Effects of Tracer Uptake Time in Non-Small Cell Lung Cancer 18F-FDG PET Radiomics.

PET radiomics applied to oncology allow the measurement of intratumoral heterogeneity. This quantification can be affected by image protocols; hence, there is an increased interest in understanding how radiomic expression on PET images is affected by different imaging conditions. To address that interest, this study explored how radiomic features are affected by changes in 18F-FDG uptake time, image reconstruction, lesion delineation, and radiomic binning settings. Methods: Ten non-small cell lung cancer patients underwent 18F-FDG PET on 2 consecutive days. On each day, scans were obtained at 60 and 90 min after injection and reconstructed following EARL version 1 and with point-spread-function resolution modeling (PSF-EARL2). Lesions were delineated with an SUV threshold of 4.0, with 40% of SUVmax, and with a contrast-based isocontour. PET image intensity was discretized with both a fixed bin width (FBW) and a fixed bin number before the calculation of the radiomic features. Repeatability of features was measured with the intraclass correlation coefficient, and the change in feature value over time was calculated as a function of its repeatability. Features were then classified into use-case scenarios based on their repeatability and susceptibility to tracer uptake time. Results: With PSF-EARL2 reconstruction, 40% of SUVmax lesion delineation, and FBW intensity discretization, most features (94%) were repeatable at both uptake times (intraclass correlation coefficient > 0.9), 35% being classified for dual-time-point use cases as being sensitive to changes in uptake time, 39% were classified for cross-sectional studies with an unclear dependency on time, 20% were classified for cross-sectional use while being robust to uptake time changes, and 6% were discarded for poor repeatability. EARL version 1 images had 1 fewer repeatable feature (neighborhood gray-level different matrix coarseness) than PSF-EARL2; the contrast-based delineation had the poorest repeatability of the delineation methods, with 45% of features being discarded; and fixed bin number resulted in lower repeatability than FBW (45% and 6% of features were discarded, respectively). Conclusion: Repeatability was maximized with PSF-EARL2 reconstruction, lesion delineation at 40% of SUVmax, and FBW intensity discretization. On the basis of their susceptibility to uptake time, radiomic features were classified into specific non-small cell lung cancer PET radiomics use cases.

Parametric Method Performance for Dynamic 3'-Deoxy-3'-18F-Fluorothymidine PET/CT in Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Carcinoma Patients Before and During Therapy.

The objective of this study was to validate several parametric methods for quantification of 3'-deoxy-3'-18F-fluorothymidine (18F-FLT) PET in advanced-stage non-small cell lung carcinoma (NSCLC) patients with an activating epidermal growth factor receptor mutation who were treated with gefitinib or erlotinib. Furthermore, we evaluated the impact of noise on accuracy and precision of the parametric analyses of dynamic 18F-FLT PET/CT to assess the robustness of these methods. Methods: Ten NSCLC patients underwent dynamic 18F-FLT PET/CT at baseline and 7 and 28 d after the start of treatment. Parametric images were generated using plasma input Logan graphic analysis and 2 basis functions-based methods: a 2-tissue-compartment basis function model (BFM) and spectral analysis (SA). Whole-tumor-averaged parametric pharmacokinetic parameters were compared with those obtained by nonlinear regression of the tumor time-activity curve using a reversible 2-tissue-compartment model with blood volume fraction. In addition, 2 statistically equivalent datasets were generated by countwise splitting the original list-mode data, each containing 50% of the total counts. Both new datasets were reconstructed, and parametric pharmacokinetic parameters were compared between the 2 replicates and the original data. Results: After the settings of each parametric method were optimized, distribution volumes (VT) obtained with Logan graphic analysis, BFM, and SA all correlated well with those derived using nonlinear regression at baseline and during therapy (R2 ≥ 0.94; intraclass correlation coefficient > 0.97). SA-based VT images were most robust to increased noise on a voxel-level (repeatability coefficient, 16% vs. >26%). Yet BFM generated the most accurate K1 values (R2 = 0.94; intraclass correlation coefficient, 0.96). Parametric K1 data showed a larger variability in general; however, no differences were found in robustness between methods (repeatability coefficient, 80%-84%). Conclusion: Both BFM and SA can generate quantitatively accurate parametric 18F-FLT VT images in NSCLC patients before and during therapy. SA was more robust to noise, yet BFM provided more accurate parametric K1 data. We therefore recommend BFM as the preferred parametric method for analysis of dynamic 18F-FLT PET/CT studies; however, SA can also be used.

