Introduction: Epidermal growth factor receptor (EGFR) mutated NSCLC is best treated using an EGFR tyrosine kinase inhibitor (TKI). The presence and accessibility of EGFR overexpression and mutation in NSCLC can be determined using radiolabeled EGFR TKI PET/CT. However, recent research has shown a significant difference between image qualities (i.e., tumor-to-lung contrast) in three generation EGFR TKIs: ¹¹C-erlotinib, ¹⁸F-afatinib and ¹¹C-osimertinib. In this research we aim to develop a physiological pharmacokinetic (PBPK)-model to predict tumor-to-lung contrast and as a secondary outcome the uptake of healthy tissue of the three tracers. Methods: Relevant physicochemical and drug specific properties (e.g., pKa, lipophilicity, target binding) for each TKI were collected and applied in established base PBPK models. Key hallmarks of NSCLC include: immune tumor deprivation, unaltered tumor perfusion and an acidic tumor environment. Model accuracy was demonstrated by calculating the prediction error (PE) between predicted tissue-to-blood ratios (TBR) and measured PET-image-derived TBR. Sensitivity analysis was performed by excluding each key component and comparing the PE with the final mechanistical PBPK model predictions. Results: The developed PBPK models were able to predict tumor-to-lung contrast for all EGFR-TKIs within threefold of observed PET image ratios (PE tumor-to-lung ratio of −90%, +44% and −6.3% for erlotinib, afatinib and osimertinib, respectively). Furthermore, the models depicted agreeable whole-body distribution, showing high tissue distribution for osimertinib and afatinib and low tissue distribution at high blood concentrations for erlotinib (mean PE, of −10.5%, range −158%–+190%, for all tissues). Conclusion: The developed PBPK models adequately predicted the image quality of afatinib and osimertinib and erlotinib. Some deviations in predicted whole-body TBR lead to new hypotheses, such as increased affinity for mutated EGFR and active influx transport (erlotinib into excreting tissues) or active efflux (afatinib from brain), which is currently unaccounted for. In the future, PBPK models may be used to predict the image quality of new tracers.

Background: Patients with non-small cell lung cancer (NSCLC) driven by activating epidermal growth factor receptor (EGFR) mutations are best treated with therapies targeting EGFR, i.e., tyrosine kinase inhibitors (TKI). Radiolabeled EGFR-TKI and PET have been investigated to study EGFR-TKI kinetics and its potential role as biomarker of response in NSCLC patients with EGFR mutations (EGFRm). In this study we aimed to compare the biodistribution and kinetics of three different EGFR-TKI, i.e., ¹¹C-erlotinib, ¹⁸F-afatinib and ¹¹C-osimertinib. Methods: Data of three prospective studies and 1 ongoing study were re-analysed; data from thirteen patients (EGFRm) were included for ¹¹C-erlotinib, seven patients for ¹⁸F-afatinib (EGFRm and EGFR wild type) and four patients for ¹¹C-osimertinib (EGFRm). From dynamic and static scans, SUV and tumor-to-blood (TBR) values were derived for tumor, lung, spleen, liver, vertebra and, if possible, brain tissue. AUC values were calculated using dynamic time-activity-curves. Parent fraction, plasma-to-blood ratio and SUV values were derived from arterial blood data. Tumor-to-lung contrast was calculated, as well as (background) noise to assess image quality. Results: ¹¹C-osimertinib showed the highest SUV and TBR (AUC) values in nearly all tissues. Spleen uptake was notably high for ¹¹C-osimertinib and to a lesser extent for ¹⁸F-afatinib. For EGFRm, ¹¹C-erlotinib and ¹⁸F-afatinib demonstrated the highest tumor-to-lung contrast, compared to an inverse contrast observed for ¹¹C-osimertinib. Tumor-to-lung contrast and spleen uptake of the three TKI ranked accordingly to the expected lysosomal sequestration. Conclusion: Comparison of biodistribution and tracer kinetics showed that ¹¹C-erlotinib and ¹⁸F-afatinib demonstrated the highest tumor-to-background contrast in EGFRm positive tumors. Image quality, based on contrast and noise analysis, was superior for ¹¹C-erlotinib and ¹⁸F-afatinib (EGFRm) scans compared to ¹¹C-osimertinib and ¹⁸F-afatinib (EGFR wild type) scans.

