Evaluation of PD-L1 Expression Level in Patients With Non-Small Cell Lung Cancer by 18F-FDG PET/CT Radiomics and Clinicopathological Characteristics

PurposeIn the present study, we aimed to evaluate the expression of programmed death-ligand 1 (PD-L1) in patients with non-small cell lung cancer (NSCLC) by radiomic features of 18F-FDG PET/CT and clinicopathological characteristics.MethodsA total 255 NSCLC patients (training cohort: n = 170; validation cohort: n = 85) were retrospectively enrolled in the present study. A total of 80 radiomic features were extracted from pretreatment 18F-FDG PET/CT images. Clinicopathologic features were compared between the two cohorts. The least absolute shrinkage and selection operator (LASSO) regression was used to select the most useful prognostic features in the training cohort. Radiomics signature and clinicopathologic risk factors were incorporated to develop a prediction model by using multivariable logistic regression analysis. The receiver operating characteristic (ROC) curve was used to assess the prognostic factors.ResultsA total of 80 radiomic features were extracted in the training dataset. In the univariate analysis, the expression of PD-L1 in lung tumors was significantly correlated with the radiomic signature, histologic type, Ki-67, SUVmax, MTV, and TLG (p< 0.05, respectively). However, the expression of PD-L1 was not correlated with age, TNM stage, and history of smoking (p> 0.05). Moreover, the prediction model for PD-L1 expression level over 1% and 50% that combined the radiomic signature and clinicopathologic features resulted in an area under the curve (AUC) of 0.762 and 0.814, respectively.ConclusionsA prediction model based on PET/CT images and clinicopathological characteristics provided a novel strategy for clinicians to screen the NSCLC patients who could benefit from the anti-PD-L1 immunotherapy.

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PD-L1 expression correlation with metabolic parameters of FDG PET/CT and clinicopathological characteristics in non-small cell lung cancer

EJNMMI Research ◽

10.1186/s13550-020-00639-9 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Xiaodong Wu ◽

Yan Huang ◽

Qingping Zhao ◽

Lei Wang ◽

Xiao Song ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Fdg Pet ◽

Clinicopathological Characteristics ◽

Small Cell ◽

Metabolic Parameters ◽

Small Cell Lung ◽

Pet Ct ◽

Fdg Pet Ct

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The clinical impact and prognostic value of 18F-fluorodeoxyglucose PET/CT in the initial staging non-small cell lung cancer at MD Anderson Cancer Center.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.11079 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. 11079-11079

Author(s):

Satoshi Takeuchi ◽

Benjapa Khiewvan ◽

Stephen Swisher ◽

Eric Rohren ◽

Homer A. Macapinlac

Keyword(s):

Fdg Pet ◽

Small Cell ◽

Cancer Center ◽

Stage Migration ◽

Conventional Imaging ◽

Small Cell Lung ◽

Pet Ct ◽

Md Anderson ◽

Fdg Pet Ct ◽

Nsclc Patients

11079 Background: 18F-fluorodeoxyglucosePositron Emission Tomography/Computed Tomography (FDG-PET/CT) has an important role for Non-Small Cell lung cancer (NSCLC) management, especially in staging. Our objective was to assess stage migration, the clinical impact, and prognostic value of PET/CT in patients with NSCLC at MD Anderson Cancer Center (MDACC). Methods: We retrospectively reviewed the database from MDACC, and identified 729 NSCLC patients referred for staging between 2006 and 2011. Stage was classified using TNM classification. FDG-PET/CT and conventional imaging staging were compared with all-cause mortality and the survival rates of the respective clinical stage. The management impact of FDG-PET/CT was determined based on conventional imaging and PET/CT management plans. A change in stage was confirmed by histopathology and/or further imaging. Results: We identified 598 NSCLC patients with FDG-PET/CT and conventional imaging performed. FDG-PET/CT changed stage in 28.1 % (16.4 % upstaged, 11.7 % downstaged). Based on FDG-PET/CT, treatment plans were modified in 38 % of patients. Median progression free survival (PFS) and overall survival (OS) was significantly worse in patients with management impact of FDG-PET/CT than patients without impact (PFS, 24.9 v 60.6 months, P < 0.001; OS, 66.7 v 115.9 months, P < 0.001). Multivariate analysis showed that the impact of FDG-PET/CT impact on management was an independent prognostic factor for DFS (hazard ratio [HR] = 2.08; 95 % CI, 1.63 to 2.65; P < 0.001) and OS (HR = 2.16; 95 % CI, 1.56 to 2.99; P < 0.001). Stage migration from stage I (40/249 patients) showed worse outcome than those without change (PFS, 21.0 v 60.0 months, P < 0.001; OS, 64.7 v 115.9 months, P = 0.003). Conclusions: FDG-PET/CT has major role in NSCLC management. The added staging information provided by FDG-PET/CT as compared to conventional imaging resulted in a change in management in more than one third NSCLC patients. FDG-PET/CT is also a powerful tool for outcome prediction. Even in patients diagnosed as stage I by conventional method, FDG-PET/CT at initial diagnosis may have an impact on survival.

