Detection Of Early-stage Lung Cancer Research Articles

Technical Advances in Segmentectomy for Lung Cancer: A Minimally Invasive Strategy for Deep, Small, and Impalpable Tumors.

Simple SummaryThe use of minimally invasive lung segmentectomy for early-stage lung cancer is increasing. This procedure is associated with technical challenges because (1) it requires a thorough understanding of the complex segmental anatomy that frequently accompanies anomalies, and (2) it is difficult to confirm the location of small tumors during minimally invasive surgery, which makes it difficult to obtain adequate surgical margins. Herein, we summarize the published evidence and discuss key issues related to minimally invasive segmentectomy. We focus on overall efforts to overcome these challenges, including preoperative planning and simulation for segmentectomy, and intraoperative localization of small tumors.With the increased detection of early-stage lung cancer and the technical advancement of minimally invasive surgery (MIS) in the field of thoracic surgery, lung segmentectomy using MIS, including video- and robot-assisted thoracic surgery, has been widely adopted. However, lung segmentectomy can be technically challenging for thoracic surgeons due to (1) complex segmental and subsegmental anatomy with frequent anomalies, and (2) difficulty in localizing deep, small, and impalpable tumors, leading to difficulty in obtaining adequate margins. In this review, we summarize the published evidence and discuss key issues related to MIS segmentectomy, focusing on preoperative planning/simulation and intraoperative tumor localization. We also demonstrate two of our techniques: (1) three-dimensional computed tomography (3DCT)-based resection planning using a novel 3DCT processing software, and (2) tumor localization using a novel radiofrequency identification technology.

29MO Early-stage lung cancer detection by a noninvasive breath test

29MO Early-stage lung cancer detection by a noninvasive breath test

Females and Males Show Differences in Early-Stage Transcriptomic Biomarkers of Lung Adenocarcinoma and Lung Squamous Cell Carcinoma.

The incidence and mortality rates of lung cancers are different between females and males. Therefore, sex information should be an important part of how to train and optimize a diagnostic model. However, most of the existing studies do not fully utilize this information. This study carried out a comparative investigation between sex-specific models and sex-independent models. Three feature selection algorithms and five classifiers were utilized to evaluate the contribution of the sex information to the detection of early-stage lung cancers. Both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) showed that the sex-specific models outperformed the sex-independent detection of early-stage lung cancers. The Venn plots suggested that females and males shared only a few transcriptomic biomarkers of early-stage lung cancers. Our experimental data suggested that sex information should be included in optimizing disease diagnosis models.

Organizational Readiness for Lung Cancer Screening: A Cross-Sectional Evaluation at a Veterans Affairs Medical Center.

Lung cancer has the highest cancer-related mortality in the United States and among Veterans. Screening of high-risk individuals with low-dose CT (LDCT) can improve survival through detection of early-stage lung cancer. Organizational factors that aid or impede implementation of this evidence-based practice in diverse populations are not well described. We evaluated organizational readiness for change and change valence (belief that change is beneficial and valuable) for implementation of LDCT screening. We performed a cross-sectional survey of providers, staff, and administrators in radiology and primary care at a single Veterans Affairs Medical Center. Survey measures included Shea's validated Organizational Readiness for Implementing Change (ORIC) scale and Shea's 10 items to assess change valence. ORIC and change valence were scored on a scale from 1 to 7 (higher scores representing higher readiness for change or valence). Multivariable linear regressions were conducted to determine predictors of ORIC and change valence. Of 523 employees contacted, 282 completed survey items (53.9% overall response rate). Higher ORIC scores were associated with radiology versus primary care (mean 5.48, SD 1.42 versus 5.07, SD 1.22, β= 0.37, P= .039). Self-identified leaders in lung cancer screening had both higher ORIC (5.56, SD 1.39 versus 5.11, SD 1.26, β= 0.43, P= .050) and change valence scores (5.89, SD 1.21 versus 5.36, SD 1.19, β= 0.51, P= .012). Radiology health professionals have higher levels of readiness for change for implementation of LDCT screening than those in primary care. Understanding health professionals' behavioral determinants for change can inform future lung cancer screening implementation strategies.