Accuracy and Precision of Partial-Volume Correction in Oncological PET/CT Studies.

Accurate quantification of tracer uptake in small tumors using PET is hampered by the partial-volume effect as well as by the method of volume-of-interest (VOI) delineation. This study aimed to investigate the effect of partial-volume correction (PVC) combined with several VOI methods on the accuracy and precision of quantitative PET. METHODS: Four image-based PVC methods and resolution modeling (applied as PVC) were used in combination with several common VOI methods. Performance was evaluated using simulations, phantom experiments, and clinical repeatability studies. Simulations were based on a whole-body 18F-FDG PET scan in which differently sized spheres were placed in lung and mediastinum. A National Electrical Manufacturers Association NU2 quality phantom was used for the experiments. Repeatability data consisted of an 18F-FDG PET/CT study on 11 patients with advanced non-small cell lung cancer and an 18F-fluoromethylcholine PET/CT study on 12 patients with metastatic prostate cancer. RESULTS: Phantom data demonstrated that most PVC methods were strongly affected by the applied resolution kernel, with accuracy differing by about 20%-50% between full-width-at-half-maximum settings of 5.0 and 7.5 mm. For all PVC methods, large differences in accuracy were seen among all VOI methods. Additionally, the image-based PVC methods were observed to have variable sensitivity to the accuracy of the VOI methods. For most PVC methods, accuracy was strongly affected by more than a 2.5-mm misalignment of true (simulated) VOI. When the optimal VOI method for each PVC method was used, high accuracy could be achieved. For example, resolution modeling for mediastinal lesions and iterative deconvolution for lung lesions were 99% ± 1.5% and 99% ± 0.9% accurate, respectively, for spheres 15-40 mm in diameter. Precision worsened slightly for resolution modeling and to a larger extent for some image-based PVC methods. Uncertainties in delineation propagated into uncertainties in PVC performance, as confirmed by the clinical data. CONCLUSION: The accuracy and precision of the tested PVC methods depended strongly on VOI method, resolution settings, contrast, and spatial alignment of the VOI. PVC has the potential to substantially improve the accuracy of tracer uptake assessment, provided that robust and accurate VOI methods become available. Commonly used delineation methods may not be adequate for this purpose.

Repeatability of Quantitative Whole-Body 18F-FDG PET/CT Uptake Measures as Function of Uptake Interval and Lesion Selection in Non-Small Cell Lung Cancer Patients.

UNLABELLED: Change in (18)F-FDG uptake may predict response to anticancer treatment. The PERCIST suggest a threshold of 30% change in SUV to define partial response and progressive disease. Evidence underlying these thresholds consists of mixed stand-alone PET and PET/CT data with variable uptake intervals and no consensus on the number of lesions to be assessed. Additionally, there is increasing interest in alternative (18)F-FDG uptake measures such as metabolically active tumor volume and total lesion glycolysis (TLG). The aim of this study was to comprehensively investigate the repeatability of various quantitative whole-body (18)F-FDG metrics in non-small cell lung cancer (NSCLC) patients as a function of tracer uptake interval and lesion selection strategies. METHODS: Eleven NSCLC patients, with at least 1 intrathoracic lesion 3 cm or greater, underwent double baseline whole-body (18)F-FDG PET/CT scans at 60 and 90 min after injection within 3 d. All (18)F-FDG-avid tumors were delineated with an 50% threshold of SUVpeak adapted for local background. SUVmax, SUVmean, SUVpeak, TLG, metabolically active tumor volume, and tumor-to-blood and -liver ratios were evaluated, as well as the influence of lesion selection and 2 methods for correction of uptake time differences. RESULTS: The best repeatability was found using the SUV metrics of the averaged PERCIST target lesions (repeatability coefficients < 10%). The correlation between test and retest scans was strong for all uptake measures at either uptake interval (intraclass correlation coefficient > 0.97 and R(2) > 0.98). There were no significant differences in repeatability between data obtained 60 and 90 min after injection. When only PERCIST-defined target lesions were included (n = 34), repeatability improved for all uptake values. Normalization to liver or blood uptake or glucose correction did not improve repeatability. However, after correction for uptake time the correlation of SUV measures and TLG between the 60- and 90-min data significantly improved without affecting test-retest performance. CONCLUSION: This study suggests that a 15% change of SUVmean/SUVpeak at 60 min after injection can be used to assess response in advanced NSCLC patients if up to 5 PERCIST target lesions are assessed. Lower thresholds could be used in averaged PERCIST target lesions (<10%).