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| http://dx.doi.org/10.1097/JS9.0000000000001333 | DOI Listing |
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Matters arising: cost-utility and cost-effectiveness analysis of disease-modifying drugs of relapsing-remitting multiple sclerosis: a systematic review.
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Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy.
Background: In their interesting systematic review, Gallehzan et al. quoted our article Cost-utility analysis of teriflunomide in naïve vs. previously treated patients with relapsing-remitting multiple sclerosis (RRMS) in Italy.
View Article and Find Full Text PDFIntegrated Deep Learning Model for the Detection, Segmentation, and Morphologic Analysis of Intracranial Aneurysms Using CT Angiography.
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January 2025
From the Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, China (Y.Y., Z.C., X.N., J.W., H.H., S.W., Q.L.); China National Clinical Research Center for Neurologic Diseases, Beijing, China (Y.Y., Z.C., X.N., J.W., S.W., Q.L.); Unimed Technology (Beijing), Tsinghua Tongfang Science and Technology Mansion, Beijing, China (J.C., W.L.); Beijing Neurosurgical Institution, Capital Medical University, Beijing, China (Z.C., H.H.); and Department of Radiology, University of Washington, Seattle, Wash (C.Z.).
Purpose To develop a deep learning model for the morphologic measurement of unruptured intracranial aneurysms (UIAs) based on CT angiography (CTA) data and validate its performance using a multicenter dataset. Materials and Methods In this retrospective study, patients with CTA examinations, including those with and without UIAs, in a tertiary referral hospital from February 2018 to February 2021 were included as the training dataset. Patients with UIAs who underwent CTA at multiple centers between April 2021 and December 2022 were included as the multicenter external testing set.
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Misregistration between CT and PET in PET/CT is mainly caused by respiratory motion or irregular respiration during the CT scan in PET/CT. Other than repeat CT, repeat PET/CT, or data-driven gated (DDG) CT, there is no practical approach to mitigate the misregistration artifacts and subsequent CT attenuation correction (CTAC) of the PET data. DDG PET derives a respiratory motion model based on the multiple phases of PET images without hardware gating and it allows for a potential correction of the misregistration artifacts based on the respiratory motion model.
View Article and Find Full Text PDFIn Reply to the Letter to the Editor Regarding "Development of a Nomogram Model Based on Lactate-to-Albumin Ratio for Prognostic Prediction in Hospitalized Patients with Intracerebral Hemorrhage".
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School of Microelectronics and Data Science, Anhui University of Technology, Anhui, China; Anhui Provincial Joint Key Laboratory of Disciplines for Industrial Big Data Analysis and Intelligent Decision, Anhui, China. Electronic address:
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