Liquid biopsy for lung cancer screening: Usefulness of circulating tumor cells and other circulating blood biomarkers.

Screening for lung cancer has become a reality in certain countries, most notably the United States, but its implementation currently is under discussion and not established in many nations, including France. Screening for lung cancer currently is proposed using a low-dose computed tomography scanner. However, this approach lacks sensitivity and specificity, and could be improved when combined with a blood test (so-called "liquid biopsy"). Such tests attempt to detect biomarker (s) of early cancer development. Thus, numerous studies performed within the last few years have examined different blood components including circulating tumor cells and free DNA and other circulating elements such as microRNAs, exosomes, antibodies, and proteins. Recent studies have highlighted the value of seeking a signature for the methylation of circulating free DNA, which can be specific for certain solid tumors, including lung carcinoma. The current study describes some recent developments in the use of liquid biopsies for the detection of early-stage lung cancers, even those that are not yet visible using a low-dose computed tomography scanner.

Abstract LB-267: Detection of lung cancer by metabolomics of exhaled breath and machine learning

Abstract Background: Exhaled breath-based test is an attractive option for cancer detection due to it is non-invasive and feasible nature. Here, we reported an effective approach to detect early-stage lung cancer (LC) by integration of metabolomics of exhaled breath and machine learning. Methods: Healthy controls (HC) were adults who received low-dose CT for annual physical examination with no calcified pulmonary nodules and without history of cancer within 5 years. Treatment-naïve LC patients without history of cancer were enrolled. Exhaled breath samples of LC patients were collected before surgery. Exhaled breath samples were collected and stored in Tedla bags and detected by a high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS). A CO2 sensor was applied during exhaled breath collection to ensure only “alveolar air” was collected. Detection model construction and feature selection were performed by support vector machine (SVM). Results: Firstly, an exploratory cohort of 119 HC and 118 LC was set up. Exhaled breath samples were directly detected by HPPI-TOFMS and 32500 features were extracted from each sample. 22 features were selected and subjected to SVM to construct detection model in the exploratory cohort, which was randomly divided into training (n=159) and test (n=78) set. This model achieved a sensitivity of 89.74%, specificity of 92.31%, and accuracy of 89.74% in the test set, suggesting exhaled breath is accurate for LC detection. Secondly, a quantitative detection method was established by introducing mixed internal standard gas at 15 mL/min controlled by a mass flow meter, by which individual violate organic compound could be quantified. Then, a prospective cohort of 53 LC and 129 HC was set up and detected by the quantitative method. For mass spectrometry data with inner standard gas, 21 features were selected by SVM. Similarly, the prospective cohort was randomly divided into training (n=122) and test (n=60) set. The 21 features-based quantified model was trained and tested in the prospective cohort and achieved a sensitivity of 88.24%, specificity of 100%, and accuracy of 96.67% in the test dataset. Conclusions: Exhaled breath with machine learning is a highly accurate approach for early-stage LC detection and inner standard gas could improve detection performance. Citation Format: Mantang Qiu, Hang Li, Shushi Meng, Qingyun Li, Zuli Zhou, Jun Wang. Detection of lung cancer by metabolomics of exhaled breath and machine learning [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-267.

Detection of early-stage lung cancer by exhaled volatile organic compounds using a high-pressure photon ionization time-of-flight mass spectrometry.

