannula tip. CONCLUSIONS: The delta-opioid receptor agonist in the PVN increased ethanol intake in strong preference over food and water, while the kappa-opioid agonist suppressed ethanol intake. Prior studies show that learning to drink ethanol stimulates PVN expression and production of the peptides enkephalin and dynorphin, which are endogenous agonists for the delta- and kappa-receptors, respectively. These results suggest that enkephalin via the delta-opioid system can function locally within a positive feedback circuit to cause ethanol intake to escalate and ultimately contribute to the abuse of ethanol. This is in contrast to dynorphin via the kappa-opioid system, which may act to counter this escalation. Naltrexone therapy for alcoholism may act, in part, by blocking the enkephalin-triggered positive feedback cycle.

Opioids in the nucleus accumbens stimulate ethanol intake.

The nucleus accumbens (NAc) participates in the control of both motivation and addiction. To test the possibility that opioids in the NAc can cause rats to select ethanol in preference to food, Sprague-Dawley rats with ethanol, food, and water available, were injected with two doses each of morphine, the mu-receptor agonist [D-Ala(2),N-Me-Phe(4),Gly(5)-ol]-Enkephalin (DAMGO), the delta-receptor agonist D-Ala-Gly-Phe-Met-NH2 (DALA), the k-receptor agonist (+/-)-trans-U-50488 methanesulfonate (U-50,488H), or the opioid antagonist naloxone methiodide (m-naloxone). As an anatomical control for drug reflux, injections were also made 2mm above the NAc. The main result was that morphine in the NAc significantly increased ethanol and food intake, whereas m-naloxone reduced ethanol intake without affecting food or water intake. Of the selective receptor agonists, DALA in the NAc increased ethanol intake in preference to food. This is in contrast to DAMGO, which stimulated food but not ethanol intake, and the k-agonist U-50,488H, which had no effect on intake. When injected in the anatomical control site 2mm dorsal to the NAc, the opioids had no effects on ethanol intake. These results demonstrate that ethanol intake produced by morphine in the NAc is driven in large part by the delta-receptor. In light of other studies showing ethanol intake to increase enkephalin expression in the NAc, the present finding of enkephalin-induced ethanol intake suggests the existence of a positive feedback loop that fosters alcohol abuse. Naltrexone therapy for alcohol abuse may then act, in part, in the NAc by blocking this opioid-triggered cycle of alcohol intake.