The role of bronchoscopy in the diagnosis of early lung cancer: a review

The Risk Factors for Post-Bronchoscopy Respiratory Infection in Lung Cancer Patients-A Retrospective Case-Control Study from a Center in Greece

Introduction: Flexible bronchoscopy and its new methods have revolutionized the era of the diagnosis, staging, and restaging of lung cancer. A rare late complication is post-bronchoscopy respiratory infection, but it is critical due to treatment delays, treatment cancellation, and death. The aim of this study is to identify risk factors for respiratory tract infection after bronchoscopy in patients with lung cancer. Methods: A retrospective single-center observational study of 182 hospitalized patients was conducted at U.G.H. "ATTIKON" who underwent bronchoscopy for diagnosis/staging/restaging of lung cancer from January 2022 to April 2023. Patients were divided into two groups based on whether or not they developed post-bronchoscopy respiratory infection. Results: Analyzing the data between the groups, several potential risk factors for infection were identified, including recent hospitalization for COVID-19 within the last month (OR: 6.16; p = 0.01), history of COPD (OR: 8; p = 0.03), presence of emphysema on CT scan (OR: 8; p = 0.03), endobronchial lesions causing ≥ 50% bronchial obstruction with inability to advance the bronchoscope (OR: 9.6; p < 0.01), increased white blood cell count (≥8.5 K/μL) before bronchoscopy (OR: 8; p = 0.03), and advanced stage IV non-small-cell lung cancer (OR: 9.67; p = 0.02). Conclusions: Comparing our results with previous studies on risk factors for respiratory infections after bronchoscopy, we found that recent hospitalization for SARS-CoV-2 infection was a unique finding in our study. With the increasing incidence of lung cancer worldwide and the critical role of bronchoscopy in diagnosis/staging/restaging, large multicenter studies are needed to identify these risk factors and develop strategies for early detection, treatment, and prevention.

Clinical TNM Lung Cancer Staging: A Diagnostic Algorithm with a Pictorial Review

Lung cancer is a prevalent malignant disease with the highest mortality rate among oncological conditions. The assessment of its clinical TNM staging primarily relies on contrast-enhanced computed tomography (CT) of the thorax and proximal abdomen, sometimes with the addition of positron emission tomography/CT scans, mainly for better evaluation of mediastinal lymph node involvement and detection of distant metastases. The purpose of TNM staging is to establish a universal nomenclature for the anatomical extent of lung cancer, facilitating interdisciplinary communication for treatment decisions and research advancements. Recent studies utilizing a large international database and multidisciplinary insights indicate a need to update the TNM classification to enhance the anatomical categorization of lung cancer, ultimately optimizing treatment strategies. The eighth edition of the TNM classification, issued by the International Association for the Study of Lung Cancer (IASLC), transitioned to the ninth edition on 1 January 2025. Key changes include a more detailed classification of the N and M descriptor categories, whereas the T descriptor remains unchanged. Notably, the N2 category will be split into N2a and N2b based on the single-station or multi-station involvement of ipsilateral mediastinal and/or subcarinal lymph nodes, respectively. The M1c category will differentiate between single (M1c1) and multiple (M1c2) organ system involvement for extrathoracic metastases. This review article emphasizes the role of radiologists in implementing the updated TNM classification through CT imaging for correct clinical lung cancer staging and optimal patient management.

Machine learning allows robust classification of lung neoplasm tissue using an electronic biopsy through minimally-invasive electrical impedance spectroscopy

New bronchoscopy techniques like radial probe endobronchial ultrasound have been developed for real-time sampling characterization, but their use is still limited. This study aims to use classification algorithms with minimally invasive electrical impedance spectroscopy to improve neoplastic lung tissue identification during biopsies. Decision Tree, Support Vector Machines (SVM), Ensemble Method, K-Nearest Neighbors, Naïve Bayes and Discriminant Analysis were applied using mean averaged bioimpedance modulus and phase angle spectra from lung tissue across 15 frequencies (15-307 kHz). Mann-Whitney U test assessed statistical significance between neoplasm and other tissues. Grid search analysis was conducted to determine the optimal hyperparameter configuration for each model, employing a 5-fold cross-validation approach. Model performance was evaluated using Receiver Operating Characteristic curves, with the Area Under Curve (AUC), precision, recall, and F1-score calculated. All the frequencies used to train and test the algorithms obtained high significant differences between neoplasm and the other types of tissues (P < 0.001). All the algorithms implemented obtained an accuracy, AUC and F1-score above the 95% except for Naïve Bayes. Decision Tree, Discriminant Analysis and SVM algorithms are suitable for the implementation of a new low-cost guidance method during bronchoscopy.

