Metabolic tumor volume predicts overall survival and local control in patients with stage III non-small cell lung cancer treated in ACRIN 6668/RTOG 0235

Prognostic significance of total metabolic tumor volume on baseline 18F-FDG PET/CT in patients with lung adenocarcinoma: further stratification of the ninth edition of TNM staging subgroups

BACKGROUND

This study aimed to investigate the prognostic value of baseline total metabolic tumor volume (TMTV) on 18F-fluorodeoxyglucose positron emission tomography/computed tomography and its potential for further stratification within the ninth tumor-node-metastasis (TNM) staging system in patients with lung adenocarcinoma (LUAD).

METHODS

A cohort of 384 patients with LUAD who had undergone pretreatment PET/CT were included in this retrospective study. The optimal cutoff value for TMTV was determined through analysis of time-dependent receiver operating characteristic curves. The analysis of overall survival (OS) was conducted utilizing Kaplan-Meier curves. Predictive capacity was evaluated using the C statistic.

RESULTS

The optimal cutoff value for TMTV was 40.13 ml. The survival rates of patients varied significantly across stages I (n = 164), II (n = 37), III (n = 46), and IV (n = 137); however, there was no statistically significant difference between stages II and III (P = 0.440). In stages II-IV, the 2-year OS rates for patients with TMTV less than 40.13 ml were significantly higher at 81.7 and 86.7%, respectively, compared with patients with TMTV greater than equal to 40.13 ml who had rates of only 56.5 and 42.5%. No patients with stage I presented TMTV greater than or equal to 40.13 ml, and the 2-year OS rate was 98.3%. The C index did not reveal a significant difference between TNM and TMTV in their predictive ability for OS (0.83 vs. 0.85, P = 0.159).

CONCLUSION

The TNM staging system demonstrates robust prognostic utility in patients with LUAD, while the incorporation of baseline TMTV may offer additional risk stratification within distinct TNM stages.

Prognostic value of metabolic tumor volume on [18F]FDG PET/CT in addition to the TNM classification system of locally advanced non-small cell lung cancer

PURPOSE

Staging of non-small cell lung cancer (NSCLC) is commonly based on [18F]FDG PET/CT, in particular to exclude distant metastases and guide local therapy approaches like resection and radiotherapy. Although it is hoped that PET/CT will increase the value of primary staging compared to conventional imaging, it is generally limited to the characterization of TNM. The first aim of this study was to evaluate the PET parameter metabolic tumor volume (MTV) above liver background uptake as a prognostic marker in lung cancer. The second aim was to investigate the possibility of incorporating MTV into the TNM classification system for disease prognosis in locally advanced NSCLC treated with chemoradiotherapy.

METHODS

Retrospective evaluation of 235 patients with histologically proven, locally advanced NSCLC from the multi-centre randomized clinical PETPLAN trial and a clinical cohort from a hospital registry. The PET parameters SUVmax, SULpeak, MTV and TLG above liver background uptake were determined. Kaplan-Meier curves and stratified Cox proportional hazard regression models were used to investigate the prognostic value of PET parameters and TNM along with clinical variables. Subgroup analyses were performed to compare hazard ratios according to TNM, MTV, and the two variables combined.

RESULTS

In the multivariable Cox regression analysis, MTV was associated with significantly worse overall survival independent of stage and other prognostic variables. In locally advanced disease stages treated with chemoradiotherapy, higher MTV was significantly associated with worse survival (median 17 vs. 32 months). Using simple cut-off values (45 ml for stage IIIa, 48 ml for stage IIIb, and 105 ml for stage IIIc), MTV was able to further predict differences in survival for stages IIIa-c. The combination of TNM and MTV staging system showed better discrimination for overall survival in locally advanced disease stages, compared to TNM alone.

CONCLUSION

Higher metabolic tumor volume is significantly associated with worse overall survival and combined with TNM staging, it provides more precise information about the disease prognosis in locally advanced NSCLC treated with chemoradiotherapy compared to TNM alone. As a PET parameter with volumetric information, MTV represents a useful addition to TNM.

Prognostic significance of pretreatment PET parameters in inoperable, node-positive NSCLC patients with poor prognostic factors undergoing hypofractionated radiotherapy: a single-institution retrospective study

BACKGROUND

Node-positive non-small cell lung cancers (NSCLCs) present a challenge for treatment decisions, particularly in patients ineligible for concurrent chemoradiotherapy (CRT) due to poor performance status and compromised lung function. We aimed to investigate the prognostic value of pretreatment positron emission tomography (PET) parameters in high-risk patients undergoing hypofractionated radiotherapy.

METHODS

A retrospective analysis was conducted on 42 consecutive patients with inoperable node-positive NSCLC, who underwent hypofractionated radiotherapy between 2014 and 2021 at a single institution. Clinical, treatment-related, and [18F]FDG PET-based parameters were correlated with progression-free survival (PFS) and overall survival (OS). Median dichotomisation was performed to establish risk groups. Statistical analyses included univariable and multivariable Cox regression and Kaplan-Meier survival analyses.

RESULTS

After a median follow-up of 47.1 months (range: 0.5-101.7), the median PFS and OS were 11.5 months (95% CI: 7.4-22.0), and 24.3 months (95% CI: 14.1-31.8). In univariable Cox regression analysis, significant predictors of PFS included receipt of salvage systemic treatment (p=0.007), SUVmax (p=0.032), and tMTV (p=0.038). Similarly, ECOG-PS (p=0.014), Histology (p=0.046), and tMTV (p=0.028) were significant predictors of OS. Multivariable Cox regression analysis (MVA) identified SUVmax as a significant predictor for PFS [HR: 2.29 (95% CI: 1.02-5.15); p=0.044]. For OS, ECOG-PS remained a significant prognosticator [HR: 3.53 (95% CI: 1.49-8.39); p=0.004], and tMTV approached significance [HR: 2.24 (95% CI: 0.95-5.26); p=0.065]. Furthermore, the high tMTV group exhibited a median PFS of 5.3 months [95% CI: 2.8-10.4], while the low tMTV group had a PFS of 15.2 months [95% CI: 10.1-33.5] (p=0.038, log-rank test). Median OS was 33.5 months [95% CI: 18.3-56.8] for tMTV ≤ 36.6 ml vs. 14.1 months [95% CI: 8.1-27.2] for tMTV > 36.6 ml (p=0.028, log-rank test).

CONCLUSION

Pretreatment PET parameters, especially tMTV, hold promise as prognostic indicators in NSCLC patients undergoing hypofractionated radiotherapy. The study highlights the potential of PET metrics as biomarkers for patient stratification.

