Correlation of F-18 fluorodeoxyglucose-positron emission tomography maximal standardized uptake value and EGFR mutations in advanced lung adenocarcinoma

The HIF-1α/PKM2 Feedback Loop in Relation to EGFR Mutational Status in Lung Adenocarcinoma

OBJECTIVE

Gene mutations in tumor cells can lead to several unique metabolic phenotypes, which are crucial for the proliferation of cancer cells. EGFR mutation (EGFR-mt) is the main oncogenic driving mutation in lung adenocarcinoma (LUAD). HIF-1 α and PKM2 are two key metabolic regulatory proteins that can form a feedback loop and promote cancer growth by promoting glycolysis. Here, the linkage between EGFR mutational status and HIF-1α/PKM2 feedback loop in LUAD were evaluated.

METHODS

Retrospective study were performed on LUAD patients (n = 89) undergoing first-time therapeutic surgical resection. EGFR mutation was analyzed by real-time PCR. Immunohistochemistry was used to measure the expressions of HIF-1α and PKM2.

RESULTS

We found that the protein expressions of HIF-1α and PKM2 were significantly higher in LUAD than normal lung tissues. In adenocarcinomas, the two protein expressions were both correlated with worse pTNM stage. Moreover, the correlation between the proteins of HIF-1α/PKM2 feedback loop and the EGFR mutational status were also analyzed. We found that EGFR-mt tumors showed higher HIF-1α and PKM2 proteins compared to tumors with EGFR wild-type. Meanwhile, HIF-1α expression was significantly correlated with higher pTNM stage, and PKM2 showed a similar trend, only in EGFR-mutated tumors. The expression of HIF-1α was positively correlated with PKM2 in LUAD, furthermore, this correlation was mainly in patients with EGFR-mt.

CONCLUSION

Different expression and clinical features of HIF-1α/PKM2 feedback loop was existed between LUAD and normal lung tissues, especially in EGFR mutational tumors, supporting the relationship between EGFR mutation and the key related proteins of aerobic glycolysis (HIF-1α and PKM2) in lung adenocarcinomas.

The value of dynamic FDG PET/CT in the differential diagnosis of lung cancer and predicting EGFR mutations

OBJECTIVES

18F-fluorodeoxyglucose (FDG) PET/CT has been widely used for the differential diagnosis of cancer. Semi-quantitative standardized uptake value (SUV) is known to be affected by multiple factors and may make it difficult to differentiate between benign and malignant lesions. It is crucial to find reliable quantitative metabolic parameters to further support the diagnosis. This study aims to evaluate the value of the quantitative metabolic parameters derived from dynamic FDG PET/CT in the differential diagnosis of lung cancer and predicting epidermal growth factor receptor (EGFR) mutation status.

METHODS

We included 147 patients with lung lesions to perform FDG PET/CT dynamic plus static imaging with informed consent. Based on the results of the postoperative pathology, the patients were divided into benign/malignant groups, adenocarcinoma (AC)/squamous carcinoma (SCC) groups, and EGFR-positive (EGFR+)/EGFR-negative (EGFR-) groups. Quantitative parameters including K1, k2, k3, and Ki of each lesion were obtained by applying the irreversible two-tissue compartmental modeling using an in-house Matlab software. The SUV analysis was performed based on conventional static scan data. Differences in each metabolic parameter among the group were analyzed. Wilcoxon rank-sum test, independent-samples T-test, and receiver-operating characteristic (ROC) analysis were performed to compare the diagnostic effects among the differentiated groups. P < 0.05 were considered statistically significant for all statistical tests.

RESULTS

In the malignant group (N = 124), the SUVmax, k2, k3, and Ki were higher than the benign group (N = 23), and all had-better performance in the differential diagnosis (P < 0.05, respectively). In the AC group (N = 88), the SUVmax, k3, and Ki were lower than in the SCC group, and such differences were statistically significant (P < 0.05, respectively). For ROC analysis, Ki with cut-off value of 0.0250 ml/g/min has better diagnostic specificity than SUVmax (AUC = 0.999 vs. 0.70). In AC group, 48 patients further underwent EGFR testing. In the EGFR (+) group (N = 31), the average Ki (0.0279 ± 0.0153 ml/g/min) was lower than EGFR (-) group (N = 17, 0.0405 ± 0.0199 ml/g/min), and the difference was significant (P < 0.05). However, SUVmax and k3 did not show such a difference between EGFR (+) and EGFR (-) groups (P>0.05, respectively). For ROC analysis, the Ki had a cut-off value of 0.0350 ml/g/min when predicting EGFR status, with a sensitivity of 0.710, a specificity of 0.588, and an AUC of 0.674 [0.523-0.802].

CONCLUSION

Although both techniques were specific, Ki had a greater specificity than SUVmax when the cut-off value was set at 0.0250 ml/g/min for the differential diagnosis of lung cancer. At a cut-off value of 0.0350 ml/g/min, there was a 0.710 sensitivity for EGFR status prediction. If EGFR testing is not available for a patient, dynamic imaging could be a valuable non-invasive screening method.

Efficient 18F-fluorodeoxyglucose positron emission tomography/computed tomography-based machine learning model for predicting epidermal growth factor receptor mutations in non-small cell lung cancer

BACKGROUND

Beyond the human eye's limitations, radiomics provides more information that can be used for diagnosis. We develop a personalized and efficient model based on 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) to predict epidermal growth factor receptor (EGFR) mutations to help identify which non-small cell cancer (NSCLC) patients are candidates for EGFR-tyrosine kinase inhibitors (TKIs) therapy.

METHODS

We retrospectively included 100 patients with NSCLC and randomized them according to 70 patients in the training group and 30 patients in the validation group. The least absolute shrinkage and selection operator logistic regression (LLR) algorithm and support vector machine (SVM) classifier were used to build the models and predict whether EGFR is mutated or not. The predictive efficacy of the LLR algorithm-based model and the SVM classifier-based model was evaluated by plotting the receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC).

RESULTS

The AUC, sensitivity and specificity of our radiomics model by LLR algorithm were 0.792, 0.967, and 0.600 for the training group and 0.643, 1.00, and 0.378 for the validation group, respectively, in predicting EGFR mutations. The AUC was 0.838 for the training group and 0.696 for the validation group after combining radiomics features with clinical features. The prediction results based on the SVM classifier showed that the validation group had the best performance when based on radial kernel function with AUC, sensitivity, and specificity of 0.741, 0.667, and 0.825, respectively.

CONCLUSIONS

Radiomics models based on 18F-FDG PET/CT modeled with different machine learning algorithms can improve the predictive efficacy of the models. Models that combine clinical features are more clinically valuable.

FDG PET texture indices as imaging biomarkers for epidermal growth factor receptor mutation status in lung adenocarcinoma

Identifying the epidermal growth factor receptor (EGFR) mutation status is important for the optimal treatment of patients with EGFR mutations. We investigated the relationship between ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) texture indices and EGFR mutation status in patients with newly diagnosed lung adenocarcinoma. We retrospectively analyzed data of patients with newly diagnosed lung adenocarcinoma who underwent pretreatment FDG PET/computed tomography and EGFR mutation testing between August 2014 and November 2020. Patients were divided into mutated EGFR and wild-type EGFR groups. The maximum standardized uptake value (SUVmax) and 31 texture indices for the primary tumor were calculated from PET images and compared between the two groups. Of the 66 patients included, 22 had mutated EGFR and 44 had wild-type EGFR. The SUVmax did not significantly differ between the two groups. Among the 31 evaluated texture indices, the following five showed a statistically significant difference between the groups: correlation (P = 0.003), gray-level nonuniformity for run (P = 0.042), run length nonuniformity (P = 0.02), coarseness (P = 0.006), and gray-level nonuniformity for zone (P = 0.04). Based on the preliminary results of this study in a small patient population, FDG PET texture indices may be potential imaging biomarkers for the EGFR mutation status in patients with newly diagnosed lung adenocarcinoma.

A Review of the Correlation Between Epidermal Growth Factor Receptor Mutation Status and 18F-FDG Metabolic Activity in Non-Small Cell Lung Cancer

PET/CT with 18F-2-fluoro-2-deoxyglucose (18F-FDG) has been proposed as a promising modality for diagnosing and monitoring treatment response and evaluating prognosis for patients with non-small cell lung cancer (NSCLC). The status of epidermal growth factor receptor (EGFR) mutation is a critical signal for the treatment strategies of patients with NSCLC. Higher response rates and prolonged progression-free survival could be obtained in patients with NSCLC harboring EGFR mutations treated with tyrosine kinase inhibitors (TKIs) when compared with traditional cytotoxic chemotherapy. However, patients with EGFR mutation treated with TKIs inevitably develop drug resistance, so predicting the duration of resistance is of great importance for selecting individual treatment strategies. Several semiquantitative metabolic parameters, e.g., maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG), measured by PET/CT to reflect 18F-FDG metabolic activity, have been demonstrated to be powerful in predicting the status of EGFR mutation, monitoring treatment response of TKIs, and assessing the outcome of patients with NSCLC. In this review, we summarize the biological and clinical correlations between EGFR mutation status and 18F-FDG metabolic activity in NSCLC. The metabolic activity of 18F-FDG, as an extrinsic manifestation of NSCLC, could reflect the mutation status of intrinsic factor EGFR. Both of them play a critical role in guiding the implementation of treatment modalities and evaluating therapy efficacy and outcome for patients with NSCLC.

