ArticleJapanese journal of radiology2023
Noninvasive assessment of significant liver fibrosis in rabbits by spectral CT parameters and texture analysis.
Article in Japanese journal of radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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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1 citing paper in PubMed, 4 citations in OpenAlex.
- The value of spectral CT quantitative parameters in predicting Ki-67 level in ovarian cancer.Frontiers in oncology · 2025Article
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6 authors at 2 institutions in 1 country.
Funding
Abstract
purposeNoninvasive assessment of significant liver fibrosis in rabbits by spectral CT parameters and texture analysis. MATERIALS AND
methodsThirty-three rabbits were randomly divided into 27 carbon tetrachloride-induced liver fibrosis group and 6 control group. Spectral CT contrast-enhanced scan was performed in batches, and the liver fibrosis was staged according to the histopathological results. The portal venous phase spectral CT parameters [70 keV CT value, normalized iodine concentration (NIC), spectral HU curve slope (λ
resultsA total of 23 experimental rabbits and 6 control rabbits were included, of which 16 had significant liver fibrosis. Three spectral CT parameters with significant liver fibrosis were significantly lower than those of non-significant liver fibrosis (p < 0.05), and the AUC ranged from 0.846 to 0.913. The combination analysis of mutual information (MI) and nonlinear discriminant analysis (NDA) had the lowest MCR, which with 0%. In the filtered texture features, four were statistically significant and AUC > 0.5, ranges from 0.764 to 0.875. The logistic regression model showed that Perc.90% and NIC could be used as independent predictors, the overall prediction accuracy of the model was 89.7% and the AUC was 0.976.
conclusionSpectral CT parameters and texture features have high diagnostic value for predicting significant liver fibrosis in rabbits, and the combination of the two can improve its diagnostic efficiency.
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