Wednesday, June 7, 2023

FDG PET texture indices as imaging biomarkers for epidermal growth factor receptor mutation status in lung adenocarcinoma – Scientific Reports

In the present study, we found that five FDG PET texture indices, but not SUVmax, were related with the EGFR mutation status in patients with newly diagnosed lung adenocarcinoma.

Tyrosine kinase inhibitors targeting EGFR mutations have proven to be one of the most effective therapeutic options currently available, and EGFR mutations predict a favorable prognosis in patients treated with them2. However, previous studies using the FDG SUVmax to predict the EGFR mutation status have reported inconsistent findings. Mak et al.8 and Caicedo et al.9 found no significant association between the EGFR mutation status and SUVmax, which is consistent with the findings of the present study. Zhang et al.11 and Cho et al.5 indicated that tumors with a lower SUVmax tended to have EGFR mutations. All patients enrolled in the four aforementioned studies had NSCLC. Conversely, Ko et al.6 and Huang et al.7 reported that a higher SUVmax was a predictor of EGFR mutations. However, these two studies included only patients with lung adenocarcinoma, which has been reported to have a high EGFR mutation rate16. This discrepancy in the findings may be due to differences in the sample size, patient selection criteria, and methodology among these studies. Furthermore, the inconsistent findings may be attributed to the intratumor heterogeneity in NSCLC. SUVmax, which reflects the highest FDG uptake within the tumor, is the value of a single voxel within the region. Texture indices may be able to reflect more metabolic information on tumor behaviors than SUVmax, such as intratumor metabolic heterogeneity and genetic mutation status.

Intratumor metabolic heterogeneity is a key sign of tumor development and reflects the molecular biology or genetic alterations during tumor evolution17. In the present study, 5 out of 31 texture indices were significantly different between the mutated EGFR and wild-type EGFR groups in patients with newly diagnosed lung adenocarcinoma. Yip et al. investigated the relationship between the EGFR mutation status and 19 FDG PET radiomic features in 348 patients with NSCLC, and they showed that eight radiomic features were related to the EGFR mutation status13. Zhang et al. examined the intratumor heterogeneity among various subtypes of NSCLC through multi-region tissue sequencing and concluded that EGFR-mutant lung adenocarcinoma has the highest intratumor heterogeneity compared with that of other NSCLC subtypes14. Zhang et al. investigated the utility of FDG PET and CT radiomic features for discriminating the EGFR mutation status in NSCLC11. Although CT and PET alone radiomic models had a better predictive performance than SUVmax, the combined PET/CT radiomic model further improved the predictive performance for the EGFR mutation status11. Another study also showed that FDG PET/CT-based radiomic features, comprising two PET and four CT features, had good performance in predicting the EGFR mutation in NSCLC12. In their study, the diagnostic accuracies of PET radiomics, CT radiomics, and PET/CT radiomics for EGFR mutation status were 0.712, 0.753, and 0.771, respectively12. In our study, the accuracy of FDG PET texture indices ranged from 0.621 to 0.712. Yamazaki et al. evaluated 14 intratumoral and 18 peritumoral CT radiomics for the prediction of EGFR mutation in lung cancer18. The AUCs of intratumoral CT radiomics and combined intratumoral and peritumoral CT radiomics were 0.730 and 0.774, respectively18. In our study, the AUCs of FDG PET texture indices ranged from 0.662 to 0.753. Their results were not comparable to our findings, but it is difficult to compare them due to the different methodologies used. Shi et al. calculated the coefficient of variation as a heterogeneity index in NSCLC and found that a high coefficient of variation was significantly related to EGFR mutations15. Although these studies have investigated intratumor heterogeneity, the calculation methods vary across studies. At present, there are limited reports available on the association between intratumor glucose metabolic heterogeneity and EGFR mutation status. Orlhac et al. observed that healthy tissue showed higher homogeneity, lower entropy, higher low gray-level zone emphasis, and lower high gray-level zone emphasis than tumor tissue on FDG PET19. Chan et al. reported that the parameters of FDG PET heterogeneity such as coarseness, contrast, and busyness were associated with overall survival in patients with pharyngeal carcinoma20. Many texture indices have been reported as potentially useful; however, there is no clear indication as to which one should be used. To understand these texture indices, it is essential to carefully investigate their relationship with actual tumor characteristics.

There are several limitations to this study. First, it was retrospective in design with a small sample size. Second, the EGFR mutation status was investigated only in one lung cancer type (adenocarcinoma); thus, further studies in other lung cancer types are warranted. Third, although patients with co-mutations were excluded from this study, not all oncogenes could be evaluated. Fourth, we only analyzed FDG PET parameters. Although the optimal threshold of tumor volume for texture analysis varies across studies, previous studies have suggested that combining promising parameters, such as PET and CT, may be helpful for identifying the EGFR mutation status11,12. Therefore, further studies with a larger number of patients are needed to explore the role of FDG PET reflecting intratumor metabolic heterogeneity in identifying the EGFR mutation status, which can be very important for the selection of targeted therapies in clinical practice.

In conclusion, our preliminary findings in a small patient population indicated that FDG PET texture indices may be potential imaging biomarkers for the EGFR mutation status in patients with newly diagnosed lung adenocarcinoma, although the mechanism and biological significance remain unclear. Further prospective studies with bigger sample sizes will help to clarify the utility of FDG PET as an alternative indicator of EGFR mutation status when tissue samples are not available.

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