Correlation of epidermal growth factor receptor mutation status and PD-L1 expression with [18F]FDG PET using volume-based parameters in non-small cell lung cancer

OBJECTIVE

We investigated the relationship between 2-deoxy-2-[18F]fluoro-D-glucose (FDG) PET using volume-based parameters and epidermal growth factor receptor (EGFR) mutation status, programmed death-ligand-1 (PD-L1) expression level, and their combination, in pretreated non-small cell lung cancer (NSCLC).

METHODS

FDG PET findings and EGFR mutation status and PD-L1 expression level were investigated retrospectively in 93 patients with newly diagnosed NSCLC (77 adenocarcinomas, 16 squamous cell carcinomas). Tumors were divided into six groups: EGFR mutant/negative PD-L1, EGFR mutant/low PD-L1, EGFR mutant/high PD-L1, EGFR wild/negative PD-L1, EGFR wild/low PD-L1, and EGFR wild/high PD-L1. The maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) for primary tumor were measured from PET images. The EGFR mutation status and PD-L1 expression level were estimated in tumor tissue specimens and compared with the PET parameters.

RESULTS

None of the PET parameters differed significantly between EGFR-mutated and wild-type EGFR. According to the PD-L1 level, significant differences were detected in SUVmax (P = 0.001) and TLG (P = 0.016), but not MTV. Comparing all six groups, significant difference was detected in only SUVmax (P = 0.011).

CONCLUSION

Based on the preliminary results of this study, FDG PET may help in the prediction of PD-L1 expression level, but not EGFR mutation status, in patients with newly diagnosed NSCLC. The SUVmax rather than MTV or TLG, may be of value in predicting the six groups according to the combination of EGFR mutation status and PD-L1 expression level.

Predictive value of multiple metabolic and heterogeneity parameters of 18F-FDG PET/CT for EGFR mutations in non-small cell lung cancer

OBJECTIVES

To explore the value of multiple metabolic and heterogeneity parameters of 2-deoxy-2-[fluorine-18] fluoro-D-glucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) in predicting epidermal growth factor receptor gene (EGFR) mutations in non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

A retrospective analysis was performed by reviewing 98 patients with NSCLC who underwent EGFR mutation testing and ¹⁸F-FDG PET/CT examination in our hospital between March 2016 and March 2021. Patients were divided into an EGFR-mutant group and a wild-type group. A multivariate logistic regression analysis was performed to screen and construct a prediction model. The diagnostic performance of the model was evaluated using a receiver-operating characteristic (ROC) curve.

RESULTS

The study found that EGFR mutations were more likely to occur in women, non-smokers, and patients with peripheral lesions, shorter maximum tumor diameter, adenocarcinoma, and T1 stage cancer. Low maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume, total lesion glycolysis, and high coefficient of variation (COV) were significantly correlated with EGFR mutations, and the area under the ROC curve (AUC) was 0.622, 0.638, 0.679, 0.687, and 0.672, respectively. Multivariate logistic regression analysis indicated that non-smokers (odds ratio (OR) = 0.109, P = 0.014), peripheral lesions (OR = 6.917, P = 0.022), low SUVmax (≤ 7.85, OR = 5.471, P = 0.001), SUVmean (≤ 5.34, OR = 0.044, P = 0.000), and high COV (≥ 106.08, OR = 0.996, P = 0.045) were independent predictors of EGFR mutations. The AUC of the prediction model established by combining the above factors was 0.926; the diagnostic efficiency was significantly higher than that of a single parameter.

CONCLUSION

Among the metabolic and heterogeneity parameters of ¹⁸F-FDG PET/CT, low SUVmax, SUVmean, and high COV were significantly associated with EGFR mutations, and the predictive value of EGFR mutations could be enhanced when combined with clinicopathological features.

Frequent EGFR Mutations and Better Prognosis in Positron Emission Tomography-Negative, Solid-Type Lung Cancer

BACKGROUND

The differential diagnosis of a solitary solid-type lung nodule is diverse. 18F-fluorodeoxyglucose positron emission tomography (PET) has a high sensitivity in the diagnosis of solid-type lung cancers; however, PET-negative, solid-type lung cancers are rarely observed. In this study, we analyzed the clinical/genetic features and prognosis of PET-negative, solid-type lung cancers.

PATIENTS AND METHODS

Between January 2007 and February 2020, 709 patients with solid-type lung cancers (tumor size ≥2.0 cm) underwent pulmonary resection. Clinical, genetic, and prognostic features were evaluated in 27 patients (3.8%) with tumors showing negative PET results defined as SUVmax <2.0.

RESULTS

All 27 patients had lung adenocarcinoma; 23 had invasive adenocarcinomas and 4 had invasive mucinous adenocarcinomas. The PET-negative group showed high frequencies of females and never-smokers. Recurrence-free survival was significantly better in the PET-negative group compared with PET-positive counterparts extracted using propensity score matching from patients who underwent pulmonary resection during the same period (P = .0052). Furthermore, 83% of PET-negative, solid-type invasive lung adenocarcinoma patients harbored EGFR mutation, which was significantly higher than that of PET-positive, solid-type invasive lung adenocarcinoma patients (38%, n = 225) who received EGFR mutation testing in our cohort (P < .0001). PET-negative, solid-type lung adenocarcinoma patients with EGFR mutations had significantly better recurrence-free survival compared with PET-positive, solid-type lung adenocarcinoma patients with EGFR mutations extracted using propensity score matching (P = .0030).

CONCLUSION

PET-negative, solid-type lung cancers are characterized with a high incidence of EGFR mutation and a better prognosis compared with PET-positive, solid-type lung cancer.

Can 18F-FDG PET/CT predict EGFR status in patients with non-small cell lung cancer? A systematic review and meta-analysis

OBJECTIVES

This study aimed to explore the diagnostic significance of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)/CT for predicting the presence of epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer (NSCLC).

DESIGN

A systematic review and meta-analysis.

DATA SOURCES

The PubMed, EMBASE and Cochrane library databases were searched from the earliest available date to December 2020.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

The review included primary studies that compared the mean maximum of standard uptake value (SUV_max) between wild-type and mutant EGFR, and evaluated the diagnostic value of ¹⁸F-FDG PET/CT using SUV_max for prediction of EGFR status in patients with NSCLC.

DATA EXTRACTION AND SYNTHESIS

The main analysis was to assess the sensitivity and specificity, the positive diagnostic likelihood ratio (DLR+) and DLR-, as well as the diagnostic OR (DOR) of SUV_max in prediction of EGFR mutations. Each data point of the summary receiver operator characteristic (SROC) graph was derived from a separate study. A random effects model was used for statistical analysis of the data, and then diagnostic performance for prediction was further assessed.

RESULTS

Across 15 studies (3574 patients), the pooled sensitivity for ¹⁸F-FDG PET/CT was 0.70 (95% CI 0.60 to 0.79) with a pooled specificity of 0.59 (95% CI 0.52 to 0.66). The overall DLR+ was 1.74 (95% CI 1.49 to 2.03) and DLR- was 0.50 (95% CI 0.38 to 0.65). The pooled DOR was 3.50 (95% CI 2.37 to 5.17). The area under the SROC curve was 0.68 (95% CI 0.64 to 0.72). The likelihood ratio scatter plot based on average sensitivity and specificity was in the lower right quadrant.

CONCLUSION

Meta-analysis results showed ¹⁸F-FDG PET/CT had low pooled sensitivity and specificity. The low DOR and the likelihood ratio scatter plot indicated that ¹⁸F-FDG PET/CT should be used with caution when predicting EGFR mutations in patients with NSCLC.

The diagnostic and predictive efficacy of 18F-FDG PET/CT metabolic parameters for EGFR mutation status in non-small-cell lung cancer: A meta-analysis

PURPOSE

To investigate the predictive performance of the maximum standardized uptake value (SUV_max) and mean standardized uptake value (SUV_mean) of primary lesions based on 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) for EGFR mutation status in patients with non-small cell lung cancer (NSCLC).

METHODS

The PubMed/Medline, Embase, Cochrane Library and Web of Science databases were searched as of January 1, 2021. Studies whose reported data could be used to construct contingency tables were included. Study characteristics were extracted, and methodological quality assessment was conducted by two separate reviewers using the Quality Assessment of Diagnostic Accuracy Studies. The pooled sensitivity, specificity and area under the summary receiver operating characteristic curve (AUROC) were calculated. The possible causes of heterogeneity were analysed by meta-regression.

RESULTS

The 18 included studies had a total of 4024 patients. The majority of the studies showed a low to unclear risk of bias and concerns of applicability. For differentiating EGFR-mutant NSCLC from wild-type NSCLC, the pooled sensitivity and specificity were 71 % and 60 % for SUV_max and 64 % and 63 % for SUV_mean, respectively. The summary AUROCs of SUV_max and SUV_mean were 0.69 (95 % CI, 0.65-0.73) and 0.68 (95 % CI, 0.64-0.72), respectively. The meta-regression analysis indicated that blindness to EGFR mutation test results, the number of readers and the number of PET/CT scanners were possible causes of heterogeneity.

CONCLUSIONS

Our meta-analysis implied that SUV_max and SUV_mean of primary lesions from ¹⁸F-FDG PET/CT harboured moderate predictive efficacy for the EGFR mutation status of NSCLC.

The Biological Meaning of Radiomic Features

An earlier incorrect version appeared online. This article was corrected on February 10, 2021.