Comparison of the Accuracy of a Deep Learning Method for Lesion Detection in PET/CT and PET/MRI Images

PURPOSE

Develop a universal lesion recognition algorithm for PET/CT and PET/MRI, validate it, and explore factors affecting performance.

PROCEDURES

The 2022 AutoPet Challenge's 1014 PET/CT dataset was used to train the lesion detection model based on 2D and 3D fractional-residual (F-Res) models. To extend this to PET/MRI, a network for converting MR images to synthetic CT (sCT) was developed, using 41 sets of whole-body MR and corresponding CT data. 38 patients' PET/CT and PET/MRI data were used to verify the universal lesion recognition algorithm. Image quality was assessed using signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Total lesion glycolysis (TLG), metabolic tumor volume (MTV), and lesion count were calculated from the resultant lesion masks. Experienced physicians reviewed and corrected the model's outputs, establishing the ground truth. The performance of the lesion detection deep-learning model on different PET images was assessed by detection accuracy, precision, recall, and dice coefficients. Data with a detection accuracy score (DAS) less than 1 was used for analysis of outliers.

RESULTS

Compared to PET/CT, PET/MRI scans had a significantly longer delay time (135 ± 45 min vs 61 ± 12 min) and lower SNR (6.17 ± 1.11 vs 9.27 ± 2.77). However, CNR values were similar (7.37 ± 5.40 vs 5.86 ± 6.69). PET/MRI detected more lesions (with a mean difference of -3.184). TLG and MTV showed no significant differences between PET/CT and PET/MRI (TLG: 119.18 ± 203.15 vs 123.57 ± 151.58, p = 0.41; MTV: 36.58 ± 57.00 vs 39.16 ± 48.34, p = 0.33). A total of 12 PET/CT and 14 PET/MRI datasets were included in the analysis of outliers. Outlier analysis revealed PET/CT anomalies in intestines, ureters, and muscles, while PET/MRI anomalies were in intestines, testicles, and low tracer uptake regions, with false positives in ureters (PET/CT) and intestines/testicles (PET/MRI).

CONCLUSION

The deep learning lesion detection model performs well with both PET/CT and PET/MRI. SNR, CNR and reconstruction parameters minimally impact recognition accuracy, but delay time post-injection is significant.

Quantitative evaluation of lesion response heterogeneity for superior prognostication of clinical outcome

PURPOSE

Standardized reporting of treatment response in oncology patients has traditionally relied on methods like RECIST, PERCIST and Deauville score. These endpoints assess only a few lesions, potentially overlooking the response heterogeneity of all disease. This study hypothesizes that comprehensive spatial-temporal evaluation of all individual lesions is necessary for superior prognostication of clinical outcome.

METHODS

[18F]FDG PET/CT scans from 241 patients (127 diffuse large B-cell lymphoma (DLBCL) and 114 non-small cell lung cancer (NSCLC)) were retrospectively obtained at baseline and either during chemotherapy or post-chemoradiotherapy. An automated TRAQinform IQ software (AIQ Solutions) analyzed the images, performing quantification of change in regions of interest suspicious of cancer (lesion-ROI). Multivariable Cox proportional hazards (CoxPH) models were trained to predict overall survival (OS) with varied sets of quantitative features and lesion-ROI, compared by bootstrapping with C-index and t-tests. The best-fit model was compared to automated versions of previously established methods like RECIST, PERCIST and Deauville score.

RESULTS

Multivariable CoxPH models demonstrated superior prognostic power when trained with features quantifying response heterogeneity in all individual lesion-ROI in DLBCL (C-index = 0.84, p < 0.001) and NSCLC (C-index = 0.71, p < 0.001). Prognostic power significantly deteriorated (p < 0.001) when using subsets of lesion-ROI (C-index = 0.78 and 0.67 for DLBCL and NSCLC, respectively) or excluding response heterogeneity (C-index = 0.67 and 0.70). RECIST, PERCIST, and Deauville score could not significantly associate with OS (C-index < 0.65 and p > 0.1), performing significantly worse than the multivariable models (p < 0.001).

CONCLUSIONS

Quantitative evaluation of response heterogeneity of all individual lesions is necessary for the superior prognostication of clinical outcome.

Pretreatment 18-FDG-PET/CT parameters can serve as prognostic imaging biomarkers in recurrent NSCLC patients treated with reirradiation-chemoimmunotherapy

BACKGROUND AND PURPOSE

Our study aimed to assess whether quantitative pretreatment 18F-FDG-PET/CT parameters could predict prognostic clinical outcome of recurrent NSCLC patients who may benefit from ablative reirradiation.

MATERIALS AND METHODS

Forty-eight patients with recurrent NSCLC of all UICC stages who underwent ablative thoracic reirradiation were analyzed. Twenty-nine (60%) patients received immunotherapy with or without chemotherapy in addition to reirradiation. Twelve patients (25%) received reirradiation only and seven (15%) received chemotherapy and reirradiation. Pretreatment 18-FDG-PET/CT was mandatory in initial diagnosis and recurrence, based on which volumetric and intensity quantitative parameters were measured before reirradiation and their impact on overall survival, progression-free survival, and locoregional control was assessed.

RESULTS

With a median follow-up time of 16.7 months, the median OS was 21.8 months (95%-CI: 16.2-27.3). On multivariate analysis, OS and PFS were significantly influenced by MTV (p < 0.001 for OS; p = 0.006 for PFS), TLG (p < 0.001 for OS; p = 0.001 for PFS) and SUL peak (p = 0.0024 for OS; p = 0.02 for PFS) of the tumor and MTV (p = 0.004 for OS; p < 0.001 for PFS) as well as TLG (p = 0.007 for OS; p = 0.015 for PFS) of the metastatic lymph nodes. SUL peak of the tumor (p = 0.05) and the MTV of the lymph nodes (p = 0.003) were only PET quantitative parameters that significantly impacted LRC.

CONCLUSION

Pretreatment tumor and metastastic lymph node MTV, TLG and tumor SUL peak significantly correlated with clinical outcome in recurrent NSCLC patients treated with reirradiation-chemoimmunotherapy.

The value of the Standardized Uptake Value (SUV) and Metabolic Tumor Volume (MTV) in lung cancer

The diagnosis, staging and therapeutic monitoring of lung cancer were amongst the first applications for which the utility of FDG PET was documented and FDG PET/CT is now a routine diagnostic tool for clinical decision-making. As well as having high sensitivity for detection of disease sites, which provides critical information about stage, the intensity of uptake provides deeper biological characterization, while the burden of disease also has potential clinical significance. These disease characteristics can easily be quantified on delayed whole-body imaging as the maximum standardized uptake value (SUV_max) and metabolic tumor volume (MTV), respectively. There have been significant efforts to harmonize the measurement of these features, particularly within the context of clinical trials. Nevertheless, however calculated, in general, a high SUV_max and large MTV have been shown to have an adverse prognostic significance. Nevertheless, the use of these parameters in the interpretation and reporting of clinical scans remains inconsistent and somewhat controversial. This review details the current status of semi-quantitative FDG PET/CT in the evaluation of lung cancer.