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Pre-Operative Prediction of Mediastinal Node Metastasis Using Radiomics Model Based on 18F-FDG PET/CT of the Primary Tumor in Non-Small Cell Lung Cancer Patients

Frontiers in Medicine ◽

10.3389/fmed.2021.673876 ◽

2021 ◽

Vol 8 ◽

Author(s):

Kai Zheng ◽

Xinrong Wang ◽

Chengzhi Jiang ◽

Yongxiang Tang ◽

Zhihui Fang ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Primary Tumor ◽

Fdg Pet ◽

Small Cell ◽

Small Cell Lung ◽

Training Cohort ◽

Pet Ct ◽

Fdg Pet Ct

Purpose: We investigated whether a fluorine-18-fluorodeoxy glucose positron emission tomography/computed tomography (18F-FDG PET/CT)-based radiomics model (RM) could predict the pathological mediastinal lymph node staging (pN staging) in patients with non-small cell lung cancer (NSCLC) undergoing surgery.Methods: A total of 716 patients with a clinicopathological diagnosis of NSCLC were included in this retrospective study. The prediction model was developed in a training cohort that consisted of 501 patients. Radiomics features were extracted from the 18F-FDG PET/CT of the primary tumor. Support vector machine and extremely randomized trees were used to build the RM. Internal validation was assessed. An independent testing cohort contained the remaining 215 patients. The performances of the RM and clinical node staging (cN staging) in predicting pN staging (pN0 vs. pN1 and N2) were compared for each cohort. The area under the curve (AUC) of the receiver operating characteristic curve was applied to assess the model's performance.Results: The AUC of the RM [0.81 (95% CI, 0.771–0.848); sensitivity: 0.794; specificity: 0.704] for the predictive performance of pN1 and N2 was significantly better than that of cN in the training cohort [0.685 (95% CI, 0.644–0.728); sensitivity: 0.804; specificity: 0.568], (P-value = 8.29e-07, as assessed by the Delong test). In the testing cohort, the AUC of the RM [0.766 (95% CI, 0.702–0.830); sensitivity: 0.688; specificity: 0.704] was also significantly higher than that of cN [0.685 (95% CI, 0.619–0.747); sensitivity: 0.799; specificity: 0.568], (P = 0.0371, Delong test).Conclusions: The RM based on 18F-FDG PET/CT has a potential for the pN staging in patients with NSCLC, suggesting that therapeutic planning could be tailored according to the predictions.

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Combining PD-L1 Expression and Standardized Uptake Values in FDG-PET/CT Can Predict Prognosis in Patients With Resectable Non–Small-Cell Lung Cancer

Cancer Control ◽

10.1177/10732748211038314 ◽

2021 ◽

Vol 28 ◽

pp. 107327482110383

Author(s):

Tomoyuki Miyazawa ◽

Kanji Otsubo ◽

Hiroki Sakai ◽

Hiroyuki Kimura ◽

Motohiro Chosokabe ◽

...

Keyword(s):

