Prognostic value of the quantitative metabolic volumetric measurement on 18F-FDG PET/CT in Stage IV nonsurgical small-cell lung cancer

Prognostic and Predictive Biomarkers of Oligometastatic NSCLC: New Insights and Clinical Applications

This review discusses the current data on predictive and prognostic biomarkers in oligometastatic NSCLC and discusses whether biomarkers identified in other stages and widespread metastatic disease can be extrapolated to the oligometastatic disease (OMD) setting. Research is underway to explore the prognostic and predictive value of biological attributes of tumor tissue, circulating cells, the tumor microenvironment, and imaging findings as biomarkers of oligometastatic NSCLC. Biomarkers that help define true OMD and predict outcomes are needed for patient selection for oligometastatic treatment, and to avoid futile treatments in patients that will not benefit from locoregional treatment. Nevertheless, these biomarkers are still in the early stages of development and lack prospective validation in clinical trials. Furthermore, the absence of a clear definition of OMD contributes to a heterogeneous study population in which different types of OMD are mixed and treatment strategies are different. Multiple tissue-based, circulating, and imaging features are promising regarding their prognostic and predictive role in NSCLC, but data is still limited and might be biased owing to the inclusion of heterogeneous patient populations. Larger homogeneous and prospective series are needed to assess the prognostic and predictive role of these biomarkers. As obtaining tissue can be difficult and is invasive, the most promising tools for further evaluation are liquid biopsies and imaging-based biomarkers as these can also be used for longitudinal follow-up.

The utility of 18F-FDG PET/CT for predicting the pathological response and prognosis to neoadjuvant immunochemotherapy in resectable non-small-cell lung cancer

OBJECTIVE

To evaluate the potential utility of 18F-FDG PET/CT to assess response to neoadjuvant immunochemotherapy in patients with resectable NSCLC, and the ability to screen patients who may benefit from neoadjuvant immunochemotherapy.

METHODS

Fifty one resectable NSCLC (stage IA-IIIB) patients were analyzed, who received two-three cycles neoadjuvant immunochemotherapy.18F-FDG PET/CT was carried out at baseline(scan-1) and prior to radical resection(scan-2). SULmax, SULpeak, MTV, TLG, T/N ratio, ΔSULmax%,ΔSULpeak%, ΔMTV%, ΔTLG%,ΔT/N ratio% were calculated. 18F-FDG PET/CT responses were classified using PERCIST. We then compared the RECIST 1.1 and PERCIST criteria for response assessment.With surgical pathology of primary lesions as the gold standard, the correlation between metabolic parameters of 18F-FDG PET/CT and major pathologic response (MPR) was analyzed. All metabolic parameters were compared to treatment response and correlated to PFS and OS.

RESULTS

In total of fifty one patients, MPR was achieved in 25(49%, 25/51) patients after neoadjuvant therapy. The metabolic parameters of Scan-1 were not correlated with MPR.The degree of pathological regression was negatively correlated with SULmax, SULpeak, MTV, TLG, T/N ratio of scan-2, and the percentage changes of the ΔSULmax%, ΔSULpeak%, ΔMTV%,ΔTLG%,ΔT/N ratio% after neoadjuvant therapy (p < 0.05). According to PERCIST, 36 patients (70.6%, 36/51) showed PMR, 12 patients(23.5%, 12/51) had stable metabolic disease(SMD), and 3 patients(5.9%, 3/51) had progressive metabolic disease (PMD). ROC indicated that all of scan-2 metabolic parameters and the percentage changes of metabolic parameters had ability to predict MPR and non-MPR, SULmax and T/N ratio of scan-2 had the best differentiation ability.The accuracy of RECIST 1.1 and PERCIST criteria were no statistical significance(p = 0.91). On univariate analysis, ΔMTV% has the highest correlation with PFS.

CONCLUSIONS

Metabolic response by 18F-FDG PET/CT can predict MPR to neoadjuvant immunochemotherapy in resectable NSCLC. ΔMTV% was significantly correlated with PFS.

[18F]fluorodeoxyglucose positron emission tomography/computed tomography in combination with clinical data in predicting overall survival in non-small-cell lung cancer patients: A retrospective study

INTRODUCTION

Positron emission tomography/computed tomography (PET/CT) has an established role in evaluating patients with lung cancer. The aim of this work was to assess the predictive capability of [18F]Fluorodeoxyglucose ([18F]FDG) PET/CT parameters on overall survival (OS) in lung cancer patients using an artificial neural network (ANN) in parallel with conventional statistical analysis.

METHODS

Retrospective analysis was performed on a group of 165 lung cancer patients (98M, 67F). PET features associated with the primary tumor: maximum and mean standardized uptake value (SUVmax, SUVmean), total lesion glycolysis (TLG) metabolic tumor volume (MTV) and area under the curve-cumulative SUV histogram (AUC-CSH) and metastatic lesions (SUVmaxtotal, SUVmeantotal, TLGtotal, and MTVtotal) were evaluated. In parallel with conventional statistical analysis (Chi-Square analysis for nominal data, Student's t test for continuous data), the data was evaluated using an ANN. There were 97 input variables in 165 patients using a binary classification of either below, or greater than/equal to median survival post primary diagnosis. Additionally, phantom study was performed to assess the most optimal contouring method.

RESULTS

Males had statistically higher SUVmax (mean: 10.7 vs 8.9; p = 0.020), MTV (mean: 66.5 cm3 vs. 21.5 cm3; p = 0.001), TLG (mean 404.7 vs. 115.0; p = 0.003), TLGtotal (mean: 946.7 vs. 433.3; p = 0.014) and MTVtotal (mean: 242.0 cm3 vs. 103.7 cm3; p = 0.027) than females. The ANN after training and validation was optimised with a final architecture of 4 scaling layer inputs (TLGtotal, SUVmaxtotal, SUVmeantotal and disease stage) and receiving operator characteristic (ROC) analysis demonstrated an AUC of 0.764 (sensitivity of 92.3%, specificity of 57.1%).

CONCLUSION

Conventional statistical analysis and the ANN provided concordant findings in relation to variables that predict decreased survival. The ANN provided a weighted algorithm of the 4 key features to predict decreased survival.

IMPLICATION FOR PRACTICE

Identification of parameters which can predict survival in lung cancer patients might be helpful in choosing the group of patients who require closer look during the follow-up.

FDG PET/CT Tumor Dissemination Characteristic Predicts the Outcome of First-Line Systemic Therapy in Non-small Cell Lung Cancer

RATIONALE AND OBJECTIVES

To explore the correlation between the tumor dissemination characteristic at 18F-fluoro-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) images and the outcome of first-line systemic therapy for stage IV non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

The current retrospective study included 101 NSCLC patients receiving first-line systemic therapy with baseline 18F-FDG PET/CT images available. The distance between the two lesions that were the farthest apart was defined as Dmax to calculate the tumor dissemination. The tumor metabolic volume (MTV) of the primary tumor and the MTV of the whole-body tumor lesions (MTVwb) were calculated using 18F-FDG PET/CT imaging. The Kaplan-Meier survival analyses and Cox predictive model were performed to assess the relationship between the parameters and survival.

RESULTS

Dmax and MTVwb were independent prognostic factors for overall survival (OS) (p = 0.019 and p = 0.011, respectively) and progression-free survival (PFS) (p = 0.043 and p = 0.009, respectively). Poor PFS and OS were associated with high MTVwb (>54.0 cm3) and high Dmax (>48.5 cm) (p = 0.006 and p = 0.008, respectively). When MTVwb and Dmax were combined, three risk groups were stratified with no (score 0), one (score 1), or two (score 2) factors (p < 0.001 for PFS, p < 0.001 for OS). The group with a score of 0 had a considerably longer PFS and OS than those who received a score of 1 or 2 (PFS: 61.1%, 43.5%, and 21.1%, respectively, OS: 77.8%, 54.3%, and 36.8%, respectively).

CONCLUSION

The combination of tumor dissemination characteristic (Dmax) and tumor burden (MTVwb) can further improve the prognosis stratification of NSCLC.

The prognostic relationship of 18F-FDG PET/CT metabolic and volumetric parameters in metastatic ALK + NSCLC

OBJECTIVE

The aim of this study is to determine the role of metabolic and volumetric parameters obtained from 18Fluorine-Fluorodeoxyglucose PET/computed tomography (18F-FDG PET/CT) imaging on progression-free survival (PFS) and overall survival (OS) in patients with advanced nonsquamous cell lung carcinoma (NSCLC) with anaplastic lymphoma kinase (ALK) rearrangement.

METHODS

Pre and post-treatment PET/CT images of the ALK + NSCLC patients between January 2015 and July 2020 were evaluated. The highest standardized uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) values were obtained from pre-tyrosine kinase inhibitor (TKI) basal PET/CT (PETpre) and post-TKI PET/CT (PETpost) images. Total MTV (tMTV) and total TLG (tTLG) values were calculated by summing MTV and TLG values in all tumor foci. The change (Δ) in pSUVmax, pMTV, pTLG, tMTV and tTLG before and after treatment was calculated.The relationship of these parameters with OS and PFS was analyzed.

