Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1111/j.1540-8183.2002.tb01114.x | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Development and Validation of an AI-Based Multimodal Model for Pathological Staging of Gastric Cancer Using CT and Endoscopic Images.
Acad Radiol
January 2025
Guangxi Medical University, Nanning, Guangxi 530021, China (C.Z., D.H., B.W., S.W., Y.S., X.W.); Guangxi Key Laboratory of Enhanced Recovery After Surgery for Gastrointestinal Cancer, Nanning, Guangxi 530021, China (C.Z., D.H., B.W., S.W., Y.S., X.W.); Department of Gastrointestinal Gland Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China (D.H., X.W.). Electronic address:
Rationale And Objectives: Accurate preoperative pathological staging of gastric cancer is crucial for optimal treatment selection and improved patient outcomes. Traditional imaging methods such as CT and endoscopy have limitations in staging accuracy.
Methods: This retrospective study included 691 gastric cancer patients treated from March 2017 to March 2024.
Predicting the Invasiveness of Mixed Ground-Glass Nodules Based on Spectral Computed Tomography-Derived Parameters and Tumor Abnormal Protein Levels: Development and Validation of a Model.
Acad Radiol
January 2025
Department of Radiology, Shengjing Hospital of China Medical University, China (Y.Y., T.W.). Electronic address:
Rationale And Objectives: Mixed ground-glass nodules (mGGNs) are highly malignant and common nonspecific lung imaging findings. This study aimed to explore whether combining quantitative and qualitative spectral dual-layer detector-based computed tomography (SDCT)-derived parameters with serological tumor abnormal proteins (TAPs) and thymidine kinase 1 (TK1) expression enhances invasive mGGN diagnostic efficacy and to develop a joint diagnostic model.
Materials And Methods: This prospective study included patients with mGGNs undergoing preoperative triple-phase contrast-enhanced SDCT with TAP and TK1 tests.
Radiomics and Deep Learning Model for Benign and Malignant Soft Tissue Tumors Differentiation of Extremities and Trunk.
Acad Radiol
January 2025
Department of Radiology, Southeast University Zhongda Hospital, No. 87 Dingjiaqiao Road, Gulou District, Nanjing, Jiangsu Province, China (M.Y., J.J.). Electronic address:
Rationale And Objectives: To develop radiomics and deep learning models for differentiating malignant and benign soft tissue tumors (STTs) preoperatively based on fat saturation T2-weighted imaging (FS-T2WI) of patients.
Materials And Methods: Data of 115 patients with STTs of extremities and trunk were collected from our hospital as the training set, and data of other 70 patients were collected from another center as the external validation set. Outlined Regions of interest included the intratumor and the peritumor region extending outward by 5 mm, then the corresponding radiomics features were extracted respectively.
An Automatic Deep-Radiomics Framework for Prostate Cancer Diagnosis and Stratification in Patients with Serum Prostate-Specific Antigen of 4.0-10.0 ng/mL: A Multicenter Retrospective Study.
Acad Radiol
January 2025
Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China (B.Z., F.M., X.S., S.L., Q.W.); Department of Urology, Guangdong Provincial People's Hospital, Southern Medical University, Guangzhou, Guangdong 510080, China (Q.W.). Electronic address:
Rationale And Objectives: To develop an automatic deep-radiomics framework that diagnoses and stratifies prostate cancer in patients with prostate-specific antigen (PSA) levels between 4 and 10 ng/mL.
Materials And Methods: A total of 1124 patients with histological results and PSA levels between 4 and 10 ng/mL were enrolled from one public dataset and two local institutions. An nnUNet was trained for prostate masks, and a feature extraction module identified suspicious lesion masks.
Analysis of the Clinical Characteristics and Ultrasonographic Features in 141 Cases of Cystic Neutrophilic Granulomatous Mastitis.
Acad Radiol
January 2025
Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing 100010, PR China (M.W., Y.L., D.Z., N.F., Y.W., M.L., H.Z.).
Rationale And Objectives: To summarize the clinical features and ultrasonic characteristics of patients with cystic neutrophilic granulomatous mastitis (CNGM), and to enhance the understanding of CNGM in clinical practice.
Materials And Methods: This study retrospectively analyzed the demographic data, clinical symptoms, and ultrasonic characteristics of 141 patients diagnosed with CNGM through pathological examination. This study was approved by the Medical Ethical Committee of Beijing Hospital of Traditional Chinese Medicine (2023BL02-054-01).
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!