4.1 Why the results of PERCIST criteria is inconsistent with other groups?
The PERCIST criteria utilize the hottest lesion on FDG-PET as target, considering both the primary tumor and its distant metastases. In a study conducted in 22 patients, Benz et al. [11] reported that patients who had PMD according to FDG-PET results obtained at two weeks after the start of erlotinib treatment displayed a significantly shorter time to progression and a poorer OS compared with those showing either SMD or PMR. Another report by Zander et al. [8] demonstrated that the PERCIST criteria obtained using FDG-PET data acquired after one week of erlotinib therapy predicted both PFS and OS in patients with advanced NSCLC independent of the EGFR mutation status. Similar results were obtained when the EORTC criteria were applied [8]. However, the results of our study indicate that FDG-PET response according to the PERCIST criteria on day 14 was not significantly associated with PFS and OS. A potential explanation for these findings is that some patients classified as responders according to CT imaging at day 56 using the RECIST criteria were erroneously considered as non-responders based on early FDG-PET results. Notably, incorrect patient classification was mainly caused by a high skeletal tracer uptake on day 14, ultimately resulting in a markedly lower SUV reduction compared with other study participants. It should be indeed noted that 1) all of these bone lesions disappeared on day 56 and 2) the four patients incorrectly classified by the PERCIST criteria were correctly identified as early responders according to both the EORTC and TLG-S criteria.
Starting from these premises, bone flares are a plausible explanation for misclassification when PERCIST criteria are used.
4.2 The effects of bone flare
In this study, we observed that the presence of “persistent bone uptake” in patients who showed primary tumor response resulted in an erroneous categorization of four patients (group A in Table 3).
Although the discrepancy between primary tumor (response) and bone metastasis (no-response) on day 14 may be caused by tumor heterogeneity, bone uptake was either much decreased or absent on day 56 in group A patients. Based on these findings, we reasoned that the occurrence of bone flares would be the most plausible mechanism to explain “discordant persistent” tracer uptake in the bone. However, the peak time of bone flare can be influenced by several factors (e.g., tracer, tumor type, and drugs).
Numerous data on bone flares are available from bone scintigraphy studies but less information is available on their occurrence in FDG-PET images. In this study, we defined persistent bone uptake as a SUVmax reduction of less than 30% or an increase in SUVmax values. Persistent bone uptake observed on day 14 imaging may have occurred before or after peak time. Consequently, non-peak persistent bone uptake was attributed to the bone flare phenomenon. The clinical significance of the bone flare phenomenon is still a matter of debate [39]. Osteoblastic bone flares have been previously described as transiently worsening bone lesions on FDG-PET scans in a case series of four NSCLC patients treated with bevacizumab [40]. Another study using CT imaging and the RECIST criteria identified the occurrence of osteoblastic bone flares in three NSCLC patients who received erlotinib [22]. It has been reported that 21% of NSCLC patients who undergo bone scintigraphy develop bone flares during therapy with TKIs [23]. In the present study, bone flares were observed in 31% of patients with skeletal metastases on FDG-PET scans performed on day 14. Nonetheless, a case report that used FDG-PET for the assessment of response to erlotinib indicated that disease progression might be misdiagnosed as a bone flare as well [41]. In our study, six non-responders with persistent bone lesions on day 14 had stable disease on day 56.
4.3 Tumor heterogeneity: systemic approach vs. local assessment
Consistent with previous reports [3, 5, 9, 10, 12-14], the results of our study demonstrate that assessment of early FDG-PET response using the EORTC criteria predicts OS in NSCLC patients treated with erlotinib. In our report, the number and timing of FDG-PET scans (at baseline and on days 14 and 56) were in line with the protocol utilized by Mileshkin et al. [9]. Interestingly, these authors reported that FDG-PET response according to the EORTC criteria on day 14 was significantly associated with a better OS, whereas the same response on day 56 was not. Nonetheless, the biological heterogeneity between the primary tumor and its metastatic progenies as well as the intermetastatic
heterogeneity [42] have not been previously taken into adequate account. We thus reasoned that a systemic assessment that would include the metastatic sites could be superior to the exclusive local assessment of primary tumor response according to the EORTC criteria. Our findings supported the original study hypothesis. Accordingly, a systemic approach based on the TLG-S method (including both primary and metastatic tumors up to a total of five target lesions) identified a significant association between early FDG-PET response and survival endpoints (PFS and OS).
4.4 Proposed TLG-S method
In line with the PERCIST criteria, in this study we defined PMR as a reduction of at least 45% in TLG-S, whereas PMD was diagnosed in presence of a 75% or higher increase in this parameter.
Kahraman et al. [16] have previously shown that the percentage change of TLG-S is a strong predictor of survival outcomes in NSCLC patients treated with erlotinib. In their study, the authors defined TLG-S as the sum of up to a maximum of five measurable target lesions; different cut-off values for defining the metabolic response were also calculated [16]. Another recent report demonstrated that high TLG-S values are an independent predictor of survival in patients with advanced NSCLC who receive erlotinib [19]. In the latter study, TLG-S was calculated by taking into account all of the measurable lesions in whole-body scans; in addition, TLG-S was dichotomized according to the median value [19]. Altogether these findings indicate a strong prognostic significance of TLG-S, although both the extent of target lesions and the definition of metabolic response have not yet been standardized.
4.5 Impact of tumor heterogeneity
Some controversy still exists on the discordance in EGFR and K-RAS mutation status between primary and metastatic tumors among NSCLC patients [24-26]. Therefore, local imaging assessment of the primary tumor has been mainly supported by reports showing that a heterogeneous distribution of
EGFR mutations occurs rarely [43, 44]. In our study, we demonstrate that FDG-PET response based
on the EORTC criteria is associated with OS but not PFS. However, it should be noted that small core biopsies may not correctly reflect the clonal heterogeneity of the entire tumor [45]. Moreover, intratumor heterogeneity (consisting of a mixed population of EGFR-mutated and wild-type cells) may reduce the response to TKIs [46]. A significant heterogeneity in the EGFR mutation status between primary lung tumors and their metastases can also cause a mixed response to TKIs in certain patients [30, 45]. At the imaging level, the intratumor heterogeneity of FDG uptake has been associated withtumor response and clinical outcomes in NSCLC patients treated with erlotinib [18]. Based on these findings, we believe that systemic approaches including distant metastases would be superior to single-site assessments when this patient group undergoes FDG-PET imaging. Our current findings obtained with the TLG-S method supports this contention quite strongly.
4.6 Limitation of textural analysis in current study
We found the high correlation between textural parameters and tumor volume. Therefore, it should be cautious when interpreting the usefulness of texture features for tumor prognosis [47]. Besides, it has been shown that the sensitivity of PET textural features to normal stochastic image variation and imaging parameters can be significant [48]. With very limited number of patients being included, stochastic variability of PET textural parameters might therefore have greatly confounded the results of the study. Further study with more patients included should be conducted to verify the role of textural features in tumor response evaluation and prognosis prediction.