ArticleEuropean journal of nuclear medicine and molecular imaging2019
Radiomic features of glucose metabolism enable prediction of outcome in mantle cell lymphoma.
Article in European journal of nuclear medicine and molecular imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 2 of them syntheses that pooled it.
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Who cites it
45 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The value of FDG PET/CT imaging in outcome prediction and response assessment of lymphoma patients treated with immunotherapy: a meta-analysis and systematic review.European journal of nuclear medicine and molecular imaging · 2022Pooled it
- Current status and quality of radiomics studies in lymphoma: a systematic review.European radiology · 2020Pooled it
- Development of a radiomic-clinical nomogram for prediction of survival in patients with diffuse large B-cell lymphoma treated with chimeric antigen receptor T cells.Journal of cancer research and clinical oncology · 2023Trial
- Interpretable multimodal PET/CT-EHR fusion via mixture-of-experts for prognostic stratification in mantle cell lymphoma: a multicenter study.BMC medicine · 2026Article
- Advances in biomarkers for mantle cell lymphoma in the era of targeted therapies.Haematologica · 2026Review
- Association of [Diagnostics (Basel, Switzerland) · 2025Article
- Prognostic Role of Pretreatment Tumor Burden and Dissemination Features From 2-[Hematological oncology · 2025Article
- The Role of Artificial Intelligence and Radiomics in the Management of Lymphomas by PET/CT: The Clairvoyance in Clinic.Cancer management and research · 2025Review
- Multi-slice computed tomography radiomics combined with serum alpha-L-fucosidase: a potential biomarker for precise identification of pleomorphic adenoma and Warthin tumor.Translational cancer research · 2024Article
- Long-Axial Field-of-View PET Imaging in Patients with Lymphoma: Challenges and Opportunities.PET clinics · 2024Review
- Artificial intelligence in immunotherapy PET/SPECT imaging.European radiology · 2024Review
- PET-based radiomic feature based on the cross-combination method for predicting the mid-term efficacy and prognosis in high-risk diffuse large B-cell lymphoma patients.Frontiers in oncology · 2024Article
- Semiquantitative 2-[Frontiers in medicine · 2024Review
- Methodological evaluation of original articles on radiomics and machine learning for outcome prediction based on positron emission tomography (PET).Nuklearmedizin. Nuclear medicine · 2023Review
- Performance of baseline FDG-PET/CT radiomics for prediction of bone marrow minimal residual disease status in the LyMa-101 trial.Scientific reports · 2023Article
- Development and validation of a [European radiology · 2023Article
- Imaging glucose metabolism to reveal tumor progression.Frontiers in physiology · 2023Review
- Comparing lesion and feature selections to predict progression in newly diagnosed DLBCL patients with FDG PET/CT radiomics features.European journal of nuclear medicine and molecular imaging · 2022Article
- Impact of ComBat Harmonization on PET Radiomics-Based Tissue Classification: A Dual-Center PET/MRI and PET/CT Study.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2022Article
- Role of Radiomics-Based Baseline PET/CT Imaging in Lymphoma: Diagnosis, Prognosis, and Response Assessment.Molecular imaging and biology · 2022Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
purposeTo determine whether [
methodsIncluded in this retrospective study were 107 treatment-naive MCL patients scheduled to receive CD20 antibody-based immuno(chemo)therapy. Standardized uptake values (SUV), total lesion glycolysis, and 16 co-occurrence matrix radiomic features were extracted from metabolic tumour volumes on pretherapy [
resultsSUVmean (OR 1.272, P = 0.013) and Entropy (heterogeneity of glucose metabolism; OR 1.131, P = 0.027) were significantly predictive of 2-year PFS: median areas under the curve were 0.72 based on the two radiomic features alone, and 0.82 with the addition of clinical/laboratory/biological data. Higher SUVmean in combination with higher Entropy (SUVmean >3.55 and entropy >3.5), reflecting high "metabolic risk", was associated with a poorer prognosis (median PFS 20.3 vs. 39.4 months, HR 2.285, P = 0.005). The best PFS prognostication was achieved using the MIPI-bm (MIPI-b and metabolic risk combined): median PFS 43.2, 38.2 and 20.3 months in the low-risk, intermediate-risk and high-risk groups respectively (P = 0.005).
conclusionIn MCL, the [
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