Impact of time of flight and point spread function on quantitative parameters of lung lesions in 18F-FDG PET/CT

Background

Image reconstruction algorithm is one of the important factors affecting the quantitative parameters of PET/CT. The purpose of this study was to investigate the effects of time of flight (TOF) and point spread function (PSF) on quantitative parameters of lung lesions in ¹⁸F-FDG PET/CT.

Methods

This retrospective study evaluated 60 lung lesions in 39 patients who had undergone ¹⁸F-fluoro-deoxy-glucose (FDG) PET/CT. All lesions larger than 10 mm in diameter were included in the study. The PET data were reconstructed with a baseline ordered-subsets expectation–maximization (OSEM) algorithm, OSEM + PSF, OSEM + TOF and OSEM + TOF + PSF respectively. The differences of maximum standard uptake value (SUVmax), mean standard uptake value (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG)and signal to noise ratio (SNR)were compared among different reconstruction algorithms.

Results

Compared with OSEM reconstruction, using OSEM + TOF + PSF increased SUVmean and SUVmax by 23.73% and 22.71% respectively, and SNR increased by 70.18%, MTV decreased by 23.84% (p < 0.01). The percentage difference was significantly higher in smaller lesions (diameter 10–22 mm) than in larger lesions (diameter 23–44 mm), and significantly higher in low contrast lesions (SNR ≤ 15.31) than in high contrast lesions (SNR > 15.31). The difference of TLG among various reconstruction algorithms is relatively small, the highest value is − 6.48% of OSEM + TOF + PSF, and the lowest value is 0.81% of OSEM + TOF.

Conclusion

TOF and PSF significantly affected the quantitative parameters of lung lesions in ¹⁸F-FDG PET/CT. OSEM + TOF + PSF can significantly increased SUVmax, SUVmean and SNR, and significantly reduce MTV, especially in small lesions and low contrast lesions. TLG can be relatively stable in different reconstruction algorithms.

Nodal metabolic tumour volume on baseline 18 F-FDG PET/CT and overall survival in stage II and III NSCLC patients undergoing curative-intent chemoradiotherapy/radiotherapy

INTRODUCTION

This study aims to investigate whether nodal metabolic tumour volume (nMTV) and nodal total lesion glycolysis (nTLG) on Fluorine-18 fluoro-deoxy-glucose positron emission tomography-computed tomography (¹⁸ F-FDG PET/CT) in inoperable node-positive stage II and III non-small cell lung cancer (NSCLC) are independent predictors of overall survival (OS) in patients undergoing curative-intent chemoradiotherapy/radiotherapy (CRT/RT).

METHODS

Data from two prospective trials between 2004 and 2016 were analysed retrospectively. Primary, nodal and total metabolic tumour volume and total lesion glycolysis (pMTV, nMTV, tMTV, pTLG, nTLG and tTLG, respectively) were derived from baseline ¹⁸ F-FDG PET/CT. Cox regressions were used to model OS by ¹⁸ F-FDG PET/CT parameters adjusting for overall stage.

RESULTS

89 patients with stage II (8%) and stage III (92%) were included. The median age at diagnosis was 67 years; 62% were male. The median follow-up was 6.9 years; the median OS was 2.2 years (95% CI 1.7-3.1). The median pMTV, nMTV and tMTV were 14 mL (range 0-360), 8 mL (range 0-250) and 34 mL (range 3-384), respectively. In 3 patients, the primary lesion could not be delineated from the central hilar mass. There was no association between nMTV (adjusted HR 1.04, 95% CI 0.95-1.15, P-value 0.43), pMTV (adjusted HR 1.0, 95% CI 0.96-1.04, P-value 0.92), tMTV (adjusted HR 1.0, 95% CI 0.97-1.04, P-value 0.88), nTLG, pTLG or tTLG and OS. Consistent results were noted when patients with central hilar lesions were excluded from analysis.

CONCLUSION

In node-positive stage II and III NSCLC patients who underwent ¹⁸ F-FDG PET/CT-guided target delineation curative-intent concurrent CRT/RT, metabolic parameters did not appear to provide independent prognostication.

The dynamics and prognostic value of FDG PET-metrics in weekly monitoring of (chemo)radiotherapy for NSCLC

PURPOSE

To test if the relative change in FDG-PET SUV_max over the course of treatment was associated with disease progression and overall survival. Additionally, the prognostic values of other first-order PET-metric changes were investigated.

METHODS

The study included 38 patients with stage II-III NSCLC, who underwent concurrent chemoradiotherapy. Patients received two pre-treatment FDG-PET scans and four during-treatment scans at weekly intervals. SUV_max was normalized to the start of treatment and analyzed using linear regression. Linear regression coefficients of other first order PET-metrics were grouped according to dissimilarity. Associations to patient outcome were analyzed using Cox hazard ratio.

RESULTS

Twenty-eight patients satisfied the criteria for analysis. All PET-metrics demonstrated a strong linear correlation with time during treatment [median R-range: -0.87: -0.97]. No strong associations (p > 0.10) were found for the relative slope of SUV_max to patient outcomes. Other first-order metrics did correlate with outcome but the single imaging time-point maximizing the association of PET response with outcome varied per PET metric and outcome parameter.

CONCLUSION

All investigated FDG PET metrics linearly decreased during treatment. Relative change in SUV_max was not associated to patient outcome while several other first order PET-metrics were related to patient outcome. A single optimal imaging time-point could not be identified.

PET-Based Volumetric Biomarkers for Risk Stratification of Non-Small Cell Lung Cancer Patients

Despite the recent advances in lung cancer biology, molecular pathology, and treatment, this malignancy remains the leading cause of cancer-related death worldwide and non-small cell lung cancer (NSCLC) is the most common form found at diagnosis. Accurate staging of the disease is a fundamental prognostic factor that correctly predicts progression-free (PFS) and overall survival (OS) of NSCLC patients. However, outcome of patients within each TNM staging group can change widely highlighting the need to identify additional prognostic biomarkers to better stratify patients on the basis of risk. 18F-FDG PET/CT plays an essential role in staging, evaluation of treatment response, and tumoral target delineation in NSCLC patients. Moreover, a number of studies showed the prognostic role of imaging parameters derived from PET images, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG). These parameters represent three-dimensional PET-based measurements providing information on both tumor volume and metabolic activity and previous studies reported their ability to predict OS and PFS of NSCLC patients. This review will primarily focus on the studies that showed the prognostic and predictive role of MTV and TLG in NSCLC patients, addressing also their potential utility in the new era of immunotherapy of NSCLC.

