ArticleFrontiers in oncology2026
Evaluation of a dual-energy computed tomography parameter -radiomics combined model for solitary pulmonary nodules.
Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To construct a dual-energy computed tomography (DECT) parameter-radiomics combined model based on DECT quantitative parameters and radiomic features and to evaluate its diagnostic performance in differentiating benign from malignant solitary pulmonary nodules. Materials and methods: We retrospectively collected data from inpatients who underwent contrast-enhanced thoracic DECT scans at our hospital between June 2018 and November 2024. Quantitative parameters measured and calculated included iodine concentration, effective atomic number, normalized iodine concentration, normalized effective atomic number, spectral Hounsfield unit slope, and extracellular volume fraction. These DECT parameters were used to construct a predictive model. The dataset was randomly divided into training and test sets in a 7:3 ratio. Radiomic features were extracted from mixed-energy images of the arterial and venous phases (A Results: In total, 209 patients were enrolled (166 in the malignant group and 43 in the benign group). In the test set, the diagnostic performance of the combined model (AUC = 0.906) exceeded that of the DECT-only radiomics model (AUC = 0.794). The combined model demonstrated an accuracy of 82.5%, sensitivity of 80.0%, and specificity of 92.3%. Conclusion: The DECT parameter-radiomics combined model effectively differentiated benign from malignant solitary pulmonary nodules and shows promising potential for clinical translation.
Indexed as
Identifiers
What OpenQuestion holds
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.