Publications by authors named "Mingye Xie"
Article Synopsis
- - The study aimed to predict bone marrow metastasis in neuroblastoma by analyzing radiomics features from contrast-enhanced CT scans using machine learning techniques.
- - A total of 345 patients were examined, and after analyzing 1409 features, a predictive model was created using 16 key features, primarily related to texture, achieving high accuracy and sensitivity in identifying metastasis.
- - The findings suggest that specific radiomics features from CT images are linked to bone marrow metastasis in neuroblastoma, indicating their potential as new biomarkers for diagnosis.
Article Synopsis
- Lymphoma is a prevalent cancer in children, and distinguishing between its subtypes, like Burkitt lymphoma (BL) and lymphoblastic lymphoma, is challenging due to similar CT imaging features.
- This study aimed to create a model that uses spleen radiomic features extracted from CT images to noninvasively differentiate between these two subtypes in pediatric patients.
- The developed fusion models showed better performance than individual classifiers, with the SVM_4 model achieving the highest diagnostic accuracy, indicating its potential for clinical application.
Objectives: To retrospectively investigate the impact of pre-treatment Extracellular Volume Fraction (ECV) measured by Computed Tomography (CT) on the response of primary lesions to preoperative chemotherapy in abdominal neuroblastoma.
Methods: A total of seventy-five patients with abdominal neuroblastoma were retrospectively included in the study. The regions of interest for the primary lesion and aorta were determined on unenhanced and equilibrium phase CT images before treatment, and their average CT values were measured.
Purpose: To compare the performance of radiomics from contrast-enhanced computed tomography (CECT) and non-contrast magnetic resonance imaging (MRI) in assessing cellular behavior in pediatric peripheral neuroblastic tumors (PNTs).
Materials And Methods: A retrospective analysis of 81 PNT patients who underwent venous phase CECT, T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI) scans was conducted. The patients were classified into neuroblastoma and ganglioneuroblastoma/ganglioneuroma based on their pathological subtypes.
Background: Diffuse large B-cell lymphoma (DLBCL) and Hodgkin's lymphoma (HL) are two completely different pathologic subtypes of lymphoma with distinctly different clinical presentations and treatment options. Thus, accurately differentiating between the two subtypes has important clinical implications. This study aimed to construct a radiomics model capable of distinguishing between DLBCL and HL based on enhanced computed tomography (CT) for the non-invasive diagnosis of lymphoma subtypes.
View Article and Find Full Text PDFObjective: This research aimed to investigate the feasibility of utilizing dual-energy CT virtual monoenergetic images (VMI) with prospective electrocardiogram (ECG) gating for reducing radiation and contrast agent doses in pediatric patients with congenital heart disease (CHD).
Methods: There were 100 pediatric patients with CHD included in this study. Group A (n = 50) underwent dual-energy scanning with prospective ECG-gating, and group B (n = 50) underwent conventional scanning with retrospective ECG-gating.
Background And Purpose: Myelin oligodendrocyte glycoprotein antibody-associated disorders (MOGAD) have a higher prevalence among children. For children undergoing the initial manifestation of MOGAD, prompt diagnosis has paramount importance. This study assessed the performance of multiparameter MRI-based radiomics in distinguishing patients with and without MOGAD with idiopathic inflammatory demyelinating diseases.
View Article and Find Full Text PDFRationale And Objectives: To identify ultra-high-risk (UHR) neuroblastoma patients who experienced disease-related mortality within 18 months of diagnosis within the high-risk cohort using computed tomography (CT)-based radiomics analysis.
Materials And Methods: A retrospective analysis was conducted on 105 high-risk neuroblastoma patients, divided into a training set (n = 74) and a test set (n = 31). Radiomics features were extracted and selected from arterial phase CT images, and an optimal radiomics signature was established using the support vector machine algorithm.
Purpose: To retrospectively investigate the correlations between contrast-enhanced CT (CECT)-measured extracellular volume fraction (fECV) and histopathological features, as well as MYCN amplification status, in abdominal neuroblastoma.
Materials And Methods: One hundred and forty-one patients with abdominal neuroblastoma who underwent CECT scanning were retrospectively enrolled. Calculation of fECV involved the measurement of CT values within regions of interest located within the neuroblastoma and aorta on both non-contrast-enhanced CT and equilibrium CECT.
Purpose: To predict the International Neuroblastoma Pathology Classification (INPC) in neuroblastoma using a computed tomography (CT)-based radiomics approach.
Methods: We enrolled 297 patients with neuroblastoma retrospectively and divided them into a training group (n = 208) and a testing group (n = 89). To balance the classes in the training group, a Synthetic Minority Over-sampling Technique was applied.
Purpose: To examine the potential of whole-tumor radiomics analysis of T2-weighted imaging (T2WI) in differentiating neuroblastoma (NB) from ganglioneuroblastoma/ganglioneuroma (GNB/GN) in children.
Materials And Methods: This study included 102 children with peripheral neuroblastic tumors, comprising 47 NB patients and 55 GNB/GN patients, which were randomly divided into a training group (n = 72) and a test group (n = 30). Radiomics features were extracted from T2WI images, and feature dimensionality reduction was applied.
Background: To develop and validate a radiomics signature based on computed tomography (CT) for identifying high-risk neuroblastomas.
Procedure: This retrospective study included 339 patients with neuroblastomas, who were classified into high-risk and non-high-risk groups according to the revised Children's Oncology Group classification system. These patients were then randomly divided into a training set (n = 237) and a testing set (n = 102).
Rationale And Objectives: This research examines the prevalence and occurrence of intraoperative vascular injuries in abdominal or pelvic neuroblastomas. It also investigates the correlations between preoperative radiographic vascular involvement on computed tomography (CT) and intraoperative vascular injuries in abdominal or pelvic neuroblastomas.
Materials And Methods: This study enrolled 297 patients with abdominal or pelvic neuroblastomas.