scholarly journals CT texture analysis of mediastinal lymphadenopathy: Combining with US-based elastographic parameter and discrimination between sarcoidosis and lymph node metastasis from small cell lung cancer

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243181
Author(s):  
Eriko Koda ◽  
Tsuneo Yamashiro ◽  
Rintaro Onoe ◽  
Hiroshi Handa ◽  
Shinya Azagami ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Lymph Node ◽  
Diagnostic Accuracy ◽  
Texture Analysis ◽  
Texture Features ◽  
Small Cell ◽  
Mediastinal Lymphadenopathy ◽  
Small Cell Lung

Objectives To investigate the potential of computed tomography (CT)-based texture analysis and elastographic data provided by endobronchial ultrasonography (EBUS) for differentiating the mediastinal lymphadenopathy by sarcoidosis and small cell lung cancer (SCLC) metastasis. Methods Sixteen patients with sarcoidosis and 14 with SCLC were enrolled. On CT images showing the largest mediastinal lymph node, a fixed region of interest was drawn on the node, and texture features were automatically measured. Among the 30 patients, 19 (12 sarcoidosis and 7 SCLC) underwent endobronchial ultrasound transbronchial needle aspiration, and the fat-to-lesion strain ratio (FLR) was recorded. Texture features and FLRs were compared between the 2 patient groups. Logistic regression analysis was performed to evaluate the diagnostic accuracy of these measurements. Results Of the 31 texture features, the differences between 11 texture features of CT ROIs in the patients with sarcoidosis versus patients with SCLC were significant. Among them, the grey-level run length matrix with high gray-level run emphasis (GLRLM-HGRE) showed the greatest difference (P<0.01). Differences between FLRs were significant (P<0.05). Logistic regression analysis together with receiver operating characteristic curve analysis demonstrated that the FLR combined with the GLRLM-HGRE showed a high diagnostic accuracy (100% sensitivity, 92% specificity, 0.988 area under the curve) for discriminating between sarcoidosis and SCLC. Conclusion Texture analysis, particularly combined with the FLR, is useful for discriminating between mediastinal lymphadenopathy caused by sarcoidosis from that caused by metastasis from SCLC.

scholarly journals Association Between Triglyceride Glucose Index and Non-Small Cell Lung Cancer Risk in Chinese Population

2021 ◽  
Vol 11 ◽  
Author(s):  
Xin Yan ◽  
Yujuan Gao ◽  
Jingzhi Tong ◽  
Mi Tian ◽  
Jinghong Dai ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cancer Risk ◽  
Small Cell Lung Cancer ◽  
Roc Curve ◽  
Small Cell ◽  
Small Cell Lung ◽  
Tyg Index ◽  
The Relationship

BackgroundNumerous studies showed that insulin resistance (IR) was associated with cancer risk. However, few studies investigated the relationship between IR and non-small cell lung cancer (NSCLC). The aim of this study is to explore the association of triglyceride glucose (TyG) index, a simple surrogate marker of IR, with NSCLC risk.Methods791 histologically confirmed NSCLC cases and 787 controls were enrolled in the present study. Fasting blood glucose and triglyceride were measured. The TyG index was calculated as ln [fasting triglycerides (mg/dl) ×fasting glucose (mg/dl)/2]. Logistic regression analysis was performed to estimate the relationship between NSCLC risk and the TyG index.ResultsThe TyG index was significantly higher in patients with NSCLC than that in controls (8.42 ± 0.55 vs 8.00 ± 0.45, P &lt; 0.01). Logistic regression analysis showed that the TyG index (OR = 3.651, 95%CI 2.461–5.417, P &lt; 0.001) was independently associated with NSCLC risk after adjusting for conventional risk factors. In addition, a continuous rise in the incidence of NSCLC was observed along the tertiles of the TyG index (29.4 vs 53.8 vs 67.2%, P &lt; 0.001). However, there were no differences of the TyG index in different pathological or TNM stages. In receiver operating characteristic (ROC) curve analysis, the optimal cut-off level for the TyG index to predict incident NSCLC was 8.18, and the area under the ROC curve (AUROC) was 0.713(95% CI 0.688–0.738).ConclusionsThe TyG index is significantly correlated with NSCLC risk, and it may be suitable as a predictor for NSCLC.

