Assessment of quantitative staging PET/computed tomography parameters using machine learning for early detection of progression in diffuse large B-cell lymphoma.

Journal: Nuclear medicine communications
Published Date: Jun 30, 2025

Abstract

OBJECTIVE: This study aimed to investigate the role of volumetric and dissemination parameters obtained from pretreatment 18-fluorodeoxyglucose PET/computed tomography (18F-FDG PET/CT) in predicting progression/relapse in patients with diffuse large B-cell lymphoma (DLBCL) with machine learning algorithms.

Authors

  • Ayşegül Aksu
    Başakşehir Çam ve Sakura City Hospital, Department of Nuclear Medicine, Istanbul, Turkey.
  • Anilcan Us
    Department of Nuclear Medicine.
  • Kadir Alper Küçüker
    Department of Nuclear Medicine.
  • Şerife Solmaz
    Department of Hematology, İzmir Kâtip Çelebi University, Atatürk Training and Research Hospital, İzmir, Turkey.
  • Bülent Turgut
    Department of Nuclear Medicine.

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