RESULTS

tTLGpre, tMTVpre, pTLGpre, pMTVpre, ∆SUVmax, ∆tMTV and ∆tTLG values were found to be associated with OS; ∆tMTV, ∆tTLG, tTLGpre, tMTVpre, pTLGpre and pMTVpre were associated with PFS. The cutoff values in both predicting OS and PFS were calculated as -31.6 and 391.1 for ∆tMTV and tTLGpre, respectively. In Cox regression analysis, ∆tMTV and stage for OS and ∆tMTV and tTLGpre for PFS were obtained as prognostic factors.

CONCLUSIONS

Metabolic and volumetric parameters, especially TLG values in the whole body before treatment and change in whole body MTV value, obtained from PET/CT may be useful in predicting prognosis and determining treatment strategies for patients with advanced ALK + NSCLC.

Prognostic value of 18F-FDG PET/CT in patients with advanced or metastatic non-small-cell lung cancer treated with immune checkpoint inhibitors: A systematic review and meta-analysis

PURPOSE

This study aimed to investigate the value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in predicting early immunotherapy response of immune checkpoint inhibitors (ICIs) in patients with advanced or metastatic non-small-cell lung cancer (NSCLC).

METHODS

A comprehensive search of PubMed, Web of science, Embase and the Cochrane library was performed to examine the prognostic value of 18F-FDG PET/CT in predicting early immunotherapy response of ICIs in patients with NSCLC. The main outcomes for evaluation were overall survival (OS) and progression-free survival (PFS). Detailed data from each study were extracted and analyzed using STATA 14.0 software.

RESULTS

13 eligible articles were included in this systematic review. Compared to baseline 18F-FDG PET/CT imaging, the pooled hazard ratios (HR) of maximum and mean standardized uptake values SUVmax, SUVmean, MTV and TLG for OS were 0.88 (95% CI: 0.69-1.12), 0.79 (95% CI: 0.50-1.27), 2.10 (95% CI: 1.57-2.82) and 1.58 (95% CI: 1.03-2.44), respectively. The pooled HR of SUVmax, SUVmean, MTV and TLG for PFS were 1.06 (95% CI: 0.68-1.65), 0.66 (95% CI: 0.48-0.90), 1.50 (95% CI: 1.26-1.79), 1.27 (95% CI: 0.92-1.77), respectively. Subgroup analysis showed that high MTV group had shorter OS than low MTV group in both first line group (HR: 1.97, 95% CI: 1.39-2.79) and undefined line group (HR: 2.11, 95% CI: 1.61-2.77). High MTV group also showed a shorter PFS in first line group (HR: 1.85, 95% CI: 1.28-2.68), and low TLG group had a longer OS in undefined group (HR: 1.37, 95% CI: 1.00-1.86). No significant differences were in other subgroup analysis.

CONCLUSION

Baseline MTV and TLG may have predictive value and should be prospectively studied in clinical trials. Baseline SUVmax and SUVmean may not be appropriate prognostic markers in advanced or metastatic NSCLC patients treated with ICIs.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=323906, identifier CRD42022323906.

A Nomogram for Predicting Pathological Complete Response to Neoadjuvant Chemoradiotherapy Using Semiquantitative Parameters Derived From Sequential PET/CT in Locally Advanced Rectal Cancer

We evaluated the predictive value of semiquantitative volumetric parameters derived from sequential PET/CT and developed a nomogram to predict pathological complete response (pCR) in patients with rectal cancer treated by neoadjuvant chemoradiotherapy (nCRT). From April 2008 to December 2013, among the patients who underwent nCRT, those who were taken sequential PET/CT before and after nCRT were included. MRI-based staging and semiquantitative parameters of PET/CT including standardized uptake value (SUV), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were evaluated before and after nCRT. Multivariable analysis was performed to select significant predictors to construct a nomogram. Sensitivity, specificity, accuracy, and area under the receiver operating characteristics curve (AUC) of the model were evaluated to determine its performance. Among 137 eligible patients, 17 (12.4%) had pCR. All post-PET/CT parameters showed significant differences between pCR and non-pCR groups. Patients were randomly assigned to a training group (91 patients) and a validation group (46 patients). In multivariable analysis with the training group, post-CEA, post-MRI T staging, post-SUV_max, and post-MTV were significantly associated with pCR. There was no significant pre-nCRT variable for predicting pCR. Using significant predictors, a nomogram was developed. Sensitivity, specificity, accuracy, and AUC of the nomogram were 0.882, 0.808, 0.848, and 0.884 with the training group and 0.857, 0.781, 0.783, and 0.828 with the validation group, respectively. This model showed the better performance than other predictive models that did not contain PET/CT parameters. A nomogram containing semiquantitative post-PET/CT could effectively select candidates for organ-sparing strategies.

Prognostication Based on Texture Analysis of Baseline 18F Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Nonsmall-Cell Lung Carcinoma Patients Who Underwent Platinum-Based Chemotherapy as First-Line Treatment

Objective:

Our study aims to establish the potential for tumor heterogeneity evaluated using ¹⁸F fluorodeoxyglucose positron emission tomography/computed tomography (F-18 FDG PET/CT) texture analysis in nonsmall-cell lung carcinoma (NSCLC) patients who underwent platinum-based chemotherapy to provide an independent marker for overall survival (OS) of more than 1-year.

Materials and Methods:

A total of 42 patients (34 male and 8 female) with biopsy-proven NSCLC and mean age 55.33 ± 10.71 years who underwent a baseline F-18 FDG PET/CT and received platinum-based chemotherapy as first-line treatment were retrospectively included in the study. Ten first order, 21 s order texture parameters and 7 SUV and metabolic tumor volume (MTV) based metabolic parameters were calculated. All these parameters were compared between the two survival groups based on OS ≥1 year and OS <1 year. Cut-offs of significant parameters were determined using receiver operating characteristic curve analysis. Survival patterns were compared by log-rank test and presented using Kaplan-Meier curves. Cox proportion hazard model was used to determine the independent prognostic marker for 1 year OS.

Results:

In univariate survival analysis, 3 first order texture parameters (i.e. mean, median, root mean square with hazard ratios [HRs] 2.509 [P = 0.034], 2.590 [P = 0.05], 2.509 [P = 0.034], respectively) and 6 s order texture parameters (i.e. mean, auto correlation, cluster prominence, cluster shade, sum average and sum variance with HRs 2.509 [P = 0.034], 2.509 [P = 0.034], 3.929 [0.007], 2.903 [0.018], 2.954 [0.016] and 2.906 [0.014], respectively) were significantly associated with 1 year OS in these patients. Among the metabolic parameters, only metabolic tumor volume whole-body was significantly associated with 1 year OS. In multivariate survival analysis, cluster prominence came out as the independent predictor of 1 year OS.

Conclusion:

Texture analysis based on F-18 FDG PET/CT is potentially beneficial in the prediction of OS ≥1 year in NSCLC patients undergoing platinum-based chemotherapy as first-line treatment. Thus, can be used to stratify the patients which will not be benefitted with platinum-based chemotherapy and essentially needs to undergo some other therapy option.

Metabolic active tumour volume quantified on [18F]FDG PET/CT further stratifies TNM stage IV non-small cell lung cancer patients

PURPOSE

This study aimed to assess whether the whole body metabolic active tumour volume (MTV_WB), quantified on staging [¹⁸F]FDG PET/CT, could further stratify stage IV non-small cell lung cancer (NSCLC) patients.

METHODS

A group of 160 stage IV NSCLC patients, submitted to staging [¹⁸F]FDG PET/CT between July 2010 and May 2020, were retrospectively evaluated. MTV_WB was quantified. Univariate and multivariate Cox regressions were carried out to assess correlation with overall survival (OS). C-statistic was used to test predictive power. Kaplan-Meier survival curves with Log-Rank tests were performed to compute statistical differences between strata from dichotomized variables and to calculate the estimated mean survival times (EMST). Survival rates at 1 and 5 years were calculated.

RESULTS

MTV_WB was a statistically significant predictor of OS on univariate (p < 0.0001) and multivariate analyses (p < 0.0001). The multivariate model with MTV_WB (Cindex ± SE = 0.657 ± 0.024) worked significantly better as an OS predictor than the cTNM model (Cindex ± SE = 0.544 ± 0.028) (p = 0.003). An EMST of 29.207 ± 3.627(95% CI 22.099-36.316) months and an EMST of 10.904 ± 1.171(95% CI 8.609-13.199) months (Log-Rank p < 0.0001) were determined for patients with MTV_WB < 104.3 and MTV_WB ≥ 104.3, respectively. In subsamples of stage IVA (cut-off point = 114.5) and IVB patients (cut-off point = 191.1), statistically significant differences between EMST were also reported, with p-values of 0.0001 and 0.0002, respectively. In both substages and in the entire cohort, patients with MTV_WB ≥ cut-off points had lower EMST and survival rates.