BronchoTrack: Airway Lumen Tracking for Branch-Level Bronchoscopic Localization

Localizing the bronchoscope in real time is essential for ensuring intervention quality. However, most existing vision-based methods struggle to balance between speed and generalization. To address these challenges, we present BronchoTrack, an innovative real-time framework for accurate branch-level localization, encompassing lumen detection, tracking, and airway association. To achieve real-time performance, we employ benchmark light weight detector for efficient lumen detection. We firstly introduce multi-object tracking to bronchoscopic localization, mitigating temporal confusion in lumen identification caused by rapid bronchoscope movement and complex airway structures. To ensure generalization across patient cases, we propose a training-free detection-airway association method based on a semantic airway graph that encodes the hierarchy of bronchial tree structures. Experiments on 11 patient datasets demonstrate BronchoTrack's localization accuracy of 81.72%, while accessing up to the 6th generation of airways. Furthermore, we tested BronchoTrack in an in-vivo animal study using a porcine model, where it localized the bronchoscope into the 8th generation airway successfully. Experimental evaluation underscores BronchoTrack's real-time performance in both satisfying accuracy and generalization, demonstrating its potential for clinical applications.

The Role of ctDNA in the Management of Non-Small-Cell Lung Cancer in the AI and NGS Era

Liquid biopsy (LB) involves the analysis of circulating tumour-derived DNA (ctDNA), providing a minimally invasive method for gathering both quantitative and qualitative information. Genomic analysis of ctDNA through next-generation sequencing (NGS) enables comprehensive genetic profiling of tumours, including non-driver alterations that offer prognostic insights. LB can be applied in both early-stage disease settings, for the diagnosis and monitoring of minimal residual disease (MRD), and advanced disease settings, for monitoring treatment response and understanding the mechanisms behind disease progression and tumour heterogeneity. Currently, LB has limited use in clinical practice, primarily due to its significant costs, limited diagnostic yield, and uncertain prognostic role. The application of artificial intelligence (AI) in the medical field is a promising approach to processing extensive information and applying it to individual cases to enhance therapeutic decision-making and refine risk assessment.

Mastery Learning Guided by Artificial Intelligence Is Superior to Directed Self-Regulated Learning in Flexible Bronchoscopy Training: An RCT

INTRODUCTION

Simulation-based training has proven effective for learning flexible bronchoscopy. However, no studies have tested the efficacy of training toward established proficiency criteria, i.e., mastery learning (ML). We wish to test the effectiveness of ML compared to directed self-regulated learning (DSRL) on novice bronchoscopists' end-of-training performance.

METHODS

In a standardized simulated setting, novices without prior bronchoscopy experience were trained using an artificial intelligence (AI) guidance system that automatically recognizes the bronchial segments. They were randomized into two groups: the ML group and the DSRL group. The ML group was trained until they completed two procedures meeting the proficiency targets: 18 inspected segments, 18 structured progressions, <120-s procedure time. The DSRL group was trained until they no longer perceived any additional benefits from training. Both groups then did a finalizing test, without the AI guidance enabled.

RESULTS

A total of 24 participants completed the study, with 12 in each group. Both groups had a high mean number of inspected segments (ML = 17.2 segments, DSRL = 17.3 segments, p = 0.85) and structured progressions (ML = 15.5 progressions, DSRL = 14.8 progressions, p = 0.58), but the ML group performed the test procedure significantly faster (ML = 107 s, DSRL = 180 s, p < 0.001). The ML did not spend significantly longer time training (ML = 114 min, DSRL = 109 min, p = 0.84).

CONCLUSIONS

ML is a very efficient training form allowing novice trainees to learn how to perform a thorough, systematic, and quick flexible bronchoscopy. ML does not require longer time spent training compared to DSRL, and we therefore recommend training of future bronchoscopists by this method.