Lung Cancer ◽

Lymph Node ◽

Small Cell Lung Cancer ◽

Fdg Pet ◽

Small Cell ◽

Small Cell Lung ◽

Standardized Uptake Values ◽

Pet Ct ◽

Fdg Pet Ct ◽

Nsclc Patients

Background This study aimed to determine the relationship of programmed death-ligand 1 (PD-L1) expression and standardized uptake values in fluorodeoxyglucose–positron emission tomography/computed tomography (FDG-PET/CT) with prognosis in non–small-cell lung cancer (NSCLC). Methods We retrospectively analyzed 328 NSCLC patients who underwent lobectomy/segmentectomy with lymph node dissection. PD-L1 expression was detected by immunohistochemically stained using the murine monoclonal antibody clone 22C3. The preoperative maximum standardized uptake value (SUVmax) of FDG-PET/CT at the primary lesion; pathological factors including histological type, microscopic lymphatic, venous, and pleural invasion; and lymph node metastases in resected specimens was determined. Significant prognostic clinicopathologic factors were analyzed by univariate and multivariate analyses. Results PD-L1 expression was higher in men, smokers, squamous cell carcinoma, advanced pathologic stages, positive venous invasion, positive pleural invasion, and high preoperative SUVmax (≥3). Postoperative survival analysis showed that both PD-L1 expression and preoperative SUVmax were significantly negative prognostic factors in univariate analysis for overall survival (OS) ( P = 0.0123 and P < 0.0001) and relapse-free survival (RFS) ( P = 0.0012 and P < 0.0001). Kaplan–Meier survival curves showed that the OS and RFS were the best in patients with negative PD-L1 expression and SUVmax < 3, intermediate in patients with positive PD-L1 expression and SUVmax < 3 and those with negative PD-L1 expression and SUVmax ≥ 3, and poor in patients with positive PD-L1 expression and SUVmax ≥ 3. Conclusion Combining PD-L1 expression and preoperative FDG-PET/CT SUVmax in primary tumor might help in accurate prediction of postoperative prognosis in NSCLC patients.

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Application of Artificial Neural Network to Preoperative 18F-FDG PET/CT for Predicting Pathological Nodal Involvement in Non-small-cell Lung Cancer Patients

Frontiers in Medicine ◽

10.3389/fmed.2021.664529 ◽

2021 ◽

Vol 8 ◽

Author(s):

Silvia Taralli ◽

Valentina Scolozzi ◽

Luca Boldrini ◽

Jacopo Lenkowicz ◽

Armando Pelliccioni ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Fdg Pet ◽

Small Cell ◽

Nodal Involvement ◽

Small Cell Lung ◽

Pet Ct ◽

Fdg Pet Ct ◽

Nsclc Patients

Purpose: To evaluate the performance of artificial neural networks (aNN) applied to preoperative 18F-FDG PET/CT for predicting nodal involvement in non-small-cell lung cancer (NSCLC) patients.Methods: We retrospectively analyzed data from 540 clinically resectable NSCLC patients (333 M; 67.4 ± 9 years) undergone preoperative 18F-FDG PET/CT and pulmonary resection with hilo-mediastinal lymphadenectomy. A 3-layers NN model was applied (dataset randomly splitted into 2/3 training and 1/3 testing). Using histopathological reference standard, NN performance for nodal involvement (N0/N+ patient) was calculated by ROC analysis in terms of: area under the curve (AUC), accuracy (ACC), sensitivity (SE), specificity (SP), positive and negative predictive values (PPV, NPV). Diagnostic performance of PET visual analysis (N+ patient: at least one node with uptake ≥ mediastinal blood-pool) and of logistic regression (LR) was evaluated.Results: Histology proved 108/540 (20%) nodal-metastatic patients. Among all collected data, relevant features selected as input parameters were: patients' age, tumor parameters (size, PET visual and semiquantitative features, histotype, grading), PET visual nodal result (patient-based, as N0/N+ and N0/N1/N2). Training and testing NN performance (AUC = 0.849, 0.769): ACC = 80 and 77%; SE = 72 and 58%; SP = 81 and 81%; PPV = 50 and 44%; NPV = 92 and 89%, respectively. Visual PET performance: ACC = 82%, SE = 32%, SP = 94%; PPV = 57%, NPV = 85%. Training and testing LR performance (AUC = 0.795, 0.763): ACC = 75 and 77%; SE = 68 and 55%; SP = 77 and 82%; PPV = 43 and 43%; NPV = 90 and 88%, respectively.Conclusions: aNN application to preoperative 18F-FDG PET/CT provides overall good performance for predicting nodal involvement in NSCLC patients candidate to surgery, especially for ruling out nodal metastases, being NPV the best diagnostic result; a high NPV was also reached by PET qualitative assessment. Moreover, in such population with low a priori nodal involvement probability, aNN better identify the relatively few and unexpected nodal-metastatic patients than PET analysis, so supporting the additional aNN use in case of PET-negative images.

