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Research ArticleBasic Science Investigation

Prognostic Value of 18F-FDG PET Radiomics Features at Baseline in PET-Guided Consolidation Strategy in Diffuse Large B-Cell Lymphoma: A Machine-Learning Analysis from the GAINED Study

Thomas Carlier, Gauthier Frécon, Diana Mateus, Mira Rizkallah, Françoise Kraeber-Bodéré, Salim Kanoun, Paul Blanc-Durand, Emmanuel Itti, Steven Le Gouill, René-Olivier Casasnovas, Caroline Bodet-Milin and Clément Bailly
Journal of Nuclear Medicine November 2023, jnumed.123.265872; DOI: https://doi.org/10.2967/jnumed.123.265872
Thomas Carlier
1Nantes Université, INSERM, CNRS, CRCI2NA, Université d’Angers, Nantes, France;
2Nuclear Medicine Department, University Hospital, Nantes, France;
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Gauthier Frécon
1Nantes Université, INSERM, CNRS, CRCI2NA, Université d’Angers, Nantes, France;
2Nuclear Medicine Department, University Hospital, Nantes, France;
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Diana Mateus
3Laboratoire des Sciences Numériques de Nantes, Ecole Centrale de Nantes, CNRS UMR 6004, Nantes, France;
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Mira Rizkallah
3Laboratoire des Sciences Numériques de Nantes, Ecole Centrale de Nantes, CNRS UMR 6004, Nantes, France;
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Françoise Kraeber-Bodéré
1Nantes Université, INSERM, CNRS, CRCI2NA, Université d’Angers, Nantes, France;
2Nuclear Medicine Department, University Hospital, Nantes, France;
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Salim Kanoun
4Nuclear Medicine, Georges-François Leclerc Center, Dijon, France;
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Paul Blanc-Durand
5Nuclear Medicine, CHU Henri Mondor, Paris-Est University, Créteil, France;
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Emmanuel Itti
5Nuclear Medicine, CHU Henri Mondor, Paris-Est University, Créteil, France;
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Steven Le Gouill
6Haematology Department, University Hospital, Nantes, France; and
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René-Olivier Casasnovas
7Hematology, CHU Dijon Bourgogne, Dijon, France
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Caroline Bodet-Milin
1Nantes Université, INSERM, CNRS, CRCI2NA, Université d’Angers, Nantes, France;
2Nuclear Medicine Department, University Hospital, Nantes, France;
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Clément Bailly
1Nantes Université, INSERM, CNRS, CRCI2NA, Université d’Angers, Nantes, France;
2Nuclear Medicine Department, University Hospital, Nantes, France;
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  • FIGURE 1.
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    FIGURE 1.

    Mean ROC curves for models 1–5 (A) and 6–9 (B) for 2-y PFS classification.

  • FIGURE 2.
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    FIGURE 2.

    Feature importance according to relative weight attached to each feature in LR model for models 6 (A) and 7 (B) for 2-y PFS classification. ECOG = Eastern Cooperative Oncology Group; LDH = lactate dehydrogenase; SDmax = maximum distance between 2 lesions normalized by body surface area; TLG = total lesion glycolysis.

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    FIGURE 3.

    Example of RS for training set (A) and corresponding test set (C), along with associated Kaplan–Meier plots for PFS for training set (B) and test set (D). Low- and high-risk groups were dichotomized using median RS determined on training set and applied on test set.

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    FIGURE 4.

    Log-rank P values over 100 loops for 9 models considered for survival analysis study.

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    FIGURE 5.

    Mean ROC curves for models 1, 3, 4, and 5 (A) and for models that combined several features (B) for PET4 prediction. Model 7b = combination of clinical and conventional PET features; model 8b = combination of clinical and radiomics; model 9b = combination of clinical and conventional PET features and radiomics.

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    TABLE 1.

