The use of a proposed updated EARL harmonization of 18F-FDG PET-CT in patients with lymphoma yields significant differences in Deauville score compared with current EARL recommendations

• Main Authors: John Ly, David Minarik, Lars Edenbrandt, Per Wollmer, Elin Trägårdh
• Format: Article
• Language: English
• Published: SpringerOpen 2019-07-01
• Series: EJNMMI Research
• Subjects: Deauville score; Reconstruction algorithm; Lymphoma; EARL; PET
• Online Access: http://link.springer.com/article/10.1186/s13550-019-0536-3

Abstract Background The Deauville score (DS) is a clinical tool, based on the comparison between lesion and reference organ uptake of 18F-fluorodeoxyglucose (FDG), used to stratify patients with lymphoma into categories reflecting their disease status. With a plethora of positron emission tomography with computed tomography (PET-CT) hard- and software algorithms, standard uptake value (SUV) in lesions and reference organs may differ which affects DS classification and therefore medical treatment. The EANM Research Ltd. (EARL) harmonization program from the European Association of Nuclear Medicine (EANM) partly mitigates this issue, but local preferences are common in clinical practice. We have investigated the discordance in DS calculated from patients with lymphoma referred for 18F-FDG PET-CT reconstructed with three different algorithms: the newly introduced block-sequential regularization expectation-maximization algorithm commercially sold as Q. Clear (QC, GE Healthcare, Milwaukee, WI, USA), compliant with the newly proposed updated EARL recommendations, and two settings compliant with the current EARL recommendations (EARLlower and EARLupper, representing the lower and upper limit of the EARL recommendations). Methods Fifty-two patients with non-Hodgkin and Hodgkin lymphoma were included (18 females and 34 males). Segmentation of mediastinal blood pool and liver were semi-automatically performed, whereas segmentation of lesions was done manually. From these segmentations, SUVmax and SUVpeak were obtained and DS calculated. Results There was a significant difference in DS between the QC algorithm and EARLlower/EARLupper (p < 0.0001 for both) but not between EARLlower and EARLupper (p = 0.102) when SUVmax was used. For SUVpeak, there was a significant difference between QC and EARLlower (p = 0.001), but not for QC vs EARLupper (p = 0.071) or EARLlower vs EARLupper (p = 0.102). Five non-responders (DS 4–5) for QC were classified as responders (DS 1–3) when EARLlower/EARLupper was used, both when SUVmax and SUVpeak were investigated. Conclusion Using the proposed updated EARL recommendations compared with the current recommendations will significantly change DS classification. In select cases, the discordance would affect the choice of medical treatment. Specifically, the current EARL recommendations were more often prone to classify patients as responders.