Biological Significance of 18F-FDG PET/CT Maximum Standard Uptake Value for Predicting EGFR Mutation Status in Non-Small Cell Lung Cancer Patients

Purpose

To investigate the potential of maximum standardized uptake value (SUVmax) in predicting epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) patients.

Methods

Clinical data of 311 NSCLC patients who had undergone both EGFR mutation test and ¹⁸F-FDG PET/CT scans between January 2013 and December 2017 at our hospital were retrospectively analyzed. Patients were sub-grouped by their origin of SUVmax. Univariate and multivariate analyses were performed to investigate the association between clinical factors and EGFR mutations. Receiver operating characteristic curve (ROC) analysis was performed to confirm the predictive value of clinical factors. In vitro experiments were performed to confirm the correlation between EGFR mutations and glycolysis.

Results

EGFR-mutant patients had higher SUVmax than the wild-type patients in both primary tumors and metastases. In the multivariate analysis, SUVmax, gender and histopathologic type were determined as independent predictors of EGFR mutation status for patients whose SUVmax were obtained from the primary tumors; while for patients whose SUVmax were obtained from the metastases, SUVmax, smoking status and histopathologic type were regarded as independent predictors. ROC analysis showed that SUVmax of the primary tumors (cut off >10.92), not of the metastases, has better predictive value than other clinical factors in predicting EGFR mutation status. The predict performance was improved after combined SUVmax with other independent predictors. In addition, our in vitro experiments demonstrated that lung cancer cells with EGFR mutations have higher aerobic glycolysis level than wild-type cells.

Conclusion

SUVmax of the primary tumors has the potential to serve as a biomarker to predict EGFR mutation status in NSCLC patients.

18F-FDG PET/CT SUVmax and serum CEA levels as predictors for EGFR mutation state in Chinese patients with non-small cell lung cancer

The epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) contribute to an increased response rate, compared with chemotherapy, in patients with inhibitor-sensitive EGFR mutations. The present study evaluated the association between the maximum standardized uptake value (SUV_max) of ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET/CT), as well as serum carcinoembryonic antigen (CEA) levels and EGFR mutations prior to treatment, in patients with non-small cell lung cancer (NSCLC). Patients with histologically confirmed NSCLC (n=167), who underwent an ¹⁸F-FDG PET/CT scan, EGFR mutation analysis and a serum CEA test participated in the present study. Multivariate logistic regression analysis was used to analyze predictors of EGFR mutations. Receiver-operating characteristic (ROC) curve analysis was performed to determine the efficient cut-off value. Survival rate analysis was evaluated according to SUV_max and EGFR mutation status. A decreased SUV_max and an increased CEA level was observed in patients with EGFR-mutations, compared with patients with wild-type primary lesions and metastatic lymph nodes. The exon 19 EGFR mutation was associated with increased SUV_max, compared with the exon 21 L858R mutation. The ROC analysis indicated that an ¹⁸F-FDG PET/CT uptake SUV_max >11.5 may be a predictor of the wild-type EGFR genotype and increased CEA levels (CEA >9.4 ng/ml) were associated with EGFR mutations. Furthermore, patients with no smoking history, low SUV_max of the primary tumor, metastatic lymph nodes and a high CEA level were significantly associated with EGFR mutation status. The results of the present study indicated that patients with advanced NSCLC, particularly Chinese patients, with decreased SUV_max and increased CEA levels are associated with EGFR mutations, which may serve as predictors for the EGFR-TKI therapeutic response.

Value of combining PET/CT and clinicopathological features in predicting EGFR mutation in Lung Adenocarcinoma with Bone Metastasis

Purpose: Epidermal growth factor receptor (EGFR) mutation is the most common target for precision treatment in metastatic lung adenocarcinoma. We investigated the predictive role of ¹⁸F-FDG PET/CT and clinicopathological features for EGFR mutations in lung adenocarcinoma with bone metastasis. Methods: Seventy-five lung adenocarcinoma patients with histologically confirmed bone metastasis were included. They all received EGFR status test and PET/CT before systemic treatment. The differences of maximum standardized uptake value (SUVmax) in primary tumor (pSUVmax), regional lymph node (nSUVmax) and bone metastasis (bmSUVmax) between different EGFR status groups were compared, alongside with common clinicopathological features. Multivariate logistic regression analysis was performed to evaluate predictors of EGFR mutations. Results: EGFR mutations were found in 37 patients (49.3%). EGFR mutations were more common in females, non-smokers, expression of Thyroid Transcription Factor-1 (TTF-1) and NaspinA. Low bmSUVmax was significantly associated with EGFR mutations, while no significant difference was observed in pSUVmax and nSUVmax. Multivariate analysis showed that bmSUVmax ≤7, non-smoking, expression of TTF-1 were predictors of EGFR mutations. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was 0.84 for the combination of the three factors. Conclusion: Low bmSUVmax is more frequently in EGFR mutations, and bmSUVmax is an independent predictor of EGFR mutations. Combining bmSUVmax with other clinicopathological features could forecast the EGFR status in lung adenocarcinoma with unavailable EGFR gene testing.

Relationship of EGFR Mutation to Glucose Metabolic Activity and Asphericity of Metabolic Tumor Volume in Lung Adenocarcinoma

Purpose

EGFR-mutation (EGFR-mt) is a major oncogenic driver mutation in lung adenocarcinoma (ADC) and is more often observed in Asian population. In lung ADC, some radiomics parameters of FDG PET have been reported to be associated with EGFR-mt. Here, the associations between EGFR-mt and PET parameters, particularly asphericity (ASP), were evaluated in Asian population.

Methods

Lung ADC patients who underwent curative surgical resection as the first treatment were retrospectively enrolled. EGFR mutation was defined as exon 19 deletion and exon 21 point mutation and was evaluated using surgical specimens. On FDG PET, image parameters of maximal standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and ASP were obtained. The parameters were compared between EGFR-mt and wild type (EGFR-wt) groups, and the relationships between these PET parameters and EGFR-mt were evaluated.

Results

A total of 64 patients (median age 66 years, M:F = 34:30) were included in the analysis, and 29 (45%) patients showed EGFR-mt. In EGFR-mt group, all the image parameters of SUVmax, MTV, TLG, and ASP were significantly lower than in EGFR-wt group (all adjusted P < 0.050). In univariable logistic regression, SUVmax (P = 0.003) and ASP (P = 0.010) were significant determinants for EGFR-mt, whereas MTV was not (P = 0.690). Multivariate analysis revealed that SUVmax and ASP are independent determinants for EGFR-mt, regardless of inclusion of MTV in the analysis (P < 0.05).

Conclusion

In Asian NSCLC/ADC patients, SUVmax, MTV, and ASP on FDG PET are significantly related to EGFR mutation status. Particularly, low SUVmax and ASP are independent determinants for EGFR-mt.

Influx rate constant of 18F-FDG increases in metastatic lymph nodes of non-small cell lung cancer patients

PURPOSE

Primary tumor (PT) and metastatic lymph node (MLN) status have a great influence on diagnosis and treatment of lung cancer. Our main purpose was to investigate the imaging characteristics of PT or MLN by applying the ¹⁸F-FDG PET dynamic modeling approach for non-small cell lung cancer (NSCLC).

METHODS

Dynamic ¹⁸F-FDG PET scans were performed for 76 lung cancer patients, and 62 NSCLC cases were finally included in this study: 37 with newly diagnosed early and locally advanced lung cancer without distant metastases (group M0) and 25 metastatic lung cancer (group M1). Patlak graphic analysis (K_i calculation) based on the dynamic modeling and SUV analysis from conventional static data were performed.

RESULTS

For PT, both K_i^PT (0.050 ± 0.005 vs 0.026 ± 0.004 min^-1, p < 0.001) and SUV^PT (8.41 ± 0.64 vs 5.23 ± 0.73, p < 0.01) showed significant higher values in group M1 than M0. For MLN, K_i^MLN showed significant higher values in M1 than M0 (0.033 ± 0.005 vs 0.016 ± 0.003 min^-1, p < 0.01), while no significant differences were found for SUV^MLN between M0 and M1 (4.22 ± 0.49 vs 5.57 ± 0.59, p > 0.05). Both SUV ^PT and K_i^PT showed significant high values in squamous cell carcinoma than adenocarcinoma, but neither SUV^PT nor K_i^PT showed significant differences between EGFR mutants versus wild types. The overall Spearman analysis for SUV and K_i from different groups showed variable correlation (r = 0.46-0.94).

CONCLUSION

The dynamic modeling for MLN (K_i^MLN) showed more sensitive than the static analysis (SUV) to detect metastatic lymph nodes in NSCLC, although both methods were sensitive for PT. This methodology of non-invasive imaging may become an important tool to evaluate MLN and PT status for patients who cannot undergo histological examination.

CLINICAL TRIAL REGISTRATION

The clinical trial registration number is NCT03679936 (http://www.clinicaltrials.gov/).

Relationship of radiometabolic biomarkers to KRAS mutation status and ALK rearrangements in cases of lung adenocarcinoma

PURPOSE

Rapid diagnosis of genetic mutations is important for targeted therapies such as EGFR tyrosine kinase inhibitors. KRAS mutation and ALK rearrangement are also important in determining treatment. The purpose of our study was to evaluate the diagnostic value of 18F-FDG PET to predict KRAS mutation and ALK rearrangement in order to determine the frequency of these genetic markers in our lung adenocarcinoma cases and contribute to forthcoming meta-analysis studies.

