Dataset Information

Pretreatment FDG-PET metrics in stage III non-small cell lung cancer: ACRIN 6668/RTOG 0235.

ABSTRACT: ACRIN 6668/RTOG 0235 evaluated the prognostic value of positron emission tomography with (18)F-fluorodeoxyglucose (FDG-PET) uptake before and after definitive, concurrent, platinum-based chemoradiotherapy for locally advanced non-small cell lung cancer (NSCLC). In this secondary analysis, we evaluate volumetric pretreatment PET measures as predictors of clinical outcomes.Patients with stage III NSCLC underwent FDG-PET prior to treatment. A commercially available gradient-based segmentation tool was used to contour all visible hypermetabolic lesions on each scan. For each patient, the maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total glycolytic activity (TGA) for all contoured lesions were recorded. Cox proportional hazards regression models were used to evaluate clinical variables and PET metrics as predictors of overall survival (OS) and locoregional control (LRC). Time-dependent covariables were added to the models when necessary to address nonproportional hazards. All statistical tests were two-sided.Complete data were available for 214 patients in the OS analysis and 189 subjects in the LRC analysis. In multivariable analysis incorporating clinical and imaging data available prior to treatment, MTV was an independent predictor of OS (HR = 1.04 per 10 cm(3) increase, 95% CI = 1.03 to 1.06, P < .001). High MTV was also associated with increased risk of locoregional failure at baseline (HR = 1.16 per 10 cm(3) increase, 95% CI = 1.08 to 1.23, P < .001) and at six months (HR = 1.05 per 10 cm(3) increase, 95% CI = 1.02 to 1.07, P < .001) but not at 12 months or later time points.Pretreatment MTV is a predictor of clinical outcomes for NSCLC patients treated with chemoradiotherapy. Quantitative PET measures may serve as stratification factors in clinical trials for this patient population and may help guide novel trial designs.

SUBMITTER: Ohri N

PROVIDER: S-EPMC4402361 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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Pretreatment FDG-PET metrics in stage III non-small cell lung cancer: ACRIN 6668/RTOG 0235.

Ohri Nitin N Duan Fenghai F Machtay Mitchell M Gorelick Jeremy J JJ Snyder Bradley S BS Alavi Abass A Siegel Barry A BA Johnson Douglas W DW Bradley Jeffrey D JD DeNittis Albert A Werner-Wasik Maria M

Journal of the National Cancer Institute 20150216 4

<h4>Background</h4>ACRIN 6668/RTOG 0235 evaluated the prognostic value of positron emission tomography with (18)F-fluorodeoxyglucose (FDG-PET) uptake before and after definitive, concurrent, platinum-based chemoradiotherapy for locally advanced non-small cell lung cancer (NSCLC). In this secondary analysis, we evaluate volumetric pretreatment PET measures as predictors of clinical outcomes.<h4>Methods</h4>Patients with stage III NSCLC underwent FDG-PET prior to treatment. A commercially availabl ...[more]

PMID: 25688115

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Project description:UnlabelledIn a secondary analysis of American College of Radiology Imaging Network (ACRIN) 6668/RTOG 0235, high pretreatment metabolic tumor volume (MTV) on (18)F-FDG PET was found to be a poor prognostic factor for patients treated with chemoradiotherapy for locally advanced non-small cell lung cancer (NSCLC). Here we utilize the same dataset to explore whether heterogeneity metrics based on PET textural features can provide additional prognostic information.MethodsPatients with locally advanced NSCLC underwent (18)F-FDG PET prior to treatment. A gradient-based segmentation tool was used to contour each patient's primary tumor. MTV, maximum SUV, and 43 textural features were extracted for each tumor. To address overfitting and high collinearity among PET features, the least absolute shrinkage and selection operator (LASSO) method was applied to identify features that were independent predictors of overall survival (OS) after adjusting for MTV. Recursive binary partitioning in a conditional inference framework was utilized to identify optimal thresholds. Kaplan-Meier curves and log-rank testing were used to compare outcomes among patient groups.ResultsTwo hundred one patients met inclusion criteria. The LASSO procedure identified 1 textural feature (SumMean) as an independent predictor of OS. The optimal cutpoint for MTV was 93.3 cm(3), and the optimal SumMean cutpoint for tumors above 93.3 cm(3) was 0.018. This grouped patients into three categories: low tumor MTV (n = 155; median OS, 22.6 mo), high tumor MTV and high SumMean (n = 23; median OS, 20.0 mo), and high tumor MTV and low SumMean (n = 23; median OS, 6.2 mo; log-rank P < 0.001).ConclusionWe have described an appropriate methodology to evaluate the prognostic value of textural PET features in the context of established prognostic factors. We have also identified a promising feature that may have prognostic value in locally advanced NSCLC patients with large tumors who are treated with chemoradiotherapy. Validation studies are warranted.

