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

Tumor metabolic activity is associated with subcutaneous adipose tissue radiodensity and survival in non-small cell lung cancer

BACKGROUND

Cachexia-associated body composition alterations and tumor metabolic activity are both associated with survival of cancer patients. Recently, subcutaneous adipose tissue properties have emerged as particularly prognostic body composition features. We hypothesized that tumors with higher metabolic activity instigate cachexia related peripheral metabolic alterations, and investigated whether tumor metabolic activity is associated with body composition and survival in patients with non-small-cell lung cancer (NSCLC), focusing on subcutaneous adipose tissue.

METHODS

A retrospective analysis was performed on a cohort of 173 patients with NSCLC. 18F-fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) scans obtained before treatment were used to analyze tumor metabolic activity (standardized uptake value (SUV) and SUV normalized by lean body mass (SUL)) as well as body composition variables (subcutaneous and visceral adipose tissue radiodensity (SAT/VAT radiodensity) and area; skeletal muscle radiodensity (SM radiodensity) and area). Subjects were divided into groups with high or low SAT radiodensity based on Youden Index of Receiver Operator Characteristics (ROC). Associations between tumor metabolic activity, body composition variables, and survival were analyzed by Mann-Whitney tests, Cox regression, and Kaplan-Meier analysis.

RESULTS

The overall prevalence of high SAT radiodensity was 50.9% (88/173). Patients with high SAT radiodensity had shorter survival compared with patients with low SAT radiodensity (mean: 45.3 vs. 50.5 months, p = 0.026). High SAT radiodensity was independently associated with shorter overall survival (multivariate Cox regression HR = 1.061, 95% CI: 1.022-1.101, p = 0.002). SAT radiodensity also correlated with tumor metabolic activity (SULpeak rs = 0.421, p = 0.029; SUVpeak rs = 0.370, p = 0.048). In contrast, the cross-sectional areas of SM, SAT, and VAT were not associated with tumor metabolic activity or survival.

CONCLUSION

Higher SAT radiodensity is associated with higher tumor metabolic activity and shorter survival in patients with NSCLC. This may suggest that tumors with higher metabolic activity induce subcutaneous adipose tissue alterations such as decreased lipid density, increased fibrosis, or browning.

Radiomics of Tumor Heterogeneity in 18F-FDG-PET-CT for Predicting Response to Immune Checkpoint Inhibition in Therapy-Naïve Patients with Advanced Non-Small-Cell Lung Cancer

We aimed to evaluate the predictive and prognostic value of baseline ¹⁸F-FDG-PET-CT (PET-CT) radiomic features (RFs) for immune checkpoint-inhibitor (CKI)-based first-line therapy in advanced non-small-cell lung cancer (NSCLC) patients. In this retrospective study 44 patients were included. Patients were treated with either CKI-monotherapy or combined CKI-based immunotherapy-chemotherapy as first-line treatment. Treatment response was assessed by the Response Evaluation Criteria in Solid Tumors (RECIST). After a median follow-up of 6.4 months patients were stratified into "responder" (n = 33) and "non-responder" (n = 11). RFs were extracted from baseline PET and CT data after segmenting PET-positive tumor volume of all lesions. A Radiomics-based model was developed based on a Radiomics signature consisting of reliable RFs that allow classification of response and overall progression using multivariate logistic regression. These RF were additionally tested for their prognostic value in all patients by applying a model-derived threshold. Two independent PET-based RFs differentiated well between responders and non-responders. For predicting response, the area under the curve (AUC) was 0.69 for "PET-Skewness" and 0.75 predicting overall progression for "PET-Median". In terms of progression-free survival analysis, patients with a lower value of PET-Skewness (threshold < 0.2014; hazard ratio (HR) 0.17, 95% CI 0.06-0.46; p < 0.001) and higher value of PET-Median (threshold > 0.5233; HR 0.23, 95% CI 0.11-0.49; p < 0.001) had a significantly lower probability of disease progression or death. Our Radiomics-based model might be able to predict response in advanced NSCLC patients treated with CKI-based first-line therapy.

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 Value of Combing Primary Tumor and Nodal Glycolytic-Volumetric Parameters of 18F-FDG PET in Patients with Non-Small Cell Lung Cancer and Regional Lymph Node Metastasis

We investigated whether the combination of primary tumor and nodal ¹⁸F-FDG PET parameters predict survival outcomes in patients with nodal metastatic non-small cell lung cancer (NSCLC) without distant metastasis. We retrospectively extracted pre-treatment ¹⁸F-FDG PET parameters from 89 nodal-positive NSCLC patients (stage IIB–IIIC). The Cox proportional hazard model was used to identify independent prognosticators of overall survival (OS) and progression-free survival (PFS). We devised survival stratification models based on the independent prognosticators and compared the model to the American Joint Committee on Cancer (AJCC) staging system using Harrell’s concordance index (c-index). Our results demonstrated that total TLG (the combination of primary tumor and nodal total lesion glycolysis) and age were independent risk factors for unfavorable OS (p < 0.001 and p = 0.001) and PFS (both p < 0.001), while the Eastern Cooperative Oncology Group scale independently predicted poor OS (p = 0.022). Our models based on the independent prognosticators outperformed the AJCC staging system (c-index = 0.732 versus 0.544 for OS and c-index = 0.672 versus 0.521 for PFS, both p < 0.001). Our results indicate that incorporating total TLG with clinical factors may refine risk stratification in nodal metastatic NSCLC patients and may facilitate tailored therapeutic strategies in this patient group.

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.