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18F-FDG uptake in PET/CT is a potential predictive biomarker of response to anti-PD-1 antibody therapy in non-small cell lung cancer

Scientific Reports ◽

10.1038/s41598-019-50079-2 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 6

Author(s):

Kazuki Takada ◽

Gouji Toyokawa ◽

Yasuto Yoneshima ◽

Kentaro Tanaka ◽

Isamu Okamoto ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Fdg Pet ◽

Antibody Therapy ◽

Small Cell ◽

Small Cell Lung ◽

Pet Ct ◽

Fdg Pet Ct ◽

Nsclc Patients

Abstract To examine the association between 18F-fluorodeoxyglucose (18F-FDG) uptake in positron emission tomography/computed tomography (PET/CT) and the response to anti-programmed cell death-1 (PD-1) monoclonal antibody therapy in non-small cell lung cancer (NSCLC) patients, 89 patients with advanced or recurrent NSCLC were retrospectively analysed. Maximum standardized uptake value (SUVmax) in 18F-FDG PET/CT and the response to anti-PD-1 antibodies were recorded. A cut-off value of SUVmax was determined by receiver operating characteristic curve analysis for patient stratification. Among the 89 patients evaluated, 24 were classified as responders (all partial response), and 65 as non-responders. The average SUVmax of the responders was 15.60 (range, 6.44–51.10), which was significantly higher than that of the non-responders (11.61; range, 2.13–32.75; P = 0.0168, Student’s t-test). The cut-off SUVmax value selected for stratification was 11.16 (sensitivity and specificity, 0.792 and 0.585, respectively). The response rate of patients with SUVmax value ≥ 11.16 (41.3% [19/46]) was significantly higher than that of patients with SUVmax < 11.16 (11.6% [5/43], P = 0.0012, Chi-squared test). The SUVmax in 18F-FDG PET/CT is a potential predictive marker of response to anti-PD-1 antibody therapy in NSCLC patients. Further prospective studies of large populations are necessary to validate these results.

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An exceptional group of non-small cell lung cancer difficult to diagnose: Evaluation of lipid-poor adrenal lesions

Bosnian Journal of Basic Medical Sciences ◽

10.17305/bjbms.2019.3837 ◽

2019 ◽

Author(s):

Fikri Selcuk Simsek ◽

Muhammet Arslan ◽

Yusuf Dag

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Fdg Pet ◽

Diagnostic Procedures ◽

Small Cell ◽

Small Cell Lung ◽

Pet Ct ◽

Fdg Pet Ct ◽

Nsclc Patients

In some non-small cell lung cancer (NSCLC) patients, lipid-poor adrenal adenomas cannot be adequately differentiated from metastases using imaging methods. Invasive diagnostic procedures also have a low negative predictive value (NPV) in such cases. The current study aims to establish a specific and clinically practical metabolic parameter for lipid-poor adrenal lesions (ALs) in NSCLC patients. This diagnostic approach may prevent unnecessary abdominal enhanced computed tomography (CT), magnetic resonance imaging, or invasive diagnostic procedures. Sixty-four NSCLC patients with 69 lipid-poor ALs and 28 control patients with 30 benign lipid-poor ALs, who underwent FDG-PET/CT, were retrospectively reviewed. Two morphological and four metabolic parameters were analyzed in FDG-PET/CT images of NSCLC and control patients. Baseline and post-chemotherapy images of 64 NSCLC patients were re-evaluated according to the PERCIST 1.0. In cases where ALs could not be differentiated, follow-up FDG-PET/CT images were re-examined. The receiver operating characteristic (ROC) curve method was used for the evaluation of diagnostic parameters. Out of 69 ALs, 39 were determined as metastatic lesions (adrenal metastasis), while 30 lesions were considered non-metastatic (adrenal adenomas). The mean attenuation value, SUVmax AL/SUVmax primary tumor, SUVmax, SUVmax AL/liver, and SUVmax AL/SUVmean liver were significantly different between metastatic and benign ALs from NSCLC patients. The SUVmax AL/SUVmean liver ≥1.81 had the best positive (PPV, 94.3%) and negative (NPV, 82.4%) predictive values, and the highest specificity (93.3%), sensitivity (84.6%) and accuracy (86.9%). Lipid-poor ALs with SUVmax AL/SUVmean liver ≥1.81 can be accepted as malignant in NSCLC. However, if SUVmax AL/SUVmean liver is <1.81, a pathologic examination is required. Utilizing this cut-off value to decide on adrenal core biopsy may prevent its unnecessary use. Moreover, this diagnostic approach can save time and reduce the healthcare costs.

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