Lepidic Predominant Pulmonary Lesions (LPL): CT-based Distinction From More Invasive Adenocarcinomas Using 3D Volumetric Density and First-order CT Texture Analysis.

RATIONALE AND OBJECTIVES: This study aimed to differentiate pathologically defined lepidic predominant lesions (LPL) from more invasive adenocarcinomas (INV) using three-dimensional (3D) volumetric density and first-order texture histogram analysis of surgically excised stage 1 lung adenocarcinomas. MATERIALS AND METHODS: This retrospective study was institutional review board approved and Health Insurance Portability and Accountability Act compliant. Sixty-four cases of pathologically proven stage 1 lung adenocarcinoma surgically resected between September 2006 and October 2015, including LPL (n = 43) and INV (n = 21), were evaluated using high-resolution computed tomography. Quantitative measurements included nodule volume, percent solid volume (% solid), and first-order texture histogram analysis including skewness, kurtosis, entropy, and mean nodule attenuation within each histogram quartile. Binomial logistic regression models were used to identify the best set of parameters distinguishing LPL from INV. RESULTS: Univariate analysis of 3D volumetric density and histogram features was statistically significant between LPL and INV groups (P < .05). Accuracy of a binomial logistic model to discriminate LPL from INV based on size and % solid was 85.9%. With optimized probability cutoff, the model achieves 81% sensitivity, 76.7% specificity, and area under the receiver operating characteristic curve of 0.897 (95% confidence interval, 0.821-0.973). An additional model based on size and mean nodule attenuation of the third quartile (Hu_Q3) of the histogram achieved similar accuracy of 81.3% and area under the receiver operating characteristic curve of 0.877 (95% confidence interval, 0.790-0.964). CONCLUSIONS: Both 3D volumetric density and first-order texture analysis of stage 1 lung adenocarcinoma allow differentiation of LPL from more invasive adenocarcinoma with overall accuracy of 85.9%-81.3%, based on multivariate analyses of either size and % solid or size and Hu_Q3, respectively.

Lung Adenocarcinoma: Correlation of Quantitative CT Findings with Pathologic Findings.

Purpose To identify the ability of computer-derived three-dimensional (3D) computed tomographic (CT) segmentation techniques to help differentiate lung adenocarcinoma subtypes. Materials and Methods This study had institutional research board approval and was HIPAA compliant. Pathologically classified resected lung adenocarcinomas (n = 41) with thin-section CT data were identified. Two readers independently placed over-inclusive volumes around nodules from which automated computer measurements were generated: mass (total mass) and volume (total volume) of the nodule and of any solid portion, in addition to the solid percentage of the nodule volume (percentage solid volume) or mass (percentage solid mass). Interobserver agreement and differences in measurements among pathologic entities were evaluated by using t tests. A multinomial logistic regression model was used to differentiate the probability of three diagnoses: invasive non-lepidic-predominant adenocarcinoma (INV), lepidic-predominant adenocarcinoma (LPA), and adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA). Results Mean percentage solid volume of INV was 35.4% (95% confidence interval [CI]: 26.2%, 44.5%)-higher than the 14.5% (95% CI: 10.3%, 18.7%) for LPA (P = .002). Mean percentage solid volume of AIS/MIA was 8.2% (95% CI: 2.7%, 13.7%) and had a trend toward being lower than that for LPA (P = .051). Accuracy of the model based on total volume and percentage solid volume was 73.2%; accuracy of the model based on total mass and percentage solid mass was 75.6%. Conclusion Computer-assisted 3D measurement of nodules at CT had good reproducibility and helped differentiate among subtypes of lung adenocarcinoma. (©) RSNA, 2016.

CT scan screening for lung cancer: risk factors for nodules and malignancy in a high-risk urban cohort.