scholarly journals Diagnostic utility of metabolic parameters on FDG PET/CT for lymph node metastasis in patients with cN2 non-small cell lung cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Keita Nakanishi ◽  
Shota Nakamura ◽  
Tomoshi Sugiyama ◽  
Yuka Kadomatsu ◽  
Harushi Ueno ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Logistic Regression ◽  
Multivariate Analysis ◽  
Lymph Node ◽  
Fdg Pet ◽  
Small Cell ◽  
Metabolic Parameters ◽  
Diagnostic Utility ◽  
Small Cell Lung ◽  
Pet Ct

Abstract Background The aim of this study was to assess the diagnostic utility of metabolic parameters on fluorine-18-fluoro-2-deoxy-D-glucose-positron emission tomography (FDG-PET)/computed tomography (CT) for predicting lymph node (LN) metastasis in patients with cN2 non-small cell lung cancer (NSCLC). Methods We retrospectively reviewed patients who underwent surgery for cN2 NSCLC between 2007 and 2020. Those who had clinically diagnosed positive hilar and mediastinal LNs by routine CT and PET/CT imaging were investigated. To measure the metabolic parameters of LNs, the data according to maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and LN-to-primary tumor ratio of SUVmax (LPR) were examined. The diagnosis of each retrieved LN was confirmed based on histopathological examination of surgical tissue specimens. Receiver operating characteristics (ROC) curves with area under the curve (AUC) calculations and multivariate analysis by logistic regression were performed. Results Forty-five patients with 84 clinically diagnosed positive hilar or mediastinal LNs were enrolled in the present study. Of the 84 LNs, 63 LNs were pathologically proven as positive (75%). The SUVmax, MTV, TLG, and LPR of LN metastasis were significantly higher than those of benign nodes. In the ROC analysis, the AUC value of LPR [AUC, 0.776; 95% confidence interval (CI), 0.640–0.913] was higher than that of LN SUVmax (AUC, 0.753; 95% CI, 0.626–0.880) or LN TLG3.5 (AUC, 0.746; 95% CI, 0.607–0.885). Using the optimal LPR cutoff value of 0.47, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 84.1, 66.7, 88.3, 58.3, and 79.8%, respectively. Multivariate analysis by logistic regression showed that LPR was an independent predictor for LN metastasis (odds ratio, 6.45; 95% CI, 1.785–23.301; P = 0.004). In the subgroup analysis of adenocarcinoma patients (n = 18; 32 LNs), TLG3.5 was a better predictor (AUC, 0.816; 95% CI, 0.639–0.985) than LPR (AUC, 0.792; 95% CI, 0.599–0.986) or LN SUVmax (AUC, 0.792; 95% CI, 0.625–0.959). Conclusions Our findings suggest that LPR on FDG-PET is a useful predictor for LN metastasis in patients with cN2 NSCLC. TLG can be a good predictor for LN metastasis in patients with adenocarcinoma.

scholarly journals Diagnostic utility of metabolic parameters on FDG PET/CT for lymph node metastasis in patients with cN2 non-small cell lung cancer

2021 ◽  
Author(s):  
Keita Nakanishi ◽  
Shota Nakamura ◽  
Tomoshi Sugiyama ◽  
Yuka Kadomatsu ◽  
Harushi Ueno ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Logistic Regression ◽  
Multivariate Analysis ◽  
Lymph Node ◽  
Predictive Value ◽  
Fdg Pet ◽  
Small Cell ◽  
Metabolic Parameters ◽  
Diagnostic Utility ◽  
Small Cell Lung