CONCLUSION

Baseline MTV_WB, measured on staging [¹⁸F]FDG PET/CT, further stratifies stage IV NSCLC patients. This parameter is an independent predictor of OS and provides valuable prognostic information over the 8th edition of cTNM staging.

Prognostic impact of the 18F-fluorodeoxyglucose positron-emission tomography/computed tomography metabolic parameters and correlation with hematological inflammatory markers in lung cancer

Introduction

Hematological inflammatory markers and metabolic parameters in positron-emission tomography/computed tomography (PET/CT) are important indicators predicting the prognosis of the disease in lung cancer as in many cancers. This study aimed to evaluate the correlation between pretreatment hematological inflammatory markers and PET/CT metabolic parameters in nonsmall cell lung cancer (NSCLC) patients and to predict the prognostic value of these parameters.

Materials and Methods

A total of 132 patients with diagnosed NSCLC who underwent PET/CT at staging were retrospectively evaluated. Hematological parameters were obtained from the hemogram taken no more than 2 weeks prior to PET/CT. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume (MPV) were recorded. Maximum standard uptake value, SUVmean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were calculated. Clinical stage, tumor pathology, and overall survival were analyzed with these parameters.

Results

NLR and PLR were significantly positively correlated with MTV and TLG (all P < 0.001), MPV was negatively correlated with TLG (P = 0.021). While TLG, MTV, NLR, and PLR were increased in advanced stage disease, MPV was decreased. Univariate Cox-regression analysis demonstrated that greater age (P = 0.015), advanced stage (P < 0.001), low MPV (P = 0.017), high NLR (P < 0.001), PLR (P < 0.001), MTV (P = 0.004), TLG (P = 0.001) values, multivariate Cox-regression analysis revealed that NLR (P < 0.001) and advanced stage (P < 0.001) were significant predictors of poor prognosis in patients with NSCLC.

Conclusions

There were significant associations between hematological inflammatory markers and PET/CT metabolic parameters in the patients with NSCLC at the time of diagnosis. These indicators can contribute to predicting prognosis in patients with NSCLC.

Update on Molecular Imaging and Precision Medicine in Lung Cancer

Precision medicine integrates molecular pathobiology, genetic make-up, and clinical manifestations of disease in order to classify patients into subgroups for the purposes of predicting treatment response and suggesting outcome. By identifying those patients who are most likely to benefit from a given therapy, interventions can be tailored to avoid the expense and toxicity of futile treatment. Ultimately, the goal is to offer the right treatment, to the right patient, at the right time. Lung cancer is a heterogeneous disease both functionally and morphologically. Further, over time, clonal proliferations of cells may evolve, becoming resistant to specific therapies. PET is a sensitive imaging technique with an important role in the precision medicine algorithm of lung cancer patients. It provides anatomo-functional insight during diagnosis, staging, and restaging of the disease. It is a prognostic biomarker in lung cancer patients that characterizes tumoral heterogeneity, helps predict early response to therapy, and may direct the selection of appropriate treatment.

Primary metabolic tumor volume from 18F-FDG PET/CT associated with epidermal growth factor receptor mutation in lung adenocarcinoma patients

PURPOSE

To explore the potential parameters from F-FDG PET/CT that might be associated with the epidermal growth factor receptor (EGFR) gene mutation status in lung adenocarcinoma (ADC) patients.

METHODS

Data of the test cohort of 191 patients and the validation cohort of 55 patients with newly diagnosed ADC were retrospectively reviewed. All patients underwent F-FDG PET/CT scans and EGFR mutation tests prior to treatment. The metabolic parameters obtained from F-FDG PET/CT combining with clinical characteristics were analyzed by using univariate and multivariate logistic regression analyses. Then two cohorts were enrolled to validate the predictive model by area under the receiver-operating characteristic curve (AUC), respectively.

RESULTS

EGFR mutation-positive was seen of 33.0% (63/191) and 32.7% (18/55) in two cohorts, respectively. In univariate analysis, female, nonsmokers, metabolic parameters of primary tumor [mean standardized uptake value, metabolic tumor volume (pMTV), and total lesion glycolysis], non-necrosis of primary tumor, and serum tumor markers [carbohydrate antigen 19-9, squamous cell carcinoma antigen, and precursor of gastrin releasing peptide (proGRP)] were significantly relevant with EGFR mutation. In multivariate analysis with adjustment of age and TNM stage, pMTV (<8.13 cm), proGRP (≥38.44 pg/ml) and women were independent significant predictors for EGFR mutation. The AUC for the predictive value of these factors was 0.739 [95% confidence interval (CI) 0.665-0.813] in the cohort of 191 patients and 0.716 (95% CI 0.567-0.865) in the cohort of 55 patients, respectively.

CONCLUSION

Low pMTV (<8.13 cm) was an independent predictor and could be integrated with women and high proGRP (≥38.44 pg/ml) to enhance the discriminability on the EGFR mutation status in ADC patients.

Response Prediction and Evaluation Using PET in Patients with Solid Tumors Treated with Immunotherapy

Simple Summary

In cancer treatment, immunotherapy is increasingly becoming important as a component of first-line treatment and has improved the prognosis of patients since its introduction. A large group of patients, however, do not respond to immunotherapy, and predicting a treatment response remains challenging. Furthermore, evaluating a response using conventional computed tomography (CT) scans is not straightforward due to the different mechanism of action of immunotherapy compared to chemotherapy. This review provides an overview of positron emission tomography (PET) in predicting and evaluating treatment response to immunotherapy.

Abstract

In multiple malignancies, checkpoint inhibitor therapy has an established role in the first-line treatment setting. However, only a subset of patients benefit from checkpoint inhibition, and as a result, the field of biomarker research is active. Molecular imaging with the use of positron emission tomography (PET) is one of the biomarkers that is being studied. PET tracers such as conventional ¹⁸F-FDG but also PD-(L)1 directed tracers are being evaluated for their predictive power. Furthermore, the use of artificial intelligence is under evaluation for the purpose of response prediction. Response evaluation during checkpoint inhibitor therapy can be challenging due to the different response patterns that can be observed compared to traditional chemotherapy. The additional information provided by PET can potentially be of value to evaluate a response early after the start of treatment and provide the clinician with important information about the efficacy of immunotherapy. Furthermore, the use of PET to stratify between patients with a complete response and those with a residual disease can potentially guide clinicians to identify patients for which immunotherapy can be discontinued and patients for whom the treatment needs to be escalated. This review provides an overview of the use of positron emission tomography (PET) to predict and evaluate treatment response to immunotherapy.

Differences between TNM classification and 2-[18F]FDG PET parameters of primary tumor in NSCLC patients

Background

The aim of the study was to compare the TNM classification with 2-[¹⁸F]FDG PE T biological parameters of primary tumor in patients with NSCLC.

Materials and methods

Retrospective analysis was performed on a group of 79 newly diagnosed NSCLC patients. PET scans were acquired on Gemini TF PET/CT scanner 60–70 min after injection of 2-[¹⁸F]FDG with the mean activity of 364 ± 75 MBq, with the area being examined from the vertex to mid-thigh. The reconstructed PET images were evaluated using MIM 7.0 Software for SUV_max, MTV and TLG values.

Results

The analysis of the cancer stage according to TNM 8^th edition showed stage IA2 in 8 patients, stage IA3 — 6 patients, stage IB — 4 patients, IIA — 3 patients, 15 patients with stage IIB, stage IIIA — 17 patients, IIIB — 5, IIIC — 5, IVA in 7 patients and stage IVB in 9 patients. The lowest TLG values of primary tumor were observed in stage IA2 (11.31 ± 15.27) and the highest in stage IIIC (1003.20 ± 953.59). The lowest value of primary tumor in SUV_max and MTV were found in stage IA2 (6.8 ± 3.8 and 1.37 ± 0.42, respectively), while the highest SUV_max of primary tumor was found in stage IIA (13.4 ± 11.4) and MTV in stage IIIC (108.15 ± 127.24).

Conclusion

TNM stages are characterized by different primary tumor 2-[¹⁸F]FDG PET parameters, which might complement patient outcome.

Baseline total metabolic tumour volume on 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography-computed tomography as a promising biomarker in patients with advanced non-small cell lung cancer treated with first-line pembrolizumab

INTRODUCTION

Immune checkpoint inhibitors (ICIs) have become the standard of care in the management of advanced non-small cell lung cancer (NSCLC). Nevertheless, only a small proportion of patients benefit from ICIs. The aim of the present study is to assess whether 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography-computed tomography ([18F]FDG-PET/CT)-derived parameters may be used as biomarkers in patients with advanced NSCLC receiving first-line pembrolizumab.