Project description:PURPOSE:In recent years, multiple studies have demonstrated the value of volumetric FDG-PET/CT parameters as independent prognostic factors in patients with non-small cell lung cancer (NSCLC). We aimed to determine the optimal cut-off points of pretreatment volumetric FDG-PET/CT parameters in predicting overall survival (OS) in patients with locally advanced NSCLC and to recommend imaging biomarkers appropriate for routine clinical applications. METHODS:Patients with inoperable stage IIB/III NSCLC enrolled in ACRIN 6668/RTOG 0235 were included. Pretreatment FDG-PET scans were quantified using semiautomatic adaptive contrast-oriented thresholding and local-background partial-volume-effect-correction algorithms. For each patient, the following indices were measured: metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUVmax, SUVmean, partial-volume-corrected TLG (pvcTLG), and pvcSUVmean for the whole-body, primary tumor, and regional lymph nodes. The association between each index and patient outcome was assessed using Cox proportional hazards regression. Optimal cut-off points were estimated using recursive binary partitioning in a conditional inference framework and used in Kaplan-Meier curves with log-rank testing. The discriminatory ability of each index was examined using time-dependent receiver operating characteristic (ROC) curves and corresponding area under the curve (AUC(t)). RESULTS:The study included 196 patients. Pretreatment whole-body and primary tumor MTV, TLG, and pvcTLG were independently prognostic of OS. Optimal cut-off points were 175.0, 270.9, and 35.5 cm3 for whole-body TLG, pvcTLG, and MTV, and were 168.2, 239.8, and 17.4 cm3 for primary tumor TLG, pvcTLG, and MTV, respectively. In time-dependent ROC analysis, AUC(t) for MTV and TLG were uniformly higher than that of SUV measures over all time points. Primary tumor and whole-body parameters demonstrated similar patterns of separation for those patients above versus below the optimal cut-off points in Kaplan-Meier curves and in time-dependent ROC analysis. CONCLUSION:We demonstrated that pretreatment whole-body and primary tumor volumetric FDG-PET/CT parameters, including MTV, TLG, and pvcTLG, are strongly prognostic for OS in patients with locally advanced NSCLC, and have similar discriminatory ability. Therefore, we believe that, after validation in future trials, the derived optimal cut-off points for primary tumor volumetric FDG-PET/CT parameters, or their more refined versions, could be incorporated into routine clinical practice, and may provide more accurate prognostication and staging based on tumor metabolic features.

Project description:PURPOSE:The American College of Radiology Imaging Network (ACRIN) 6668/Radiation Therapy Oncology Group (RTOG) 0235 study demonstrated that standardized uptake values (SUV) on post-treatment [(18)F]fluorodeoxyglucose-positron emission tomography (FDG-PET) correlated with survival in locally advanced non-small cell lung cancer (NSCLC). This secondary analysis determined whether SUV of regional lymph nodes (RLNs) on post-treatment FDG-PET correlated with patient outcomes. METHODS AND MATERIALS:Included for analysis were patients treated with concurrent chemoradiation therapy, using radiation doses ?60 Gy, with identifiable FDG-avid RLNs (distinct from primary tumor) on pretreatment FDG-PET, and post-treatment FDG-PET data. ACRIN core laboratory SUV measurements were used. Event time was calculated from the date of post-treatment FDG-PET. Local-regional failure was defined as failure within the treated RT volume and reported by the treating institution. Statistical analyses included Wilcoxon signed rank test, Kaplan-Meier curves (log rank test), and Cox proportional hazards regression modeling. RESULTS:Of 234 trial-eligible patients, 139 (59%) had uptake in both primary tumor and RLNs on pretreatment FDG-PET and had SUV data from post-treatment FDG-PET. Maximum SUV was greater for primary tumor than for RLNs before treatment (P<.001) but not different post-treatment (P=.320). Post-treatment SUV of RLNs was not associated with overall survival. However, elevated post-treatment SUV of RLNs, both the absolute value and the percentage of residual activity compared to the pretreatment SUV were associated with inferior local-regional control (P<.001). CONCLUSIONS:High residual metabolic activity in RLNs on post-treatment FDG-PET is associated with worse local-regional control. Based on these data, future trials evaluating a radiation therapy boost should consider inclusion of both primary tumor and FDG-avid RLNs in the boost volume to maximize local-regional control.