METHODS

A total of 218 patients with lung adenocarcinoma (EGFR analyzed) who were seen at our clinic between 2012 and 2014 were included in the study. The results of the 18 F-FDG-PET scans for each patient were retrospectively recorded with the associated medical documents. ALK rearrangements were analyzed in 166 of the 218 patients, while 50 of the 218 patients were analyzed for KRAS mutational status. SPSS 15.0 for Windows was used for statistical analysis.

RESULTS

FDG avidity was higher in cases with KRAS mutations and ALK rearrangements than those without, but the difference was not significant. ALK rearrangements were more common in younger, female, and nonsmoking patients with lung adenocarcinoma.

CONCLUSIONS

The small numbers of KRAS mutations and ALK rearrangements are the limitation of this study for evaluation of diagnostic imaging. The frequency of these genetic alterations was as reported in the literature. We believe that our work will contribute to future meta-analysis.

Alternative and New Radiopharmaceutical Agents for Lung Cancer

BACKGROUND

FDG PET/CT imaging has an established role in lung cancer (LC) management. Whilst it is a sensitive technique, FDG PET/CT has a limited specificity in the differentiation between LC and benign conditions and is not capable of defining LC heterogeneity since FDG uptake varies between histotypes.

OBJECTIVE

To get an overview of new radiopharmaceuticals for the study of cancer biology features beyond glucose metabolism in LC.

METHODS

A comprehensive literature review of PubMed/Medline was performed using a combination of the following keywords: "positron emission tomography", "lung neoplasms", "non-FDG", "radiopharmaceuticals", "tracers".

RESULTS

Evidences suggest that proliferation markers, such as 18F-Fluorothymidine and 11CMethionine, improve LC staging and are useful in evaluating treatment response and progression free survival. 68Ga-DOTA-peptides are already routinely used in pulmonary neuroendocrine neoplasms (NENs) management and should be firstly performed in suspected NENs. 18F-Fluoromisonidazole and other radiopharmaceuticals show a promising impact on staging, prognosis assessment and therapy response in LC patients, by visualizing hypoxia and perfusion. Radiolabeled RGD-peptides, targeting angiogenesis, may have a role in LC staging, treatment outcome and therapy. PET radiopharmaceuticals tracing a specific oncogene/signal pathway, such as EGFR or ALK, are gaining interest especially for therapeutic implications. Other PET tracers, like 68Ga-PSMA-peptides or radiolabeled FAPIs, need more development in LC, though, they are promising for therapy purposes.

CONCLUSION

To date, the employment of most of the described tracers is limited to the experimental field, however, research development may offer innovative opportunities to improve LC staging, characterization, stratification and response assessment in an era of increased personalized therapy.

Predictive Power of a Radiomic Signature Based on 18F-FDG PET/CT Images for EGFR Mutational Status in NSCLC

Radiomics has become an area of interest for tumor characterization in ¹⁸F-Fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) imaging. The aim of the present study was to demonstrate how imaging phenotypes was connected to somatic mutations through an integrated analysis of 115 non-small cell lung cancer (NSCLC) patients with somatic mutation testings and engineered computed PET/CT image analytics. A total of 38 radiomic features quantifying tumor morphological, grayscale statistic, and texture features were extracted from the segmented entire-tumor region of interest (ROI) of the primary PET/CT images. The ensembles for boosting machine learning scheme were employed for classification, and the least absolute shrink age and selection operator (LASSO) method was used to select the most predictive radiomic features for the classifiers. A radiomic signature based on both PET and CT radiomic features outperformed individual radiomic features, the PET or CT radiomic signature, and the conventional PET parameters including the maximum standardized uptake value (SUVmax), SUVmean, SUVpeak, metabolic tumor volume (MTV), and total lesion glycolysis (TLG), in discriminating between mutant-type of epidermal growth factor receptor (EGFR) and wild-type of EGFR- cases with an AUC of 0.805, an accuracy of 80.798%, a sensitivity of 0.826 and a specificity of 0.783. Consistently, a combined radiomic signature with clinical factors exhibited a further improved performance in EGFR mutation differentiation in NSCLC. In conclusion, tumor imaging phenotypes that are driven by somatic mutations may be predicted by radiomics based on PET/CT images.

Correlation between EGFR mutation status and F18 -fluorodeoxyglucose positron emission tomography-computed tomography image features in lung adenocarcinoma

Background

The purpose of this study was to investigate an association between EGFR mutation status and

¹⁸F‐fluorodeoxyglucose positron emission tomography‐computed tomography (¹⁸F‐FDG PET‐CT) image features in lung adenocarcinoma.

Methods

Retrospective analysis of the data of 139 patients with lung adenocarcinoma confirmed by surgical pathology who underwent preoperative ¹⁸F‐FDG PET‐CT was conducted. Correlations between EGFR mutation status, clinical characteristics, and PET‐CT parameters, including the maximum standardized uptake value (SUVmax), the mean of the SUV (SUVmean), the peak of the SUV (SUVpeak) of the primary tumor, and the ratio of SUVmax between the primary tumor and the mediastinal blood pool (SUVratio), were statistically analyzed. Multivariate logistic regression analysis was performed to identify predictors of EGFR mutation. Receiver operating characteristic curves of statistical quantitative parameters were compared.

Results

EGFR mutations were detected in 74 (53.2%) of the 139 lung adenocarcinomas and were more frequent in non‐smoking patients. Univariate analysis showed that the SUVmax, SUVmean, SUVpeak, and SUVratio were lower in EGFR‐mutated than in wild‐type tumors. The receiver operating characteristic curves showed no significant differences between their diagnostic efficiencies. Multivariate logistic regression analysis showed that being a never smoker was an independent predictor of EGFR mutation.

Conclusion

Quantitative parameters based on ¹⁸F‐FDG PET‐CT have modest power to predict the presence of EGFR mutation in lung adenocarcinoma; however, when compared to smoking history, they are not good or significant predictive factors.

Value of 18F-FDG PET/CT for predicting EGFR mutations and positive ALK expression in patients with non-small cell lung cancer: a retrospective analysis of 849 Chinese patients

PURPOSE

Epidermal growth factor receptor (EGFR) mutations and the anaplastic lymphoma kinase (ALK) rearrangement are the two most common druggable targets in non-small cell lung cancer (NSCLC). However, genetic testing is sometimes unavailable. Previous studies regarding the predictive role of 18F-FDG PET/CT for EGFR mutations in NSCLC patients are conflicting. We investigated whether or not 18F-FDG PET could be a valuable noninvasive method to predict EGFR mutations and ALK positivity in NSCLC using the largest patient cohort to date.

METHODS

We retrospectively reviewed and included 849 NSCLC patients who were tested for EGFR mutations or ALK status and subjected to 18F-FDG PET/CT prior to treatment. The differences in several clinical characteristics and three parameters based on 18F-FDG PET/CT, including the maximal standard uptake value (SUVmax) of the primary tumor (pSUVmax), lymph node (nSUVmax) and distant metastasis (mSUVmax), between the different subgroups were analyzed. Multivariate logistic regression analysis was performed to identify predictors of EGFR mutations and ALK positivity.

RESULTS

EGFR mutations were identified in 371 patients (45.9%). EGFR mutations were found more frequently in females, non-smokers, adenocarcinomas and stage I disease. Low pSUVmax, nSUVmax and mSUVmax were significantly associated with EGFR mutations. Multivariate analysis demonstrated that pSUVmax < 7.0, female sex, non-smoker status and adenocarcinoma were predictors of EGFR mutations. The receiver operating characteristic (ROC) curve yielded area under the curve (AUC) values of 0.557 and 0.697 for low pSUVmax alone and the combination of the four factors, respectively. ALK-positive patients tended to have a high nSUVmax. Younger age and distant metastasis were the only two independent predictors of ALK positivity.

CONCLUSION

We demonstrated that low pSUVmax is associated with mutant EGFR status and could be integrated with other clinical factors to enhance the discriminability on the EGFR mutation status in some NSCLC patients whose EGFR testing is unavailable.

Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis

With targeted treatments playing an increasing role in oncology, the need arises for fast non-invasive genotyping in clinical practice. Radiogenomics is a rapidly evolving field of research aimed at identifying imaging biomarkers useful for non-invasive genotyping. Radiogenomic genotyping has the advantage that it can capture tumor heterogeneity, can be performed repeatedly for treatment monitoring, and can be performed in malignancies for which biopsy is not available. In this systematic review of 187 included articles, we compiled a database of radiogenomic associations and unraveled networks of imaging groups and gene pathways oncology-wide. Results indicated that ill-defined tumor margins and tumor heterogeneity can potentially be used as imaging biomarkers for 1p/19q codeletion in glioma, relevant for prognosis and disease profiling. In non-small cell lung cancer, FDG-PET uptake and CT-ground-glass-opacity features were associated with treatment-informing traits including EGFR-mutations and ALK-rearrangements. Oncology-wide gene pathway analysis revealed an association between contrast enhancement (imaging) and the targetable VEGF-signalling pathway. Although the need of independent validation remains a concern, radiogenomic biomarkers showed potential for prognosis prediction and targeted treatment selection. Quantitative imaging enhanced the potential of multiparametric radiogenomic models. A wealth of data has been compiled for guiding future research towards robust non-invasive genomic profiling.