Abstract Background The aim of this study was to assess the diagnostic utility of metabolic parameters on fluorine-18-fluoro-2-deoxy-D-glucose-positron emission tomography (FDG-PET)/computed tomography (CT) for predicting lymph node (LN) metastasis in patients with cN2 non-small cell lung cancer (NSCLC).Methods We retrospectively reviewed 45 consecutive patients who underwent surgery for cN2 NSCLC between 2007 and 2020. Among them, 84 hilar and mediastinal LNs clinically diagnosed as positive and retrieved by surgery were investigated. To measure the metabolic parameters of LNs, preexisting PET data were reanalyzed, and the data according to maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and LN-to-primary tumor ratio of SUVmax (LPR) were examined. Diagnosis of each retrieved LN was confirmed based on histopathological examination of tissue specimens at surgery. Receiver operating characteristics (ROC) curves with area under the curve (AUC) calculations and multivariate analysis by logistic regression were performed.Results Of the 84 LNs clinically diagnosed as positive, 63 LNs were pathologically proven as positive (75%). The SUVmax, MTV, TLG, and LPR of LN metastasis were significantly higher than those of benign nodes. In the ROC analysis, the AUC value of LPR [AUC, 0.776; 95% confidence interval (CI), 0.640–0.913] was higher than that of LN SUVmax (AUC, 0.753; 95% CI, 0.626–0.880) or LN TLG3.5 (AUC, 0.746; 95% CI, 0.607–0.885). Using the optimal LPR cutoff value of 0.47, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 84.1%, 66.7%, 88.3%, 58.3%, and 79.8%, respectively. Multivariate analysis by logistic regression showed that LPR was an independent predictor for LN metastasis (odds ratio, 6.45; 95% CI, 1.785–23.301; P = 0.004). In the subgroup analysis of adenocarcinoma patients (n = 18; 32 LNs), TLG3.5 was a better predictor (AUC, 0.816; 95% CI, 0.639–0.985) than LPR (AUC, 0.792; 95% CI, 0.599–0.986) or LN SUVmax (AUC, 0.792; 95% CI, 0.625–0.959).Conclusions LPR on FDG-PET before surgery is a useful predictor for LN metastasis in patients with cN2 NSCLC. TLG can be a good predictor for LN metastasis in patients with adenocarcinoma.

scholarly journals Identified GNGT1 and NMU as Combined Diagnosis Biomarker of Non-Small-Cell Lung Cancer Utilizing Bioinformatics and Logistic Regression

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jia-Jia Zhang ◽  
Jiang Hong ◽  
Yu-Shui Ma ◽  
Yi Shi ◽  
Dan-Dan Zhang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Small Cell Lung Cancer ◽  
Logistic Regression Analysis ◽  
Cell Lung Cancer ◽  
Genetic Alterations ◽  
Small Cell ◽  
Small Cell Lung ◽  
Hub Genes

Non-small-cell lung cancer (NSCLC) is one of the most devastating diseases worldwide. The study is aimed at identifying reliable prognostic biomarkers and to improve understanding of cancer initiation and progression mechanisms. RNA-Seq data were downloaded from The Cancer Genome Atlas (TCGA) database. Subsequently, comprehensive bioinformatics analysis incorporating gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and the protein-protein interaction (PPI) network was conducted to identify differentially expressed genes (DEGs) closely associated with NSCLC. Eight hub genes were screened out using Molecular Complex Detection (MCODE) and cytoHubba. The prognostic and diagnostic values of the hub genes were further confirmed by survival analysis and receiver operating characteristic (ROC) curve analysis. Hub genes were validated by other datasets, such as the Oncomine, Human Protein Atlas, and cBioPortal databases. Ultimately, logistic regression analysis was conducted to evaluate the diagnostic potential of the two identified biomarkers. Screening removed 1,411 DEGs, including 1,362 upregulated and 49 downregulated genes. Pathway enrichment analysis of the DEGs examined the Ras signaling pathway, alcoholism, and other factors. Ultimately, eight prioritized genes (GNGT1, GNG4, NMU, GCG, TAC1, GAST, GCGR1, and NPSR1) were identified as hub genes. High hub gene expression was significantly associated with worse overall survival in patients with NSCLC. The ROC curves showed that these hub genes had diagnostic value. The mRNA expressions of GNGT1 and NMU were low in the Oncomine database. Their protein expressions and genetic alterations were also revealed. Finally, logistic regression analysis indicated that combining the two biomarkers substantially improved the ability to discriminate NSCLC. GNGT1 and NMU identified in the current study may empower further discovery of the molecular mechanisms underlying NSCLC’s initiation and progression.