Early response evaluation using primary tumor and nodal imaging features to predict progression-free survival of locally advanced non-small cell lung cancer

Prognostic biomarkers that can reliably predict early disease progression of non-small cell lung cancer (NSCLC) are needed for identifying those patients at high risk for progression, who may benefit from more intensive treatment. In this work, we aimed to identify an imaging signature for predicting progression-free survival (PFS) of locally advanced NSCLC. Methods: This retrospective study included 82 patients with stage III NSCLC treated with definitive chemoradiotherapy for whom both baseline and mid-treatment PET/CT scans were performed. They were randomly placed into two groups: training cohort (n=41) and testing cohort (n=41). All primary tumors and involved lymph nodes were delineated. Forty-five quantitative imaging features were extracted to characterize the tumors and involved nodes at baseline and mid-treatment as well as differences between two scans performed at these two points. An imaging signature was developed to predict PFS by fitting an L1-regularized Cox regression model. Results: The final imaging signature consisted of three imaging features: the baseline tumor volume, the baseline maximum distance between involved nodes, and the change in maximum distance between the primary tumor and involved nodes measured at two time points. According to multivariate analysis, the imaging model was an independent prognostic factor for PFS in both the training (hazard ratio [HR], 1.14, 95% confidence interval [CI], 1.04-1.24; P = 0.003), and testing (HR, 1.21, 95% CI, 1.10-1.33; P = 0.048) cohorts. The imaging signature stratified patients into low- and high-risk groups, with 2-year PFS rates of 61.9% and 33.2%, respectively (P = 0.004 [log-rank test]; HR, 4.13, 95% CI, 1.42-11.70) in the training cohort, as well as 43.8% and 22.6%, respectively (P = 0.006 [log-rank test]; HR, 3.45, 95% CI, 1.35-8.83) in the testing cohort. In both cohorts, the imaging signature significantly outperformed conventional imaging metrics, including tumor volume and SUV_max value (C-indices: 0.77-0.79 for imaging signature, and 0.53-0.73 for conventional metrics). Conclusions: Evaluation of early treatment response by combining primary tumor and nodal imaging characteristics may improve the prediction of PFS of locally advanced NSCLC patients.

Predicting per-lesion local recurrence in locally advanced non-small cell lung cancer following definitive radiation therapy using pre- and mid-treatment metabolic tumor volume

BACKGROUND

We evaluated whether pre- and mid-treatment metabolic tumor volume (MTV) predicts per lesion local recurrence (LR) in patients treated with definitive radiation therapy (RT, dose≥60 Gy) for locally advanced non-small cell lung cancer (NSCLC).

METHODS

We retrospectively reviewed records of patients with stage III NSCLC treated from 2006 to 2018 with pre- and mid-RT PET-CT. We measured the MTV of treated lesions on the pre-RT (MTVpre) and mid-RT (MTVmid) PET-CT. LR was defined per lesion as recurrence within the planning target volume. Receiver operating characteristic (ROC) curves, cumulative incidence rates, and uni- and multivariable (MVA) competing risk regressions were used to evaluate the association between MTV and LR.

RESULTS

We identified 111 patients with 387 lesions (112 lung tumors and 275 lymph nodes). Median age was 68 years, 69.4% were male, 46.8% had adenocarcinoma, 39.6% had squamous cell carcinoma, and 95.5% received concurrent chemotherapy. Median follow-up was 38.7 months. 3-year overall survival was 42.3%. 3-year cumulative incidence of LR was 26.8% per patient and 11.9% per lesion. Both MTVpre and MTVmid were predictive of LR by ROC (AUC = 0.71 and 0.76, respectively) and were significantly associated with LR on MVA (P = 0.004 and P = 7.1e-5, respectively). Among lesions at lower risk of LR based on MTVpre, higher MTVmid was associated with LR (P = 0.001).

CONCLUSION

Per-lesion, larger MTVpre and MTVmid predicted for increased risk of LR. MTVmid was more highly predictive of LR than MTVpre and if validated may allow for further discrimination of high-risk lesions at mid-RT informing dose painting strategies.

Total metabolic tumor volume by 18F-FDG PET/CT for the prediction of outcome in patients with non-small cell lung cancer

OBJECTIVE

Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) are imaging parameters derived from 18F-FDG PET/CT that have been proposed for risk stratification of cancer patients. The aim of our study was to test whether these whole-body volumetric imaging parameters may predict outcome in patients with non-small cell lung cancer (NSCLC).

METHODS

Sixty-five patients (45 men, 20 women; mean age ± SD, 65 ± 12 years), with histologically proven NSCLC who had undergone 18F-FDG PET/CT scan before any therapy, were included in the study. Imaging parameters including SUV_max, SUV_mean, total MTV (MTV_TOT) and whole-body TLG (TLG_WB) were determined. Univariate and multivariate analyses of clinical and imaging variables were performed using Cox proportional hazards regression. Survival analysis was performed using Kaplan-Meier method and log-rank tests.

RESULTS

A total of 298 lesions were analyzed including 65 primary tumors, 114 metastatic lymph nodes and 119 distant metastases. MTV_TOT and TLG_WB could be determined in 276 lesions. Mean value of MTV_TOT was 81.83 ml ± 14.63 ml (SE) whereas mean value of TLG_WB was 459.88 g ± 77.02 g (SE). Univariate analysis showed that, among the variables tested, primary tumor diameter (p = 0.0470), MTV of primary tumor (p = 0.0299), stage (p < 0.0001), treatment (p < 0.0001), MTV_TOT (p = 0.0003) and TLG_WB (p = 0.0002) predicted progression-free survival in NSCLC patients, while age (p = 0.0550), MTV of primary tumor (p = 0.0375), stage (p < 0.0001), treatment (p < 0.0001), MTV_TOT (p = 0.0001) and TLG_WB (p = 0.0008) predicted overall survival. At multivariate analysis age, TLG_WB and stage were retained in the model for prediction of progression-free survival (p < 0.0001), while age, MTV_TOT and stage were retained in the model for prediction of overall survival (p < 0.0001). Survival analysis showed that patients with TLG_WB ≤ 54.7 g had a significantly prolonged progression-free survival as compared to patients with TLG_WB > 54.7 g (p < 0.0001). Moreover, overall survival was significantly better in patients showing a MTV_TOT ≤ 9.5 ml as compared to those having MTV_TOT > 9.5 ml (p < 0.0001). Similar results were obtained in a subgroup of 43 patients with advanced disease (stages III and IV).