9030 Background: Exhaled breath-based test is an attractive option for cancer detection due to its non-invasive nature. Exhaled volatile organic compounds (VOCs) are produced in various biochemical processes and might be sensitive tumor biomarkers. Here, we reported an exploratory study to investigate the performance of exhaled VOCs for detection of early-stage lung cancer using a high-resolution high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS). Methods: Treatment-naïve patients with pulmonary nodules who received surgery at our department and without history of cancer were enrolled. Exhaled breath samples were collected before surgery and stored in Tedla bags. A CO2 sensor was applicated during sample collection to ensure only “alveolar air” was collected. Exhaled samples were directly detected by HPPI-TOFMS, which has a resolution > 3000. Deep learning algorithm was used to build detection model based on HPPI-TOFMS data. Results: A total of 171 patients were included in this study, including 139 patients with lung cancer (114 of TNM stage I, 14 of stage II, 9 of stage III, and 2 of stage IV) and 32 patients with benign nodules. Mass spectrum peaks with m/z < 500 detected by HPPI-TOFMS were retained and 32500 features were extracted from each exhaled breath samples. Based these extracted features, participants who were pathologically diagnosed as lung cancer could be discriminated from those with benign diseases with an accuracy of 96.19%, sensitivity of 96.43%, and specificity of 84.38%. Discrimination of lung cancer patients with lymph node metastasis (n = 12) from those without lymph node metastasis (n = 127) had an accuracy of 83.23%. Conclusions: Exhaled VOCs as detected by a high-resolution HPPI-TOFMS might be sensitive biomarkers for detection of early-stage lung cancer.

Exploring potential of different X-ray imaging methods for early-stage lung cancer detection

To explore the potential of X-ray imaging for early-stage lung cancer screening and to help finding an optimal lung cancer screening method. Experimentally and simulatively comparing performances of different X-ray techniques (absorption-contrast imaging and phase-contrast imaging) for model lung cancer samples. Absorption imaging shows performance equal to or better than that of low-radiation dose. Absorption imaging is still the most promising imaging method for early lung cancer detection.

A High-Performing Plasma Metabolite Panel for Early-Stage Lung Cancer Detection

The objective of this research is to use metabolomic techniques to discover and validate plasma metabolite biomarkers for the diagnosis of early-stage non-small cell lung cancer (NSCLC). The study included plasma samples from 156 patients with biopsy-confirmed NSCLC along with age and gender-matched plasma samples from 60 healthy controls. A fully quantitative targeted mass spectrometry (MS) analysis (targeting 138 metabolites) was performed on all samples. The sample set was split into a discovery set and validation set. Metabolite concentration data, clinical data, and smoking history were used to determine optimal sets of biomarkers and optimal regression models for identifying different stages of NSCLC using the discovery sets. The same biomarkers and regression models were used and assessed on the validation models. Univariate and multivariate statistical analysis identified β-hydroxybutyric acid, LysoPC 20:3, PC ae C40:6, citric acid, and fumaric acid as being significantly different between healthy controls and stage I/II NSCLC. Robust predictive models with areas under the curve (AUC) > 0.9 were developed and validated using these metabolites and other, easily measured clinical data for detecting different stages of NSCLC. This study successfully identified and validated a simple, high-performing, metabolite-based test for detecting early stage (I/II) NSCLC patients in plasma. While promising, further validation on larger and more diverse cohorts is still required.

Correlation between computed tomography imaging and pathological stages and subtypes in early lung adenocarcinoma.

Detection of early-stage lung cancers has increased due to computed tomography (CT). The pathological stages and subtypes of early lung cancer determine the treatment strategy. We aimed to investigate the correlation between CT characteristics and pathological status in early lung adenocarcinoma (ADC). Between June 2018 and December 2019, 415 consecutive patients who underwent surgery for lung ADC with pathological atypical adenomatous hyperplasia (AAH) and ADC in situ (AIS), T1a (mi) N0M0, and T1a-cN0M0 were analyzed. The relationship between CT imaging and pathological status was investigated using Chi-squared or Kruskal-Wallis test and binary logistic regression. When cases of AAH, AIS, and T1a (mi) N0M0 were used as the control group, the lesion size, solid component ratio (SCR), and spiculation were significantly and independently associated with T1a-cN0M0 (P < 0.01). SCR >50% (P < 0.01) and spiculation (P < 0.05) were significantly and independently associated with T1aN0M0. In cases of pathological T1a-cN0M0, SCR >50% was significantly different between adherent wall growth ADC and mucinous ADC (P < 0.01). Some CT characteristics are related to the pathological stage and subtypes of early lung ADC. Larger diameter, spiculation, and SCR >50% are associated with invasive ADC. SCR >50% is positively correlated with mucinous ADC and negatively with adherent growth ADC.