BACKGROUND: Low-dose computed tomography (CT) for lung cancer screening can reduce lung cancer mortality. The National Lung Screening Trial reported a 20% reduction in lung cancer mortality in high-risk smokers. However, CT scanning is extremely sensitive and detects non-calcified nodules (NCNs) in 24-50% of subjects, suggesting an unacceptably high false-positive rate. We hypothesized that by reviewing demographic, clinical and nodule characteristics, we could identify risk factors associated with the presence of nodules on screening CT, and with the probability that a NCN was malignant. METHODS: We performed a longitudinal lung cancer biomarker discovery trial (NYU LCBC) that included low-dose CT-screening of high-risk individuals over 50 years of age, with more than 20 pack-year smoking histories, living in an urban setting, and with a potential for asbestos exposure. We used case-control studies to identify risk factors associated with the presence of nodules (n=625) versus no nodules (n=557), and lung cancer patients (n=30) versus benign nodules (n=128). RESULTS: The NYU LCBC followed 1182 study subjects prospectively over a 10-year period. We found 52% to have NCNs >4 mm on their baseline screen. Most of the nodules were stable, and 9.7% of solid and 26.2% of sub-solid nodules resolved. We diagnosed 30 lung cancers, 26 stage I. Three patients had synchronous primary lung cancers or multifocal disease. Thus, there were 33 lung cancers: 10 incident, and 23 prevalent. A sub-group of the prevalent group were stable for a prolonged period prior to diagnosis. These were all stage I at diagnosis and 12/13 were adenocarcinomas. CONCLUSIONS: NCNs are common among CT-screened high-risk subjects and can often be managed conservatively. Risk factors for malignancy included increasing age, size and number of nodules, reduced FEV1 and FVC, and increased pack-years smoking. A sub-group of screen-detected cancers are slow-growing and may contribute to over-diagnosis and lead-time biases.

Identification of an autoantibody panel to separate lung cancer from smokers and nonsmokers.

BACKGROUND: Sera from lung cancer patients contain autoantibodies that react with tumor associated antigens (TAAs) that reflect genetic over-expression, mutation, or other anomalies of cell cycle, growth, signaling, and metabolism pathways. METHODS: We performed immunoassays to detect autoantibodies to ten tumor associated antigens (TAAs) selected on the basis of previous studies showing that they had preferential specificity for certain cancers. Sera examined were from lung cancer patients (22); smokers with ground-glass opacities (GGOs) (46), benign solid nodules (55), or normal CTs (35); and normal non-smokers (36). Logistic regression models based on the antibody biomarker levels among the high risk and lung cancer groups were developed to identify the combinations of biomarkers that predict lung cancer in these cohorts. RESULTS: Statistically significant differences in the distributions of each of the biomarkers were identified among all five groups. Using Receiver Operating Characteristic (ROC) curves based on age, c-myc, Cyclin A, Cyclin B1, Cyclin D1, CDK2, and survivin, we obtained a sensitivity = 81% and specificity = 97% for the classification of cancer vs smokers(no nodules, solid nodules, or GGO) and correctly predicted 31/36 healthy controls as noncancer. CONCLUSION: A pattern of autoantibody reactivity to TAAs may distinguish patients with lung cancer versus smokers with normal CTs, stable solid nodules, ground glass opacities, or normal healthy never smokers.

Initial experience with endobronchial ultrasound in an academic thoracic surgery program.

BACKGROUND: Mediastinoscopy is considered the gold standard for evaluating mediastinal lymph nodes. However, endobronchial ultrasound-guided transbronchial needle aspiration has lately offered a less invasive alternative, with the ability to obtain nodal samples under direct visualization. Recent literature found an early learning curve for this technique. We present the initial experience of 4 thoracic surgeons with the procedure. MATERIALS AND METHODS: A retrospective chart review was performed on the first 51 patients on whom an endobronchial ultrasound-guided transbronchial needle aspiration was performed from January 5, 2007, to July 24, 2008. This group included 43 patients with a history or known diagnosis of malignancy as well as 8 patients with a presumed sarcoidosis diagnosis. All negative results were confirmed with mediastinoscopy. The technique's sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were assessed. RESULTS: A total of 73 lymph nodes underwent biopsy in 51 patients. These individuals included 34 men and 17 women, with an average age of 62 years (range, 21-89 years). No surgical or postoperative complications were noted. Overall, a correct diagnosis was established in 88% of the patients (45 of 51). After the first 25 cases (a mean of 6 cases per surgeon), a technique modification was adapted to increase diagnostic yield. The first 25 cases had a 72.22% sensitivity and 80% accuracy, whereas the last 26 cases had a 95.45% sensitivity and 96.15% accuracy (P = .07). CONCLUSION: Endobronchial ultrasound-guided transbronchial needle aspiration is a quickly mastered technique that offers a safe, minimally invasive, and accurate means to evaluate mediastinal lymph nodes.

The diagnostic value of endobronchial ultrasound-guided needle biopsy in lung cancer and mediastinal adenopathy.