Project description:PurposeIn this prospective National Cancer Institute-funded American College of Radiology Imaging Network/Radiation Therapy Oncology Group cooperative group trial, we hypothesized that standardized uptake value (SUV) on post-treatment [(18)F]fluorodeoxyglucose positron emission tomography (FDG-PET) correlates with survival in stage III non-small-cell lung cancer (NSCLC).Patients and methodsPatients received conventional concurrent platinum-based chemoradiotherapy without surgery; postradiotherapy consolidation chemotherapy was allowed. Post-treatment FDG-PET was performed at approximately 14 weeks after radiotherapy. SUVs were analyzed both as peak SUV (SUVpeak) and maximum SUV (SUVmax; both institutional and central review readings), with institutional SUVpeak as the primary end point. Relationships between the continuous and categorical (cutoff) SUVs and survival were analyzed using Cox proportional hazards multivariate models.ResultsOf 250 enrolled patients (226 were evaluable for pretreatment SUV), 173 patients were evaluable for post-treatment SUV analyses. The 2-year survival rate for the entire population was 42.5%. Pretreatment SUVpeak and SUVmax (mean, 10.3 and 13.1, respectively) were not associated with survival. Mean post-treatment SUVpeak and SUVmax were 3.2 and 4.0, respectively. Post-treatment SUVpeak was associated with survival in a continuous variable model (hazard ratio, 1.087; 95% CI, 1.014 to 1.166; P = .020). When analyzed as a prespecified binary value (≤ v > 3.5), there was no association with survival. However, in exploratory analyses, significant results for survival were found using an SUVpeak cutoff of 5.0 (P = .041) or 7.0 (P < .001). All results were similar when SUVmax was used in univariate and multivariate models in place of SUVpeak.ConclusionHigher post-treatment tumor SUV (SUVpeak or SUVmax) is associated with worse survival in stage III NSCLC, although a clear cutoff value for routine clinical use as a prognostic factor is uncertain at this time.

Project description:ObjectivesThis study investigated harmonized pretreatment volume-based quantitative FDG-PET/CT parameters in breast cancer patients for prognostic value.ResultsDuring a median overall follow-up period of 5.3 years, 91 patients had recurrence and 40 died. Multivariate analysis of ER-positive/HER2-negative patients showed high maximum standardized uptake value (SUVmax) (p = 0.018), high total lesion glycolysis (TLG) (p = 0.010), and clinical N-classification (p = 0.0027) as independent negative predictors of RFS, while high maximum SUVmax (p = 0.037), advanced clinical T-classification (p = 0.030), and advanced TNM stage (p = 0.0067) were independent negative predictors of OS. For recurrence and death in HER2-positive patients, high total TLG (p = 0.037, p = 0.0048, respectively) and advanced TNM stage (p = 0.048, p = 0.046, respectively) were independent prediction factors. In the triple-negative group, independent factors related to recurrence and death were high maximum SUVmax (p = 0.0014, p = 0.0003, respectively) and advanced TNM stage (p < 0.0001, p < 0.0001, respectively).Materials and methodsRecords of 546 stage I-III invasive breast cancer patients, including 344 estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative, 110 HER2-positive, and 92 triple-negative cases, treated at four institutions were reviewed retrospectively. Harmonized primary tumor and nodal maximum SUVmax, metabolic tumor volume (MTV), and TLG indicated in pretreatment FDG-PET/CT results were analyzed. Evaluations of relationships of clinicopathological factors, volume-based quantitative parameters, recurrence-free survival (RFS), and overall survival (OS) for each subtype were performed with a Cox proportional hazards model and log-rank test.ConclusionsThe results indicated that potential surrogate markers for prognosis in patients with the three main subtypes of operable breast cancer include harmonized pretreatment quantitative volume-based FDG-PET/CT parameters, particularly whole-lesion SUVmax and TLG.