Relation of EGFR Mutation Status to Metabolic Activity in Localized Lung Adenocarcinoma and Its Influence on the Use of FDG PET/CT Parameters in Prognosis

OBJECTIVE

The purposes of this study were to assess the relation between epidermal growth factor receptor (EGFR) mutation status and FDG PET/CT findings and to evaluate the influence of this relation on the use of FDG PET/CT parameters to establish a prognosis in cases of localized lung adenocarcinoma.

MATERIALS AND METHODS

Patients with stage I and II lung adenocarcinomas were retrospectively enrolled. At the initial FDG PET/CT examination, maximum and peak standardized uptake, tumor-to-background ratio, and volumetric parameters of metabolic tumor volume and total lesion glycolysis were measured.

RESULTS

The values of all the metabolic and volumetric FDG PET/CT parameters were significantly lower in EGFR mutant than in EGFR wild-type lung adenocarcinomas. All parameters were statistically significant for predicting recurrence-free survival. In multivariate analyses, peak standardized uptake and total lesion glycolysis were more significant prognostic factors than was TNM stage (p < 0.001). Optimal cutoff values of parameters for predicting recurrence-free survival were slightly different between the two groups.

CONCLUSION

EGFR mutation is related to low metabolic activity of localized lung adenocarcinoma at FDG PET/CT. Because of differences in the metabolic activity of EGFR mutant and wild-type tumors, EGFR mutation status must be considered when FDG PET/CT parameters are used for prognosis.

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.

Value of combining serum carcinoembryonic antigen and PET/CT in predicting EGFR mutation in non-small cell lung cancer

Background

We sought to investigate the associations between pretreatment serum Carcinoembryonic antigen (CEA) level, ¹⁸F-Fluoro-2-deoxyglucose (¹⁸F-FDG) uptake value of primary tumor and epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC).

Methods

We retrospectively reviewed medical records of 210 NSCLC patients who underwent EGFR mutation test and ¹⁸F-FDG positron emission tomography/computed tomography (PET/CT) scan before anti-tumor therapy. The associations between EGFR mutations and patients' characteristics, serum CEA, PET/CT imaging characteristics maximal standard uptake value (SUVmax) of the primary tumor were analyzed. Receiver-operating characteristic (ROC) curve was used to assess the predictive value of these factors.

Results

EGFR mutations were found in 70 patients (33.3%). EGFR mutations were more common in high CEA group (CEA ≥7.0 ng/mL) than in low CEA group (CEA <7.0 ng/mL) (40.4% vs. 27.6%; P=0.05). Females (P<0.001), non-smokers (P<0.001), patients with adenocarcinoma (P<0.001) and SUVmax <9.0 (P=0.001) were more likely to be EGFR mutation-positive. Multivariate analysis revealed that gender, tumor histology, pretreatment serum CEA level, and SUVmax were the most significant predictors for EGFR mutations. The ROC curve revealed that combining these four factors yielded a higher calculated AUC (0.80).

Conclusions

Gender, histology, pretreatment serum CEA level and SUVmax are significant predictors for EGFR mutations in NSCLC. Combining these factors in predicting EGFR mutations has a moderate diagnostic accuracy, and is helpful in guiding anti-tumor treatment.

[Current Status and Progress in Molecular Imaging of Non-small Cell Lung Cancer for Molecular Targeted EGFR-TKI Treatment Sensitivity and Treatment Tolerance Prediction]

肺癌80%以上为非小细胞肺癌（non-small cell lung cancer, NSCLC），表皮生长因子受体（epidermal growth factor receptor, EGFR）介导的信号通路与NSCLC发生发展密切相关。针对EGFR的小分子EGFR赖氨酸激酶抑制剂（EGFR-tyrosine kinase inhibitor, EGFR-TKI）被应用于NSCLC的临床治疗，正电子发射计算机断层显像（positron emission tomography/computed tomgraphy, PET/CT）能够无创地对NSCLC患者全身EGFR表达及突变状况进行连续动态监测。¹⁸F-FDG PET/CT显像对于EGFR活化突变、EGFR-TKI治疗疗效具有预测价值，并且能够在体直接观察到药物与全身肿瘤病灶EGFR靶向结合的具体情况，通过治疗前后的PET-CT显像，实现治疗前高敏人群筛选和治疗全过程的动态监测、治疗策略指导，对实现NSCLC的EGFR-TKI精准治疗至关重要。

Non-Small-Cell Lung Cancer PET Imaging Beyond F18 Fluorodeoxyglucose

F18 Flurodeoxyglucose (FDG) is a nonspecific PET tracer representing tumor energy metabolism, with common false-positive and false-negative findings in clinical practice. Non-small cell lung cancer is highly heterogeneous histologically, biologically, and molecularly. Novel PET tracers designed to characterize a specific aspect of tumor biology or a pathway-specific molecular target have the potential to provide noninvasive key information in tumor heterogeneity for patient stratification and in the assessment of treatment response. Non-FDG PET tracers, including ⁶⁸Ga-somatostatin analogs, and some PET tracers targeting tumor proliferation, hypoxia, angiogenesis, and pathway-specific targets are briefly reviewed in this article.

Combining PET/CT with serum tumor markers to improve the evaluation of histological type of suspicious lung cancers

OBJECTIVE

Histological type is important for determining the management of patients with suspicious lung cancers. In this study, PET/CT combined with serum tumor markers were used to evaluate the histological type of lung lesions.

MATERIALS AND METHODS

Patients with suspicious lung cancers underwent 18F-FDG PET/CT and serum tumor markers detection. SUVmax of the tumor and serum levels of tumor markers were acquired. Differences in SUVmax and serum levels of tumor markers among different histological types of lung cancers and between EGFR mutation statues of adenocarcinoma were compared. The diagnostic efficiencies of SUVmax alone, each serum tumor marker alone, combined tumor markers and the combination of both methods were further assessed and compared.

RESULTS

SCC had the highest level of SUVmax, followed by SCLC and adenocarcinoma, and benign lesions had a lowest level. CYFRA21-1 and SCC-Ag were significantly higher in SCC, NSE was significantly higher in SCLC (P<0.001), and CEA was higher in adenocarcinoma (P = 0.343). The diagnostic efficiencies in evaluating histological types of suspicious lung cancers were insufficient when using each serum tumor marker or SUVmax alone. When combined, the AUC, sensitivity and specificity increased significantly (P<0.05 for all). Additionally, to adenocarcinoma, no significant difference was found between EGFR mutation statuses in SUVmax or serum tumor markers (P>0.05 for all).

CONCLUSIONS

SUVmax and serum tumor markers show values in evaluating the histological types of suspicious lung cancers. When properly combined, the diagnostic efficiency can increase significantly.

Prediction of EGFR and KRAS mutation in non-small cell lung cancer using quantitative 18F FDG-PET/CT metrics

This study investigated the relationship between epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in non-small-cell lung cancer (NSCLC) and quantitative FDG-PET/CT parameters including tumor heterogeneity. 131 patients with NSCLC underwent staging FDG-PET/CT followed by tumor resection and histopathological analysis that included testing for the EGFR and KRAS gene mutations. Patient and lesion characteristics, including smoking habits and FDG uptake parameters, were correlated to each gene mutation. Never-smoker (P < 0.001) or low pack-year smoking history (p = 0.002) and female gender (p = 0.047) were predictive factors for the presence of the EGFR mutations. Being a current or former smoker was a predictive factor for the KRAS mutations (p = 0.018). The maximum standardized uptake value (SUV_max) of FDG uptake in lung lesions was a predictive factor of the EGFR mutations (p = 0.029), while metabolic tumor volume and total lesion glycolysis were not predictive. Amongst several tumor heterogeneity metrics included in our analysis, inverse coefficient of variation (1/COV) was a predictive factor (p < 0.02) of EGFR mutations status, independent of metabolic tumor diameter. Multivariate analysis showed that being a never-smoker was the most significant factor (p < 0.001) for the EGFR mutations in lung cancer overall. The tumor heterogeneity metric 1/COV and SUV_max were both predictive for the EGFR mutations in NSCLC in a univariate analysis. Overall, smoking status was the most significant factor for the presence of the EGFR and KRAS mutations in lung cancer.

Correlation of EGFR or KRAS mutation status with 18F-FDG uptake on PET-CT scan in lung adenocarcinoma

Background

¹⁸F-fluoro-2-deoxy-glucose (¹⁸F-FDG) positron emission tomography (PET) is a functional imaging modality based on glucose metabolism. The correlation between EGFR or KRAS mutation status and the standardized uptake value (SUV) of ¹⁸F-FDG PET scanning has not been fully elucidated.

Methods

Correlations between EGFR or KRAS mutation status and clinicopathological factors including SUV_max were statistically analyzed in 734 surgically resected lung adenocarcinoma patients. Molecular causal relationships between EGFR or KRAS mutation status and glucose metabolism were then elucidated in 62 lung adenocarcinomas using cap analysis of gene expression (CAGE), a method to determine and quantify the transcription initiation activities of mRNA across the genome.

Results

EGFR and KRAS mutations were detected in 334 (46%) and 83 (11%) of the 734 lung adenocarcinomas, respectively. The remaining 317 (43%) patients had wild-type tumors for both genes. EGFR mutations were more frequent in tumors with lower SUV_max. In contrast, no relationship was noted between KRAS mutation status and SUV_max. CAGE revealed that 4 genes associated with glucose metabolism (GPI, G6PD, PKM2, and GAPDH) and 5 associated with the cell cycle (ANLN, PTTG1, CIT, KPNA2, and CDC25A) were positively correlated with SUV_max, although expression levels were lower in EGFR-mutated than in wild-type tumors. No similar relationships were noted with KRAS mutations.