MATERIALS AND METHODS

This is a monocentric retrospective cohort study including patients with advanced NSCLC (stage IV) and Programmed death-ligand 1 (PD-L1) expression ≥50% treated with pembrolizumab. A control group of patients treated with epidermal growth factor receptor (EGFR) inhibitors for EGFR-mutated NSCLC was also enrolled. Only patients with a positive [18F]18F-FDG PET/CT result within 60 days from treatment initiation were included.Total metabolic tumour volume (tMTV) was calculated for each lesion using a dedicated software (PET VCAR; GE Healthcare), which semiautomatically delineates the tumour's contours with a maximum standardised uptake value (SUVmax) threshold of 42% within the lesion. tMTV was obtained summing each lesion's MTV. Potential prognostic parameters for overall survival (OS) were analysed (tMTV, SUVmax, bone/liver metastasis, neutrophil:lymphocyte ratio ≥4, Eastern Cooperative Oncology Group performance status ≥2, lactate dehydrogenase above the upper limit of normal).

RESULTS

Overall, 34 patients treated with first line-pembrolizumab and 40 patients treated with EGFR tyrosine kinase inhibitors were included. In the pembrolizumab group, the median follow-up was 20.3, while the median OS was 4.7 months (95% confidence interval [CI] = 0.3-9.1) for patients with tMTV ≥75 cm³ vs not reached (NR) for patients with tMTV <75 cm³ (95% CI = NR-NR; hazard ratio [HR] = 5.37; 95% CI = 1.72-16.77; p = 0.004). No difference was found in the control group (HR = 1.43; 95% CI = 0.61-3.34; p = 0.411).

CONCLUSION

Our data suggest that tMTV ≥75cm³ can be used as a prognostic biomarker of poor outcomes in patients with PD-L1-high advanced NSCLC treated with first-line pembrolizumab. This information could be useful for the selection of patients who may require the addition of chemotherapy to pembrolizumab.

Metabolic Parameters as Biomarkers of Response to Immunotherapy and Prognosis in Non-Small Cell Lung Cancer (NSCLC): A Real World Experience

Immune-checkpoint inhibitors (ICIs) have been proven to have great efficacy in non-small cell lung cancer (NSCLC) as single agents or in combination therapy, being capable to induce deep and durable remission. However, severe adverse events may occur and about 40% of patients do not benefit from the treatment. Predictive factors of response to ICIs are needed in order to customize treatment. The aim of this study is to evaluate the correlation between quantitative positron emission tomography (PET) parameters defined before starting ICI therapy and responses to treatment and patient outcome. We retrospectively analyzed 92 NSCLC patients treated with nivolumab, pembrolizumab or atezolizumab. Basal PET/computed tomography (CT) scan parameters (whole-body metabolic tumor volume-wMTV, total lesion glycolysis-wTLG, higher standardized uptake volume maximum and mean-SUVmax and SUVmean) were calculated for each patient and correlated with outcomes. Patients who achieved disease control (complete response + partial response + stable disease) had significantly lower MTV median values than patients who had not (progressive disease) (77 vs. 160.2, p = 0.039). Furthermore, patients with MTV and TLG values lower than the median values had improved OS compared to patients with higher MTV and TLG (p = 0.03 and 0.05, respectively). No relation was found between the other parameters and outcome. In conclusion, baseline metabolic tumor burden, measured with MTV, might be an independent predictor of treatment response to ICI and a prognostic biomarker in NSCLC patients.

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.

Value of 18F-FDG PET/CT-Based Radiomics Nomogram to Predict Survival Outcomes and Guide Personalized Targeted Therapy in Lung Adenocarcinoma With EGFR Mutations

Objectives

To investigate the development and validation of a radiomics nomogram based on PET/CT for guiding personalized targeted therapy in patients with lung adenocarcinoma mutation(s) in the EGFR gene.

Methods

A cohort of 109 (77/32 in training/validation cohort) consecutive lung adenocarcinoma patients with an EGFR mutation was enrolled in this study. A total of 1672 radiomic features were extracted from PET and CT images, respectively. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to select the radiomic features and construct the radiomics nomogram for the estimation of overall survival (OS), which was then assessed with respect to calibration and clinical usefulness. Patients with an EGFR mutation were divided into high- and low- risk groups according to their nomogram score. The treatment strategy for high- and low-risk groups was analyzed using Kaplan–Meier analysis and a log-rank test.

Results

The C-index of the radiomics nomogram for the prediction of OS in lung adenocarcinoma in patients with an EGFR mutation was 0.840 and 0.803 in the training and validation cohorts, respectively. Distant metastasis [(Hazard ratio, HR),1.80], metabolic tumor volume (MTV, HR, 1.62), and rad score (HR, 17.23) were the independent risk factors for patients with an EGFR mutation. The calibration curve showed that the predicted survival time was remarkably close to the actual time. Decision curve analysis demonstrated that the radiomics nomogram was clinically useful. Targeted therapy for patients with high-risk EGFR mutations attained a greater benefit than other therapies (p < 0.0001), whereas the prognoses of the two therapies were similar in the low-risk group (p = 0.85).

Conclusions

Development and validation of a radiomics nomogram based on PET/CT radiomic features combined with clinicopathological factors may guide targeted therapy for patients with lung adenocarcinoma with EGFR mutations. This is conducive to the advancement of precision medicine.

Characterization of FDG PET Images Using Texture Analysis in Tumors of the Gastro-Intestinal Tract: A Review

Radiomics or textural feature extraction obtained from positron emission tomography (PET) images through complex mathematical models of the spatial relationship between multiple image voxels is currently emerging as a new tool for assessing intra-tumoral heterogeneity in medical imaging. In this paper, available literature on texture analysis using FDG PET imaging in patients suffering from tumors of the gastro-intestinal tract is reviewed. While texture analysis of FDG PET images appears clinically promising, due to the lack of technical specifications, a large variability in the implemented methodology used for texture analysis and lack of statistical robustness, at present, no firm conclusions can be drawn regarding the predictive or prognostic value of FDG PET texture analysis derived indices in patients suffering from gastro-enterologic tumors. In order to move forward in this field, a harmonized image acquisition and processing protocol as well as a harmonized protocol for texture analysis of tumor volumes, allowing multi-center studies excluding statistical biases should be considered. Furthermore, the complementary and additional value of CT-imaging, as part of the PET/CT imaging technique, warrants exploration.

Diagnostic and Predictive Values of 18F-FDG PET/CT Metabolic Parameters in EGFR-Mutated Advanced Lung Adenocarcinoma

Purpose

The clinical implications of the metabolic parameters of ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (¹⁸F-FDG PET/CT) in epidermal growth factor receptor (EGFR)-mutated lung cancer are not fully understood. The aim of this study was to evaluate the diagnostic and prognostic utility of the parameters in EGFR-mutated lung cancer patients.

Patients and Methods

We retrospectively enrolled 134 patients with advanced lung adenocarcinoma (72 EGFR-negative and 62 EGFR-positive). We evaluated the correlation between EGFR mutational status and the maximum standardized uptake value (SUVmax), as well as the associations between treatment outcomes in EGFR-mutated patients and various metabolic parameters of primary tumors. For the best predictive parameters, we calculated the metabolic tumor volume (MTV) and total lesion glycolysis (TLG) using two SUV cutoffs: 1.5 (MTV_1.5, TLG_1.5) and 2.5 (MTV_2.5, TLG_2.5).

Results

Mean SUVmax was lower for EGFR-mutated tumors compared with EGFR wild-type (6.11 vs 10.41, p < 0.001) tumors. Low SUVmax was significantly associated with positive EGFR mutation (odds ratio = 1.74). Multivariate analysis for survival demonstrated that high MTV_1.5, TLG_1.5, MTV_2.5, and TLG_2.5 were independently associated with shorter progression-free survival (PFS) and overall survival (OS), and the highest hazard ratios were found in TLG_1.5 (3.26 for PFS and 4.62 for OS).

Conclusion

SUVmax may be predictive for EGFR mutational status, and MTV and TLG of primary tumors may be promising prognostic parameters; ¹⁸F-FDG PET/CT has potential utility for the risk stratification of EGFR-mutated patients treated with targeted therapy.

Prognostic value of metabolic tumor volume and total lesion glycolysis from ¹⁸F-FDG PET/CT in lymph node metastases and risk stratification of endometrial carcinoma

Objective

To investigate the prognostic value of metabolic tumor volume (MTV) and total lesion glycolysis (TLG), measured by preoperative ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT), in risk stratification of patients with endometrial carcinoma (EC).

Methods

The patients with pathological diagnosis of EC who underwent preoperative ¹⁸F-FDG PET/CT imaging were retrospectively selected for analysis of the prognostic values of PET parameters in risk classification and lymph node metastases (LNMs). Receiver-operating-characteristic analysis was used to analyze the correlation of PET parameters cutoff values with deep myometrial invasion (MI), lymphovascular space involvement and LNM for prognostic values in risk stratification.

Results

The sensitivity, specificity, positive predictive value, negative predictive value and accuracy for detection of LNM are 83.3%, 99.7%, 90.9%, 99.5% and 99.2%, respectively. The MTV and TLG of primary lesion of EC in the patients with LNM are notably higher than those in patients without LNM, p<0.010. The MTV and TLG of the EC primary lesions in high-risk patients are significantly higher than those in low-risk patients (p<0.010), but the maximum standardized uptake value (SUVmax) is not. The MTV and TLG of primary lesions were superior to SUVmax for predicting of deep MI, LNM and high-risk of EC (p<0.005).