Artificial intelligence, complex system analysis and simulation modeling in recognition of N1–2 lymph node metastases of non-small cell lung cancer

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 17123-17123
Author(s):  
O. Kshivets
Keyword(s):  
Lung Cancer ◽  
Neural Networks ◽  
Logistic Regression ◽  
Lymph Node ◽  
Discriminant Analysis ◽  
Lymph Node Metastases ◽  
Small Cell ◽  
Small Cell Lung ◽  
Bootstrap Simulation ◽  
Node Metastases

17123 Background: Precise recognition of N1–2 lymph node metastases (RLN) of non-small cell lung cancer (LC) means great importance in prediction LC patients (LCP) survival after surgery. We examined the immunologic factors associated with LCP with N0 and N1–2. Methods: In trial (1987–2005) the data of consecutive 289 LCP after complete pneumonectomies/lobectomies and mediastinal lymph node dissection (age = 58.1 ± 0.5 years; tumor size = 4.4 ± 0.1 cm; m = 260, f = 29) with pathologic stage I-III (T1–4N0–2M0) (squamous = 169, adenocarcinoma = 102, large cell = 18; G1 = 67, G2 = 110, G3 = 112; T1 = 100, T2 = 114, T3 = 54, T4 = 21; N0 = 147, N1 = 70, N2 = 72; pneumonectomies = 135, bi/lobectomies = 154) was reviewed. Variables selected for ED study were input levels of 64 immunity blood parameters, sex, age. Representativeness of samplings was reached by means of randomisation based on unrepeated random selection. Logistic regression, clustering, discriminant analysis, neural networks computing, structural equation modeling, Monte Carlo and bootstrap simulation were used to determine any significant regularity. Results: Logistic regression modeling displayed that RLN of LC significantly depended on: CDw26, CD16, phagocytic number, ratio of lymphocytes, T-lymphocytes, CD4+2H to LC cells (P = 0.003–0.043). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships between N1–2 and blood IgM (rank = 1), eosinophils (2), T-lymphocytes (3), CD8 (4), phagocytic number (5), CD8+VV (6), CDw26 (7), B-lymphocytes (8), IS2 (9), CD4 (10), CD4+2H (11), NST-A2 (12), monocytes (13), index of thymus function (14), IgA (15). Conclusions: Correct RLN of LC was 79.2% by logistic regression (odds ratio = 15.65), 82.0% by discriminant analysis and 99.6% by neural networks computing (area under ROC curve = 0.99; error = 0.059). No significant financial relationships to disclose.

Chemical Anaplasia in Atypical Debut of Non-small Cell Lung Cancer with Inguinal and Obturator Lymph Node Metastases

2018 ◽  
Vol 69 (10) ◽  
pp. 2833-2836
Author(s):  
Laura Rebegea ◽  
Aurel Nechita ◽  
Cristina Serban ◽  
Camelia Diaconu ◽  
Luana Andreea Macovei ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lymph Node ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Lymph Node Metastases ◽  
Palliative Chemotherapy ◽  
Small Cell ◽  
Lumbar Region ◽  
Small Cell Lung ◽  
Node Metastases