Conclusions

EGFR-mutated adenocarcinomas are biologically indolent with potentially lower levels of glucose metabolism than wild-type tumors. Several genes associated with glucose metabolism and the cell cycle were specifically down-regulated in EGFR-mutated adenocarcinomas.

Relationship of Radiometabolic Biomarkers to KRAS Mutation Status and ALK Rearrangements in Cases of Lung Adenocarcinoma

Purpose Rapid diagnosis of genetic mutations is important for targeted therapies such as EGFR tyrosine kinase inhibitors. KRAS mutation and ALK rearrangement are also important in determining treatment. The purpose of our study was to evaluate the diagnostic value of 18F-FDG PET to predict KRAS mutation and ALK rearrangement in order to determine the frequency of these genetic markers in our lung adenocarcinoma cases and contribute to forthcoming meta-analysis studies. Methods A total of 218 patients with lung adenocarcinoma (EGFR analyzed) who were seen at our clinic between 2012 and 2014 were included in the study. The results of the 18 F-FDG-PET scans for each patient were retrospectively recorded with the associated medical documents. ALK rearrangements were analyzed in 166 of the 218 patients, while 50 of the 218 patients were analyzed for KRAS mutational status. SPSS 15.0 for Windows was used for statistical analysis. Results FDG avidity was higher in cases with KRAS mutations and ALK rearrangements than those without, but the difference was not significant. ALK rearrangements were more common in younger, female, and nonsmoking patients with lung adenocarcinoma. Conclusions The small numbers of KRAS mutations and ALK rearrangements are the limitation of this study for evaluation of diagnostic imaging. The frequency of these genetic alterations was as reported in the literature. We believe that our work will contribute to future meta-analysis.

Contribution of ¹⁸Fluorodeoxyglucose positron emission tomography uptake and TTF-1 expression in the evaluation of the EGFR mutation in patients with lung adenocarcinoma

AIM

The aim of this study is to evaluate the diagnostic value of PET-CT scan for the prediction of EGFR mutation status and the contribution of TTF-1 expression to PET-CT scan.

METHODS

We retrospectively studied 218 cases with a diagnosis of pulmonary adenocarcinoma between 2012-2014 which underwent EGFR analysis, TTF-1 and PET-CT before treatment.

RESULTS

The EGFR mutation was present in 28.9% (n= 63) of cases. TTF-1 positivity was 66.9% (n= 105). Standardized uptake value (SUV max) was 16.7 ± 6.8 in EGFR mutant type, 13.8 ± 7.6 in cases having no EGFR mutations. According to our evaluations, high SUVmax is positively correlated with EGFR mutation status. TTF-1 expression in multivariate analysis strengthens the accuracy of detecting an EGFR mutation.

CONCLUSION

PET-CT FDG uptake may, together with TTF-1 expression, help diagnosis in lung adenocarcinoma cases when evaluating for EGFR mutation status.

Superior Treatment Response and In-field Tumor Control in Epidermal Growth Factor Receptor-mutant Genotype of Stage III Nonsquamous Non-Small cell Lung Cancer Undergoing Definitive Concurrent Chemoradiotherapy

BACKGROUND

Although previous in vitro data have suggested a more radio-sensitive nature of epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) cell lines, the clinical behavior according to the EGFR mutational status has not been well-established. In this study, we performed a comparative outcome analysis of EGFR-mutant and wild-type locally advanced NSCLC with chemoradiotherapy (CRT).

PATIENTS AND METHODS

A total of 102 patients with stage III nonsquamous NSCLC undergoing primary CRT were identified. Clinicopathologic characteristics, including the degree of glucose uptake, were evaluated. Failure patterns considering the radiation field and survival outcomes were compared according to the EGFR mutational status.

RESULTS

Pre- and post-CRT maximum standardized uptake values were significantly lower in EGFR-mutant tumors (P = .010 and .018, respectively). The overall response rate was higher in the EGFR-mutant group compared with the wild-type (89% vs. 64%, respectively; P = .023). The 3-year overall survival rate was better with the genetic alteration (68.0% vs. 47.4%, P = .046), but the statistical significance did not remain in multivariate analysis (hazard ratio, 0.68; 95% confidence interval, 0.30-1.55). Considering the tumor progression inside or outside the radiation field, the EGFR-mutant group showed longer in-field time to progression (P = .002), even after adjusting for other related baseline variables (hazard ratio, 0.27; 95% confidence interval, 0.11-0.71).

CONCLUSION

The differential metabolic activity, failure patterns, and prognosis suggest the distinct nature of the EGFR-mutant tumors. EGFR mutational status needs to be considered for more precise curative-intent treatment strategies of locally advanced nonsquamous NSCLC.

PET Imaging-Based Phenotyping as a Predictive Biomarker of Response to Tyrosine Kinase Inhibitor Therapy in Non-small Cell Lung Cancer: Are We There Yet?

The increased understanding of the molecular pathology of different malignancies, especially lung cancer, has directed investigational efforts to center on the identification of different molecular targets and on the development of targeted therapies against these targets. A good representative is the epidermal growth factor receptor (EGFR); a major driver of non-small cell lung cancer tumorigenesis. Today, tumor growth inhibition is possible after treating lung tumors expressing somatic mutations of the EGFR gene with tyrosine kinase inhibitors (TKI). This opened the doors to biomarker-directed precision or personalized treatments for lung cancer patients. The success of these targeted anticancer therapies depends in part on being able to identify biomarkers and their patho-molecular make-up in order to select patients that could respond to specific therapeutic agents. While the identification of reliable biomarkers is crucial to predict response to treatment before it begins, it is also essential to be able to monitor treatment early during therapy to avoid the toxicity and morbidity of futile treatment in non-responding patients. In this context, we share our perspective on the role of PET imaging-based phenotyping in the personalized care of lung cancer patients to non-invasively direct and monitor the treatment efficacy of TKIs in clinical practice.

Associations Between Somatic Mutations and Metabolic Imaging Phenotypes in Non-Small Cell Lung Cancer

PET-based radiomics have been used to noninvasively quantify the metabolic tumor phenotypes; however, little is known about the relationship between these phenotypes and underlying somatic mutations. This study assessed the association and predictive power of ¹⁸F-FDG PET-based radiomic features for somatic mutations in non-small cell lung cancer patients. Methods: Three hundred forty-eight non-small cell lung cancer patients underwent diagnostic ¹⁸F-FDG PET scans and were tested for genetic mutations. Thirteen percent (44/348) and 28% (96/348) of patients were found to harbor epidermal growth factor receptor (EGFR) or Kristen rat sarcoma viral (KRAS) mutations, respectively. We evaluated 21 imaging features: 19 independent radiomic features quantifying phenotypic traits and 2 conventional features (metabolic tumor volume and maximum SUV). The association between imaging features and mutation status (e.g., EGFR-positive [EGFR+] vs. EGFR-negative) was assessed using the Wilcoxon rank-sum test. The ability of each imaging feature to predict mutation status was evaluated by the area under the receiver operating curve (AUC) and its significance was compared with a random guess (AUC = 0.5) using the Noether test. All P values were corrected for multiple hypothesis testing by controlling the false-discovery rate (FDR_Wilcoxon, FDR_Noether) with a significance threshold of 10%. Results: Eight radiomic features and both conventional features were significantly associated with EGFR mutation status (FDR_Wilcoxon = 0.01-0.10). One radiomic feature (normalized inverse difference moment) outperformed all other features in predicting EGFR mutation status (EGFR+ vs. EGFR-negative, AUC = 0.67, FDR_Noether = 0.0032), as well as differentiating between KRAS-positive and EGFR+ (AUC = 0.65, FDR_Noether = 0.05). None of the features was associated with or predictive of KRAS mutation status (KRAS-positive vs. KRAS-negative, AUC = 0.50-0.54). Conclusion: Our results indicate that EGFR mutations may drive different metabolic tumor phenotypes that are captured in PET images, whereas KRAS-mutated tumors do not. This proof-of-concept study sheds light on genotype-phenotype interactions, using radiomics to capture and describe the phenotype, and may have potential for developing noninvasive imaging biomarkers for somatic mutations.

18F-FDG uptake for prediction EGFR mutation status in non-small cell lung cancer

Epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC) are a response to EGFR-tyrosine kinase inhibitor. However, a lack of sufficient tumor tissue has been a limitation for determining EGFR mutation status in clinical practice. The objective of this study was to predict EGFR mutation status in NSCLC patients based on a model including maximum standardized uptake value (SUVmax) and clinical features.We retrospectively reviewed NSCLC patients undergoing EGFR mutation testing and pretreatment positron emission tomography/computed tomography between March 2009 and December 2013. The relationships of EGFR mutations with both SUVmax and patient characteristics were evaluated, and a multivariate logistic regression analysis was performed. The model was assessed by area under the receiver-operating characteristic curve (AUC) and was prospectively validated during January to June 2014.Three hundred and sixteen patients meeting the criteria were enrolled for model construction. The SUVmax values were significantly lower for EGFR mutations (mean, 9.5 ± 5.74) than for EGFR wild-type (mean, 12.7 ± 6.43; P < 0.001). ROC curve analysis showed that the SUVmax cutoff point was 8.1, for which the AUC was 0.65 (95% confidence interval [CI], 0.60-0.72). In addition, multivariate analysis also showed that low SUVmax (≤8.1) was a predictor of EGFR mutations, for which the AUC was 0.77, combining nonsmoking history and primary tumor size (≤5 cm). Eighty-five patients were enrolled to validate the predictive model, and the overall accuracy, sensitivity, and specificity were 77.6%, 64.6% (95% CI 40.7-82.8), and 82.5% (95% CI 70.9-91.0), respectively.The specific FDG uptake value could be considered to effectively predict EGFR mutation status of NSCLC patients by considering smoking history and primary tumor size when genetic tests are not available.