CONCLUSIONS

Whole-body PET-based volumetric imaging parameters are able to predict outcome in NSCLC patients.

Epidermal Growth Factor Receptor (EGFR)-Tyrosine Kinase Inhibitors (TKIs) Combined with Chemotherapy Delay Brain Metastasis in Patients with EGFR-Mutant Lung Adenocarcinoma

BACKGROUND

Whether epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) combined with chemotherapy can delay the occurrence of brain metastasis (BM) is unclear.

OBJECTIVE

This retrospective study aimed to evaluate whether EGFR-TKIs combined with chemotherapy can delay BM and decrease the incidence of BM as initial progression.

PATIENTS AND METHODS

The data of 100 patients with EGFR-mutant advanced lung adenocarcinoma were retrospectively reviewed. The patients had no BM at initial diagnosis, and BM occurred during the treatment. Patients received EGFR-TKI only or EGFR-TKI combined with chemotherapy. Intracranial progression-free survival (iPFS), systemic progression-free survival (PFS), and overall survival (OS) were evaluated.

RESULTS

The overall median OS was 39 months (95% confidence interval (CI), 35.6-42.4 months). The median OS of EGFR-TKI combined with chemotherapy and EGFR-TKI only are 41 months (95% CI 35.5-46.5 months) and 39 months (95% CI 36.8-41.2 months), respectively. Patients in the combination treatment group had longer PFS (16 vs. 10 months; P = 0.030) and iPFS (21 vs. 14 months; P = 0.026). Further, as initial progression, fewer patients developed BM in the combined treatment group compared with the EGFR-TKI-only group (30.6% vs. 52.9%, P = 0.002) with a hazard ratio of 0.64 (95% CI 0.43-0.96). After controlling for significant covariables in a multivariable model, the different treatment strategies were independently associated with improved iPFS.

CONCLUSIONS

In this retrospective analysis, EGFR-TKIs combined with chemotherapy could improve PFS. Further, the combined treatment could delay BM occurrence and decrease the incidence of BM as initial progression.

Clinical implications of circulating cell-free DNA quantification and metabolic tumor burden in advanced non-small cell lung cancer

OBJECTIVES

This study unravels the significance of cell-free DNA (cfDNA) quantification as a promising measure of the biological behavior/aggressiveness of tumors. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) measured by positron emission tomography/computed tomography scan enable a precise assessment of metabolic tumor burden. However, their clinical implications in identifying patients who need more aggressive treatment in advanced non-small cell lung cancer (NSCLC) are not fully understood.

MATERIALS AND METHODS

In the current prospective trial, we analyzed 101 newly diagnosed advanced NSCLC (stage III-IV) patients with measurable baseline MTV, TLG, and cfDNA quantification. The best cut-offs for cfDNA levels, MTV, and TLG to predict progression-free survival and overall survival were determined using X-tile analysis.

RESULTS

There were significant positive correlations between cfDNA and MTV (r = 0.488, p <  0.001) and between cfDNA and TLG (r = 0.554, p <  0.001). High-cfDNA levels and high-MTV/TLG negatively correlated with overall survival (OS) (all p <  0.001). Patients with high-MTV showed similar median OS irrespective of their cfDNA levels (low-cfDNA vs. high-cfDNA=9.2 vs 6.6 months; p >  0.05). However, patients with low-MTV and low-cfDNA levels showed longer OS than those with low-MTV and high-cfDNA levels (low-cfDNA vs. high-cfDNA=49.3 vs 11.5 months; p <  0.001). The patient group with low-TLG also showed similar trends. The cfDNA level was an independent prognostic factor for OS by Cox-proportional hazard analysis.

CONCLUSION

Although the patients with high metabolic tumor burden had a poor prognosis, regardless of the biological behavior/aggressiveness of the tumor, patients with low metabolic tumor burden and high cfDNA levels showed a poor prognosis. Taken together, this study indicates a stronger prognostic value of baseline cfDNA levels in identifying patients with advanced NSCLC and personalizing their treatment strategies for better survival.

Quantitative FDG PET/CT may help risk-stratify early-stage non-small cell lung cancer patients at risk for recurrence following anatomic resection

BACKGROUND

Preoperative identification of non-small cell lung cancer (NSCLC) patients at risk for disease recurrence has proven unreliable. The extraction of quantitative metrics from imaging based on tumor intensity and texture may enhanced disease characterization. This study evaluated tumor-specific 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computerized tomography (PET/CT) uptake patterns and their association with disease recurrence in early-stage NSCLC.

METHODS

Sixty-four stage I/II NSCLC patients who underwent anatomic resection between 2001 and 2014 were examined. Pathologically or radiographic confirmed disease recurrence within 5 years of resection comprised the study group. Quantitative imaging metrics were extracted within the primary tumor volume. Squamous cell carcinoma (SCC) (N=27) and adenocarcinoma (AC) (N=41) patients were compared using a Wilcoxon signed-rank test. Associations between imaging and clinical variables with 5-year disease-free survival (DFS) and overall survival (OS) were evaluated by Cox proportional-hazards regression.

RESULTS

Clinical and pathologic characteristics were similar between recurrence (N=34) and patients achieving 5-year DFS (N=30). Standardized uptake value (SUV)max and SUVmean varied significantly by histology, with SCC demonstrating higher uptake intensity and heterogeneity patterns. Entropy-grey-level co-occurrence matrix (GLCM) was a significant univariate predictor of DFS (HR =0.72, P=0.04) and OS (HR =0.65, P=0.007) independent of histology. Texture features showed higher predictive ability for DFS in SCC than AC. Pathologic node status and staging classification were the strongest clinical predictors of DFS, independent of histology.

CONCLUSIONS

Several imaging metrics correlate with increased risk for disease recurrence in early-stage NSCLC. The predictive ability of imaging was strongest when patients are stratified by histology. The incorporation of 18F-FDG PET/CT texture features with preoperative risk factors and tumor characteristics may improve identification of high-risk patients.

Pretreatment metabolic tumour volume in stage IIIA/B non-small-cell lung cancer uncovers differences in effectiveness of definitive radiochemotherapy schedules: analysis of the ESPATUE randomized phase 3 trial

PURPOSE

According to the ACRIN 6668/RTOG 0235 trial, pretreatment metabolic tumour volume (MTV) as detected by ¹⁸F-fluorodeoxyglucose PET/CT is a prognostic factor in patients with stage III non-small-cell lung cancer (NSCLC) after definitive radiochemotherapy (RCT). To validate the prognostic value of MTV in patients with stage III NSCLC after RCT, we analysed mature survival data from the German phase III trial ESPATUE.

