ArticleQuantitative imaging in medicine and surgery2023
Diagnostic value of dynamic
Article in Quantitative imaging in medicine and surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 11 citations in OpenAlex.
- Article
- The value of predicting the invasiveness and degree of infiltration of pulmonary ground-glass nodules based on computed tomography features and enhanced quantitative analysis.Quantitative imaging in medicine and surgery · 2024Article
- Revolutionizing lymph node metastasis imaging: the role of drug delivery systems and future perspectives.Journal of nanobiotechnology · 2024Review
- Diagnostic value of FDG PET-CT in differentiating lung adenocarcinoma from squamous cell carcinoma.EJNMMI reports · 2024Article
- Article
- Diagnostic Value of DynamicDiagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: We aimed to investigate the diagnostic value of dynamic 2-deoxy-2-[ Methods: Patients who made an active appointment for positron emission tomography-computed tomography were randomly enrolled by referring to previous imaging data and clinical information. Finally, 34 histopathologically confirmed non-small cell lung cancers (18 adenocarcinoma and 16 squamous cell carcinoma cases) were prospectively studied using dynamic and static 2-deoxy-2-[ Results: There was a significant difference in the V_Median values of adenocarcinoma and squamous cell carcinoma. The regression models for K1, k3, and V provided good predictions of adenocarcinoma and squamous cell carcinoma typology. Significant differences were observed in k3_Entropy, VB_Entropy, K1_Uniformity, and ki_Uniformity between benign and malignant lymph nodes. The regression model of Ki, VB, and k3 could make a good prediction for identifying benign and malignant lymph nodes. Conclusions: Dynamic 2-deoxy-2-[
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.