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*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

61 Scopus citations

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.

Original languageEnglish
Pages (from-to)410-416
Number of pages7
JournalAnnals of Nuclear Medicine
Volume32
Issue number6
DOIs
StatePublished - 1 Jul 2018
Externally publishedYes

Keywords

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

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