Assessment of alteration in liver ¹⁸F–FDG uptake due to steatosis in lymphoma patients and its impact on the Deauville score

Steatosis or non-alcoholic fatty liver disease (NAFLD) is a hepatic complication of the metabolic syndrome and the major cause of hepatic abnormality throughout the world. It affects 10–24% of the general population in different countries [1]. NAFLD is histologically diagnosed by macrovesicular steatosis in >5% of hepatocytes. NAFLD comprises two main entities: simple steatosis or non-alcoholic fatty liver and non-alcoholic steato-hepatitis (NASH), which is characterised by lobular inflammation and ballooning degeneration.

Because of the prevalence of this disease, imaging diagnosis of hepatic steatosis has been evaluated as an alternative to invasive histological diagnosis. Several studies have demonstrated that liver attenuation on unenhanced computed tomography (CT) is an efficient tool to screen for moderate-to-severe hepatic steatosis, {corresponding to macrovesicular steatosis of 33% or greater [2]}, using a cut-off value of 42 Hounsfield units (HU) [3].

In the framework of treatment evaluation of diffuse large B cell lymphoma (DLBCL), follicular lymphoma (FL) and Hodgkin lymphoma (HL), liver uptake of ¹⁸F-FDG is taken as the reference tissue in assigning a Deauville score (DS), which underpins current criteria for interim PET and at the end of the treatment (EoT) PET response assessment. DS1–3 (less than or equal to liver background) versus D4–5 (greater than liver) are used to discriminate between responders and non-responders, respectively. This score has been shown to have a prognostic value early in the course of treatment and/or at the end of the treatment [4]. Importantly, visual assessment has to be confirmed by quantification, which is less user-dependent and circumvents optical misinterpretation due to the influence of background activity [5]. The use of liver background is based on previous studies that have determined that ¹⁸F-FDG uptake in the liver is relatively constant within the acquisition time specified by the EANM and SNMMI guidelines [6]. However, these statements were assessed in patients free of cancer and without any indication regarding the presence or not of hepatic steatosis. Therefore, extrapolation to current clinical practice could be challenged. To go further, this may lead to direct therapeutic implications when liver uptake is taken as the reference.

The aims of the present study were (1) to evaluate the prevalence of hepatic steatosis in lymphoma patients and its evolution across different time points (2) to evaluate the impact of hepatic steatosis on FDG liver uptake in the lymphoma population taking into consideration other known confounding parameters, especially body mass index (BMI) [7] and blood glucose level (BGL) [8]; and (3) to evaluate the potential impact of hepatic steatosis on therapeutic assessment according to the Deauville criteria.

Quantitative data are presented as mean ± standard deviation (SD) or median (interquartile range) when appropriate. Characteristics of populations were compared by using Fischer’s exact tests or Chi-square tests for discrete variables and Mann-Whitney tests for continuous variables. Univariate and multivariate regressions were performed to determined parameters that affected liver SUV_max or SUL_max. The difference between liver SUL_max in steatotic and non-steatotic patients was tested using the non-parametric Mann-Whitney test. Graphs and analyses were carried out using Prism version 5.0 (GraphPad Software, La Jolla, CA, USA) and MedCalc Statistical Software version 16.4.3 (MedCalc Software bvba, Ostend, Belgium). A p-value <0.05 was considered to denote statistical significance.

The prevalence of NAFLD increases by a factor of 4.6 in obese people, defined as those with a body-mass index of at least 30 [12]. Considering the increasing prevalence of obesity among adults and children [13], steatosis may soon become a greater issue. In the present study involving 227 lymphoma patients over a period of 1 year, hepatic steatosis was observed in 11.9% of the patients at some point during their baseline or post-treatment evaluation. This is less than the prevalence observed in the general population and could certainly be explained by the cut-off of 42 HU used to discriminate steatotic versus non-steatotic patients. Indeed, the use of this cut-off value enables the diagnosis of macrovesicular steatosis of 30% or greater. Therefore, mild macrovesicular steatosis (<30%) was not considered in the present study. Yet, by virtue of higher fatty than hepatic parenchymal density, this cut-off value permits an easy recognition of steatosis on the non-contrast CT component of a PET/CT and can easily be performed in clinical practice. Interestingly, post-treatment hepatic steatosis was not apparently related to the type of chemotherapy regimen, nor to the time-course of treatment and therefore does not explain the variability of liver ¹⁸F–FDG uptake previously observed in patients with DLBCL and HL [14].