NOVEL APPROACH FOR TUMOR LOCALIZATION MARKING WITH ENOUGH SURGICAL MARGIN FOR LUNG NEOPLASMS BY USING FLUORESCENCE-GUIDED SURGERY

SESSION TITLE: Advancing the Decision-Making Process in Lung Cancer SESSION TYPE: Original Investigations PRESENTED ON: 10/22/2019 10:45 AM - 10:45 AM PURPOSE: Recent advances of computer tomography make the increase of early stage lung cancer detection and various methods of tumor localization marking have been reported in minimally invasive surgery. However, precise tumor localization with enough surgical margin has not been well established. We previously developed and reported a novel approach for performing segmentectomy by using an infrared thoracoscopy with transbronchial instillation of indocianine green (ICG) by combining with 3D virtual sublobar resection with enough surgical margin. We applied this method to serve both as tumor localization marking and anatomical partial lung resection with enough surgical margin. The purpose of this study is the feasibility of anatomical partial lung resection by using combination of 3D image analyzer and fluorescence guided surgery. METHODS: From September 2014 to November 2018, 15 cases (9 lung cancers, 7 metastatic lung tumors) were enrolled and attempted anatomical partial resection under the guidance of fluorescence. For each case, several virtual sublobar resections were created by 3D Image Analyzer (Fujifilm Co, Tokyo, Japan) preoperatively. The surgical margin was measured in each simulated sublobar resection and the most appropriate procedure was selected. Surgical resection with matching virtual sublobar resection was performed using infrared thoracoscopy with transbronchial indocyanine green instillation. Ten ml of the 10-fold saline-autologous blood-diluted ICG was instilled into each associated subsubsegmental bronchus under general anesthesia. At the beginning of the surgery, a near-infrared (NIR) thoracoscope (PINPOINT, Stryker, MI, USA) was used to visualize the intersegmental lines and planes. The visceral pleura was marked using electric cautery along the border of ICG fluorescence. During operation, the lung was deeply catted according to the border by electric cautery and staplers. The border clarity of ICG fluorescence was evaluated and the distance from the tumor to the surgical margin was compared to simulation in order to investigate success of ICG injection. RESULTS: The mean diameter of the tumor was 15.5+/-7.4mm. The success rate of transbronchial ICG injections was 100% (15/15), because a targeted tumor was involved in the resected specimen in all cases. The shortest distances to the surgical margin by simulation and by actual measurement were 15.1+/-12.2 mm and 14.1+/-6.5mm, respectively (p=0.6474). CONCLUSIONS: ICG-guided anatomical partial resection by transbronchial ICG instillation based on the preoperative 3D image analysis is feasible and obtain enough surgical margin. CLINICAL IMPLICATIONS: This novel approach is fulfill not only precise tumor localization marking but also enough tumor resection margin for nonpalpable small nodule. DISCLOSURES: no disclosure on file for Hidehisa Hoshino; No relevant relationships by Eitetsu Koh, source=Web Response no disclosure on file for Hodaka Oheda; No relevant relationships by YASUO SEKINE, source=Web Response

Transthoracic fine-needle aspiration diagnosis of solid, subsolid, and partially calcified lung nodules: A retrospective study from a single academic center.