Non-small cell lung cancer (NSCLC) represents almost 80-85% of lung cancer cases. It is the most frequent malignancy after skin cancer. The therapeutic options for stage IV of disease consider histology, molecular characteristics, age, performance status, comorbidities, and not in the lust, patient�s option. This paper presents the case of a male patient, 73 years old, smoker, presented and treated in May 2016 in the Sf. Ap. Andrei Emergency Clinical Hospital Galati. The first sign of disease was inguinal and obturator right lymph node metastases whose histopathological test revealed metastases from malignant melanoma. Immunohistochemical tests (IHC) indicated undifferentiated carcinoma with lung as starting point, (Ck7 (+), TTF1 (+)). Thorax, abdominal and pelvic computed tomography (CT) imaging not evidenced space replacement processes in lung, but with mediastinal, right obturator and inguinal adenopathy. From personal pathological history we retain basocellular carcinoma in lumbar region, treated with surgery in 2009. It was initiated palliative chemotherapy and radiotherapy with remission of obturator and inguinal adenopathy, and at 9 months from diagnosis the Positron Emission Tomography (PET-CT) evidenced primary lung tumor situated in right superior lobe (RSL). At the present, patient is alive performing palliative chemotherapy. This case presented diagnostic and treatment issues, being a challenge for multidisciplinary team. We are mentioning the paucity of literature data regarding cases of primary tumors situated upper diaphragm which metastases in inguinal lymph nodes.

scholarly journals Clinical Impact of Supraclavicular Lymph Node Involvement of Stage IIIC Non-Small Cell Lung Cancer Patients

Medicina ◽  
2021 ◽  
Vol 57 (3) ◽  
pp. 301
Author(s):  
Sunmin Park ◽  
Won Sup Yoon ◽  
Mi Hee Jang ◽  
Chai Hong Rim
Keyword(s):  
Lung Cancer ◽  
Lymph Node ◽  
Small Cell Lung Cancer ◽  
Local Control ◽  
Small Cell ◽  
Clinical Impact ◽  
Small Cell Lung ◽  
Stage Iiic ◽  
Supraclavicular Lymph Node ◽  
Grade 3

Background and Objective: Investigations on the clinical impact of supraclavicular lymph node (SCN) involvement in stage IIIC non-small cell lung cancer (NSCLC) remain scarce. We evaluated the oncological outcomes of definitive radiochemotherapy and the clinical significance of SCN involvement. Materials and Methods: Between November 2009 and June 2019, a total of 40 patients with N3-positivity and NSCLC were evaluated. Most patients received concomitant chemotherapy, but six patients who received radiotherapy (RT) alone were also included. Twenty-one patients (52.5%) received 3D-conformal RT (3DCRT), and the remainder received intensity-modulated RT (IMRT). Results: The median follow-up duration was 10.7 months (range: 1.7–120.6 months). Median overall survival (OS) and cause-specific survival (CSS) times were 10.8 months and 16.3 months, respectively. Among the 40 patients, 17 (42.5%) had SCN involvement. SCN involvement negatively affected progression-free survival (hazard ratio (HR): 2.08, 95% confidence interval (CI): 1.04–4.17, p = 0.039) and local control (HR: 3.05, 95% CI: 1.09–8.50, p = 0.034). However, IMRT use was correlated with higher local control (HR: 0.28, 95% CI: 0.09–0.86, p = 0.027). Grade ≥3 esophagitis and pneumonitis accounted for 7.5% and 15.0% of all cases, respectively. A higher RT dose (mean dose: 66.6 vs. 61.7 Gy) was significantly correlated with grade ≥3 pneumonitis (p = 0.001). RT modality was a significant factor (p = 0.042, five of six cases occurred in the IMRT group). Conclusions: SCN involvement could negatively affect oncologic outcomes of stage IIIC NSCLC patients. High-dose irradiation with IMRT could increase local control but may cause lung toxicities.

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