Project description:We investigated the correlation between metabolic response by (18)F-FDG PET and objective response, glucose transporter type 4 (GLUT4) expression, and KIT/PDGFRA mutation status in patients with gastrointestinal stromal tumor undergoing neoadjuvant imatinib mesylate therapy.(18)F-FDG PET was performed at baseline, 1-7 d, and 4 or 8 wk after imatinib mesylate initiation. Best objective response was defined by version 1.0 of the Response Evaluation Criteria in Solid Tumors (RECIST). Mutational analysis and tumor GLUT4 expression by immunohistochemistry were done on tissue obtained at baseline or surgery.(18)F-FDG PET showed high baseline tumor glycolytic activity (mean SUV(max), 14.2; range, 1.3-53.2), decreasing after 1 wk of imatinib mesylate (mean, 5.5; range, -0.5-47.7, P < 0.001, n = 44), and again before surgery (mean, 3.0; range, -0.5-36.1, P < 0.001, n = 40). At week 1, there were 3 patients with complete metabolic response (CMR), 33 with partial metabolic response (PMR), 6 with stable metabolic disease (SMD), and 2 with progressive metabolic disease (PMD). Before surgery, there were 3 with CMR, 33 with PMR, 4 with SMD, and none with PMD. The best response according to RECIST was 2 with partial response, 36 with stable disease, and 1 with progressive disease (n = 39). Of the patients with a posttreatment decrease in GLUT4 expression, 1 had CMR, 15 had PMR, 2 had SMD, and 1 had PMD at week 1, whereas before surgery 1 patient had CMR, 16 had PMR, 2 had SMD, and none had PMD. Among 27 patients with KIT exon 11 mutations, 1 had CMR, 22 had PMR, 3 had SMD, and 1 had PMD at week 1, whereas 1 had CMR, 22 had PMR, 2 had SMD, and 2 were unknown before surgery; among 4 patients with a wild-type genotype, 2 had PMR and 2 SMD at week 1, whereas 1 had CMR, 2 had PMR, and 1 had SMD before surgery.After imatinib mesylate initiation, metabolic response by (18)F-FDG PET was documented earlier (1-7 d) and was of much greater magnitude (36/44) than that documented by RECIST (2/39). Immunohistochemistry data suggest that GLUT4 may play a role in (18)F-FDG uptake in gastrointestinal stromal tumor, GLUT4 levels decrease after imatinib mesylate therapy in most patients with PMR, and the biologic action of imatinib mesylate interacts with glycolysis and GLUT4 expression. A greater than 85% metabolic response was observed as early as days 1-7 in patients with exon 11 mutations.

Project description:PurposeFor pediatric lymphoma, quantitative FDG PET/CT imaging features such as metabolic tumor volume (MTV) are important for prognosis and risk stratification strategies. However, feature extraction is difficult and time-consuming in cases of high disease burden. The purpose of this study was to fully automate the measurement of PET imaging features in PET/CT images of pediatric lymphoma.Methods18F-FDG PET/CT baseline images of 100 pediatric Hodgkin lymphoma patients were retrospectively analyzed. Two nuclear medicine physicians identified and segmented FDG avid disease using PET thresholding methods. Both PET and CT images were used as inputs to a three-dimensional patch-based, multi-resolution pathway convolutional neural network architecture, DeepMedic. The model was trained to replicate physician segmentations using an ensemble of three networks trained with 5-fold cross-validation. The maximum SUV (SUVmax), MTV, total lesion glycolysis (TLG), surface-area-to-volume ratio (SA/MTV), and a measure of disease spread (Dmaxpatient) were extracted from the model output. Pearson's correlation coefficient and relative percent differences were calculated between automated and physician-extracted features.ResultsMedian Dice similarity coefficient of patient contours between automated and physician contours was 0.86 (IQR 0.78-0.91). Automated SUVmax values matched exactly the physician determined values in 81/100 cases, with Pearson's correlation coefficient (R) of 0.95. Automated MTV was strongly correlated with physician MTV (R = 0.88), though it was slightly underestimated with a median (IQR) relative difference of - 4.3% (- 10.0-5.7%). Agreement of TLG was excellent (R = 0.94), with median (IQR) relative difference of - 0.4% (- 5.2-7.0%). Median relative percent differences were 6.8% (R = 0.91; IQR 1.6-4.3%) for SA/MTV, and 4.5% (R = 0.51; IQR - 7.5-40.9%) for Dmaxpatient, which was the most difficult feature to quantify automatically.ConclusionsAn automated method using an ensemble of multi-resolution pathway 3D CNNs was able to quantify PET imaging features of lymphoma on baseline FDG PET/CT images with excellent agreement to reference physician PET segmentation. Automated methods with faster throughput for PET quantitation, such as MTV and TLG, show promise in more accessible clinical and research applications.

Dataset Information

Pretreatment FDG-PET metrics in stage III non-small cell lung cancer: ACRIN 6668/RTOG 0235.

Publications

Pretreatment FDG-PET metrics in stage III non-small cell lung cancer: ACRIN 6668/RTOG 0235.

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