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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 Metser
Original Article

Abstract

Purpose

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.

Methods

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).

Results

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).

Conclusions

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.

Keywords

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
  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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