¹⁸F-FDG PET/CT has already been explored in the context of hepatic steatosis but never in a population of lymphoma patients. These previous studies led to contradictory results with positive [15], negative [16] or even no relationship [17] between hepatic steatosis and liver SUVs. This could potentially be explained by other factors influencing the liver uptake, such as BMI, which is definitely linked to hepatic steatosis [18], not being considered. However, Lin’s results were in accordance with ours [16] and in the same line Abele et al., observed lower SUV_mean in steatotic patients even though statistical significance was not reached [17]. The study showing a positive relationship between steatosis and SUV_max did not actually take into account patients BMI, and; therefore, these results were certainly biased [15]. In our study, BMI and BGL appeared to be statistically different between steatotic and non-steatotic groups of patients whereas other parameters described as potentially affecting hepatic uptake {age, sex, treatment, time course of treatment [14, 19‐21]} were not. Concerning BGL, a proportional relationship with ¹⁸F–FDG liver uptake has been shown, even for blood glucose in line with EANM recommendations [22]. However, in our study, liver SUL_max values were not significantly linked to BGL recorded at injection time for either interim or EoT PET scans. To take into account the BMI, which is the main confounding parameter regarding steatosis, we used liver SUL_max values instead of the recommended SUV_max values for the determination of Deauville Scores [11]. However, according to the EANM procedure guidelines for tumour imaging [22], SUL is a recommended quantitative measure of ¹⁸F-FDG uptake and, in our study, SUL_max values gave the same DS as SUV_max values in almost all cases except in two examinations among 215 interim and EoT PET examinations (0.9%). Furthermore, these corresponded to changes between DS 4 and 5 or DS 2 and 3, meaning no change between responder versus non-responder status. These results suggest that either SUV_max or SUL_max can be used to score patients with relatively consistent results. However, the use of SUL_max has the advantage of giving the opportunity to reveal and potentially take into account parameters other than BMI that could influence the liver uptake, such as steatosis in the present case.

Liver SUL_max values were significantly lower in the presence of hepatic steatosis (defined as a mean liver density ≤ 42 HU) in both interim and EoT PET scans with an average decrease of 29.5% and 29.9%, respectively (Fig. 3a). Liver SUV_max values were also significantly lower in the presence of hepatic steatosis in EoT PET scans of normal-weight and overweight patients (BMI < 30 kg/m²) with an average decrease of 21.1% (Fig. 6a). The same results were not observed in obese patients (BMI ≥ 30 kg/m²) underlining the fact that this group clearly benefit from the use of SUL instead of SUV values that do not take into account the absence of ¹⁸F–FDG uptake in adipose tissue. One could thus expect a possible overestimation of the DS in steatotic patients from DS3 to DS4 with the risk of inducing erroneous modifications in patients’ management. Indeed, being classified as a non-responder (DS4) on an EoT PET usually prompts the use of a subsequent line of chemotherapy. Another important finding is that liver HU_mean values were the only independent factor correlated to liver SUL_max values in interim and EoT groups (Table 3) which allowed us to successfully correct liver SUL_max values by using a graphical method (Fig. 5) based on the slope of the calculated linear regression. Importantly, the application of this liver SUL_max correction led to the reclassification of all steatotic patients scored DS4 to DS3. Given the small number of steatotic patients scored DS4 on interim and EoT PET scans in our series, it is not possible to assess the clinical impact and veracity of these changes with respect to therapeutic intervention or patient outcome. Larger and more homogeneous studies are needed to substantiate the advantage of correcting the liver uptake of steatotic patients initially scored DS4. Our findings could also be confirmed in trials with homogeneously treated patients for which central reviewing has been performed. For instance, in the IELSG-26 study in patients with primary mediastinal DLBLC [23], the rate of DS4 was 24/115 (21%) and in a recent trial in advanced HL [24], it was 144/1119 (12.9%). However, at the present time, attention should be paid to the interpretation of the PET examinations scored DS4 with a percentage difference between the target lesion and the liver background lower than 30%, which is the average decrease in our series, and steatosis should be sought for on the CT part of the PET/CT examination to avoid erroneous alteration of patient’ management. When steatosis is depicted, the application of a correction as described in the results section or the use of delta SUL should be considered.

In a population of 227 lymphoma patients referred for interim and EoT PET scans over a 1-year period, prevalence of steatosis was 11.9%. Irrespective of patient’s BMI, blood glucose level and the type of chemotherapy regimen, liver SUL_max values were significantly lower in steatotic patients as compared to non-steatotic patients, with an average decrease of almost 30%. This is actually a theoretical but not a practical issue in most patients but should be recognised and corrected in appropriate cases, namely, for those patients scored DS4 with a percentage difference between the target lesion and the liver background lower than 30%.