Correlations between circulating tumor cell phenotyping and 18F-fluorodeoxyglucose positron emission tomography uptake in non-small cell lung cancer

PURPOSE

The epithelial-to-mesenchymal transition (EMT) phenotype-based subsets of circulating tumor cells (CTCs) might be predictors of tumor progression. We evaluated the clinical properties of different phenotypic CTCs in patients with non-small cell lung cancer (NSCLC). Secondly, we explored the association between different phenotypic CTCs and the uptake of 18F-fluorodeoxyglucose (FDG) by the primary tumor on a positron emission tomographic (PET) scan.

METHODS

Venous blood samples from 34 pathologically confirmed Stage IIB-IVB NSCLC patients were collected prospectively. CTCs were immunoassayed using a SE-i·FISH®CTC kit. We identified CTCs into cytokeratin positive (CK⁺) and cytokeratin negative (CK^-) phenotypes. CTC classifications were correlated with the maximum standardized uptake value (SUVmax) measured by 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT). Overall survival (OS) and progression-free survival (PFS) curves were produced using the Kaplan-Meier method.

RESULTS

CTCs were detected in 91.2% of NSCLC patients. CTC counting was associated with TNM stage (P = 0.014) and distant metastasis (P = 0.007). The number of CK^-CTCs was also positively associated with TNM stage (P = 0.022) and distant metastasis (P = 0.007). Both total CTC counting and CK^-CTC counting did not show association with SUVmax value (P = 0.959, P = 0.903). Kaplan-Meier survival analysis demonstrated that patients with ≥ 7 CTCs had shorter OS (P = 0.003) and PFS (P = 0.001) relative to patients with < 7 CTCs). Notably, the number of CK^-CTCs can act as independent risk factors for PFS (P = 0.044) and OS (P = 0.043) in NSCLC patients. However, SUVmax value was not associated with OS (P = 0.895) and PFS (P = 0.686).

CONCLUSION

The CTC subpopulations could be useful evidence for testing metastasis and prognosis in NSCLC patients. The SUVmax value of the primary tumor was not related to prognosis in patients with NSCLC.

Development and External Validation of a Nomogram for Predicting Survival in Patients With Stage IA Non-small Cell Lung Cancer ≤2 cm Undergoing Sublobectomy

Background: Postoperative prognosis of early stage non-small cell lung cancer (NSCLC) undergoing sublobectomy is heterogeneous. Therefore, we sought to construct a novel survival prediction model for stage IA NSCLC ≤2 cm undergoing sublobectomy.

Methods: Based on the data from the Surveillance, Epidemiology, and End Results (SEER) program, we successfully determined and incorporated independent prognostic markers to construct the nomogram. Internal validation of the constructed nomogram was conducted through 1,000 bootstrap resamples. The constructed nomogram was further subjected to external validation with an independent cohort of patients from two Chinese institutions. The performance of the survival prediction model was assessed by concordance index, calibration plots, and risk subgroup classification.

Results: A total of 3,238 patients from SEER registries (development cohort), as well as 769 patients from two Chinese institutions (validation cohort) was included. Gender, age, size, histologic type, grade, and examined lymph nodes count were identified as significant prognostic parameters. A novel nomogram was developed and externally validated. Concordance index of constructed nomogram was significantly better than that of the current TNM staging system. Calibration plots demonstrated an optimal consistency between the nomogram predicted and actual observed probability of survival. Survival curves of different risk subgroups within respective TNM stage demonstrated significant distinctions.

Conclusion: We developed and externally validated a survival prediction model for patients with stage IA NSCLC ≤2 cm undergoing sublobectomy. This novel nomogram outperforms the conventional TNM staging system and could help clinicians in postoperative surveillance and future clinical trial design.

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.

Protein kinase C-iota-mediated glycolysis promotes non-small-cell lung cancer progression

Purpose

To determine whether protein kinase C-iota (PKC-iota) is associated with glucose metabolism in non-small-cell lung cancer (NSCLC) and whether its regulatory effect on metabolic and biological changes observed in NSCLC can be mediated by glucose transporter 1 (GLUT1).

Patients and methods

Forty-five NSCLC patients underwent combined ¹⁸F-fludeoxyglucose (¹⁸F-FDG) positron emission tomography and computed tomography (PET/CT) before surgery, and another eighty-one NSCLC patients were followed-up for 1–91 months after tumor resection. The rate of glucose metabolism in NSCLC was quantified by measuring the maximum standardized uptake value (SUVmax) by ¹⁸F-FDG PET/CT. PKC-iota and GLUT1 in NSCLC were detected by immunostaining. In vitro, PKC-iota was knocked down, whereas GLUT1 was silenced with or without PKC-iota overexpression to identify the role of PKC-iota in glycolysis. Spearman’s rank correlation coefficient was used in the correlation analysis. Kaplan-Meier analysis was used to assess survival duration.

Results

There was a positive relationship between PKC-iota expression and SUVmax in NSCLC (r=0.649, P<0.001). PKC-iota expression also showed a positive relationship with GLUT1 in NSCLC tissues (r=0.686, P<0.001). Patients whose NSCLC tissues highly co-expressed PKC-iota and GLUT1 had worse prognosis compared with patients without high co-expression of PKC-iota and GLUT1. In vitro, PKC-iota silencing significantly decreased the expression of GLUT1 and inhibited glucose uptake and glycolysis; c-Myc silencing restrained PKC-iota-mediated GLUT1 elevation; GLUT1 knockdown remarkably suppressed PKC-iota-mediated glycolysis and cell growth.

Conclusion

In NSCLC, the rate of glucose metabolism was positively correlated with PKC-iota expression. PKC-iota increased glucose accumulation and glycolysis by upregulating c-Myc/GLUT1 signaling and is thus involved in tumor progression.

[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。