FDG uptake in non-small cell lung cancer is not an independent predictor of EGFR or KRAS mutation status: a retrospective analysis of 206 patients

PURPOSE

Data in the literature regarding the use of F-FDG avidity of non-small cell lung cancer (NSCLC) as an imaging biomarker to predict the status of epidermal growth factor receptor (EGFR) mutation are conflicting. Association between KRAS mutation and FDG avidity of NSCLC on PET/CT is not well known. We assessed whether the EGFR or KRAS mutation status in NSCLC can be predicted by FDG avidity by performing several different subgroup analyses to better compare with various published results.

PATIENTS AND METHODS

After obtaining institutional review board approval, we enrolled patients (1) who had FDG PET/CT performed for staging of NSCLC, (2) with EGFR and KRAS mutational status of tumor identified, and (3) without uncontrolled diabetes. Univariate and multivariate regression analyses were performed to assess the relationship between the independent clinical variables (sex, age, smoking history, tumor histology, tumor size, stage, and SUV-derived variables) and the EGFR and KRAS mutation status. Separate analyses were performed for patients with adenocarcinomas.

RESULTS

There were 206 patients (age, 33-88 years; 148 male/58 female; 71 ever-smokers/135 never-smokers; 135 adenocarcinoma/71 squamous cell carcinoma; 22 stage I-II/184 stage III-IV; tumor size, 1.2-15.0 cm; SUVmax, 2.9-36.4; EGFR mutations present in 47; KRAS mutations present in 20). In multivariate analysis, sex, smoking history, histology, and tumor size were significantly associated with EGFR mutation but none of the SUV-derived variables was. Likewise, no correlation was found between the SUV-derived variables and KRAS mutation.

CONCLUSIONS

Our results suggest that FDG avidity of NSCLC has no significant clinical value in predicting the EGFR or KRAS mutation status.

(18)F-FDG PET/CT imaging in rectal cancer: relationship with the RAS mutational status

OBJECTIVE

Treating metastatic colorectal cancer with anti-EGFR monoclonal antibodies is recommended only for patients whose tumour does not harbour mutations of KRAS or NRAS. The aim of this study was to investigate the biology of rectal cancers and specifically to evaluate the relationship between fluorine-18 fludeoxyglucose ((18)F-FDG) positron emission tomography (PET) intensity and heterogeneity parameters and their mutational status.

METHODS

151 patients with newly diagnosed rectal cancer were included in this retrospective study. All patients underwent a baseline (18)F-FDG PET/CT within a median time interval of 27 days of tumour tissue sampling, which was performed before any treatment. Standardized uptake values (SUVs), volume-based parameters and texture analysis were studied. We retrospectively performed KRAS genotyping on codons 12, 13, 61, 117 and 146, NRAS genotyping on codons 12, 13 and 61 and BRAF on codon 600. Associations between PET/CT parameters and the mutational status were assessed using univariate and multivariate analysis.

RESULTS

83 (55%) patients had an RAS mutation: 74 KRAS and 9 NRAS, while 68 patients had no mutation (wild-type tumours). No patient had BRAF mutation. First-order features based on intensity histogram analysis were significantly associated with RAS mutations: maximum SUV (SUVmax) (p-value = 0.002), mean SUV (p-value = 0.006), skewness (p-value = 0.049), SUV standard deviation (p-value = 0.001) and SUV coefficient of variation (SUVcov) (p-value = 0.001). Both SUVcov and SUVmax showed an area under the curve of 0.65 with sensitivity of 56% and 69%, respectively, and specificity of 64% and 52%, respectively. None of the volume-based (metabolic tumour volume and total lesion glycolysis), nor local or regional textural features were associated with the presence of RAS mutations.

CONCLUSION

Although rectal cancers with KRAS or NRAS mutations display a significantly higher glucose metabolism than wild-type cancers, the accuracy of the currently proposed quantitative metrics extracted from (18)F-FDG PET/CT is not sufficiently high for playing a meaningful clinical role.

ADVANCES IN KNOWLEDGE

RAS-mutated rectal cancers have a significantly higher glucose metabolism. However, the accuracy of (18)F-FDG PET/CT quantitative metrics is not as such as the technique could play a clinical role.

Correlation between EGFR gene mutation, cytologic tumor markers, 18F-FDG uptake in non-small cell lung cancer

Background

EGFR mutation-induced cell proliferation causes changes in tumor biology and tumor metabolism, which may reflect tumor marker concentration and 18F-FDG uptake on PET/CT. Direct aspirates of primary lung tumors contain different concentrations of tumor markers than serum tumor markers, and may correlate better with EGFR mutation than serum tumor markers.

The purpose of this study is to investigate an association between cytologic tumor markers and FDG uptake with EGFR mutation status in non-small cell lung cancer (NSCLC).

Methods

We prospectively collected tumor aspirates of 61 patients who underwent EGFR mutation analysis. Serum and cytologic CYFRA 21-1, CEA, and SCCA levels were measured and correlated with EGFR gene mutations. FDG PET/CT was performed on 58 patients for NSCLC staging, and SUV was correlated with EGFR mutation status.

Results

Thirty (50 %) patients had EGFR mutation and 57 patients had adenocarcinoma subtype. Univariate analysis showed that female gender, never smoker, high levels of cytologic CYFRA 21-1 (c-CYFRA) and lower maximum standard uptake value (SUVmax) were correlated with EGFR mutations. ROC generated cut-off values of 20.8 ng/ml for c-CYFRA and SUVmax of 9.6 showed highest sensitivity for EGFR mutation detection. Multivariate analysis revealed that female gender [hazard ratio (HR): 18.15, p = 0.025], higher levels of c-CYFRA (HR: 7.58, and lower SUVmax (HR: 0.08, p = 0.005) were predictive of harboring EGFR mutation.

Conclusions

The cytologic tumor marker c-CYFRA was positively associated with EGFR mutations in NSCLC. EGFR mutation-positive NSCLCs have relatively lower glycolysis compared with NSCLCs without EGFR mutation.

Metabolic phenotype of stage IV lung adenocarcinoma: relationship with epidermal growth factor receptor mutation

PURPOSE

Epidermal growth factor receptor (EGFR) mutation status is important in treatment stratification of stage IV lung adenocarcinoma. We evaluated the relationship between the SUV max measured on PET/CT and EGFR mutations and the value of SUV max in predicting EGFR mutations.

PATIENTS AND METHODS

Seventy-one stage IV lung adenocarcinoma patients with verified EGFR mutations (48 EGFR mutant, 23 EGFR wild-type) having pretreatment PET/CT were retrospectively reviewed. SUV max values of the primary tumors (n = 71), nodal (n = 246), and distant metastases (n = 618) were compared between EGFR-mutant and EGFR wild-type adenocarcinoma by Mann-Whitney U test. The receiver operating characteristics curve and logistic regression were performed for factors, SUV max, age, sex, and smoking status. The significant predictors were assessed individually and in combination in discriminating EGFR mutation status. Statistical significance was assumed at P < 0.05 RESULTS: The metastases in EGFR-mutant adenocarcinoma had lower SUV max than EGFR wild-type adenocarcinoma (nodal SUV max 3.4 vs 5.5, distant metastasis SUV max 3.4 vs 4.7, respectively; both P < 0.001). No statistical significant difference was observed in the primary tumors SUV max between the 2 groups (SUV max 7.4 vs 8.1, P = 0.311). A receiver operating characteristics-derived SUV max less than or equal to 7.2 in metastasis could separate EGFR-mutant from EGFR wild-type adenocarcinoma (area under the curve, 0.71-0.74; P < 0.05). SUV max was a significant independent predictor, and when combined with age, sex, and smoking status, it is highly predictive of EGFR mutation status (area under the curve, 0.90).

CONCLUSIONS

Low SUV max in the metastasis favors the presence of EGFR mutations in stage IV lung adenocarcinoma, and SUV max is an independent predictor of EGFR mutations.

Role of [¹⁸F]FDG PET in prediction of KRAS and EGFR mutation status in patients with advanced non-small-cell lung cancer

PURPOSE

The tumour molecular profile predicts the activity of epidermal growth factor receptor (EGFR) inhibitors in non-small-cell lung cancer (NSCLC). However, tissue availability and tumour heterogeneity limit its assessment. We evaluated whether [(18)F]FDG PET might help predict KRAS and EFGR mutation status in NSCLC.

METHODS

Between January 2005 and October 2011, 340 NSCLC patients were tested for KRAS and EGFR mutation status. We identified patients with stage III and IV disease who had undergone [(18)F]FDG PET/CT scanning for initial staging. SUVpeak, SUVmax and SUVmean of the single hottest tumour lesions were calculated, and their association with KRAS and EGFR mutation status was assessed. A receiver operator characteristic (ROC) curve analysis and a multivariate analysis (including SUVmean, gender, age and AJCC stage) were performed to identify the potential value of [(18)F]FDG PET/CT for predicting KRAS mutation.

