2.1 Patients
Eligibility criteria for this study were as follows: 1) stage IIIB-IV lung adenocarcinoma or recurrent
adenocarcinoma of the lung that failed to respond to frontline chemotherapy or relapsed thereafter; 2) complete recovery from any toxic effects of previous antitumor therapy, and 3) no chemotherapy within one month of enrolment. Patients were excluded in presence of the following criteria: 1) symptomatic brain metastases; 2) severe comorbidities; 3) presence of malignant pleural effusion without other measurable lesions, and 4) active infections. The Institutional Review Board of the Chang Gung memorial hospital approved the study protocol. Written informed consent was obtained from all participants.
2.2 Study Design
This was a single-center, single-arm, open-label study. All patients received oral erlotinib at a fixed dose of 150 mg (one tablet per day). Baseline FDG-PET examinations (day 0 FDG-PET) were performed in the two weeks preceding the start of erlotinib therapy. Follow-up FDG-PET scans were performed at days 14 and 56 after the beginning of erlotinib for the assessment of early and late treatment response, respectively. CT scans were performed both at baseline and on day 56 (Figure
1).
Figure 1
Study schema
2.3 FDG-PET/CT Image Acquisition
Patients were asked to fast 4 h before examination and blood glucose levels were <200mg/dL in all participants. No intravenouscontrast enhancement was used. Patients were injected intravenously with 370–555 MBq 18F-FDG (depending on body weight) and images were acquired 50 min after its
administration. Whole-body PET emission scans were performed from the base of the skull to the mid-thigh with no position changes. FDG-PET/CT was performed using a Discovery ST 16 scanner (GE Healthcare, Milwaukee, WI, USA) in 18 patients, whereas the remaining 5 subjects were imaged on a Biograph mCT scanner (Siemens Medical Solutions, Malvern, PA, USA). Low-dose CT images were used for attenuation correction of PET data. PET images were reconstructed using a CT-based attenuation correction with an ordered-subset expectation maximization iterative reconstruction algorithm (4 iterations and 10 subsets for the Discovery ST16 scanner; 2 iterations and 21 subsets for the Biograph mCT scanner). Using these reconstruction parameters, axial spatial resolutions of PET at the center of the gantry were 4.80 mm and 2.16 mm for the Discovery ST16 and the Biograph mCT scanners, respectively. The two scanners were calibrated for quantitative correlation.
2.4 Imaging Analysis and Assessment of Treatment Response
2.4.1 PET parameters
FDG-PET images were obtained in transaxial planes using a dedicated workstation (Syngo; Siemens Medical Solutions). The SUV for each tumor volume was calculated with the following formula:
(measured activity concentration [Bq/mL])/(injected activity [Bq]/body weight [kg] × 1,000). Rather than the peak SUV utilized by the PERCIST criteria, we measured the maximum SUV within a region of interest (ROI) [11]. A SUV >2.5 was used as the threshold for target volume delineation of the metabolic tumor volume (MTV) [33]. TLG-S was calculated as follows: TLG-S = mean SUV × MTV (cm3) [34].
2.4.2 EORTC criteria
The metabolic response according to the EORTC criteria is based on the same ROI volumes sampled on subsequent scans. A partial metabolic response (PMR) was defined as a SUV reduction ≥25%.
Stable metabolic disease (SMD) was diagnosed in presence of either an increase or a decrease <25%.
Finally, progressive metabolic disease (PMD) was defined as a SUV increase >25% [20].
2.4.3 PERCIST criteria
In line with the standard procedures recommended by the PERCIST criteria, we measured the change in SUV between the hottest single tumor lesion on baseline scan and the hottest single lesion on the subsequent scan. The target lesions may differ between each scan. A complete
metabolic response (CMR) was defined as a complete abrogation of tumor FDG uptake; PMR as a SUV reduction of at least 30%; PMD as either a SUV increase of at least 30% or the development of a new lesion. Finally, SMD was considered to be present when CMR, PMR, and PMD did not occur [21].
2.4.4 TLG-S method
According to the PERCIST recommendations [21], the measurement of TLG-S was based on the delineation of target lesions (two lesions or less per organ, with a maximum of five lesions). PMR was defined 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 [21]. SMD was considered to be present when PMR or PMD did not occur [21].
2.4.5 RECIST criteria
Standard CT response was assessed through an independent review of CT images obtained at day 56 compared with baseline scans. All CT images were analyzed by investigators blinded to PET results.
Target lesions (two lesions or less per organ, with a maximum of five lesions) were identified.
Tumor response was classified as complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD) according to the Response Evaluation Criteria in Solid Tumors (RECIST), version 1.1 [35]. Based on FDG-PET results, patients with CMR or PMR were considered as responders whereas those with SMD or PMD were classified as non-responders. Patients with CR or PR on CT images were classified as responders, whereas those who showed SD or PD were considered as non-responders.
2.5 Texture analysis
Distinct sets of texture features can be extracted from PET images using different matrices. In the present study, we used neighborhood grey-tone difference matrix (NGTDM) for the assessment of third-order texture features [31]. The texture parameters of coarseness, contrast, busyness, complexity, and strength were calculated from the NGTDM according to previous literatures of lung cancer studies [32, 36]. The computations of the textural features were performed using a homemade software package (Chang-Gung Image Texture Analysis toolbox; CGITA) implemented under MATLAB 2012a (Mathworks Inc., Natick, MA, USA) [37].
2.6 Statistical Analysis
Progression-free survival (PFS) and overall survival (OS) served as the main outcome measures.
PFS was defined as the time from the date of inclusion in the study to disease recurrence or progression. OS was defined as the time from the date of inclusion in the study to the date of death from any cause or last follow-up. Survival curves were plotted with the Kaplan-Meier method and compared using the log-rank test. Cox regression analysis was used to calculate the adjusted hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs). All calculations were performed with the SPSS 18.0 statistical package (SPSS Inc. Chicago, IL, USA). Two-tailed P values < 0.05 were considered statistically significant.