Conclusion

MTV and TLG of primary lesions are more valuable in predicting risk stratification of EC patients. Preoperative ¹⁸F-FDG PET/CT imaging is useful in predicting the LNM of EC and may help guide pelvic lymphadenectomy to avoid unnecessary pelvic lymphadenectomy in EC patients with low-risk stratification.

18F-fluorodeoxyglucose positron emission tomography/computed tomography-based radiomic features for prediction of epidermal growth factor receptor mutation status and prognosis in patients with lung adenocarcinoma

Background

To investigate whether radiomic features from (¹⁸F)-fluorodeoxyglucose positron emission tomography/computed tomography [(¹⁸F)-FDG PET/CT] can predict epidermal growth factor receptor (EGFR) mutation status and prognosis in patients with lung adenocarcinoma.

Methods

One hundred and seventy-four consecutive patients with lung adenocarcinoma underwent (¹⁸F)-FDG PET/CT and EGFR gene testing were retrospectively analyzed. Radiomic features combined with clinicopathological factors to construct a random forest (RF) model to identify EGFR mutation status. The mutant/wild-type model was trained on a training group (n=139) and validated in an independent validation group (n=35). The second RF classifier predicting the 19/21 mutation site was also built and evaluated in an EGFR mutation subset (training group, n=80; validation group, n=25). Radiomic score and 5 clinicopathological factors were integrated into a multivariate Cox proportional hazard (CPH) model for predicting overall survival (OS). AUC (the area under the receiver characteristic curve) and C-index were calculated to evaluate the model’s performance.

Results

Of 174 patients, 109 (62.6%) harbored EGFR mutations, 21L858R was the most common mutation type [55.9% (61/109)]. The mutant/wild-type model was identified in the training (AUC, 0.77) and validation (AUC, 0.71) groups. The 19/21 mutation site model had an AUC of 0.82 and 0.73 in the training and validation groups, respectively. The C-index of the CPH model was 0.757. The survival time between targeted therapy and chemotherapy for patients with EGFR mutations was significantly different (P=0.03).

Conclusions

Radiomic features based on (¹⁸F)-FDG PET/CT combined with clinicopathological factors could reflect genetic differences and predict EGFR mutation type and prognosis.

The Relative Importance of Clinical and Socio-demographic Variables in Prognostic Prediction in Non-Small Cell Lung Cancer: A Variable Importance Approach

BACKGROUND

Prognostic modeling in health care has been predominantly statistical, despite a rapid growth of literature on machine-learning approaches in biological data analysis. We aim to assess the relative importance of variables in predicting overall survival among patients with non-small cell lung cancer using a Variable Importance (VIMP) approach in a machine-learning Random Survival Forest (RSF) model for posttreatment planning and follow-up.

METHODS

A total of 935 non-small cell lung cancer patients were randomly and equally divided into 2 training and testing cohorts in an RFS model. The prognostic variables included age, sex, race, the TNM Classification of Malignant Tumors (TNM) stage, smoking history, Eastern Cooperative Oncology Group performance status, histologic type, treatment category, maximum standard uptake value of whole-body tumor (SUVmaxWB), whole-body metabolic tumor volume (MTVwb), and Charlson Comorbidity Index. The VIMP was calculated using a permutation method in the RSF model. We further compared the VIMP of the RSF model to that of the standard Cox survival model. We examined the order of VIMP with the differential functional forms of the variables.

RESULTS

In both the RSF and the standard Cox models, the most important variables are treatment category, TNM stage, and MTVwb. The order of VIMP is more robust in RSF model than in Cox model regarding the differential functional forms of the variables.

CONCLUSIONS

The RSF VIMP approach can be applied alongside with the Cox model to further advance the understanding of the roles of prognostic factors, and improve prognostic precision and care efficiency.

The effect of systemic inflammation indexes and 18FDG PET metabolic parameters on survival in advanced lung adenocarcinoma

OBJECTIVE

To determine the effect of systemic inflammation indexes and fluorine-18 fluorodeoxyglucose (¹⁸FDG) positron emission tomography (PET) metabolic parameters on survival in advanced lung adenocarcinoma.

METHODS

A total of 133 patients who underwent ¹⁸FDG PET for initial staging were investigated retrospectively. Baseline patient characteristics, routine blood test results, ¹⁸FDG PET metabolic parameters, and treatment history were examined. Overall survival (OS) was demonstrated by Kaplan-Meier analysis, and the curves were compared by the log-rank test. Systemic inflammation response index (SIRI) was defined as neutrophil x monocyte/lymphocyte count.

RESULTS

Lymphocyte/monocyte ratio (LMR) and SIRI were found to be significant for OS. The cutoff point was 2.25 for LMR. Median OS was 8 months for ⩽2.25 and 14 months for >2.25 (p = 0.005). For SIRI, the cutoff point was 2. SIRI ⩽2 was associated with a median OS of 16 months compared to 10 months for patients with SIRI >2 (p = 0.043). Maximum of standardized uptake value, total lesion glycolysis, and metabolic tumor volume were not found to be significant for OS (p = 0.225, p = 0.061, p = 0.355, respectively). No correlation was found between inflammatory indexes and PET metabolic parameters.

CONCLUSION

Age and LMR parameters were prognostic for survival in Cox regression analysis. There was no correlation between ¹⁸FDG PET parameters and inflammatory indexes.

18F-FDG PET/CT in lung adenosquamous carcinoma and its correlation with clinicopathological features and prognosis

OBJECTIVE

Lung adenosquamous carcinoma (ASC) is a rare histological subtype of non-small cell lung cancer (NSCLC). Due to its rarity, the studies about ¹⁸F-FDG PET/CT in this kind of pulmonary tumor were quite limited. Thus, this study investigated ¹⁸F-FDG PET/CT findings in ASC and its correlation with clinicopathological features and clinical outcomes.

METHODS

Preoperative ¹⁸F-FDG PET/CT findings and parameters of maximum standard uptake value (SUV_max), metabolic tumor volume and total lesion glycolysis of primary lesion (MTV-P, TLG-P), combination of primary lesion and metastases (MTV-C, TLG-C), and clinicopathological features were retrospectively investigated in patients with ASC. Moreover, progression-free survival (PFS) was also analyzed.

RESULTS

All 41 patients (25 men; 16 women; age: 60 ± 7 years) had single ASC with the mean diameter of 33 ± 14 mm. Six lesions were located centrally and 35 peripherally. Serum tumor markers were abnormally increased sporadically. Twenty-two cases were at TNM stage I, 9 at II, and 10 at III. The primary tumors were FDG-avid in all cases, with the average SUV_max of 11.5 ± 6.0. SUV_max was significantly associated with tumor location, size, and TNM stage (P < 0.05). Forty-one lesions were subgrouped into 23 AC-predominant and 18 SCC-predominant lesions, and significant differences were observed for age, tumor size, and SUV_max in two groups (P < 0.05). The median PFS of 41 cases was 19 months, and 12-month and 24-month PFS rates were 72.1% and 36.1%, respectively. SUV_max, MTV-P, and TLG-C were significantly associated with PFS (P < 0.05).

CONCLUSIONS

ASC of the lung displayed high SUV_max on ¹⁸F-FDG PET/CT, which was associated with tumor location, size, TNM stage, and predominant histologic component. Moreover, metabolic parameters of ¹⁸F-FDG PET/CT were independent prognostic factors of this rare lung malignancy.

Prognostic value of [18F]FDG PET/CT parameters in surgically resected primary lung adenocarcinoma: a single-center experience

OBJECTIVE

To evaluate the prognostic role of maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) measured by FDG-positron emission tomography (PET)/computed tomography (CT) in patients with primary lung adenocarcinoma undergoing surgical resection.

METHODS

All consecutive patients undergoing curative surgery for primary lung adenocarcinoma at the Thoracic Surgery Unit of the University Hospital of Parma between January 2009 and December 2014 were retrospectively analyzed. The cutoff point of each continuous PET parameter was determined through receiver operating characteristic curve and Youden index, using overall survival (OS) as the classification status. Univariate and multivariate Cox proportional hazards models were applied to evaluate the association between OS and potential prognostic variables, including SUVmax, MTV, and TLG.

RESULTS

A total of 193 patients were considered eligible for this study. The mean 5-year OS rate was 70.5 ± 3.5%. Acinar and lepidic patterns were more frequently associated with absent or low (<2.5) SUVmax values [18F]FDG uptake. At univariate analysis, male sex, advanced stage, micropapillary and solid pattern, lymphatic, blood vessels and pleural invasion, high SUVmax, MTV, and TLG were significantly associated with poorer OS. Multivariate analyses revealed that only sex, stage, and TLG were independent factors for OS, with male sex, stage 3+4, and high TLG value (p = 0.041) significantly associated with poorer OS.

