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Fully automated segmentation and classification of renal tumors on CT scans via machine learning.
BMC Cancer
January 2025
Department of Urology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea.
Background: To develop and test the performance of a fully automated system for classifying renal tumor subtypes via deep machine learning for automated segmentation and classification.
Materials And Methods: The model was developed using computed tomography (CT) images of pathologically proven renal tumors collected from a prospective cohort at a medical center between March 2016 and December 2020. A total of 561 renal tumors were included: 233 clear cell renal cell carcinomas (RCCs), 82 papillary RCCs, 74 chromophobe RCCs, and 172 angiomyolipomas.
Integration of MRI radiomics and clinical data for preoperative prediction of vascular invasion in breast cancer: A deep learning approach.
Magn Reson Imaging
January 2025
GE Healthcare, Guangzhou 510623, China.
Background: Accurate preoperative prediction of vascular invasion in breast cancer is crucial for surgical planning and patient management. MRI radiomics has shown promise in enhancing diagnostic precision. This study aims to evaluate the effectiveness of integrating MRI radiomic features with clinical data using a deep learning approach to predict vascular invasion in breast cancer patients.
View Article and Find Full Text PDFThe naples prognostic score as a new predictor for heart failure: A cross-sectional study.
Heart Lung
January 2025
Henan University, 379 North Section of Mingli Road, Zhengzhou, China.
Background: The Naples prognostic score (NPS), a novel nutritional and inflammatory index, holds great promise for predicting the prognosis of heart failure (HF), but research on its association with HF outcomes is limited.
Objective: To analyze the relationship between the NPS and the incidence rate and long-term prognosis of HF.
Methods: Participants from the National Health and Nutrition Examination Survey (NHANES) data were allocated into three groups (group 0 (the NPS=0), group 1-2 (the NPS=1-2), and group 3-4 (the NPS=3-4)) based on the NPS level.
Early MRI Can Predict the Indication for Surgery in Brachial Plexus Birth Injury: Results of the NAPTIME Study.
J Bone Joint Surg Am
January 2025
Shriners Children's Northern California, Sacramento, California.
Background: Magnetic resonance imaging (MRI) has not been routinely used for infants with brachial plexus birth injury (BPBI); instead, the decision to operate is based on the trajectory of clinical recovery by 6 months of age. The aim of this study was to develop an MRI protocol that can be performed without sedation or contrast in order to identify infants who would benefit from surgery at an earlier age than the age at which that decision could be made clinically.
Methods: This prospective multicenter NAPTIME (Non-Anesthetized Plexus Technique for Infant MRI Evaluation) study included infants aged 28 to 120 days with BPBI from 3 tertiary care centers.
Replication-Poison Treatment in BRCA1-Deficient Breast Cancer Causes MRE11 Over-Resection that Induces Single-Stranded DNA Accumulation and Mitotic Catastrophe.
Cancer Res
January 2025
INSERM U1194, Montpellier Cedex 05, Occitanie, France.
BRCA1 deficiency is observed in approximately 25% of triple-negative breast cancer (TNBC). BRCA1, a key player of homologous recombination (HR) repair, is also involved in stalled DNA replication fork protection and repair. Here, we investigated the sensitivity of BRCA1-deficient TNBC models to the frequently used replication chain terminator gemcitabine, which does not directly induce DNA breaks.
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