METHODS

This analysis included patients who were staged by PET/CT and who were enrolled in the ESPATUE trial, a randomized study comparing definitive RCT (arm A) with surgery (arm B) after induction chemotherapy and RCT in patients with resectable stage IIIA/IIIB NSCLC. Patients refusing surgery and those with nonresectable disease were scheduled to receive definitive RCT. MTV was measured using a fixed threshold-based approach and a model-based iterative volume thresholding approach. Data were analysed using proportional hazards models and Kaplan-Meier survival functions.

RESULTS

MTV as a continuous variable did not reveal differences in survival between the 117 patients scheduled to receive definitive RCT and all 169 enrolled patients who underwent pretreatment PET/CT (p > 0.5). Five-year survival rates were 33% (95% CI 17-49%) in patients scheduled for definitive RCT with a high MTV (>95.4 ml) and 32% (95% CI: 22-42%) in those with a low MTV. The hazard ratio for survival was 0.997 (95% CI 0.973-1.022) per 10-ml increase in MTV and the slope was significantly shallower than that in the ACRIN 6668/RTOG 0235 trial (random effects model, p = 0.002). There were no differences in MTV size distributions between the ACRIN and ESPATUE trials (p = 0.97).

CONCLUSION

Patients with stage III NSCLC and a large MTV in whom definitive RCT had a particularly good survival in the ESPATUE trial. Treatment individualization according to MTV is not supported by this study. The ESPATUE and ACRIN trials differed by the use of cisplatin-containing induction chemotherapy and an intensified radiotherapy regimen that were particularly effective in patients with large MTV disease.

Prognostic value of metabolic tumor volume of pretreatment 18F-FAMT PET/CT in non-small cell lung Cancer

Background

This study aimed to determine the prognostic value of positron emission tomography (PET) metabolic parameters—namely metabolic tumor volume (MTV), total lesion glycolysis (TLG), and total lesion retention (TLR)—on fluorine-18 (¹⁸F) fluorodeoxyglucose (FDG) and L- [3-¹⁸F]-α-methyltyrosine (¹⁸F-FAMT) PET/CT in patients with non-small-cell lung cancer (NSCLC).

Methods

The study group comprised 112 NSCLC patients who underwent ¹⁸F-FDG and ¹⁸F-FAMT PET/CT prior to any therapy. The MTV, TLG, TLR, and maximum standardized uptake value (SUV_max) of the primary tumors were determined. Automatic MTV measurement was performed using PET volume computer assisted reading software. (GE Healthcare). Cox proportional hazards models were built to assess the prognostic value of MTV, TLG (for ¹⁸F-FDG), TLR (for ¹⁸F-FAMT), SUV_max, T stage, N stage, M stage, clinical stage, age, sex, tumor histological subtype, and treatment method (surgery or other therapy) on overall survival (OS).

Results

Higher TNM, higher clinical stage, inoperable status, and higher values for all PET parameters (both ¹⁸F-FAMT and ¹⁸F-FDG PET) were significantly associated (P < 0.05) with shorter OS. Multivariate analysis revealed that a higher MTV of ¹⁸F-FAMT (hazard ratio [HR]: 2.88, CI: 1.63–5.09, P < 0.01) and advanced clinical stage (HR: 5.36, CI: 1.88–15.34, P < 0.01) were significant predictors of shorter OS.

Conclusions

MTV of ¹⁸F-FAMT is of prognostic value for OS in NSCLC cases and can help guide decision-making during patient management.

Greater reduction in mid-treatment FDG-PET volume may be associated with worse survival in non-small cell lung cancer

BACKGROUND AND PURPOSE

This study tested the hypotheses that 1) changes in mid-treatment fluorodeoxyglucose (FDG)-positron emission tomography (PET) parameters are predictive of overall survival (OS) and 2) mid-treatment FDG-PET-adapted treatment has the potential to improve survival in patients with non-small cell lung cancer (NSCLC).

MATERIAL AND METHODS

Patients with stage I-III NSCLC requiring daily fractionated radiation were eligible. FDG-PET-CT scans were obtained prior to and mid-treatment with radiotherapy at 40-50 Gy. The normalized maximum standardized uptake value (NSUVmax), normalized mean SUV (NSUVmean), PET-metabolic tumor volume (MTV), total lesion glycolysis (TLG), and computed tomography-based gross tumor volume (CT-GTV) were consistently measured for all patients. The primary study endpoint was OS.

RESULTS

The study is comprised of 102 patients who received 3-dimensional conformal radiotherapy, among whom 30 patients who received mid-treatment PET-adapted dose escalation radiotherapy. All PET-CT parameters decreased significantly (P < 0.001) mid-treatment, with greater reductions in FDG-volumetric parameters compared to FDG-activity factors. Mid-treatment changes in MTV (P = 0.053) and TLG (P = 0.021) were associated with OS, while changes in NSUVmax, NSUVmean, and CT-GTV were not (all Ps>0.1). Patients receiving conventional radiation (60-70 Gy) with MTV reductions greater than the mean had a median survival of 14 months, compared to those with MTV reductions less than the mean who had a median survival of 22 months. By contrast, patients receiving mid-treatment PET-adapted radiation with MTV reductions greater than the mean had a median survival of 33 months, compared to those with MTV reductions less than the mean who had a median survival of 19 months. Overall, PET-adapted treatment resulted in a 19% better 5-year survival than conventional radiation.

CONCLUSION

Changes in mid-treatment PET-volumetric parameters were significantly associated with survival in NSCLC. A greater reduction in the mid-treatment MTV was associated with worse survival in patients treated with standard radiation, but with better survival in patients who received mid-treatment PET-adapted treatment.

Impact of the EARL harmonization program on automatic delineation of metabolic active tumour volumes (MATVs)

BACKGROUND

The clinical validation of the EARL harmonization program for standardised uptake value (SUV) metrics is well documented; however, its potential for defining metabolic active tumour volume (MATV) has not yet been investigated. We aimed to compare delineation of MATV on images reconstructed using conventional ordered subset expectation maximisation (OSEM) with those reconstructed using point spread function modelling (PSF-reconstructed images), and either optimised for diagnostic potential (PSF) or filtered to meet the EANM/EARL harmonising standards (PSF7).

METHODS

Images from 18 stage IIIA-IIIB lung cancer patients were reconstructed using all the three methods. MATVs were then delineated using both a 40% isocontour and a gradient-based method. MATVs were compared by means of Bland-Altman analyses, and Dice coefficients and concordance indices based on the unions and intersections between each pair of reconstructions (PSF vs OSEM, PSF7 vs PSF and PSF7 vs OSEM).

