{
  "abstract": "Primary mediastinal B-cell lymphoma (PMBL) is an uncommon aggressive lymphoma with generally favorable outcomes; however, 15-20% of patients develop refractory disease. Reliable baseline prognostic biomarkers remain lacking. We evaluated the prognostic value of radiomic parameters derived from baseline 18F-FDG PET/CT in newly diagnosed PMBL. This post-hoc analysis included 180 treatment-naïve patients from the multicenter LYSA cohort (2007-2017) treated with rituximab plus ACVBP, R-CHOP14, or R-CHOP21. Twelve 3D PET-derived radiomic features were extracted using Oncometer3D. Inter-parameter correlations were assessed using Spearman coefficients. Receiver operating characteristic (ROC) analyses determined optimal cut-offs. Progression-free survival (PFS) and overall survival (OS) were analyzed using Kaplan-Meier estimates and Cox regression models. Four clusters of correlated features were identified: activity, tumor burden, massiveness/fragmentation, and dispersion. Among these, total metabolic tumor volume (TMTV), maximal inter-lesion distance (Dmax), and median peripheral centroid distance (medPCD) demonstrated the strongest prognostic associations. TMTV and Dmax were significantly associated with shorter PFS and OS, while medPCD predicted OS. In multivariable analysis adjusted for IPI, bulky disease, B symptoms, and treatment regimen, a composite radiomic score (2-3 high-risk features vs 0-1) independently predicted OS (HR 7.76, 95% CI 1.59-37.74) and showed a strong trend for PFS. The composite score outperformed conventional clinical risk factors. Baseline PET-derived radiomic features capturing tumor burden, spatial dispersion, and compactness provide independent prognostic information in PMBL. A three-parameter radiomic score outperformed conventional risk factors and identified a high-risk subgroup at diagnosis, warranting prospective and external validation before clinical implementation.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 35,
  "authors": [
    {
      "name": "Pierre Decazes"
    },
    {
      "name": "Cedric Rossi"
    },
    {
      "name": "Pierre Sesques"
    },
    {
      "name": "Stéphanie Becker"
    },
    {
      "name": "Mathieu Viennot"
    },
    {
      "name": "Sorina-Dana Mihailescu"
    },
    {
      "name": "François Lemonnier"
    },
    {
      "name": "Eric Durot"
    },
    {
      "name": "Nicolas Gower"
    },
    {
      "name": "Alexandre Willaume"
    },
    {
      "name": "Lucie Obéric"
    },
    {
      "name": "Jérôme Paillassa"
    },
    {
      "name": "Chloe Antier"
    },
    {
      "name": "Loic Renaud"
    },
    {
      "name": "Olivier Tournilhac"
    },
    {
      "name": "Catherine Thieblemont"
    },
    {
      "name": "Caroline Besson"
    },
    {
      "name": "Laure Lebras"
    },
    {
      "name": "Sylvain Choquet"
    },
    {
      "name": "Katell Le Dû"
    },
    {
      "name": "Christophe Bonnet"
    },
    {
      "name": "Sarah Bailly"
    },
    {
      "name": "Gandhi-Laurent Damaj"
    },
    {
      "name": "Kamel Laribi"
    },
    {
      "name": "Nadine Morineau"
    },
    {
      "name": "Roch Houot"
    },
    {
      "name": "Adrien Chauchet"
    },
    {
      "name": "Fabrice Jardin"
    },
    {
      "name": "Hervé Tilly"
    },
    {
      "name": "Elena-Liana Veresezan"
    },
    {
      "name": "Fanny Drieux"
    },
    {
      "name": "Marie Donzel"
    },
    {
      "name": "Alexandra Traverse-Glehen"
    },
    {
      "name": "David Tonnelet"
    },
    {
      "name": "Vincent Camus"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1q9jcevm2zmvx.bib",
  "cited_by": 0,
  "doi": "10.1182/bloodadvances.2026020168",
  "fulltext_url": null,
  "id": "1q9jcevm2zmvx",
  "issns": [
    "2473-9529",
    "2473-9537"
  ],
  "landing_url": "https://hal.science/hal-05654892v1",
  "language": "en",
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "hal",
      "0.sdv"
    ],
    [
      "hal",
      "1.sdv.can"
    ],
    [
      "hal",
      "1.sdv.mhep"
    ],
    [
      "hal",
      "2.sdv.mhep.aha"
    ],
    [
      "openalex",
      "2741|Radiomics and Machine Learning in Medical Imaging"
    ]
  ],
  "openalex": "W7160922459",
  "pdf_url": "https://hal.science/hal-05654892/document",
  "pmcid": null,
  "pmid": "42118857",
  "published": "2026-05-12",
  "publisher": "The American Society of Hematology",
  "ris": "https://research.draconitic.com/paper/1q9jcevm2zmvx.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:56Z",
      "native_id": "hal-05654892",
      "source": "hal",
      "url": "https://hal.science/hal-05654892v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "hal:0.sdv",
      "subfield": "general"
    },
    {
      "field": "medicine",
      "origin": "hal:1.sdv.can",
      "subfield": "oncology"
    },
    {
      "field": "medicine",
      "origin": "hal:2.sdv.mhep.aha",
      "subfield": "physiology"
    }
  ],
  "title": "Prognostic Value of Combined Baseline FDG PET/CT Radiomic Parameters in Primary Mediastinal B-Cell Lymphoma",
  "title_text": "Prognostic Value of Combined Baseline FDG PET/CT Radiomic Parameters in Primary Mediastinal B-Cell Lymphoma",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:56Z",
  "url": "https://research.draconitic.com/paper/1q9jcevm2zmvx",
  "venue": "Blood Advances",
  "versions": []
}