CONCLUSIONS

In this study, [18F]FDG PET/CT parameters SUVmax, MTV, and TLG were prognostic factors in patients with surgically resected lung adenocarcinoma, able to predict OS and helping to further stratify these patients into prognostic subsets. Elevated TLG was also an independent predictor for shorter OS.

Correlation Study of 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Pathological Subtypes of Invasive Lung Adenocarcinoma and Prognosis

Purpose: To investigate the correlation between ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) metabolic parameters and clinicopathological factors in pathological subtypes of invasive lung adenocarcinoma and prognosis.

Patients and Methods: Metabolic parameters and clinicopathological factors from 176 consecutive patients with invasive lung adenocarcinoma between August 2008 and August 2016 who underwent ¹⁸F-FDG PET/CT examination were retrospectively analyzed. Invasive lung adenocarcinoma was divided into five pathological subtypes:lepidic predominant adenocarcinoma (LPA), acinar predominant adenocarcinoma (APA), papillary predominant adenocarcinoma (PPA), solid predominant adenocarcinoma (SPA), and micropapillary predominant adenocarcinoma (MPA). The differences in metabolic parameters [maximal standard uptake value (SUVmax), mean standard uptake value (SUVmean), total lesion glycolysis (TLG), and metabolic tumor volume (MTV)] and tumor diameter for different pathological subtypes were analyzed. Patients were divided into two groups according to their prognosis: good prognosis group (LPA, APA, PPA) and poor prognosis group (SPA, MPA). Logistic regression was used to filter predictors and construct a predictive model, and areas under the receiver operating curve (AUC) were calculated. Cox regression analysis was performed on prognostic factors.

Results: 82 (46.6%) females and 94 (53.4%) males of patients with invasive lung adenocarcinoma were enrolled in this study. Metabolic parameters and tumor diameter of different pathological subtype had statistically significant (P < 0.05). The predictive model constructed using independent predictors (Distant metastasis, Ki-67, and SUVmax) had good classification performance for both groups. The AUC for SUVmax was 0.694 and combined with clinicopathological factors were 0.745. Cox regression analysis revealed that Stage, TTF-1, MTV, and pathological subtype were independent risk factors for patient prognosis. The hazard ratio (HR) of the poor prognosis group was 1.948 (95% CI 1.042–3.641) times the good prognosis group. The mean survival times of good and poor prognosis group were 50.2621 (95% CI 47.818–52.706) and 35.8214 (95% CI 27.483–44.159) months, respectively, while the median survival time was 47.00 (95% CI 45.000–50.000) and 31.50 (95% CI 23.000–49.000) months, respectively.

Conclusion: PET/CT metabolic parameters combined with clinicopathological factors had good classification performance for the different pathological subtypes, which may provide a reference for treatment strategies and prognosis evaluation of patients.

[Application of Metabolic Parameters Measured by ¹⁸F-FDG PET/CT in the Evaluation of the Prognosis of Non-small Cell Lung Cancer]

基于肺癌肿瘤-淋巴结-转移（tumor-node-metastasis, TNM）分期的治疗方案制定和预后评价是目前国内外肺癌指南中的基本原则。18氟代脱氧葡萄糖正电子发射计算机断层显像（¹⁸F-deoxyglucose positron emission tomography/computed tomography, ¹⁸F-FDG PET/CT）代谢参数如标准摄取值（standardized uptake value, SUV）、肿瘤代谢体积（metabolic tumor volume, MTV）、病灶糖酵解总量（total lesion glycolysis, TLG）可以反映肿瘤侵袭性的信息，提供额外的预后信息。将量化的肿瘤代谢负荷MTV、TLG联合传统的TNM分期对患者进行危险分层，作为一种新的分期方式可以辅助临床医师制定更为合适的治疗方案。¹⁸F-FDG PET/CT图像纹理分析作为一种新兴研究方法，可以量化肿瘤内放射性摄取的空间分布异质性，进而了解肿瘤的生物学特征。本文对¹⁸F-FDG PET/CT代谢参数在非小细胞肺癌患者预后评估的应用进行阐述。

Sub-cutaneous Fat Mass measured on multislice computed tomography of pretreatment PET/CT is a prognostic factor of stage IV non-small cell lung cancer treated by nivolumab

Introduction: Our aim was to explore the prognostic value of anthropometric parameters in patients treated with nivolumab for stage IV non-small cell lung cancer (NSCLC). Methods: We retrospectively included 55 patients with NSCLC treated by nivolumab with a pretreatment ¹⁸FDG positron emission tomography coupled with computed tomography (PET/CT). Anthropometric parameters were measured on the CT of PET/CT by in-house software (Anthropometer3D) allowing an automatic multi-slice measurement of Lean Body Mass (LBM), Fat Body Mass (FBM), Muscle Body Mass (MBM), Visceral Fat Mass (VFM) and Sub-cutaneous Fat Mass (SCFM). Clinical and tumor parameters were also retrieved. Receiver operator characteristics (ROC) analysis was performed and overall survival at 1 year was studied using Kaplan-Meier and Cox analysis. Results: FBM and SCFM were highly correlated (ρ = 0.99). In ROC analysis, only FBM, SCFM, VFM, body mass index (BMI) and metabolic tumor volume (MTV) had an area under the curve (AUC) significantly higher than 0.5. In Kaplan-Meier analysis using medians as cut-offs, prognosis was worse for patients with low SCFM (<5.69 kg/m²; p = 0.04, survivors 41% vs 75%). In Cox univariate analysis using continuous values, BMI (HR = 0.84, p= 0.007), SCFM (HR = 0.75, p = 0.003) and FBM (HR = 0.80, p= 0.004) were significant prognostic factors. In multivariate analysis using clinical parameters (age, gender, WHO performance status, number prior regimens) and SCFM, only SCFM was significantly associated with poor survival (HR = 0.75, p = 0.006). Conclusions: SCFM is a significant prognosis factor of stage IV NSCLC treated by nivolumab.

Clinical utility of tumor genomic profiling in patients with high plasma circulating tumor DNA burden or metabolically active tumors

BACKGROUND

This retrospective study was undertaken to determine if the plasma circulating tumor DNA (ctDNA) level and tumor biological features in patients with advanced solid tumors affected the detection of genomic alterations (GAs) by a plasma ctDNA assay.

METHOD

Cell-free DNA (cfDNA) extracted from frozen plasma (N = 35) or fresh whole blood (N = 90) samples were subjected to a 62-gene hybrid capture-based next-generation sequencing assay FoundationACT. Concordance was analyzed for 51 matched FoundationACT and FoundationOne (tissue) cases. The maximum somatic allele frequency (MSAF) was used to estimate the amount of tumor fraction of cfDNA in each sample. The detection of GAs was correlated with the amount of cfDNA, MSAF, total tumor anatomic burden (dimensional sum), and total tumor metabolic burden (SUVmax sum) of the largest ten tumor lesions on PET/CT scans.

RESULTS

FoundationACT detected GAs in 69 of 81 (85%) cases with MSAF > 0. Forty-two of 51 (82%) cases had ≥ 1 concordance GAs matched with FoundationOne, and 22 (52%) matched to the National Comprehensive Cancer Network (NCCN)-recommended molecular targets. FoundationACT also detected 8 unique molecular targets, which changed the therapy in 7 (88%) patients who did not have tumor rebiopsy or sufficient tumor DNA for genomic profiling assay. In all samples (N = 81), GAs were detected in plasma cfDNA from cancer patients with high MSAF quantity (P = 0.0006) or high tumor metabolic burden (P = 0.0006) regardless of cfDNA quantity (P = 0.2362).

CONCLUSION

This study supports the utility of using plasma-based genomic assays in cancer patients with high plasma MSAF level or high tumor metabolic burden.

Prognostic value of metabolic tumour volume and total lesion glycolysis measured by 18F-fluorodeoxyglucose positron emission tomography/computed tomography in small cell lung cancer: A systematic review and meta-analysis

The aim of this study was to evaluate the prognostic value of metabolic tumour volume (MTV) and total lesion glycolysis (TLG) for small cell lung cancer (SCLC). MEDLINE, EMBASE and Cochrane Library databases were systematically searched. The pooled hazard ratio (HR) was used to measure the influence of MTV and TLG on survival. The subgroup analysis according to VALSG stage and the measured extent of MTV was performed. Patients with high MTV values experienced a significantly poorer prognosis with a HR of 2.42 (95% CI 1.46-4.03) for overall survival (OS) and a HR of 2.78 (95% CI 1.39-5.53) for progression-free survival (PFS) from the random effect model, and the pooled HR from the fixed effect model was 2.10 (95% CI 1.77-2.50) for OS and 2.27 (95% CI 1.83-2.81) for PFS. Patients with high TLG experienced a poorer prognosis with a HR of 1.61 (95% CI: 1.24-2.07) for OS from the random effect model, and the pooled HR from the fixed effect model was 1.64 (95% CI 1.37-1.96). Heterogeneity among studies was high for MTV in both OS and PFS meta-analyses (I²  = 87% and 88% respectively). After removing one outlier study the heterogeneity was substantially reduced (I²  = 0%) and the pooled HR for the effect of MTV on OS was 1.80 (1.51-2.16, P < 0.00001), and on PFS it was 1.86 (1.49-2.33, P < 0.00001), using either the fixed or random effects model. High MTV is associated with a significantly poorer prognosis OS and PFS, and high TLG is associated with a significantly poorer prognosis regarding OS for SCLC.