RESULTS

Using the 40% isocontour method and taking the MATVs delineated on OSEM images as a reference standard, the use of PSF7 images led to significantly higher Dice coefficients (median value = 0.96 vs 0.77; P < 0.0001) and concordance indices (median value = 0.92 vs 0.64; P < 0.0001) than those obtained using PSF images. The gradient-based methodology was less sensitive to reconstruction variability than the 40% isocontour method; Dice coefficients and concordance indices were superior to 0.8 for both PSF reconstruction methods. However, the use of PSF7 images led to narrower interquartile ranges and significantly higher Dice coefficients (median value = 0.96 vs 0.94; P = 0.01) and concordance indices (median value = 0.89 vs 0.85; P = 0.003) than those obtained with PSF images.

CONCLUSION

This study demonstrates that automatic contouring of lung tumours on EARL-compliant PSF images using the widely adopted automatic isocontour methodology is an accurate means of overcoming reconstruction variability in MATV delineation. Although gradient-based methodology appears to be less sensitive to reconstruction variability, the use of EARL-compliant PSF images significantly improved the Dice coefficients and concordance indices, demonstrating the importance of harmonised-images, even when more advanced contouring algorithms are used.

EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program

BACKGROUND

This study evaluates the consistency of PET evaluation response criteria in solid tumours (PERCIST) and European Organisation for Research and Treatment of Cancer (EORTC) classification across different reconstruction algorithms and whether aligning standardized uptake values (SUVs) to the European Association of Nuclear Medicine acquisition (EANM)/EARL standards provides more consistent response classification.

MATERIALS AND METHODS

Baseline (PET1) and response assessment (PET2) scans in 61 patients with non-small cell lung cancer were acquired in protocols compliant with the EANM guidelines and were reconstructed with point-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction for optimal tumour detection and with a standardized ordered subset expectation maximization (OSEM) reconstruction known to fulfil EANM harmonizing standards. Patients were recruited in three centres. Following reconstruction, EQ.PET, a proprietary software solution was applied to the PSF ± TOF data (PSF ± TOF.EQ) to harmonize SUVs to the EANM standards. The impact of differing reconstructions on PERCIST and EORTC classification was evaluated using standardized uptake values corrected for lean body mass (SUL).

RESULTS

Using OSEMPET1/OSEMPET2 (standard scenario), responders displayed a reduction of -57.5% ± 23.4 and -63.9% ± 22.4 for SULmax and SULpeak, respectively, while progressing tumours had an increase of +63.4% ± 26.5 and +60.7% ± 19.6 for SULmax and SULpeak respectively. The use of PSF ± TOF reconstruction impacted the classification of tumour response. For example, taking the OSEMPET1/PSF ± TOFPET2 scenario reduced the apparent reduction in SUL in responding tumours (-39.7% ± 31.3 and -55.5% ± 26.3 for SULmax and SULpeak, respectively) but increased the apparent increase in SUL in progressing tumours (+130.0% ± 50.7 and +91.1% ± 39.6 for SULmax and SULpeak, respectively). Consequently, variation in reconstruction methodology (PSF ± TOFPET1/OSEMPET2 or OSEM PET1/PSF ± TOFPET2) led, respectively, to 11/61 (18.0%) and 10/61 (16.4%) PERCIST classification discordances and to 17/61 (28.9%) and 19/61 (31.1%) EORTC classification discordances. An agreement was better for these scenarios with application of the propriety filter, with kappa values of 1.00 and 0.95 compared to 0.75 and 0.77 for PERCIST and kappa values of 0.93 and 0.95 compared to 0.61 and 0.55 for EORTC, respectively.

CONCLUSION

PERCIST classification is less sensitive to reconstruction algorithm-dependent variability than EORTC classification but harmonizing SULs within the EARL program is equally effective with either.

Analysis of primary tumor metabolic volume during chemoradiotherapy in locally advanced non-small cell lung cancer

PURPOSE

Positron emission tomography with 2‑deoxy-2-[fluorine-18] fluoro-d-glucose integrated with computed tomography (18F-FDG-PET/CT) has an established role in the initial diagnosis and staging of lung cancer. However, a prognostic value of PET/CT during multimodality treatment has not yet been fully clarified. This study evaluated the role of primary tumor metabolic volume (PT-MV) changes on PET/CT before, during, and after chemoradiotherapy (CRT).

METHODS

A total of 65 patients with non-small-cell lung cancer (NSCLC) UICC stage IIIA/B (TNM 7th Edition) were treated with definitive chemoradiotherapy (sequential or concurrent setting). PET/CT was acquired before the start, at the end of the third week, and 6 weeks following CRT.

RESULTS

Median overall survival (OS) for the entire cohort was 16 months (95% confidence interval [CI]: 12-20). In all, 60 (92.3%) patients were eligible for pre-treatment (pre-PT-MV), 28 (43%) for mid-treatment (mid-PT-MV), and 53 (81.5%) for post-treatment (post-PT-MV) volume analysis. Patients with pre-PT-MV >63 cm³ had worse OS (p < 0.0001). A reduction from mid-PT-MV to post-PT-MV of >15% improved OS (p = 0.001). In addition, patients with post-PT-MV > 25 cm³ had significantly worse outcome (p = 0.001). On multivariate analysis, performance status (p = 0.002, hazard ratio [HR] 0.007; 95% CI 0.00-0.158), pre-PT-MV1 < 63 cm³ (p = 0.027, HR 3.98; 95% CI 1.17-13.49), post-PT-MV < 25 cm³ (p = 0.013, HR 11.90; 95% CI 1.70-83.27), and a reduction from mid-PT-MV to post-PT-MV > 15% (p = 0.004, HR 0.25; 95% CI 0.02-0.31) correlated with improved OS.

CONCLUSIONS

Our results demonstrated that pre- and post-treatment PT-MV, as well as an at least 15% reduction in mid- to post-PT-MV, significantly correlates with OS in patients with inoperable locally advanced NSCLC.

Clustering of multi-parametric functional imaging to identify high-risk subvolumes in non-small cell lung cancer

BACKGROUND AND PURPOSE

We aimed to identify tumour subregions with characteristic phenotypes based on pre-treatment multi-parametric functional imaging and correlate these subregions to treatment outcome. The subregions were created using imaging of metabolic activity (FDG-PET/CT), hypoxia (HX4-PET/CT) and tumour vasculature (DCE-CT).

MATERIALS AND METHODS

36 non-small cell lung cancer (NSCLC) patients underwent functional imaging prior to radical radiotherapy. Kinetic analysis was performed on DCE-CT scans to acquire blood flow (BF) and volume (BV) maps. HX4-PET/CT and DCE-CT scans were non-rigidly co-registered to the planning FDG-PET/CT. Two clustering steps were performed on multi-parametric images: first to segment each tumour into homogeneous subregions (i.e. supervoxels) and second to group the supervoxels of all tumours into phenotypic clusters. Patients were split based on the absolute or relative volume of supervoxels in each cluster; overall survival was compared using a log-rank test.