Endobronchial ultrasonography (EBUS) has emerged as a new diagnostic tool that allows the bronchoscopist to see beyond the airway, including pulmonary and mediastinal lesion. The real time EBUS-guided transbronchial needle aspiration (TBNA) has advanced the diagnostic yield in primary lung pathology and mediastinal lymph node staging of lung carcinoma. Sixty-four patients (36 males, 28 females, ages ranging from 16 to 86 years) with peribronchial lung lesions and mediastinal and/or hilar lymph node lesions underwent EBUS-TBNA. All patients had intraoperative cytological assessment by smears on aspiration samples or touch preparation on needle core biopsies.The cytological final diagnoses were categorized as negative, suspicious/positive, and non-diagnostic. Forty-nine samples were obtained from lymph node lesions and 15 samples were obtained from lung lesions. In cytology specimens, 32 patients had suspicious/positive diagnoses and 32 patients had negative diagnosis. In follow-up histology specimens, 35 patients had malignant diagnoses, including 18 adenocarcinomas, 8 small cell carcinomas, 6 squamous cell carcinomas, 1 metastatic hepatocellular carcinoma, 1 metastatic melanoma, and 1 lymphoma. Twenty-nine patients had negative diagnoses. Sensitivity and specificity were 88.9% and 96.4%, respectively. Positive and negative predictive values were 97.0% and 87.1%, respectively. Diagnostic accuracy was 92.2%. EBUS-TBNA is an efficient and effective technique for diagnosis of intrapulmonary and mediastinal/hilar lymph nodes. It becomes significantly invaluable on clinical management for staging in those patients with lung cancer of other metastatic malignancies. This technique enables us to obtain tissue samples for quick diagnoses beyond central airway with minimal complications.

S-adenosylmethionine as a biomarker for the early detection of lung cancer.

BACKGROUND: S-Adenosylmethionine (AdoMet) is a major methyl donor for transmethylation reactions and propylamine donor for the biosynthesis of polyamines in biological systems, and therefore may play a role in lung cancer development. We hypothesized that AdoMet levels were elevated in patients with lung cancer and may prove useful as a biomarker for early lung cancer. METHODS: High-performance liquid chromatography was used to analyze plasma AdoMet levels in triplicate samples from 68 patients. This included 13 patients with lung cancer, 33 smokers with benign lung disease, and 22 healthy nonsmokers. The three groups of subjects were compared with respect to the distribution of demographic and disease characteristics and AdoMet levels. Distributions were examined using summary statistics and box plots, and nonparametric analysis of variance procedures. RESULTS: Serum AdoMet levels were elevated in patients with lung cancer as compared to smokers with benign lung disorders and healthy nonsmokers. There were no significant correlations between AdoMet levels and tumor cell types, nodule size, or other demographic variables. CONCLUSIONS: Our data demonstrate that plasma levels of AdoMet are significantly elevated in patients with lung cancer. Plasma AdoMet levels may prove to be a useful tool for the diagnosis of early lung cancer, in combination with chest CT. Registered at: clinicaltrials.gov (NCT00301119).

Sentinel lymph node mapping and molecular staging in nonsmall cell lung carcinoma.

BACKGROUND: Lymph node (LN) involvement predicts recurrence in patients who have undergone resection of apparently localized nonsmall cell lung carcinoma (NSCLC). Standard detection methods for LN disease have a low sensitivity, and many patients with apparent N0 disease status develop recurrent disease. Molecular techniques can improve the detection of micrometastases, whereas sentinel lymph node (SLN) mapping can indicate which LN may contain micrometastases. These methods, although potentially complementary, have not, to the authors' knowledge, been used together previously. METHODS: The authors used SLN mapping and molecular staging to improve the detection of LN micrometastases in patients with NSCLC. Reverse transcriptase-polymerase chain reaction (RT-PCR) analysis for cytokeratin-7 (CK7), expressed both in normal lung and in malignant lung, was used to identify tumor-derived material in LN. RESULTS: SLN mapping was performed in 13 patients, with 1-3 SLNs identified in each patient, and sufficient RNA for RT-PCR was obtained in 12 of these 13 patients. Eleven of 12 tumors expressed CK7. Overall, 32 LNs were positive for CK7, including 13 of 21 SLNs. Ten of 11 patients with evaluable SLNs had at least 1 CK7-positive SLN. Routine pathology showed Stage I disease in eight patients, T3N0 disease in one patient, and LN-positive disease in two patients. Of the nine patients with N0 disease according to routine pathology that was evaluable by RT-PCR, eight patients were upstaged by this technique. All patients with positive LN status by routine pathology who were evaluable by RT-PCR analysis had positive RT-PCR results. CONCLUSIONS: LN micrometastases were common in resected NSCLC, including patients with N0 disease according to routine pathology. SLN mapping was useful for identifying disease-containing LNs. This approach may be useful for stratifying histologically N0 patients into higher risk and lower risk groups.