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MRI-based deep learning radiomics to differentiate dual-phenotype hepatocellular carcinoma from HCC and intrahepatic cholangiocarcinoma: a multicenter study.
Insights Imaging
January 2025
Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Objectives: To develop and validate radiomics and deep learning models based on contrast-enhanced MRI (CE-MRI) for differentiating dual-phenotype hepatocellular carcinoma (DPHCC) from HCC and intrahepatic cholangiocarcinoma (ICC).
Methods: Our study consisted of 381 patients from four centers with 138 HCCs, 122 DPHCCs, and 121 ICCs (244 for training and 62 for internal tests, centers 1 and 2; 75 for external tests, centers 3 and 4). Radiomics, deep transfer learning (DTL), and fusion models based on CE-MRI were established for differential diagnosis, respectively, and their diagnostic performances were compared using the confusion matrix and area under the receiver operating characteristic (ROC) curve (AUC).
TERT-TP53 mutations: a novel biomarker pair for hepatocellular carcinoma recurrence and prognosis.
Sci Rep
January 2025
Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China.
Hepatocellular carcinoma (HCC) is the most prevalent form of liver cancer, and ranks among the most lethal malignancies globally, primarily due to its high rates of recurrence and metastasis. Despite the urgency, no reliable biomarkers currently exist for predicting tumor recurrence in HCC. Telomerase reverse transcriptase (TERT) promoter mutations (TERTpm) and cellular tumor antigen p53 mutations (TP53m) have been frequently documented in HCC, but their combined clinical significance remains undefined.
View Article and Find Full Text PDFLeveraging survival analysis and machine learning for accurate prediction of breast cancer recurrence and metastasis.
Sci Rep
January 2025
Center for Informatics Science (CIS), School of Information Technology and Computer Science, Nile University, 26th of July Corridor, Sheikh Zayed City, Giza, 12588, Egypt.
Breast cancer, with its high incidence and mortality globally, necessitates early prediction of local and distant recurrence to improve treatment outcomes. This study develops and validates predictive models for breast cancer recurrence and metastasis using Recurrence-Free Survival Analysis and machine learning techniques. We merged datasets from the Molecular Taxonomy of Breast Cancer International Consortium, Memorial Sloan Kettering Cancer Center, Duke University, and the SEER program, creating a comprehensive dataset of 272, 252 rows and 23 columns.
View Article and Find Full Text PDFSystemic therapy for patients with metastatic pheochromocytoma and paraganglioma.
Best Pract Res Clin Endocrinol Metab
January 2025
Department of Endocrine Neoplasia and HormonalDisorders, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA. Electronic address:
Pheochromocytomas and paragangliomas are rare neuroendocrine tumors derived from the paraganglia. These tumors frequently secrete excessive amounts of catecholamines leading to cardiovascular and gastrointestinal complications. While all pheochromocytomas and paragangliomas possess the potential for metastasis, actual metastatic occurrences are observed in approximately one third of cases.
View Article and Find Full Text PDFEnhanced bile acid detection and analysis in liver fibrosis with pseudo-targeted metabolomics.
J Pharm Biomed Anal
January 2025
State Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine, The MOE Key Laboratory of Standardization of Chinese Medicines, the SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines and Shanghai Key Laboratory of Compound Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China. Electronic address:
Bile acids (BAs) are essential signaling molecules that engage in host and gut microbial metabolism, playing a crucial role in maintaining organismal stability. Liquid chromatography-mass spectrometry (LC-MS) is a widely employed technique for metabolite analysis in biological samples due to its high sensitivity, excellent specificity, and low detection limits. This method has emerged as the mainstream approach for the detection and analysis of BAs.
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