RESULTS

Unsupervised clustering of supervoxels yielded four independent clusters. One cluster (high hypoxia, high FDG, intermediate BF/BV) related to a high-risk tumour type: patients assigned to this cluster had significantly worse survival compared to patients not in this cluster (p = 0.035).

CONCLUSIONS

We designed a subregional analysis for multi-parametric imaging in NSCLC, and showed the potential of subregion classification as a biomarker for prognosis. This methodology allows for a comprehensive data-driven analysis of multi-parametric functional images.

Prognostic Value of 18F-Fluorodeoxyglucose PET/Computed Tomography in Non-Small-Cell Lung Cancer

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related death with a poor prognosis. Numerous factors contribute to treatment outcome. 18F-fluorodeoxyglucose (FDG) uptake reflects tumor metabolic activity and is an important prognosticator in patients with NSCLC. Volume-based FDG-PET parameters reflect the metabolic status of a malignancy more accurately than maximum standardized uptake value and thus are better prognostic markers in lung cancer. FDG-avid tumor burden parameters may help clinicians to predict treatment outcomes before and during therapy so that treatment can be adjusted to achieve the best possible outcomes while avoiding side effects.

Metabolic tumor burden quantified on [18F]FDG PET/CT improves TNM staging of lung cancer patients

PURPOSE

The purpose of our study was to test a new staging algorithm, combining clinical TNM staging (cTNM) with whole-body metabolic active tumor volume (MATV-WB), with the goal of improving prognostic ability and stratification power.

METHODS

Initial staging [¹⁸F]FDG PET/CT of 278 non-small cell lung cancer (NSCLC) patients, performed between January/2011 and April/2016, 74(26.6%) women, 204(73.4%) men; aged 34-88 years (mean ± SD:66 ± 10), was retrospectively evaluated, and MATV-WB was quantified. Each patient's follow-up time was recorded: 0.7-83.6 months (mean ± SD:25.1 ± 20.3).

RESULTS

MATV-WB was an independent and statistically-significant predictor of overall survival (p < 0.001). The overall survival predictive ability of MATV-WB (C index: mean ± SD = 0.7071 ± 0.0009) was not worse than cTNM (C index: mean ± SD = 0.7031 ± 0.007) (Z = -0.143, p = 0.773). Estimated mean survival times of 56.3 ± 3.0 (95%CI:50.40-62.23) and 21.7 ± 2.2 months (95%CI:17.34-25.98) (Log-Rank = 77.48, p < 0.001), one-year survival rate of 86.8% and of 52.8%, and five-year survival rate of 53.6% and no survivors, were determined, respectively, for patients with MATV-WB < 49.5 and MATV-WB ≥ 49.5. Patients with MATV-WB ≥ 49.5 had a mortality risk 2.9-5.8 times higher than those with MATV-WB < 49.5 (HR = 4.12, p < 0.001). MATV-WB cutoff points were also determined for each cTNM stage: 23.7(I), 49.5(II), 52(III), 48.8(IV) (p = 0.029, p = 0.227, p = 0.025 and p = 0.001, respectively). At stages I, III and IV there was a statistically-significant difference in the estimated mean overall survival time between groups of patients defined by the cutoff points (p = 0.007, p = 0.004 and p < 0.001, respectively). At stage II (p = 0.365), there was a clinically-significant difference of about 12 months between the groups. In all cTNM stages, patients with MATV-WB ≥ cutoff points had lower survival rates. Combined clinical TNM-PET staging (cTNM-P) was then tested: Stage I < 23.7; Stage I ≥ 23.7; Stage II < 49.5; Stage II ≥ 49.5; Stage III < 52; Stage III ≥ 52; Stage IV < 48.8; Stage IV ≥ 48.8. cTNM-P staging presented a superior overall survival predictive ability (C index = 0.730) compared with conventional cTNM staging (C index = 0.699) (Z = -4.49, p < 0.001).

CONCLUSION

cTNM-P staging has superior prognostic value compared with conventional cTNM staging, and allows better stratification of NSCLC patients.

Risk-stratifying capacity of PET/CT metabolic tumor volume in stage IIIA non-small cell lung cancer

OBJECTIVES

Stage IIIA non-small cell lung cancer (NSCLC) is heterogeneous in tumor burden, and its treatment is variable. Whole-body metabolic tumor volume (MTVWB) has been shown to be an independent prognostic index for overall survival (OS). However, the potential of MTVWB to risk-stratify stage IIIA NSCLC has previously been unknown. If we can identify subgroups within the stage exhibiting significant OS differences using MTVWB, MTVWB may lead to adjustments in patients' risk profile evaluations and may, therefore, influence clinical decision making regarding treatment. We estimated the risk-stratifying capacity of MTVWB in stage IIIA by comparing OS of stratified stage IIIA with stage IIB and IIIB NSCLC.

METHODS

We performed a retrospective review of 330 patients with clinical stage IIB, IIIA, and IIIB NSCLC diagnosed between 2004 and 2014. The patients' clinical TNM stage, initial MTVWB, and long-term survival data were collected. Patients with TNM stage IIIA disease were stratified by MTVWB. The optimal MTVWB cutoff value for stage IIIA patients was calculated using sequential log-rank tests. Univariate and multivariate cox regression analyses and Kaplan-Meier OS analysis with log-rank tests were performed.

RESULTS

The optimal MTVWB cut-point was 29.2 mL for the risk-stratification of stage IIIA. We identified statistically significant differences in OS between stage IIB and IIIA patients (p < 0.01), between IIIA and IIIB patients (p < 0.01), and between the stage IIIA patients with low MTVWB (below 29.2 mL) and the stage IIIA patients with high MTVWB (above 29.2 mL) (p < 0.01). There was no OS difference between the low MTVWB stage IIIA and the cohort of stage IIB patients (p = 0.485), or between the high MTVWB stage IIIA patients and the cohort of stage IIIB patients (p = 0.459). Similar risk-stratification capacity of MTVWB was observed in a large range of cutoff values from 15 to 55 mL in stage IIIA patients.

CONCLUSIONS

Using MTVWB cutoff points ranging from 15 to 55 mL with an optimal value of 29.2 mL, stage IIIA NSCLC may be effectively stratified into subgroups with no significant survival difference from stages IIB or IIIB NSCLC. This may result in more accurate survival estimation and more appropriate risk adapted treatment selection in stage IIIA NSCLC.

Optimal FDG PET/CT volumetric parameters for risk stratification in patients with locally advanced non-small cell lung cancer: results from the ACRIN 6668/RTOG 0235 trial

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.