ArticleFrontiers in oncology2025
CT-based texture analysis predicts BRAF
Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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7 authors.
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Abstract
Background: The BRAF gene plays an essential role in papillary thyroid carcinoma (PTC). Purpose: To investigate the potential of CT-based texture analysis in predicting BRAF Material and methods: 475 cases of calcified PTC from two centers, who underwent CT scans, surgery, and BRAF Results: The NDA method demonstrated excellent diagnostic performance compared to the LDA and PCA methods, with error rates of less than 10%, less than 25%, and greater than 30%, respectively in the training and validation sets. For parenchymal and calcified areas of PTC, the POE+ACC+NDA and MI+NDA methods exhibited the lowest error rates, with an area under the curve (AUC) of 0.969 in the training set and 0.964 in the internal validation set. Conversely, the Fisher+PCA and MI+PCA methods had the highest error rates, with AUC values of 0.413 and 0.525 in the training set, and 0.433 and 0.560 in the internal validation set, respectively. Conclusion: The POE+ACC+NDA or MI+NDA method provided high diagnostic performance for predicting BRAF
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