Despite considerable improvements in the treatment options for advanced-stage non-small-cell lung cancer (NSCLC), disease-specific survival remains poor. With the aim of improving patient outcome, the treatment paradigm of locally advanced NSCLC has shifted from solely radiotherapy towards combined and intensified treatment approaches. Also, treatment for patients with stage IV (oligo)metastatic NSCLC has evolved rapidly, with therapeutic options that include a number of targeted agents, surgery, and stereotactic ablative radiotherapy. However, personalizing treatment to the individual patient remains difficult and requires monitoring of biological parameters responsible for treatment resistance to facilitate treatment selection, guidance, and adaptation. PET is a well-established molecular imaging platform that enables non-invasive quantification of many biological parameters that are relevant to both local and systemic therapy. With increasing clinical evidence, PET has gradually evolved from a purely diagnostic tool to a multifunctional imaging modality that can be utilized for treatment selection, adaptation, early response monitoring, and follow up in patients with NSCLC. Herein, we provide a comprehensive overview of the available clinical data on the use of this modality in this setting, and discuss future perspectives of PET imaging for the clinical management of patients with locally advanced and metastatic NSCLC.

Accurate measurement of intratumor heterogeneity using parameters of texture on PET images is essential for precise characterization of cancer lesions. In this study, we investigated the influence of respiratory motion and varying noise levels on quantification of textural parameters in patients with lung cancer. Methods: We used an optimal-respiratory-gating algorithm on the list-mode data of 60 lung cancer patients who underwent 18 F-FDG PET. The images were reconstructed using a duty cycle of 35% (percentage of the total acquired PET data). In addition, nongated images of varying statistical quality (using 35% and 100% of the PET data) were reconstructed to investigate the effects of image noise. Several global image-derived indices and textural parameters (entropy, high-intensity emphasis, zone percentage, and dissimilarity) that have been associated with patient outcome were calculated. The clinical impact of optimal respiratory gating and image noise on assessment of intratumor heterogeneity was evaluated using Cox regression models, with overall survival as the outcome measure. The threshold for statistical significance was adjusted for multiple comparisons using Bonferroni correction. Results: In the lower lung lobes, respiratory motion significantly affected quantification of intratumor heterogeneity for all textural parameters (P , 0.007) except entropy (P . 0.007). The mean increase in entropy, dissimilarity, zone percentage, and high-intensity emphasis was 1.3% ± 1.5% (P 5 0.02), 11.6% ± 11.8% (P 5 0.006), 2.3% ± 2.2% (P 5 0.002), and 16.8% ± 17.2% (P 5 0.006), respectively. No significant differences were observed for lesions in the upper lung lobes (P . 0.007). Differences in the statistical quality of the PET images affected the textural parameters less than respiratory motion, with no significant difference observed. The median follow-up time was 35 mo (range, 7-39 mo). In multivariate analysis for overall survival, total lesion glycolysis and high-intensity emphasis were the two most relevant image-derived indices and were considered to be independent significant covariates for the model regardless of the image type considered. Conclusion: The tested textural parameters are robust in the presence of respiratory motion artifacts and varying levels of image noise.

Quantifying lesion volume and uptake in PET is important for patient management. Respiratory motion artefacts introduce inaccuracies in quantification of PET images. Amplitude-based optimal respiratory gating maintains image quality through selection of duty cycle. The effect of respiratory gating on lesion quantification depends on anatomical location.

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