Annals of Nuclear Medicine

, Volume 32, Issue 6, pp 410–416 | Cite as

18F-FDG PET/CT metabolic tumor parameters and radiomics features in aggressive non-Hodgkin’s lymphoma as predictors of treatment outcome and survival

  • Aatif Parvez
  • Noam Tau
  • Douglas Hussey
  • Manjula Maganti
  • Ur MetserEmail author
Original Article



To determine whether metabolic tumor parameters and radiomic features extracted from 18F-FDG PET/CT (PET) can predict response to therapy and outcome in patients with aggressive B-cell lymphoma.


This institutional ethics board-approved retrospective study included 82 patients undergoing PET for aggressive B-cell lymphoma staging. Whole-body metabolic tumor volume (MTV) using various thresholds and tumor radiomic features were assessed on representative tumor sites. The extracted features were correlated with treatment response, disease-free survival (DFS) and overall survival (OS).


At the end of therapy, 66 patients (80.5%) had shown complete response to therapy. The parameters correlating with response to therapy were bulky disease > 6 cm at baseline (p = 0.026), absence of a residual mass > 1.5 cm at the end of therapy CT (p = 0.028) and whole-body MTV with best performance using an SUV threshold of 3 and 6 (p = 0.015 and 0.009, respectively). None of the tumor texture features were predictive of first-line therapy response, while a few of them including GLNU correlated with disease-free survival (p = 0.013) and kurtosis correlated with overall survival (p = 0.035).


Whole-body MTV correlates with response to therapy in patient with aggressive B-cell lymphoma. Tumor texture features could not predict therapy response, although several features correlated with the presence of a residual mass at the end of therapy CT and others correlated with disease-free and overall survival. These parameters should be prospectively validated in a larger cohort to confirm clinical prognostication.


PET/CT Non-Hodgkin’s lymphoma Texture Radiomics Metabolic tumor volume 

Supplementary material

12149_2018_1260_MOESM1_ESM.docx (15 kb)
Supplementary material 1 (DOCX 14 KB)


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Copyright information

© The Japanese Society of Nuclear Medicine 2018

Authors and Affiliations

  • Aatif Parvez
    • 1
  • Noam Tau
    • 1
  • Douglas Hussey
    • 1
  • Manjula Maganti
    • 2
  • Ur Metser
    • 1
    Email author
  1. 1.Joint Department of Medical Imaging, Princess Margaret Cancer Centre, University Health Network, Mount Sinai Hospital and Women’s College HospitalUniversity of TorontoTorontoCanada
  2. 2.Department of BiostatisticsPrincess Margaret Cancer CentreTorontoCanada

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