Purpose: The purpose of this study is to explore the application value of CDFI and SMI combined with serological markers in distinguishing benign and malignant thyroid nodules.
Method: A total of 192 patients with thyroid nodules admitted to our hospital from July 2019 to December 2020 were selected as subjects. Color Doppler blood flow imaging (CDFI) and supermicro blood flow imaging (SMI) methods are used to detect the blood flow of patients and the levels of serum thyroglobulin antibody (TgAb), thyroid peroxidase antibody (TPOAb), and thyroid stimulating hormone (TSH). The receiver operating characteristic curve (ROC curve) was used to observe the sensitivity and specificity of serological markers for distinguishing benign and malignant thyroid nodules, and combined with CDFI and SMI to observe the sensitivity and specificity for distinguishing benign and malignant thyroid nodules.
Results: The levels of TgAb, TPOAb and TSH in benign thyroid nodules were lower than those of the malignant group, and the difference was statistically significant (P < 0.01). There was no statistically significant difference between benign and malignant thyroid nodules in the presence or absence of the capsule and the presence or absence of vocal halo (P > 0.05), while the differences in the nodule morphology, boundary, internal echo and internal calcification were statistically significant (P < 0.01).
Conclusion: CDFI and SMI combined with serological index detection have higher value in the differential diagnosis of thyroid cancer, which can significantly improve the sensitivity and specificity of differential diagnosis.
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http://dx.doi.org/10.1007/s12094-022-02880-1 | DOI Listing |
Cancer Manag Res
January 2025
Department of Pancreatic and Gastric Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People's Republic of China.
Introduction: Early diagnosis is crucial for improving the prognosis of patients with gastric cancer (GC). However, the currently used biomarkers for diagnosing GC have limited sensitivity and specificity. This study aimed to develop a novel diagnostic model based on miRNAs from glycosylated extracellular vesicles and evaluate its effectiveness in diagnosing gastric cancer.
View Article and Find Full Text PDFJ Multidiscip Healthc
January 2025
Department of Nuclear Medicine, The First People's Hospital of Yunnan Province, the Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, 650032, People's Republic of China.
Objective: This study aimed to explore the value of a radiomic nomogram based on contrast-enhanced computed tomography (CECT) for differentiating benign and malignant solid-containing renal masses.
Materials And Methods: A total of 122 patients with pathologically confirmed benign (n=47) or malignant (n=75) solid-containing renal masses were enrolled in this study. Radiomic features were extracted from the arterial, venous and delayed phases and further analysed by dimensionality reduction and selection.
Hepat Oncol
December 2024
Advanced Imaging Research Center, University of Texas Southwestern Medical Center at Dallas, Dallas, TX 75390, USA.
The aim of this study was to assess the utility of weighted amide proton transfer (APT) MRI in three different rodent models of hepatocellular carcinoma (HCC). APT MRI was evaluated in models of diethylnitrosamine (DEN) induced HCC, N1S1 syngeneic orthotopic xenograft and human HepG2 ectopic xenograft. All models of HCC showed a higher APT signal over the surrounding normal tissues.
View Article and Find Full Text PDFBMC 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.
Neurooncol Adv
January 2025
Institute for Artificial Intelligence in Medicine, University Hospital Essen, Germany.
Background: This study aimed to develop an automated algorithm to noninvasively distinguish gliomas from other intracranial pathologies, preventing misdiagnosis and ensuring accurate analysis before further glioma assessment.
Methods: A cohort of 1280 patients with a variety of intracranial pathologies was included. It comprised 218 gliomas (mean age 54.
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