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Purpose: To assess ChatGPT's ability as a resource for educating patients on various aspects of cardiac imaging, including diagnosis, imaging modalities, indications, interpretation of radiology reports, and management., Methods: 30 questions were posed to ChatGPT-3.5 and ChatGPT-4 three times in three separate chat sessions. Responses were scored as correct, incorrect, or clinically misleading categories by three observers-two board certified cardiologists and one board certified radiologist with cardiac imaging subspecialization. Consistency of responses across the three sessions was also evaluated. Final categorization was based on majority vote between at least two of the three observers., Results: ChatGPT-3.5 answered seventeen of twenty eight questions correctly (61 %) by majority vote. Twenty one of twenty eight questions were answered correctly (75 %) by ChatGPT-4 by majority vote. Majority vote for correctness was not achieved for two questions. Twenty six of thirty questions were answered consistently by ChatGPT-3.5 (87 %). Twenty nine of thirty questions were answered consistently by ChatGPT-4 (97 %). ChatGPT-3.5 had both consistent and correct responses to seventeen of twenty eight questions (61 %). ChatGPT-4 had both consistent and correct responses to twenty of twenty eight questions (71 %)., Conclusion: ChatGPT-4 had overall better performance than ChatGTP-3.5 when answering cardiac imaging questions with regard to correctness and consistency of responses. While both ChatGPT-3.5 and ChatGPT-4 answers over half of cardiac imaging questions correctly, inaccurate, clinically misleading and inconsistent responses suggest the need for further refinement before its application for educating patients about cardiac imaging., Competing Interests: Declaration of competing interest Lorenzo Nardo, MD PhD, is the principal investigator (PI) of a service agreement with United Imaging Healthcare, site PI of clinical trials supported by Novartis Pharmaceuticals Corporation, PI of a clinical trial supported by Telix Pharmaceuticals, PI of a clinical trial supported by Lantheus Medical Imaging, and PI of a clinical trial supported by GE Healthcare. None of the other authors have any disclosures., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Standard follow-up care for patients with high-grade glioma (HGG) involves routine surveillance imaging to detect disease progression, assess treatment response, and monitor clinical symptoms. Although logical in nature, evidence supporting this practice is limited. We hypothesize patients with tumor recurrence detected on routine surveillance imaging will experience superior outcomes relative to symptomatic detection, using measures of survival and postrecurrence neurologic function., Methods: Adult patients receiving treatment for HGG at our institution from 2004 to 2018 were identified, and data including tumor characteristics, imaging results, neurologic status, and survival were extracted from the medical records of patients meeting inclusion criteria. All participants were followed for a minimum of 12 months, or for survival duration. Survival and neurologic function differences were assessed using log rank and 2-sample t tests with 2-sided 0.05 alpha level of significance., Results: Of the 74 patients meeting inclusion criteria, 47 (63.5%) had recurrence detected via routine surveillance imaging, and 27 (36.5%) had symptomatic detection outside of the surveillance schedule. Neither median overall survival (14.8 months for surveillance and 15.7 months for symptomatic; P = 0.600) nor postrecurrence neurologic function (assessed by Karnofsky Performance Scale Index and Eastern Cooperative Oncology Group) differed between the surveillance and symptomatic detection groups (P = 0.699 and P = 0.908, respectively)., Conclusions: Recurrence detection occurring via routine surveillance imaging did not yield superior patient outcomes relative to symptomatic detection occurring outside of the standard surveillance schedule in patients with HGG. Further evaluation of surveillance imaging and alternative follow-up methods for this patient population may be warranted., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Neurofibromatosis type 1 (NF1) is a common neurogenetic disorder in which affected children and adults are predisposed to the development of benign and malignant nervous system tumors. Caused by a germline mutation in the NF1 tumor suppressor gene, individuals with NF1 are prone to optic gliomas, malignant gliomas, neurofibromas, and malignant peripheral nerve sheath tumors, as well as behavioral, cognitive, motor, bone, cardiac, and pigmentary abnormalities. Although NF1 is a classic monogenic syndrome, the clinical features of the disorder and their impact on patient morbidity are variable, even within individuals who bear the same germline NF1 gene mutation. As such, NF1 affords unique opportunities to define the factors that contribute to disease heterogeneity and to develop therapies personalized to a given individual (precision medicine). This review highlights the clinical features of NF1 and the use of genetically engineered mouse models to define the molecular and cellular pathogenesis of NF1-associated nervous system tumors.

Neurofibromatosis type 1 is a common neurogenetic disorder characterized by significant clinical variability. As such, numerous studies have focused on identifying clinical, radiographic, or molecular biomarkers that predict the occurrence or progression of specific clinical features in individuals with neurofibromatosis type 1. One of these clinical biomarkers, macrocephaly, has been proposed as a prognostic factor for optic pathway glioma development. In the current study, the authors demonstrate that macrocephaly is not associated with the development of these brain tumors or the need to institute treatment for clinical progression. These findings suggest that macrocephaly is not a robust biomarker of optic pathway glioma formation or progression in children with neurofibromatosis type 1., (© The Author(s) 2016.)

Background: Recent policy initiatives in Baltimore City, MD significantly reduced access disparities between methadone and buprenorphine in the publicly funded treatment sector., Objectives: This study examines reasons for choosing buprenorphine over methadone among patients with access to both medications., Method: This study was embedded within a larger clinical trial conducted at two outpatient substance abuse treatment programs offering buprenorphine. Qualitative and quantitative data on treatment choice were collected for new patients starting buprenorphine treatment (n = 80). The sample consisted of predominantly urban African American (94%) heroin users who had prior experience with non-prescribed street buprenorphine (85%), and opioid agonist treatment (68%). Qualitative data were transcribed and coded for themes, while quantitative data were analyzed using descriptive and bivariate statistics., Results: Participants typically conveyed their choice of buprenorphine treatment as a decision against methadone. Buprenorphine was perceived as a helpful medication while methadone was perceived as a harmful narcotic with multiple unwanted physical effects. Positive experiences with non-prescribed "street buprenorphine" were a central factor in participants' decisions to seek buprenorphine treatment., Conclusions: Differences in service structure between methadone and buprenorphine did not strongly influence treatment-seeking decisions in this sample. Personal experiences with medications and the street narrative surrounding them play an important role in treatment selection decisions., Scientific Significance: This study characterizes important decision factors that underlie patients' selection of buprenorphine over methadone treatment., (Copyright © American Academy of Addiction Psychiatry.)