Background:The large-scale National Lung Cancer Screening Trial demonstrated an increased detection of early-stage lung cancers using low-dose computed tomography scan in the screening population. It also demonstrated a 20% reduction of lung cancer-related deaths in these patients.Aims:Although both solid and subsolid lung nodules are evaluated in studies, subsolid and partially calcified lung nodules are often overlooked.Materials and Methods:We reviewed transthoracic fine-needle aspiration (FNA) cases from lung nodule patients in our clinics and correlated cytological diagnoses with radiologic characteristics of lesions. A computer search of the pathology archive was performed over a period of 12 months for transthoracic FNAs, including both CT- and ultrasound-guided biopsies.Results:A total of 111 lung nodule cases were identified. Lesions were divided into three categories: solid, subsolid, and partially calcified nodules according to radiographic findings. Of 111 cases, the average sizes of the solid (84 cases), subsolid (22 cases), and calcified (5 cases) lesions were 1.952 ± 2.225, 1.333 ± 1.827, and 1.152 ± 1.984 cm, respectively. The cytological diagnoses of three groups were compared. A diagnosis of malignancy was made in 64.28% (54 cases) in solid, 22.72% (5 cases) in subsolid, and 20% (1 case) in partially calcified nodules. Among benign lesions, eight granulomatous inflammations were identified, including one case of solid, five cases of subsolid, and two cases of calcified nodules.Conclusions:Our study indicates that solid nodules have the highest risk of malignancy. Furthermore, the cytological evaluation of subsolid and partially calcified nodules is crucial for the accurate diagnosis and appropriate clinical management of lung nodule patients.

DNA methylation analysis of selected genes for the detection of early-stage lung cancer using circulating cell-free DNA.

Lung cancer is still the deadliest cancer in the world, but early diagnosis cannot be achieved because of the limitations of diagnostic methods. DNA methylation has been proven to be a potentially powerful tool for cancer detection and diagnosis over the past decade. We explored whether free DNA methylation in plasma can be a reliable biomarker for noninvasive lung cancer detection. We detected the methylation of 8 genes in plasma-free DNA of patients with pulmonary space-occupying lesions using real-time quantitative methylation-specific polymerase chain reaction (QMSP). Among the 50 selected patients, 39 were confirmed using pathological analysis as having early lung cancer and 11 had an inflammatory pseudotumor. The QMSP detection showed that the methylation levels of 8 genes in the patients were significantly higher than in the non-lung cancer group. The methylation level of CALCA was the highest and the methylation level of HOXA9 was the lowest. Methylation of RASSF1A, CDKN2A and DLEC1 occured only in lung cancer patients, while methylation of CALCA, CDH13, PITX2, HOXA9, and WT1 occured not only in lung cancer patients, but also in non-lung cancers. The specificity reached 95~100%, whether for a single gene or overall, but the sensitivity was relatively low for each gene. The sensitivity can reach 72% if the methylation of any of the 8 genes is positive and the overall specificity was 91%. The positive and negative predictive values were 96% and 60%, respectively. Quantitative detection of DNA methylation in plasma is a potential method for early diagnosis of lung cancer.

Bronchoscopic Laser Interstitial Thermal Therapy: An Experimental Study in Normal Porcine Lung Parenchyma.

Population aging and lung cancer screening strategies may lead to an increase in detection of early-stage lung cancer in medical inoperable patients. Recent advances in peripheral bronchoscopy have made it a suitable platform for ablation of small peripheral tumors. We investigated the tissue-ablative effect of a diode laser bronchoscopically applied by a laser delivery fiber (LDF) with wide aperture on porcine lung parenchyma. Laser was tested ex vivo and in vivo to identify the most effective power settings and LDF. Chest computed tomography (CT) were obtained immediately after ablation and after 3 days of observation. At day 3, necropsy was performed. On the basis of our ex vivo and in vivo experiments, we selected the round-tip LDF to be activated at 25 W for 20 seconds. Ten ablations were performed in 5 pigs. One ablation resulted in a pneumothorax requiring aspiration. All animals remained stable for 72 hours. CT findings at days 1 and 3 showed an area of cavitation surrounded by consolidation and ground glass. Median size of CT findings (long axis) was 26 mm (range, 24 to 38) at day 1, and 34 mm (range, 30 to 44) at day 3. Necropsy showed an area of central char measuring from 0.8×0.7×0.9 cm to 2.4×3.5×1.2 cm, surrounded by a gray-brown to dark red area. On histology, variable degrees of necrosis were evident around the charred areas. Bronchoscopic laser interstitial thermal therapy can achieve relatively large areas of ablation of normal lung parenchyma with a low rate of periprocedural complications.

