ArticleCancers2025
18F-FDG PET/CT Radiomics for Predicting Therapy Response in Primary Mediastinal B-Cell Lymphoma: A Bi-Centric Pilot Study.
Article in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
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.
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Who cites it
4 citing papers in PubMed.
- Metabolic heterogeneity-based radiomic model predicts treatment outcomes of primary mediastinal B-cell lymphoma patients in the IELSG37 study.British journal of haematology · 2026Trial
- Applications of artificial intelligence in nuclear medicine.Zeitschrift fur medizinische Physik · 2026Review
- Precision theranostics in oncology: integrating antibody-drug conjugates, radioimmunotherapy, and immuno‑PET for adaptive cancer care.Discover oncology · 2026Review
- Investigation of MRI features in subtypes of primary central nervous system diffuse large B-cell lymphoma.BMC medical imaging · 2025Article
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis bi-centric pilot study investigates the predictive value of pre-treatment [
methodsAll PMBCL patients underwent PET/CT with [
resultsThe entire dataset was composed of 29 samples for the Rome cohort (23 from D1-D3 and 6 from D4/D5) and 9 samples for the Ferrara cohort (4 from D1-D3 and 5 from D4/D5). A total of 27 RFts were identified as robust for each imaging modality. Both the CT and PET models effectively predicted the Deauville score. The performance metrics of the best classifier (SVM) for the CT and PET models in external validation were AUC = 0.75/0.80, CA = 0.85/0.77, Prec = 0.97/0.67, Sen = 0.60/0.80, Spec = 0.98/0.75, TP = 75.0%/66.7%, and TN = 77.8%/85.7%, respectively.
conclusionsML models trained on [
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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.