    Description of Different Models

    Model no.Model nameAssociated features
    1aaIPIaaIPI
    2ConsolidationChemotherapy regimen, autologous cell transplantation, salvage therapy
    3ClinicalAge, Ann Arbor stage, ECOG status, number of extranodal sites, LDH
    4Conventional PETTMTV, total lesion glycolysis, SUVmax, sDmax
    5Radiomics PETSelected RFs after selection step using largest lesion
    6Consolidation + clinical (models 2 + 3)All features from clinical and consolidation
    7Consolidation + clinical + conventional PET (models 2 + 3 + 4)All features from clinical, conventional (PET), and consolidation
    8Consolidation + clinical + radiomics PET (models 2 + 3 + 5)All features from clinical, radiomics (PET), and consolidation
    9Consolidation + clinical + conventional PET + radiomics PET (models 2 + 3 + 4 + 5)All features from clinical and conventional (PET), radiomics (PET). and consolidation
    • aaIPI = age-adjusted international prognostic index; ECOG = Eastern Cooperative Oncology Group; LDH = lactate dehydrogenase; sDmax = maximum distance between 2 lesions normalized by body surface area.

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    TABLE 2.

    Patient Characteristics

    Characteristic2-y PFS classification (n = 545)Survival (n = 561)
    Events86 (100%)107 (100%)
    Age (y)48 (18–60)48 (18–60)
    Sex, male305 (56%)314 (56%)
    aaIPI
     0–1230 (42%)242 (43%)
     2–3315 (58%)319 (57%)
    Ann Arbor stage
     I–II102 (19%)106 (19%)
     III–IV443 (81%)455 (81%)
    Extranodal involvement
     <2259 (48%)269 (48%)
     ≥2286 (52%)292 (52%)
    Performance status
     0–1470 (86%)485 (86%)
     >175 (14%)76 (14%)
    LDH
     ≤Normal147 (27%)155 (28%)
     >Normal398 (73%)406 (72%)
    Treatment arm
     GA-101278 (51%)286 (51%)
     Rituximab267 (49%)275 (49%)
    Induction treatment
     GA-101-CHOP142 (26%)145 (26%)
     Rituximab-CHOP144 (26%)148 (26%)
     GA-101-ACVBP136 (25%)141 (25%)
     Rituximab-ACVBP123 (23%)127 (23%)
    • aaIPI = age-adjusted international prognostic index; CHOP = cyclophosphamide, doxorubicin, vincristine, and prednisone.

    • Qualitative data are number and percentage; continuous data are mean and range.

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Journal of Nuclear Medicine: 66 (5)
Journal of Nuclear Medicine
Vol. 66, Issue 5
May 1, 2025
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Prognostic Value of 18F-FDG PET Radiomics Features at Baseline in PET-Guided Consolidation Strategy in Diffuse Large B-Cell Lymphoma: A Machine-Learning Analysis from the GAINED Study
Thomas Carlier, Gauthier Frécon, Diana Mateus, Mira Rizkallah, Françoise Kraeber-Bodéré, Salim Kanoun, Paul Blanc-Durand, Emmanuel Itti, Steven Le Gouill, René-Olivier Casasnovas, Caroline Bodet-Milin, Clément Bailly
Journal of Nuclear Medicine Nov 2023, jnumed.123.265872; DOI: 10.2967/jnumed.123.265872

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Prognostic Value of 18F-FDG PET Radiomics Features at Baseline in PET-Guided Consolidation Strategy in Diffuse Large B-Cell Lymphoma: A Machine-Learning Analysis from the GAINED Study
Thomas Carlier, Gauthier Frécon, Diana Mateus, Mira Rizkallah, Françoise Kraeber-Bodéré, Salim Kanoun, Paul Blanc-Durand, Emmanuel Itti, Steven Le Gouill, René-Olivier Casasnovas, Caroline Bodet-Milin, Clément Bailly
Journal of Nuclear Medicine Nov 2023, jnumed.123.265872; DOI: 10.2967/jnumed.123.265872
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Keywords

  • DLBCL
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