Genome-wide sequencing for early stage lung cancer detection from plasma cell-free DNA (cfDNA): The Circulating Cancer Genome Atlas (CCGA) study.

LBA8501 Background: Plasma cfDNA genomic analysis is used widely for the care of advanced lung cancer, but its suitability for early stage lung cancer detection is not well established. CCGA (NCT02889978) is a prospective, multi-center, observational study launched for the development of a noninvasive assay for cancer detection. Methods: Blood was prospectively collected (N = 1627) from 749 controls (no cancer diagnosis) and 878 participants (pts) with newly-diagnosed untreated cancer in this preplanned substudy, including 127 pts with lung cancer. Three prototype sequencing assays were performed: paired cfDNA and white blood cell (WBC) targeted sequencing (507 genes, 60,000X) for single nucleotide variants/indels; paired cfDNA and WBC whole genome sequencing (WGS) for copy number variation (30X); and cfDNA whole genome bisulfite sequencing (WGBS) for methylation (30X). For each assay, a classification model using 10-fold cross-validation was developed for all pts with cancer, then evaluated in the pts with lung cancer; sensitivity was estimated at 95% specificity. Results: We evaluated pts with lung cancer (127) and a subset of controls (580) with similar ages (mean±SD yrs: 67±9, 60±13), 85% and 43% were ever-smokers, and 46% and 22% were men, respectively. Of 3055 nonsynonymous mutations detected across 122 evaluable pts with lung cancer, &gt; 50% were detected in WBC consistent with clonal hematopoiesis (CH). Accounting for CH, sensitivity in 63 stage I-IIIA pts evaluable across all 3 assays was 48% (35-61, targeted), 54% (41-67, WGS), and 56% (43-68, WGBS); in 54 stage IIIB-IV pts it was 85% (73-93, targeted), 91% (80-97, WGS), and 93% (82-98, WGBS) . Similar sensitivities were observed across histological subtypes (adenocarcinoma, squamous cell, small cell). Comparison to tumor WGS and multi-assay classification will be reported. Conclusions: Early stage lung cancers are detectable in cfDNA using a genome-wide sequencing approach. For lung cancer detection using targeted assays, CH must be accounted for to minimize false positives. Assay optimization is ongoing to allow further clinical development in the intended use population. Clinical trial information: NCT02889978.

Surgical Resection and Outcome of Synchronous and Metachronous Primary Lung Cancer in Breast Cancer Patients.

Women with breast cancer are at increased risk of subsequent primary malignancies, specifically lung cancer. The aim of this study was to report the frequency of lung cancer in patients with breast cancer, and patients' characteristics and surgical outcomes. We investigated 1,066 consecutive female patients undergoing surgical resection for breast cancer and 666 undergoing surgical resection for lung cancer. Lung cancer with breast cancer was observed in 14 patients (1.3% of breast cancer and 2.1% of lung cancer cases; mean age=65 years), and 3/14 (21.4%) patients were smokers. Sixteen lung cancer lesions in 14 patients were adenocarcinomas and one was squamous cell carcinoma. All 14 patients were alive at the time of this report; 4/14 (28.6%) patients had recurrent breast cancer and 1/14 (7.1%) had recurrent lung cancer. In synchronous cases, 5/6 (83.3%) patients received concomitant surgery for both breast cancer and lung cancer. Patients' postoperative courses were uneventful. In metachronous cases, eight patients had lung cancer a mean of 33 months after breast cancer surgery. All eight patients received adjuvant therapies and 4/8 (50%) patients received adjuvant therapies for recurrent breast cancer, including chemotherapy, radiotherapy, hormonal therapy, and anti-HER2 therapy. All patients had early-stage lung adenocarcinoma and underwent surgical resection. Concomitant surgery for synchronous lung and breast cancer was feasible and safe. In metachronous cases, lung cancers tended to be detected within 3 years after surgery for breast cancer. Careful follow-up for postoperative breast cancer may contribute to the detection of early-stage lung cancer.

