ArticleEuropean radiology2019
Computed tomography textural analysis for the differentiation of chronic lymphocytic leukemia and diffuse large B cell lymphoma of Richter syndrome.
Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Current status and quality of radiomics studies in lymphoma: a systematic review.European radiology · 2020Pooled it
- Early imaging differentiation of children with acute hematologic malignancies that present in pancytopenia: a retrospective study.Frontiers in oncology · 2026Article
- Non-Hodgkin's lymphoma classification using 3D radiomics machine learning models for precision imaging in oncology.BMC medical imaging · 2025Article
- Virtual biopsy for non-invasive identification of follicular lymphoma histologic transformation using radiomics-based imaging biomarker from PET/CT.BMC medicine · 2025Article
- Richter Transformation of Chronic Lymphocytic Leukemia-Are We Making Progress?Current hematologic malignancy reports · 2023Review
- Deep Neural Networks and Machine Learning Radiomics Modelling for Prediction of Relapse in Mantle Cell Lymphoma.Cancers · 2022Article
- Radiomics Features of the Spleen as Surrogates for CT-Based Lymphoma Diagnosis and Subtype Differentiation.Cancers · 2022Article
- Radiomics in the Setting of Neoadjuvant Radiotherapy: A New Approach for Tailored Treatment.Cancers · 2021Review
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo test the hypothesis that both indolent and aggressive chronic lymphocytic leukemia (CLL) can be differentiated from diffuse large B cell lymphoma (DLBCL) of Richter syndrome (RS) by CT texture analysis (CTTA) of involved lymph nodes. MATERIAL AND
methodsWe retrospectively included 52 patients with indolent CLL (26/52), aggressive CLL (8/52), and DLBCL of RS (18/52), who underwent standardized contrast-enhanced CT. In main lymphoma tissue, VOIs were generated from which CTTA features including first-, second-, and higher-order textural features were extracted. CTTA features were compared between the entire CLL group, the indolent CLL subtype, the aggressive CLL subtype, and DLBCL using a Kruskal-Wallis test. All p values were adjusted after the Bonferroni correction. ROC analyses for significant CTTA features were performed to determine cut-off values for differentiation between the groups.
resultsCompared with DLBCL of RS, CTTA of the entire CLL group showed significant differences of entropy heterogeneity (p < 0.001), mean intensity (p < 0.001), mean average (p = 0.02), and number non-uniformity gray-level dependence matrix (NGLDM) (p = 0.03). Indolent CLL significantly differed for entropy (p < 0.001), uniformity of heterogeneity (p = 0.02), mean intensity (p < 0.001), and mean average (p = 0.01). Aggressive CLL showed significant differences in mean intensity (p = 0.04). For differentiation between CLL and DLBCL of RS, cut-off values for mean intensity and entropy of heterogeneity were defined (e.g., 6.63 for entropy heterogeneity [aggressive CLL vs. DLBCL]; sensitivity 0.78; specificity 0.63).
conclusionsCTTA features of ultrastructure and vascularization significantly differ in CLL compared with that in DLBCL of Richter syndrome, allowing complementary to visual features for noninvasive differentiation by contrast-enhanced CT. KEY POINTS: • Richter transformation of CLL into DLBCL results in structural changes in lymph node architecture and vascularization that can be detected by CTTA. • First-order CT textural features including intensity and heterogeneity significantly differ between both indolent CLL and aggressive CLL and DLBCL of Richter syndrome. • CT texture analysis allows for noninvasive detection of Richter syndrome which is of prognostic value.
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