ArticleQuantitative imaging in medicine and surgery2024
The value of radiomics features of the spleen as surrogates for differentiating subtypes of common pediatric lymphomas.
Article in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Splenic FDG PET uptake and CT volume as prognostic biomarkers in diffuse large B cell lymphoma.La Radiologia medica · 2026Article
- Machine learning models for the prediction of preclinical coal workers' pneumoconiosis: integrating CT radiomics and occupational health surveillance records.Journal of translational medicine · 2025Article
- Radiomics analysis based on T2-weighed imaging and T2 mapping for staging endometrial fibrosis.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Lymphoma is a common malignant tumor in children. The pathologic subtyping of lymphoma is high complex, and the treatment options vary. The different pathologic subtypes of lymphomas have no significant differences on computed tomography (CT) images. As it is a hematologic disease, patients with lymphoma often show abnormalities in the spleen, and so the aim of this study was to construct a model for differentiating Burkitt lymphoma (BL) from lymphoblastic lymphoma through the extraction of radiomic features of the spleen from CT images. This could provide an efficient, noninvasive method that can differentiate the common pathological subtypes in patients with pediatric lymphoma. Methods: The clinical data and imaging data of 48 patients with lymphoblastic lymphoma and 61 patients with BL were retrospectively analyzed. The dataset was divided into a training set (n=76) and a test set (n=33) through complete randomization. Radiomics features of the spleen were separately extracted from CT images in the noncontrast enhanced, arterial, and venous phases. These phase-specific features were integrated to construct fusion models. Three classifiers, quadratic discriminant analysis (QDA), logistic regression (LR), and support vector machine (SVM), were employed to build the models. Results: The fusion model exhibited superior performance compared to individual models. There was no significant difference between the fusion models constructed by QDA and LR in either the training set or the test set. Among the four fusion models constructed with the SVM classifier, SVM_4 emerged as the best performing model. The area under the curve, sensitivity, specificity, and F1-score of the SVM_4 model were 0.967 [95% confidence interval (CI): 0.935-0.998], 0.86, 0.97, and 0.913 in the training set, respectively, and 0.754 (95% CI: 0.584-0.924), 0.611, 0.867, and 0.71 in the test set, respectively. Conclusions: The radiomics features of the spleen demonstrated the capability to distinguish between the two most common lymphoma subtypes in pediatric patients. This noninvasive approach holds promise for efficient and accurate discrimination.
Indexed as
Identifiers
What Socratic 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 Socratic graph.