RESULTS

From 102 patients staged using [(18)F]FDG PET/CT, 28 (27%) had KRAS mutation (KRAS+), 22 (22%) had EGFR mutation (EGFR+) and 52 (51%) had wild-type KRAS and EGFR profiles (WT). KRAS+ patients showed significantly higher [(18)F]FDG uptake than EGFR+ and WT patients (SUVmean 9.5, 5.7 and 6.6, respectively; p < 0.001). No significant differences were observed in [(18)F]FDG uptake between EGFR+ patients and WT patients. ROC curve analysis for KRAS mutation status discrimination yielded an area under the curve of 0.740 for SUVmean (p < 0.001). The multivariate analysis showed a sensitivity and specificity of 78.6% and 62.2%, respectively, and the AUC was 0.773.

CONCLUSION

NSCLC patients with tumours harbouring KRAS mutations showed significantly higher [(18)F]FDG uptake than WT patients, as assessed in terms of SUVpeak, SUVmax and SUVmean. A multivariate model based on age, gender, AJCC stage and SUVmean might be used as a predictive marker of KRAS mutation status in patients with stage III or IV NSCLC.

Value of ¹⁸F-FDG uptake on PET/CT and CEA level to predict epidermal growth factor receptor mutations in pulmonary adenocarcinoma

PURPOSE

The identification of the mutation status of the epidermal growth factor receptor (EGFR) is important for the optimization of treatment in patients with pulmonary adenocarcinoma. The acquisition of adequate tissues for EGFR mutational analysis is sometimes not feasible, especially in advanced-stage patients. The aim of this study was to predict EGFR mutation status in patients with pulmonary adenocarcinoma based on (18)F-fluorodeoxyglucose (FDG) uptake and imaging features in positron emission tomography/computed tomography (PET/CT), as well as on the serum carcinoembryonic antigen (CEA) level.

METHODS

We retrospectively reviewed 132 pulmonary adenocarcinoma patients who underwent EGFR mutation testing, pretreatment FDG PET/CT and serum CEA analysis. The associations between EGFR mutations and patient characteristics, maximal standard uptake value (SUVmax) of primary tumors, serum CEA level and CT imaging features were analyzed. Receiver-operating characteristic (ROC) curve analysis was performed to quantify the predictive value of these factors.

RESULTS

EGFR mutations were identified in 69 patients (52.2 %). Patients with SUVmax ≥6 (p = 0.002) and CEA level ≥5 (p = 0.013) were more likely to have EGFR mutations. The CT characteristics of larger tumors (≥3 cm) (p = 0.023) and tumors with a nonspiculated margin (p = 0.026) were also associated with EGFR mutations. Multivariate analysis showed that higher SUVmax and CEA level, never smoking and a nonspiculated tumor margin were the most significant predictors of EGFR mutation. The combined use of these four criteria yielded a higher area under the ROC curve (0.82), suggesting a good discrimination.

CONCLUSION

The combined evaluation of FDG uptake, CEA level, smoking status and tumor margins may be helpful in predicting EGFR mutation status in patients with pulmonary adenocarcinoma, especially when the tumor sample is inadequate for genetic analysis or genetic testing is not available. Further large-scale prospective studies are needed to validate these results.

Prognostic impact of 18F-FDG uptake on PET in non-small cell lung cancer patients with postoperative recurrence following platinum-based chemotherapy

BACKGROUND

Whether fluorine-18-fluorodeoxyglucose ((18)F-FDG) uptake within tumor cells differs between primary and recurrent lung cancers is unknown. The aim of this study was to investigate the prognostic significance of (18)F-FDG uptake by comparing that measured preoperatively at the primary site to that measured postoperatively at sites of non-small cell lung cancer (NSCLC) recurrence. Only patients with postoperative recurrences who received platinum-based chemotherapy as the initial treatment after recurrence were included in the study.

METHODS

Fifty-two patients underwent (18)F-FDG positron emission tomography (PET) examinations before thoracotomy and at the time of recurrence after curative surgery. All recurrences were treated with platinum-based chemotherapy.

RESULTS

(18)F-FDG uptake in the preoperative primary tumors was significantly higher than that in the recurrent tumors (p=0.028), demonstrating a statistically significant correlation (Pearson's correlation coefficient γ=0.482, p<0.001), especially in adenocarcinoma (AC) patients. Low (18)F-FDG avidity within the primary tumor significantly correlated with the presence of epidermal growth receptor factor (EGFR) mutations. (18)F-FDG uptake in the primary tumors was an independent prognostic factor for predicting outcome in NSCLC patients receiving platinum-based chemotherapy for the treatment of postoperative recurrence.

CONCLUSIONS

In NSCLC patients treated by chemotherapy for recurrence, preoperative measurements of (18)F-FDG uptake may be a more powerful surrogate marker for predicting outcome when measured preoperatively at the primary tumor site rather than postoperatively at sites of recurrence.

Distinct features of distant metastasis and lymph node stage in lung adenocarcinoma patients with epidermal growth factor receptor gene mutations

BACKGROUND

The influence of epidermal growth factor receptor (EGFR) mutation status on distant and lymph node metastasis is not fully understood.

METHODS

Ninety-five consecutive patients with stage IV lung adenocarcinoma, who had been examined for the EGFR mutation status, were retrospectively analyzed with regard to numbers of distant metastasis and clinical stage of lymph node metastasis at the time of diagnosis.

RESULTS

While EGFR mutation status did not influence the presence or absence of distant metastasis in the lung, brain, or liver, patients with EGFR mutations demonstrated a significantly greater number of metastatic lesions in the lung (median: 85 vs. 4, P=0.01) and the brain (11 vs. 3.5, P=0.04). On the other hand, patients with EGFR mutations showed a significantly lower lymph node staging (P<0.01).

CONCLUSION

The presence of EGFR mutations in patients with lung adenocarcinoma correlates with lower lymph node stage and a greater number of metastatic lesions in the lung and brain.

Metabolic and metastatic characteristics of ALK-rearranged lung adenocarcinoma on FDG PET/CT

INTRODUCTION

ALK rearrangement in lung cancer has been identified as a novel molecular target in lung adenocarcinoma. In this study, we evaluated metabolic and metastatic features of lung adenocarcinoma by using FDG PET/CT, with regard to specific genotypes of ALK and EGFR mutation.

METHODS

Patients with lung adenocarcinoma initially diagnosed and examined with FDG PET/CT and molecular genotyping with biopsy specimen, from September 2009 to September 2011, were selected retrospectively. ALK fluorescence in situ hybridization and EGFR mutations were tested. Maximum standardized uptake value (SUVmax) and metastatic characteristics on FDG PET/CT were analyzed with regard to ALK and EGFR status.

RESULTS

Of the 331 lung adenocarcinoma patients, 18 were ALK positive (ALK(+)), 156 were EGFR mutation positive (EGFR(+)), and 157 were wild type (WT) for both ALK and EGFR mutation. The ALK(+) tumor showed significantly higher SUVmax and more common metastasis to lymph nodes and distant organs than those of other genotypes in overall patients (P<0.01). In a subgroup analysis of advanced stage (stage IIIb and IV), ALK(+) lung cancer showed significantly higher SUVmax (P<0.05) than EGFR(+) tumors. In another subgroup analysis of size matched groups, ALK(+) tumors showed significant difference in SUVmax, lymph node and distant metastasis (P<0.01), particularly in the moderate-sized tumors (1.5-3cm).

CONCLUSION

ALK-rearranged lung adenocarcinoma represents higher glucose metabolism and more rapid metastasis to lymph nodes or distant sites compared with those with EGFR mutation and wild type, which suggests more aggressive features of ALK rearrangement.

Correlation between (18)f-fluorodeoxyglucose uptake and epidermal growth factor receptor mutations in advanced lung cancer

PURPOSE

Mutations in the epidermal growth factor receptor (EGFR) gene have been identified as potential targets for the treatment and prognostic factors for non-small cell lung cancer (NSCLC). We assessed the correlation between fluorodeoxyglucose (FDG) uptake and EGFR mutations, as well as their prognostic implications.

METHODS

A total of 163 patients with pathologically confirmed NSCLC were enrolled (99 males and 64 females; median age, 60 years). All patients underwent FDG positron emission tomography before treatment, and genetic studies of EGFR mutations were performed. The maximum standardized uptake value (SUVmax) of the primary lung cancer was measured and normalized with regard to liver uptake. The SUVmax between the wild-type and EGFR mutant groups was compared. Survival was evaluated according to SUVmax and EGFR mutation status.

RESULTS

EGFR mutations were found in 57 patients (60.8 %). The SUVmax tended to be higher in wild-type than mutant tumors, but was not significantly different (11.1 ± 5.7 vs. 9.8 ± 4.4, P = 0.103). The SUVmax was significantly lower in patients with an exon 19 mutation than in those with either an exon 21 mutation or wild type (P = 0.003 and 0.009, respectively). The EGFR mutation showed prolonged overall survival (OS) compared to wild-type tumors (P = 0.004). There was no significant difference in survival according to SUVmax. Both OS and progression-free survival of patients with a mutation in exon 19 were significant longer than in patients with wild-type tumors.

CONCLUSION

In patients with NSCLC, a mutation in exon 19 was associated with a lower SUVmax and is a reliable predictor for good survival.