In this study, we investigated the predictive value of using 18F-FDG-PET parameters before and during RT for predicting treatment outcomes in patients with NSCLC. Although there was a significant difference in LRC according to GTVpre, metabolic response showed some degree of impact based on subgroup analysis. However, changes in SUVmax were significantly associated with DF, and this criterion has proved its diagnostic value to predict response to RT.
Tumor burden, measured by GTV, is important in tumor control models of RT; a given dose induces a log cell kill, assuming that the larger the tumor, the more cells and, therefore, the more radiation needed for LRC[15]. Given that GTVpre defined on CT was significantly associated with LRR at the RT dose (total dose of 60–63 Gy) used in the present study, it can be assumed that dose escalation is needed to achieve local control in NSCLC[16]. Secondary analysis of the RTOG 9311 study revealed that increasing GTV (> 45 cm3) was related to poor OS and progression-free survival[17]. Several other series[18, 19] have also suggested that tumor volume is a significant prognostic factor for survival. However, a recent prospective, observational factor study of TROG 99.05[20] found that a large primary tumor volume was not associated with poor survival, after adjusting for the effects of T and N stage. Instead, large primary tumor volume had an adverse impact on survival only within the first 18 months (comparable to the median follow-up period for the present study). In addition, changes in GTV had no impact on the treatment outcomes, and metabolic response could help stratify patients: those with a large GTVpre and favorable metabolic response showed an LRC rate comparable to that of patients with a small GTVpre and poor metabolic response. Several series provide evidence for a correlation between SUV and tumor cell proliferation[21]. An early reduction in FDG uptake during treatment can predict tumor response. In addition, SUVmax represents the enhanced tapping of 18F-FDG into the tumor cells, due to biological mechanisms, tumor aggressiveness, and hypoxia[22].
Owing to the heterogeneity of patient populations with NSCLC at an advanced stage, there is no concrete evidence regarding the prognostic value of PETpre. A recent meta-analysis of 13 studies with 1474 patients demonstrated that high SUVmax(pre) in the primary tumor was associated with reduced survival[23]. Another meta-analysis of 36 studies on 5807 patients with surgically treated NSCLC also identified SUVmax(pre) as a prognostic factor for disease-free survival, with an HR of 1.52 (95% CI 1.16-2.00). However, the retrospective study by Hoang et al. [24] with a homogeneous population did not find a correlation between metabolic parameters on PETpre and survival, which is consistent with the findings of the present study.
Discriminating non-responders from responders can help physicians to avoid unnecessary toxicity in patients expected to have a poor prognosis, by early interruption of ineffective therapy. Because changes in FDG uptake were associated with tumor shrinkage, PETinterim can also help physicians decide when to modify the RT plan, with PTV modification or dose escalation. Several series with various sample sizes (10–77 patients) have shown the prognostic value of PETinterim in patients with NSCLC treated with RT[25, 26] and in those with other solid tumors[27, 28]. And secondary analysis of ESPATUE study revealed that remaining SUVmax in the primary tumor after induction chemotherapy was associated with survival and freedom from extracranial progression in consistent to the current study.[29] Furthermore, a recent meta-analysis of 21 studies on 627 patients reported PETinterim as a promising tool for the early judgment of treatment[11]. However, because most of these studies were retrospective and examined multiple outcomes, concerns around the statistics include the fact that there were multiple comparisons and selective reporting of endpoints. More importantly, definite criteria or standard parameters have not yet been determined, and prognostic metrics range from SUVmax[26] and ΔSUVmax[30] to total lesion glycolysis[31] and metabolic tumor volume[13]. In our series, ΔSUVmax was associated with DF and LRR, suggesting that this parameter helps to stratify patients. Metabolic response based on ΔSUVmax was not significantly associated with LRC on univariable analysis, possibly due to the lack of statistical power.
However, SUV as a semiquantitative index has limitations owing to poor reproducibility,[23] making it difficult to adopt a threshold among different centers. In place of the SUV value itself, we calculated a cut-off value for ΔSUVmax (a 40% reduction), which was predictive of both LRR and DF. Criteria for the relative change in SUVmax can be a tool for predicting early treatment response in the same institution, which, in turn, can minimize the issue of variability and enhance the prognostic value of this metabolic parameter.
Early response appears to be an indicator of tumor biology and a predictor of the likelihood of treatment failure. Thus, the assessment of early response makes it easier to identify poor responders who are eligible for the intensification or modification of treatment, instead of continuation of the initial treatment (the so-called 18F-FDG-PET/CT-guided treatment algorithm). A recent phase II trial proved that adaptive RT with escalated doses accompanied by PETinterim is feasible and results in favorable LRC[32]. A further ongoing clinical trial (RTOG 1106) is examining adaptive RT with dose escalation for FDG-avid tumors on PETinterim. Another promising area of research that needs further prospective trials is the early switching of systemic chemotherapy in patients with a small decrease in SUVmax. Recently, there are several on-going trials in other solid tumors investigating the role of immune checkpoint blockade stratified by PET parameters (NCT 03829007, NCT 03853187, NCT 02760225).
Our study had several limitations. First, as a retrospective analysis, the results should be interpreted with caution. Second, there are inherent biases since this study was carried out in a single institution. However, our analysis was strengthened using consistent modern 18F-FDG-PET/CT, imaging analyses, chemotherapy regimen, and RT techniques. Other limiting factors include possible inflammatory changes caused by irradiation, which may mimic changes in tumor glucose metabolism associated with treatment. In addition, there is a possibility of overestimation of changes in SUV, because of the partial-volume effect; tumor reduction may underestimate the FDG uptake. Lastly, lack of a univocal parameter remains a challenge in dealing with the metabolic parameters as a universal prognostic or predictive factor. Although FDG uptake is generally used as a parameter to reflect the proportion of viable tumor cells, new tracers are now available for specifically detecting apoptosis and proliferation to provide a highly accurate prediction of treatment response.