An updated and validated PET/CT volumetric prognostic index for non-small cell lung cancer

OBJECTIVES

Whole-body metabolic tumor volume (MTV_WB) and TNM staging are independent prognostic factors for overall survival (OS) in non-small cell lung cancer (NSCLC). We aimed to update and validate the PET/CT volumetric prognostic index (PVP index) using the new 8th edition TNM staging system to evaluate its prognostic power versus TNM staging and MTV_WB alone.

MATERIALS AND METHODS

This study was a retrospective analysis of 949 non-small cell lung cancer (NSCLC) patients diagnosed between 2004 and 2014. Clinical TNM stage, MTV_WB, age and gender, tumor histology type at the initial staging PET/CT exam, as well as treatment history and long-term survival data were obtained. Patients were randomly assigned to modeling or validation group. Univariate and multivariate Cox regression analyses were performed to compare PVP index, TNM stage, and MTV_WB in the validation group.

RESULTS

The updated PVP index included the 3 variables TNM stage, and MTV_WB and age. Univariate Cox models showed significant association of PVP index with overall survival (OS) in patients with NSCLC (with Hazard ratio HR = 2.88 in the validation group, p < 0.001). The C-statistic of the PVP index (C-statistic = 0.71 in the validation group) was significantly greater than that of 8th edition TNM staging (C-statistic = 0.68, p = 0.029), MTV_WB (C-statistic = 0.68, p = 0.001), and patient age (C-statistic = 0.53, p < 0.001). Multivariate Cox regression analyses demonstrated significant association of PVP index with OS (with HR = 2.80, p < 0.001) after adjusting patient's gender and tumor histology.

CONCLUSIONS

The updated PVP index provides a quantitative risk assessment for NSCLC patients using 8th edition TNM staging, MTV_WB, and age. The index provides a simple and practical way for the care team to incorporate the independent prognostic value of both the TNM stage and MTV_WB. This approach can further improve the accuracy of overall survival prognosis.

Developing and validating a novel metabolic tumor volume risk stratification system for supplementing non-small cell lung cancer staging

PURPOSE

We hypothesized that whole-body metabolic tumor volume (MTVwb) could be used to supplement non-small cell lung cancer (NSCLC) staging due to its independent prognostic value. The goal of this study was to develop and validate a novel MTVwb risk stratification system to supplement NSCLC staging.

METHODS

We performed an IRB-approved retrospective review of 935 patients with NSCLC and FDG-avid tumor divided into modeling and validation cohorts based on the type of PET/CT scanner used for imaging. In addition, sensitivity analysis was conducted by dividing the patient population into two randomized cohorts. Cox regression and Kaplan-Meier survival analyses were performed to determine the prognostic value of the MTVwb risk stratification system.

RESULTS

The cut-off values (10.0, 53.4 and 155.0 mL) between the MTVwb quartiles of the modeling cohort were applied to both the modeling and validation cohorts to determine each patient's MTVwb risk stratum. The survival analyses showed that a lower MTVwb risk stratum was associated with better overall survival (all p < 0.01), independent of TNM stage together with other clinical prognostic factors, and the discriminatory power of the MTVwb risk stratification system, as measured by Gönen and Heller's concordance index, was not significantly different from that of TNM stage in both cohorts. Also, the prognostic value of the MTVwb risk stratum was robust in the two randomized cohorts. The discordance rate between the MTVwb risk stratum and TNM stage or substage was 45.1% in the modeling cohort and 50.3% in the validation cohort.

CONCLUSION

This study developed and validated a novel MTVwb risk stratification system, which has prognostic value independent of the TNM stage and other clinical prognostic factors in NSCLC, suggesting that it could be used for further NSCLC pretreatment assessment and for refining treatment decisions in individual patients.

Role of Various Metabolic Parameters Derived From Baseline 18F-FDG PET/CT as Prognostic Markers in Non-Small Cell Lung Cancer Patients Undergoing Platinum-Based Chemotherapy

PURPOSE

The aim of this study was to prospectively evaluate the role of various quantitative and semiquantitative metabolic parameters derived from dynamic and static baseline F-FDG PET/CT in prediction of overall survival (OS) in non-small cell lung cancer (NSCLC) patients who were planned to undergo platinum-based chemotherapy.

METHODS

Sixty patients (51 male and 9 female patients) with biopsy-proven NSCLC and mean age 59.55 ± 10.06 years who were planned to undergo platinum-based chemotherapy were enrolled in the study. Each patient underwent a baseline regional dynamic and a static whole-body F-FDG PET/CT after injecting 0.21 mCi/kg (5.18-7.77 MBq/kg) of F-FDG intravenously. Two dynamic PET/CT parameters, that is, net influx rate constant and glucose metabolic rate at 30 and 60 minutes, were evaluated. In addition, whole-body PET/CT parameters, that is, SUVmax, average SUV, tumor-to-background ratio, metabolic tumor volume (MTV), total lesion glycolysis (TLG) of the primary tumor, and MTV and TLG of whole-body tumor lesions, were evaluated. Best possible cutoffs for all parameters were calculated using receiver operating characteristic curve analysis. Survival analysis was performed using log-rank test, Kaplan-Meier curves, and Cox proportional hazards model to determine the prognostic markers for OS.

RESULTS

The median follow-up period was 4.4 months (range, 8 days to 15.9 months). In univariate analysis, the 4 static whole-body PET/CT parameters, that is, MTV, TLG, and MTV and TLG of whole-body tumor lesions, were found to be significantly associated with OS with cutoff values of 120, 800, 160, and 1350 cm and hazard ratios of 3.64 (P = 0.001), 3.35 (P = 0.002), 2.51 (P = 0.019), and 2.69 (P = 0.008), respectively. In multivariate survival analysis, MTV was found to be an independent prognostic marker for OS.

CONCLUSIONS

Baseline MTV and TLG evaluated from primary tumor as well as the whole-body tumor lesions are reliable prognostic markers of OS in NSCLC patients undergoing platinum-based chemotherapy. However, other baseline whole-body PET/CT parameters (SUVmax, average SUV, and tumor-to-background ratio) and dynamic PET/CT parameters (net influx rate constant, glucose metabolic rate) have no prognostic value in these patients.

The role of metabolic tumor volume (MTV) measured by [18F] FDG PET/CT in predicting EGFR gene mutation status in non-small cell lung cancer

Many noninvasive methods have been explored to determine the mutation status of the epidermal growth factor receptor (EGFR) gene, which is important for individualized treatment of non-small cell lung cancer (NSCLC). We evaluated whether metabolic tumor volume (MTV), a parameter measured by [18F] fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) might help predict EGFR mutation status in NSCLC. Overall, 87 patients who underwent EGFR genotyping and pretreatment PET/CT between January 2013 and September 2016 were reviewed. Clinicopathologic characteristics and metabolic parameters including MTV were evaluated. Univariate and multivariate analyses were used to assess the independent variables that predict mutation status to create prediction models. Forty-one patients (41/87) were identified as having EGFR mutations. The multivariate analysis showed that patients with lower MTV (MTV≤11.0 cm3, p=0.001) who were non-smokers (p=0.037) and had a peripheral tumor location (p=0.033) were more likely to have EGFR mutations. Prediction models using these criteria for EGFR mutation yielded a high AUC (0.805, 95% CI 0.712–0.899), which suggests that the analysis had good discrimination. In conclusion, NSCLC patients with EGFR mutations showed significantly lower MTV than patients with wild-type EGFR. Prediction models based on MTV and clinicopathologic characteristics could provide more information for the identification of EGFR mutations.

Development of an Immune-Pathology Informed Radiomics Model for Non-Small Cell Lung Cancer

With increasing use of immunotherapy agents, pretreatment strategies for identifying responders and non-responders is useful for appropriate treatment assignment. We hypothesize that the local immune micro-environment of NSCLC is associated with patient outcomes and that these local immune features exhibit distinct radiologic characteristics discernible by quantitative imaging metrics. We assembled two cohorts of NSCLC patients treated with definitive surgical resection and extracted quantitative parameters from pretreatment CT imaging. The excised primary tumors were then quantified for percent tumor PDL1 expression and density of tumor-infiltrating lymphocyte (via CD3 count) utilizing immunohistochemistry and automated cell counting. Associating these pretreatment radiomics parameters with tumor immune parameters, we developed an immune pathology-informed model (IPIM) that separated patients into 4 clusters (designated A-D) utilizing 4 radiomics features. The IPIM designation was significantly associated with overall survival in both training (5 year OS: 61%, 41%, 50%, and 91%, for clusters A-D, respectively, P = 0.04) and validation (5 year OS: 55%, 72%, 75%, and 86%, for clusters A-D, respectively, P = 0.002) cohorts and immune pathology (all P < 0.05). Specifically, we identified a favorable outcome group characterized by low CT intensity and high heterogeneity that exhibited low PDL1 and high CD3 infiltration, suggestive of a favorable immune activated state. We have developed a NSCLC radiomics signature based on the immune micro-environment and patient outcomes. This manuscript demonstrates model creation and validation in independent cohorts.

