EANM/EARL harmonization strategies in PET quantification: from daily practice to multicentre oncological studies

Abstract

Quantitative positron emission tomography/computed tomography (PET/CT) can be used as diagnostic or prognostic tools (i.e. single measurement) or for therapy monitoring (i.e. longitudinal studies) in multicentre studies. Use of quantitative parameters, such as standardized uptake values (SUVs), metabolic active tumor volumes (MATVs) or total lesion glycolysis (TLG), in a multicenter setting requires that these parameters be comparable among patients and sites, regardless of the PET/CT system used. This review describes the motivations and the methodologies for quantitative PET/CT performance harmonization with emphasis on the EANM Research Ltd. (EARL) Fluorodeoxyglucose (FDG) PET/CT accreditation program, one of the international harmonization programs aiming at using FDG PET as a quantitative imaging biomarker. In addition, future accreditation initiatives will be discussed. The validation of the EARL accreditation program to harmonize SUVs and MATVs is described in a wide range of tumor types, with focus on therapy assessment using either the European Organization for Research and Treatment of Cancer (EORTC) criteria or PET Evaluation Response Criteria in Solid Tumors (PERCIST), as well as liver-based scales such as the Deauville score. Finally, also presented in this paper are the results from a survey across 51 EARL-accredited centers reporting how the program was implemented and its impact on daily routine and in clinical trials, harmonization of new metrics such as MATV and heterogeneity features.

Keywords: Deauville score; EARL accreditation; EORTC; Harmonization; MATV; PERCIST; PET/CT; SUV.

Fig. 1

Number of articles reporting the use of MATV, SUV_max and SUV_peak as a function of year of publication. Articles were identified by Medline search with the following keywords: (MTV OR MATV AND PET), (SUV_max AND PET) or (SUV_peak AND PET). Only human studies were included

Fig. 2

Illustration of reconstruction harmonization methods and brief summary of the main factors influencing SUV

Fig. 3

Effect of reconstruction inconsistencies and impact of harmonization on therapy assessment with EORTC response criteria and PERCIST. Relationship between standardized uptake values normalized to lean body mass (SUL)_max and SUL_peak in lesions extracted from PSF ± TOF (a) or PSF ± TOF.EQ (b) and OSEM images, assessed using Bland-Altman plots. Of note is the greater sensitivity of SUV_max to reconstruction variability, compared to SUV_peak: the number of cases exceeding the threshold to discriminate between SMD and PMD, due to reconstruction inconsistency, is higher for SUV_max. Conversely, PERCIST appears less sensitive than EORTC criteria to reconstruction inconsistency between pre- and post-treatment scans: panel c displays EORTC classification and PERCIST for the standard of reference (OSEM_PET1/OSEM_PET2) and for other scenarios. d: representative images of a 72-year-old male patient with NSCLC treated by chemotherapy, classified as SMD according to the standard of reference. The use of OSEM for baseline scan and PSF + TOF for post-treatment scan, mimicking a system upgrade during a trial, would lead to PMD classification for both EORTC and PERCIST, while the use of harmonized data would correctly classify the patient

Fig. 4

Results from the EARL electronic survey. Data are displayed as pie charts