Abstract 5383: Non-invasive diagnosis of early-stage lung cancer via targeted high-throughput DNA methylation sequencing of circulating tumor DNA (ctDNA)

Abstract Current state-of-the-art lung cancer early screening involves using low-dose CT scan to identify lung nodules smaller than 3cm in diameter. However, it’s still a clinical dilemma to differentiate between malignant and benign nodules. We took the approach of methylation profiling by high-throughput bisulfite DNA sequencing in tissue samples to identify specific methylation signatures. We learned methylation patterns that differentiate malignant vs. benign lesions from tissue samples by in-depth data mining, and then used pattern matching to classify plasma samples. Given the usual low amount of ctDNA in plasma, we also developed an ultra-sensitive library preparation method to perform targeted bisulfite DNA sequencing from as low as 1ng of cfDNA or 1mL of plasma. From a training set of 88 tissue samples, which includes 60 malignant specimens with different subtypes (invasive adenomas, IA; minimally invasive adenomas, MIA; atypical adenomatous hyperplasia, AAH; adenocarcinoma in situ, AIS; carcinoid; lymphoepithelioma-like carcinoma of the lung, LELC; squamous carcinoma, SC; as well as 28 benign specimens in different categories including hematomas, granuloma, tuberculosis, inflammatory pseudotumor (IPT), sclerosing hemangiomas (SHL) and infections, we were able to achieve a sensitivity of 95% for identification of malignant lesions, with a specificity of 78.6%. From an independent validation set of 45 plasma samples, we achieved a sensitivity of 94.7% and a specificity of 85.7% for differentiating patients with malignant tumor from patients with benign lesions. Specifically, our assay is demonstrated to be highly sensitive towards early-stage lung cancer detection, with a sensitivity of 93.3% in a total of 15 patients with stage IA/B lung cancer. In summary, we have developed a highly sensitive blood-based non-invasive diagnostic assay for identification of early stage lung cancer, which can aid clinical decisions for patients with a CT scan positive for lung nodules. This approach can also be extended to non-invasive early screening for various cancer types. Citation Format: Xuyu Cai, Yangbin Gao, Hui Shen, Peter Laird, Jian-bing Fan, Weihong Xu, Wenhua Liang, Jianxing He. Non-invasive diagnosis of early-stage lung cancer via targeted high-throughput DNA methylation sequencing of circulating tumor DNA (ctDNA) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5383. doi:10.1158/1538-7445.AM2017-5383

Detection of Lung Cancer Using Digital Image Processing Techniques: A Comparative Study

This paper focuses on early stage lung cancer detection. Lung cancer is prominent cancer as it states large number of deaths of more than a million every year. It creates need of detecting the lung nodule at early stage in Computer Tomography medical images. So to detect the occurrence of cancer nodule at early stage, the requirement of methods and techniques is increasing. There are different methods and techniques existing but none of them provide a better accuracy of detection. One of the techniques is content based image retrieval Computer Aided Diagnosis System (CAD) for early detection of lung nodules from the Chest Computer Tomography (CT) images. This optimization algorithm allows physicians to identify the nodules present in the CT lung images in the early stage hence the lung cancer. The MATLAB image processing toolbox based implementation is done on the CT lung images and the classifications of these images are carried out. The performance measures like the classification rate and the false positive rates are analyzed.

Radiofrequency ablation in primary non-small cell lung cancer: What a radiologist needs to know.

