A5101453201- Intracerebral and Subarachnoid Hemorrhage Research
- Radiomics and Machine Learning in Medical Imaging
- Advanced X-ray and CT Imaging
- MRI in cancer diagnosis
- Acute Ischemic Stroke Management
- Nuclear Physics and Applications
- Pancreatic and Hepatic Oncology Research
- Radiation Dose and Imaging
- Thyroid Cancer Diagnosis and Treatment
- Hepatocellular Carcinoma Treatment and Prognosis
- Cancer, Hypoxia, and Metabolism
- Machine Learning in Materials Science
- Machine Learning in Healthcare
- Medical Imaging Techniques and Applications
First People's Hospital of Chongqing
2022-2024
Second Affiliated Hospital of Chongqing Medical University
2020-2022
Dalian Medical University
2020-2022
Chongqing Medical University
2020-2022
To determine whether noncontrast computed tomography (NCCT) models based on multivariable, radiomics features, and machine learning (ML) algorithms could further improve the discrimination of early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (sICH). We retrospectively reviewed 261 sICH who underwent initial NCCT within 6 hours ictus follow-up CT 24 after NCCT, between April 2011 March 2019. The clinical characteristics, imaging signs features extracted from...
The misdiagnosis of papillary thyroid microcarcinoma (PTMC) and micronodular goiter (MNG) may lead to overtreatment unnecessary medical expenditure by patients. This study developed validated a dual-energy computed tomography (DECT)-based nomogram for the preoperative differential diagnosis PTMC MNG.This retrospective analyzed data 366 pathologically confirmed micronodules, which 183 were PTMCs MNGs, from 326 patients who underwent DECT examinations. cohort was divided into training (n=256)...
Objective: To derive and validate a location-specific radiomics score (Rad-score) based on noncontrast computed tomography for predicting poor deep lobar spontaneous intracerebral hemorrhage (SICH) outcome. Methods: In total, 494 SICH patients from multiple centers were retrospectively reviewed. Poor outcome was considered mRS 3-6 at 6 months. The Rad-score derived using optimal features. cut-offs outcomes identified receiver operating characteristic curve analysis. Univariable multivariable...
To investigate the potential value of a contrast enhanced computed tomography (CECT)-based radiological-radiomics nomogram combining lymph node (LN) radiomics signature and LNs' radiological features for preoperative detection LN metastasis in patients with pancreatic ductal adenocarcinoma (PDAC).In this retrospective study, 196 LNs 61 PDAC were enrolled divided into training (137 LNs) validation (59 cohorts. Radiomic extracted from portal venous phase images LNs. The least absolute...
Thyroid nodules (TNs) cytologically defined as category Bethesda III and IV pose a major diagnostic challenge before surgery, demanding new methods to reduce unnecessary thyroid lobectomies for patients with benign TNs. This study aimed assess whether model combining dual-energy computed tomography (DECT) quantitative parameters morphologic features could reliably differentiate between malignant lesions in
There is no unified scope for regional lymph node (LN) dissection in patients with pancreatic ductal adenocarcinoma (PDAC). Incomplete LN can lead to postoperative recurrence, while blind expansion of the significantly increases perioperative risk without prolonging overall survival. We aimed establish a noninvasive visualization tool based on dual-layer detector spectral computed tomography (DLCT) predict probability metastasis PDAC.
The value of Liver Imaging Reporting and Data System (LI-RADS) radiological features tumor three-dimensional volumetric quantification in preoperative magnetic resonance imaging (MRI) for predicting the vessels encapsulating clusters (VETC) pattern solitary hepatocellular carcinoma (HCC) is unknown. This study aimed to assess these indicators VETC HCC.