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Deep-Learning Generated Synthetic Material Decomposition Images Based on Single-Energy CT to Differentiate Intracranial Hemorrhage and Contrast Staining Within 24 Hours After Endovascular Thrombectomy.
CNS Neurosci Ther
January 2025
Department of Radiology, Affiliated Hangzhou First People's Hospital, Westlake University School of Medicine, Hangzhou, China.
Aims: To develop a transformer-based generative adversarial network (trans-GAN) that can generate synthetic material decomposition images from single-energy CT (SECT) for real-time detection of intracranial hemorrhage (ICH) after endovascular thrombectomy.
Materials: We retrospectively collected data from two hospitals, consisting of 237 dual-energy CT (DECT) scans, including matched iodine overlay maps, virtual noncontrast, and simulated SECT images. These scans were randomly divided into a training set (n = 190) and an internal validation set (n = 47) in a 4:1 ratio based on the proportion of ICH.
Diagnostic Accuracy of Hyperdense Artery Sign in Early Detection of Middle Cerebral Artery Infarction: A Cross-Sectional Validation Study.
Ann Neurosci
October 2024
Department of Radiology, Aga Khan University Hospital, Stadium Road, Karachi, Pakistan.
Background: Hyperdense middle cerebral artery sign (HMCAS) on a non-enhanced multidetector computed tomography (MDCT) scan is considered an important radiological marker in detecting acute arterial thrombotic occlusion, and it is one of the earliest signs of ischemic cerebrovascular accident (CVA). This finding has been observed within 90 min of symptom onset. Modern approaches to patients with cerebral infarction emphasize early diagnosis and management.
View Article and Find Full Text PDFA novel nomogram based on the patient's clinical data and CT signs to predict poor outcomes in AIS patients.
PeerJ
January 2025
Department of Medical Imaging, Guangzhou Hospital of Integrated Traditional and Western Medicine, Guangzhou, China.
Background: The 2019 American Heart Association/American Stroke Association (AHA/ASA) guidelines strongly advise using non-contrast CT (NCCT) of the head as a mandatory test for all patients with suspected acute ischemic stroke (AIS) due to CT's advantages of affordability and speed of imaging. Therefore, our objective was to combine patient clinical data with head CT signs to create a nomogram to predict poor outcomes in AIS patients.
Methods: A retrospective analysis was conducted on 161 patients with acute ischemic stroke who underwent mechanical thrombectomy at the Guangzhou Hospital of Integrated Traditional and Western Medicine from January 2019 to June 2023.
The value of radiomics-based hyperdense middle cerebral artery sign in predicting hemorrhagic transformation in acute ischemic stroke patients undergoing endovascular treatment.
Front Neurol
December 2024
Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Objective: To establish and validate a model based on hyperdense middle cerebral artery sign (HMCAS) radiomics features for predicting hemorrhagic transformation (HT) in patients with acute ischemic stroke (AIS) after endovascular treatment (EVT).
Methods: Patients with AIS who presented with HMCAS on non-contrast computed tomography (NCCT) at admission and underwent EVT at three comprehensive hospitals between June 2020 and January 2024 were recruited for this retrospective study. A radiomics model was constructed using the HMCAS radiomics features most strongly associated with HT.
Mobile photon counting detector CT with multi material decomposition methods for neuroimaging of patients in intensive care unit.
Sci Rep
December 2024
Health & Medical Equipment Business, Samsung Electronics Co., Ltd, 8, Gumi-ro, Bundang-gu, Seongnam- si, 13638, Gyeonggi-do, Republic of Korea.
The photon-counting detector computed tomography (PCD-CT) is a promising new technology that provides more spectral information in medical imaging. PCD-CT enables bedside imaging in the neuro intensive care unit (neuro ICU) for patients with life-threatening conditions such as brain hemorrhage and ischemic stroke. The primary purpose of this study is to evaluate a multi-material decomposition algorithm available on PCD-CT, dubbed MD Plus, to differentiate between contrast agent and hemorrhage in hyperdense lesions.
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