Lung cancer continues to be one of the leading causes of death worldwide. In advanced cases of lung cancer, a multimodality approach is often applied, however with poor local control rates. In early non-small cell lung cancer (NSCLC), surgery is the standard of care. Only 15-30% of patients are eligible for surgical resection. Improvements in imaging and treatment delivery systems have provided new tools to better target these tumors. Stereotactic body radiation therapy (SBRT) has evolved as the next best option. The role of radiofrequency ablation (RFA) is also growing. Currently, it is a third-line option in stage 1 NSCLC, when SBRT cannot be performed. More recent studies have demonstrated usefulness in recurrent tumors and some authors have also suggested combination of RFA with other modalities in larger tumors. Following the National Lung Screening Trial (NLST), screening by low-dose computed tomography (CT) has demonstrated high rates of early-stage lung cancer detection in high-risk populations. Hence, even considering the current role of RFA as a third-line option, in view of increasing numbers of occurrences detected, the number of potential RFA candidates may see a steep uptrend. In view of all this, it is imperative that interventional radiologists be familiar with the techniques of lung ablation. The aim of this article is to discuss the procedural technique of RFA in the lung and review the current evidence regarding RFA for NSCLC.

Microwave medicals

Researchers at the University of Queensland, Australia, have published results suggesting microwave imaging could be used to detect even early-stage lung tumours. This imaging would also be suitable for frequent monitoring as it doesn't involve ionising radiation and can be made portable for small clinic and even home use for a range of diseases. The authors working with the test setup for the microwave imaging system in the lab at the University of Queensland There is currently great interest in building portable microwave imaging systems as safe, low-cost and reliable diagnostic tools for medical applications. This is because microwave-based diagnostic systems use non-ionising radiation and are non-invasive so they can be used frequently as a monitoring tool. “By virtue of being low-cost and portable, microwave diagnostic systems will provide a technology platform that is easy to use and offers a significant complement to the existing diagnostic technologies, such as MRI and X-rays. In contrast to the current tools that are only available in major medical centres, microwave-based systems can be deployed in ambulances, rural clinics, and doctors’ offices. They could also be used as a self-monitoring tool for healthcare at home leading to a huge reduction in healthcare costs,” explained Queensland team member Ali Zamani. “Lung cancer is the number one cancer killer in the world. Unfortunately, there is no fully reliable and accepted screening tool for the early detection of lung cancer. The significant difference in the dielectric properties between cancerous and healthy lung tissues at microwave frequencies motivated us to investigate the feasibility of building a microwave imaging tool for early-stage lung cancer detection.” The difficulty with using a microwave approach for lung cancer detection is that the human torso also contains different healthy tissues with a wide range of dielectric properties, making microwave signal propagation and penetration complex, and introducing signal clutter. The resulting signals need to be processed to remove this clutter. The complexity and the sheer size of the torso mean that the results of traditional microwave imaging algorithms are very slow to process, and inaccurate. In addition, strong reflections, especially from the outer layers of the torso tissues, mask cancerous tissue signals. To address these problems, the Queensland team's algorithms process the signals in the frequency domain to remove the effect of the clutter, while at the same time a field intensity enhancement factor is used to enhance the signals from abnormal tissues for more accurate tumour detection. As well as developing new algorithms for this system the team have created a compact, unidirectional wideband three-dimensional slot-rotated antenna, working at the 1.5-3 GHz frequency band and integrated it into the imaging platform. In this issue of Electronics Letters the team report results from using their system to image an artificial torso phantom with an emulated lung cancer. Running off a laptop, the results show that their system can detect smaller abnormalities than previous approaches; detecting an emulated cancer only two cubic centimetres in size. The microwave group at the University of Queensland is now looking to gain the proper ethical clearances to proceed with human trials of this approach. They expect human trials to introduce several new challenges, including the effect of normal body movements like heartbeat and breathing, and for this reason they plan to use a three-dimensional multi-static scanning system so that the whole torso can be scanned and imaged in a fraction of a second. The imaging results for the torso phantom containing an emulated lung tumour In addition to this work, the group has been active in building portable microwave imaging systems for medical applications including detection of strokes, brain tumours, heart failure and pulmonary oedema. They currently have ethical approval for human trials on the early detection of strokes, and congestive heart failure. Looking ahead the authors see this imaging technology becoming commonplace and freeing medical imaging from being confined to major medical establishments. “In the next decade, microwave imaging systems are likely to become a reliable diagnostic tool for many medical applications. Those tools will also be available as a monitoring tool, not only in major clinical centres but also at home for self-monitoring.”