Defining the optimal method for measuring baseline metabolic tumour volume in diffuse large B cell lymphoma

Hajira Ilyas, N George Mikhaeel, Joel T Dunn, Fareen Rahman, Henrik Møller, Daniel Smith, Sally F Barrington

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112 Citations (Scopus)
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Abstract

PURPOSE: Metabolic tumour volume (MTV) is a promising prognostic indicator in diffuse large B cell lymphoma (DLBCL). Optimal thresholds to divide patients into 'low' versus 'high' MTV groups depend on clinical characteristics and the measurement method. The aim of this study was to compare in consecutive unselected patients with DLBCL, different software algorithms and published methods of MTV measurement using FDG PET.

METHOD: Pretreatment MTV was measured on 147 patients treated at Guy's and St Thomas' Hospital. We compared 3 methods: SUV ≥2.5, SUV ≥41% of maximum SUV and SUV ≥ mean liver uptake (PERCIST) and compared 2 software programs for measuring SUV ≥2.5; in-house 'PETTRA' software and Hermes commercial software.

RESULTS: There was strong correlation between MTV using the 4 methods, although derived thresholds were very different for the 41% method. Optimal cut-offs for predicting PFS ranged from 166-400cm3. All methods predicted survival with similar accuracy. 5y-PFS was 83-87% vs. 42-44% and 5y-OS was 85-89% vs. 55-58% for the low- and high-MTV groups, respectively. Interobserver variation in 50 patients showed excellent agreement, though variation was lowest using the SUV ≥ 2.5 method. The 41% method was the most complex and took the longest time.

CONCLUSION: All methods predicted PFS and OS with similar accuracy, but the derived cut-off separating good from poor prognosis varied markedly depending on the method. The choice of the optimal method should rely primarily on prognostic value, but for clinical use needs to take account of ease of use and reproducibility. In this study, all methods predicted prognosis, but SUV ≥ 2.5 had the best inter-observer agreement and was easiest to apply.

Original languageEnglish
JournalEuropean Journal of Nuclear Medicine and Molecular Imaging
Early online date19 Feb 2018
DOIs
Publication statusPublished - 1 Jul 2018

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