Prognostic significance of combined radiologic imaging modalities for prognosis of clinical IA adenocarcinomas

Background

We previously proposed measuring tumor size using mediastinal window setting on high-resolution computed tomography (CT) as a simple and useful modality for preoperative prognostication of small adenocarcinoma. Hence, the importance of tumor volume and positron emission tomography (PET) for preoperative prognostication of clinical stage IA (cIA) adenocarcinoma was studied.

Materials and Methods

We retrospectively evaluated total 324 patients who underwent pulmonary resection of cIA adenocarcinoma between July 2008 and August 2015. Reconstructed three-dimensional (3D) images from 1–1.5 mm-sliced CT were evaluated for whole tumor volume including ground grass opacity, consolidation volume on lung window setting, and mediastinal window volume (MWV). The values examined by PET were total lesion glycolysis (TLG), and maximum standardized uptake (SUV max) and mean. Pathologic status was evaluated according to tumor maximum size, invasive size (IS), lymphatic and vascular vessels, pleural invasion (ly/v/pl), and TNM staging.

Results

According to ly/v/pl invasion and lymph node positivity, no variables were superior to IS. We used Mean/MWV (SUV mean x MWV) to evaluate tumor quality and quantity in the role of surrogate TLG. Mean/MWV were superior to IS. Additionally, Mean/MV was associated with lymph node metastases. Among the various histologic subtypes, solid-predominant had the highest expression of Mean/MV. The higher Mean/MV significantly contributed to unfavorable disease-free survival in cIA adenocarcinomas, but not to overall survival.

Conclusions

The mean/MWV value determination on 3D-reconstructed CT images was a simple and useful preoperative modality for predicting invasive facet in cIA adenocarcinoma. However, higher values didn't significantly affect overall survival.

Whole body metabolic tumor volume is a prognostic marker in patients with newly diagnosed stage 3B non-small cell lung cancer, confirmed with external validation

Purpose

TNM Stage 3B encompasses a wide range of primary tumor and nodal metastatic tumor burden. This study aimed to evaluate the prognostic value of quantitative FDG PET/CT parameters in patients with newly diagnosed Stage 3B Non-Small Cell Lung Cancer (NSCLC).

Materials and Methods

Institutional review board approved retrospective study identified patients diagnosed with Stage 3B NSCLC (8^th edition TNM classification) on baseline FDG PET/CT at two medical centers (Medical centers A and B), between Feb 2004 and Dec 2014. Patients were excluded if they had prior NSCLC treatment or recent diagnosis of a second primary cancer. Quantitative FDG PET/CT parameters including whole body metabolic tumor volume (MTVwb), total lesion glycolysis (TLGwb), and maximum standardized uptake value (SUVmaxwb) were measured from baseline PET/CT using Edge method with Mimvista software. The primary endpoint was overall survival (OS). Cox proportional hazard regression and Kaplan-Meier overall survival analyses were used to test for an association between OS and quantitative FDG PET/CT parameters. The distributions of MTVwb, TLGwb, SUVmaxwb were skewed, so a natural logarithm transformation was applied and the transformed variables [(ln(MTVwb), ln(TLGwb), and ln(SUVmaxwb)] were used in the analysis.

Results

The training set included 110 patients from center A with Stage 3B NSCLC. 78.2% of patients expired during follow-up. Median OS was 14 months. 1-year, 2-year, and 5-year OS was 56.5%, 34.6% and 13.9%, respectively. Univariate Cox regression analysis showed no significant difference in OS on the basis of age, gender, histology, ln(TLGwb), or ln(SUVmaxwb). ln(MTVwb) was positively associated with OS [hazard ratio (HR) of 1.23, p = 0.037]. This association persisted on multivariate Cox regression analysis (HR 1.28, p = 0.043), with adjustments for age, gender, treatment and tumor histology. External validation with 44 patients from center B confirmed increasing MTVwb was associated significantly worse OS. An MTVwb cut-off point of 85.6 mL significantly stratified Stage 3B NSCLC patient prognosis.

Conclusion

MTVwb is a prognostic marker for OS in patients with Stage 3B NSCLC, independent of age, gender, treatment, and tumor histology.

Comparison of different automated lesion delineation methods for metabolic tumor volume of 18F-FDG PET/CT in patients with stage I lung adenocarcinoma

The aim of the study was to investigate the suitable segmentation method in small, low uptake and heterogeneous nodules of stage I lung adenocarcinoma.133 stage I lung adenocarcinoma patients with F-FDG PET/CT scans were enrolled in this retrospective study. All lesions were divided into different groups according to nodule density, nodule size, and the maximum standard uptake value (SUVmax) level. Four different PET segmentation methods were performed, including percentage threshold of SUVmax (T42% and T42% × RC), gradient-based threshold (adaptive iterative algorithm, AT-AIA), and background-related threshold (adaptive thresholding at 40% SUVmax, AT40%) approaches. The MTVs were evaluated and compared with CT volume (CTV). Percentage volume error (%VE) compared to CTV was calculated and the correlations between MTVs and CTV were analyzed.AT-AIA had the highest accuracy in large, high uptake, and solid nodules (72.5%, 72.4%, and 65.6%, respectively). AT40% had the highest accuracy in small, low uptake and nonsolid nodules (56.6%, 56.1%, and 62.6%, respectively). In part-solid nodules, the accuracy of AT-AIA (60.0%) and AT40% (56.7%) were higher than that of T42% and T42% × RC. The MTV of AT-AIA was in excellent correlation with the CTV in solid nodules (R = 0.831, P < .001) and in high uptake nodules (R = 0.830, P < .001). The MTV of AT40% was in good correlation with the CTV in nonsolid nodules (R = 0.686, P = .003) and in part-solid nodules (R = 0.731, P < .001).AT40% showed best performance in small, low uptake, nonsolid and part-solid lesions. AT-AIA was suitable for large, high uptake, and solid lesions.

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.

Current Methods to Define Metabolic Tumor Volume in Positron Emission Tomography: Which One is Better?

Numerous methods to segment tumors using ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG PET) have been introduced. Metabolic tumor volume (MTV) refers to the metabolically active volume of the tumor segmented using FDG PET, and has been shown to be useful in predicting patient outcome and in assessing treatment response. Also, tumor segmentation using FDG PET has useful applications in radiotherapy treatment planning. Despite extensive research on MTV showing promising results, MTV is not used in standard clinical practice yet, mainly because there is no consensus on the optimal method to segment tumors in FDG PET images. In this review, we discuss currently available methods to measure MTV using FDG PET, and assess the advantages and disadvantages of the methods.

Volumetric parameters of 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography/computed tomography can predict histopathologic treatment response after neoadjuvant chemoradiotherapy in pancreatic adenocarcinoma

PURPOSE

The purpose of this study was to investigate the clinical potential of 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography/computed tomography (FDG PET/CT) to evaluate histopathologic effects of preoperative chemoradiotherapy (CRT) in pancreatic adenocarcinoma, with particular focus on volumetric PET/CT parameters.

MATERIAL AND METHODS

This study included 25 patients with pancreatic adenocarcinoma who underwent radical surgery after gemcitabine- and S-1-based preoperative-CRT. The extent of residual tumor was graded using the Evans grading systems, and patients with more than 50% destruction of tumor cells were defined as responder. Peak SUV corrected for lean body mass (SULpeak), metabolic tumor volume (MTV) with a threshold of SUV=2.0, total lesion glycolysis (TLG) of pre- and post-CRT, and reduction rates of SULpeak in those parameters were assessed by PET/CT. These parameters were compared using the student's t-test between responder and non-responder. The treatment effect was also assessed by contingency table analysis divided with median value of each parameter using chi-square tests.

RESULTS

Eight patients (32%) showed histopathologic poor response (Evans grade I), 11 cases (44%) had mild response (Evans grade IIa), and six cases (24%) had moderate response (Evans grade IIb); therefore, six cases (24%) were assigned to responders and others 19 cases (76%) were non-responders. With regards to volumetric PET parameters, post-CRT SULpeak of responders was significantly lower than that of non-responders (p=0.013). Post-CRT MTV and TLG were negative for all six cases of responders. There were significant differences between responder and non-responder on the contingency table analysis of post-CRT MTV and TLG status (p=0.014 for both).

CONCLUSIONS

This study demonstrated that the volumetric PET/CT parameters, higher post-treatment SULpeak and positive MTV/TLG could predict the unfavorable histopathological effects of CRT in patients with pancreatic adenocarcinoma.

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.