Non-small cell lung cancer (NSCLC) tumors harboring common (exon19del, L858R) and uncommon (e.g. G719X, L861Q) activating epidermal growth factor receptor (EGFR) mutations are best treated with EGFR tyrosine kinase inhibitors (TKI) such as the first-generation EGFR TKI erlotinib, second-generation afatinib or third-generation osimertinib. However, identifying these patients through biopsy is not always possible. Therefore, our aim was to evaluate whether 18F-afatinib PET/CT could identify patients with common and uncommon EGFR mutations. Furthermore, we evaluated the relation between tumor 18F-afatinib uptake and response to afatinib therapy. 18F-afatinib PET/CT was performed in 12 patients: 6 EGFR wild type (WT), 3 EGFR common and 3 EGFR uncommon mutations. Tumor uptake of 18F-afatinib was quantified using TBR_WB60-90 (tumor-to-whole blood activity ratio 60-90 min post-injection) for each tumor. Response was quantified per lesion using percentage of change (PC): [(response measurement (RM)-baseline measurement (BM))/BM]×100. Statistical analyses were performed using t-tests, correlation plots and sensitivity/specificity analysis. Twenty-one tumors were identified. Injected dose was 348 ± 31 MBq. Group differences were significant between WT versus EGFR (common and uncommon) activating mutations (p = 0.03). There was no significant difference between EGFR common versus uncommon mutations (p = 0.94). A TBR_WB60-90 cut-off value of 6 showed the best relationship with response with a sensitivity of 70 %, a specificity of 100 % and a positive predictive value of 100 %. 18F-afatinib uptake was higher in tumors with EGFR mutations (common and uncommon) compared to WT. Furthermore, a TBR_WB60-90 cut-off of 6 was found to best predict response to therapy. 18F-afatinib PET/CT could provide a means to identify EGFR mutation positive patients who benefit from afatinib therapy.

Introduction: Only a subgroup of non-small cell lung cancer (NSCLC) patients benefit from treatment using epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI) such as afatinib. Tumour uptake of [¹⁸F]afatinib using positron emission tomography (PET) may identify those patients that respond to afatinib therapy. Therefore, the aim of this study was to find the optimal tracer kinetic model for quantification of [¹⁸F]afatinib uptake in NSCLC tumours. Methods: [¹⁸F]Afatinib PET scans were performed in 10 NSCLC patients. The first patient was scanned for the purpose of dosimetry. Subsequent patients underwent a 20-min dynamic [¹⁵O]H₂O PET scan (370 MBq) followed by a dynamic [¹⁸F]afatinib PET scan (342 ± 24 MBq) of 60 or 90 min. Using the Akaike information criterion (AIC), three pharmacokinetic plasma input models were evaluated with both metabolite-corrected sampler-based input and image-derived (IDIF) input functions in combination with discrete blood samples. Correlation analysis of arterial on-line sampling versus IDIF was performed. In addition, perfusion dependency and simplified measures were assessed. Results: Ten patients were included. The injected activity of [¹⁸F]afatinib was 341 ± 37 MBq. Fifteen tumours could be identified in the field of view of the scanner. Based on AIC, tumour kinetics were best described using an irreversible two-tissue compartment model and a metabolite-corrected sampler-based input function (Akaike 50%). Correlation of plasma-based input functions with metabolite-corrected IDIF was very strong (r² = 0.93). The preferred simplified uptake parameter was the tumour-to-blood ratio over the 60- to 90-min time interval (TBR_60–90). Tumour uptake of [¹⁸F]afatinib was independent of perfusion. Conclusion: The preferred pharmacokinetic model for quantifying [¹⁸F]afatinib uptake in NSCLC tumours was the 2T3K_vb model. TBR_60–90 showed excellent correlation with this model and is the best candidate simplified method. Trial registration: https://eudract.ema.europa.eu/ nr 2012-002849-38

Non-small cell lung cancer (NSCLC) has one of the highest cancer-related mortality rates worldwide. In a subgroup of NSCLC, tumor growth is driven by epidermal growth factor receptors (EGFR) that harbor an activating mutation. These patients are best treated with EGFR tyrosine kinase inhibitors (EGFR TKI). Identifying the EGFR mutational status on a tumor biopsy or a liquid biopsy using tumor DNA sequencing techniques is the current approach to predict tumor response on EGFR TKI therapy. However, due to difficulty in reaching tumor sites, and varying inter- and intralesional tumor heterogeneity, biopsies are not always possible or representative of all tumor lesions, highlighting the need for alternative biomarkers that predict tumor response. Positron emission tomography (PET) studies using EGFR TKI-based tracers have shown that EGFR mutational status could be identified, and that tracer uptake could potentially be used as a biomarker for tumor response. However, despite their likely predictive and monitoring value, the EGFR TKI-PET biomarkers are not yet qualified to be used in the routine clinical practice. In this review, we will discuss the currently investigated EGFR-directed PET biomarkers, elaborate on the typical biomarker development process, and describe how the advances, challenges, and opportunities of EGFR PET biomarkers relate to this process on their way to qualification for routine clinical practice.