e. To determine whether the radiomic features of F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) contribute to prognosis prediction in primary gastric diffuse large B-cell lymphoma (PG-DLBCL) patients. . This retrospective study included 35 PG-DLBCL patients who underwent PET/CT scans at West China Hospital before curative treatment. The volume of interest (VOI) was drawn around the tumor, and radiomic analysis of the PET and CT images, within the same VOI, was conducted. The metabolic and textural features of PET and CT images were evaluated. Correlations of the extracted features with the overall survival (OS) and progression-free survival (PFS) were evaluated. Univariate and multivariate analyses were conducted to assess the prognostic value of the radiomic parameters. . In the univariate model, many of the textural features, including kurtosis and volume, extracted from the PET and CT datasets were significantly associated with survival (5 for OS and 7 for PFS (PET); 7 for OS and 14 for PFS (CT)). Multivariate analysis identified kurtosis (hazard ratio (HR): 28.685, 95% confidence interval (CI): 2.067-398.152, =0.012), metabolic tumor volume (MTV) (HR: 26.152, 95% CI: 2.089-327.392, =0.011), and gray-level nonuniformity (GLNU) (HR: 14.642, 95% CI: 2.661-80.549, =0.002) in PET and sphericity (HR: 11.390, 95% CI: 1.360-95.371, =0.025) and kurtosis (HR: 11.791, 95% CI: 1.583-87.808, =0.016), gray-level nonuniformity (GLNU) (HR: 6.934, 95% CI: 1.069-44.981, =0.042), and high gray-level zone emphasis (HGZE) (HR: 9.805, 95% CI: 1.359-70.747, =0.024) in CT as independent prognostic factors. . F-FDG PET/CT radiomic features are potentially useful for survival prediction in PG-DLBCL patients. However, studies with larger cohorts are needed to confirm the clinical prognostication of these parameters.
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http://dx.doi.org/10.1155/2019/5963607 | DOI Listing |
PLoS One
January 2025
Department of Geriatric Medicine, the Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, China.
Objective: To develop a predictive model for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) through radiomics analysis, integrating data from both enhanced computed tomography (CT) and magnetic resonance imaging (MRI).
Methods: A retrospective analysis was conducted on 93 HCC patients who underwent partial hepatectomy. The gold standard for MVI was based on the histopathological diagnosis of the tissue.
Radiol Med
January 2025
Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
Purpose: Bodyweight loss is commonly found in Nasopharyngeal Carcinoma patients during Concurrent Chemo-radiotherapy (CCRT) and has implications for treatment decisions. However, the prognostic value of this weight loss remains uncertain. We addressed it by proposing a novel index Weight Censorial Score (WCS) that characterizes the patient-specific CCRT response on actual to estimated weight loss.
View Article and Find Full Text PDFPurpose: We hypothesised that applying radiomics to [F]PSMA-1007 PET/CT images could help distinguish Unspecific Bone Uptakes (UBUs) from bone metastases in prostate cancer (PCa) patients. We compared the performance of radiomic features to human visual interpretation.
Materials And Methods: We retrospectively analysed 102 hormone-sensitive PCa patients who underwent [F]PSMA-1007 PET/CT and exhibited at least one focal bone uptake with known clinical follow-up (reference standard).
Front Cardiovasc Med
January 2025
Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Objectives: To evaluate the feasibility of utilizing cardiac computer tomography (CT) images for extracting the radiomic features of the myocardium at the junction between the left atrial appendage (LAA) and the left atrium (LA) in patients with atrial fibrillation (AF) and to evaluate its asscociation with the risk of AF.
Methods: A retrospective analysis was conducted on 82 cases of AF and 56 cases in the control group who underwent cardiac CT at our hospital from May 2022 to May 2023, with recorded clinical information. The morphological parameters of the LAA were measured.
Front Neurol
January 2025
Department of Radiology, Affiliated Hospital 6 of Nantong University, Yancheng Third People's Hospital, Yancheng, Jiangsu, China.
Introduction: Early prognosis prediction of acute ischemic stroke (AIS) can support clinicians in choosing personalized treatment plans. The aim of this study is to develop a machine learning (ML) model that uses multiple post-labeling delay times (multi-PLD) arterial spin labeling (ASL) radiomics features to achieve early and precise prediction of AIS prognosis.
Methods: This study enrolled 102 AIS patients admitted between December 2020 and September 2024.
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