Unlocking the Potential of Computed Tomography-Guided Tracers in Pinpointing Lung Lesions during Surgery: A Collaborative Multi-Institutional Journey

Background: Multiple techniques exist for the preoperative localization of small, deeply located solid or subsolid pulmonary nodules to guide limited thoracoscopic resection. This study aims to conduct a multi-institutional comparison of three different tomography-guided tracers' methods. Methods: A retrospective multicenter cross-sectional study was conducted. All patients suitable for CT-guided tracers with microcoil (GROUP1, n = 58), hook wire (GROUP2, n = 86), or bioabsorbable hydrogel plug (GROUP3, n = 33) were scheduled for video-assisted thoracoscopic wedge resection. Outcome variables: successful nodule localization, safety, and the feasibility of the tracers' placement. A χ2 test or Fisher's test for expected numbers less than five and a Kruskal-Wallis test were used to analyze the categorical and continuous variables, respectively. For the power calculations, we used G*Power version 3.1.9.6. Results: One hundred seventy-seven patients underwent the localization and resection of 177 nodules detected with three different CT-guided tracers. A significant difference was recorded for cancer history (p = 0.030), respiratory function, Charlson comorbidity index (p = 0.018), lesion type (p < 0.0001), distance from pleura surface (p < 0.0001), and time between preoperative CT-guided tracers and surgical procedures (p < 0.0001). Four post-procedural complications were recorded and in GROUP2, four cases of tracer dislocations occurred. Finally, hook wire group was associated with the shortest surgical time (93 min, p = 0.001). Conclusions: All methods were feasible and efficient, resulting in a 100% success rate for the microcoils and the bioabsorbable hydrogel plugs and a 94.2% success rate for the hook wires. Our results highlight the need to choose a technique that is less stressful for the patient and helps the surgeon by extending the approach to deep nodules and resecting over the course of several days from deployment.

Artificial intelligence for automatic and objective assessment of competencies in flexible bronchoscopy

Background

Bronchoscopy is a challenging technical procedure, and assessment of competence currently relies on expert raters. Human rating is time consuming and prone to rater bias. The aim of this study was to evaluate if a bronchial segment identification system based on artificial intelligence (AI) could automatically, instantly, and objectively assess competencies in flexible bronchoscopy in a valid way.

Methods

Participants were recruited at the Clinical Skills Zone of the European Respiratory Society Annual Conference in Milan, 9th-13th September 2023. The participants performed one full diagnostic bronchoscopy in a simulated setting and were rated immediately by the AI according to its four outcome measures: diagnostic completeness (DC), structured progress (SP), procedure time (PT), and mean intersegmental time (MIT). The procedures were video-recorded and rated after the conference by two blinded, expert raters using a previously validated assessment tool with nine items regarding anatomy and dexterity.

Results

Fifty-two participants from six different continents were included. All four outcome measures of the AI correlated significantly with the experts' anatomy-ratings (Pearson's correlation coefficient, P value): DC (r=0.47, P<0.001), SP (r=0.57, P<0.001), PT (r=-0.32, P=0.02), and MIT (r=-0.55, P<0.001) and also with the experts' dexterity-ratings: DC (r=0.38, P=0.006), SP (r=0.53, P<0.001), PT (r=-0.34, P=0.014), and MIT (r=-0.47, P<0.001).

Conclusions

The study provides initial validity evidence for AI-based immediate and automatic assessment of anatomical and navigational competencies in flexible bronchoscopy. SP provided stronger correlations with human experts' ratings than the traditional DC.

Utility of auto fluorescence-guided biopsy in suspected lung cancer patients with bronchial mucosal lesions

BACKGROUND

Bronchoscopy is currently the most common technique for lung cancer diagnosis. Patients suspected of malignancy often undergo bronchoscopic examination, and biopsy is routinely used in patients with visible bronchial lesions. However, it is difficult to differentially diagnose lung cancer in patients with bronchial mucosal lesions. Thus, this study was conducted to investigate the utility of fluorescence-guided biopsy in suspected lung cancer patients with bronchial mucosal lesions.

METHODS

We conducted a retrospective study in a single screening center to assess the sensitivity and specificity of fluorescence-guided biopsy compared with white light bronchoscopy (WLB) in patients with bronchial mucosal lesions.

RESULTS

A total of 301 patients with bronchial mucosal lesions were enrolled in this study. The sensitivity for patients with fluorescence-guided biopsy was 60.3 % (95 % confidence interval [CI]: 53.1 %-67.1 %), which was higher than that of patients with WLB alone (45.2 %, 95 % CI: 38.2-52.4 %) (P = 0.0026). Additionally, compared with the WLB group, the fluorescence -guided biopsy group was found to have a significantly higher specificity (100 %, 95 % CI: 95.5-100 % versus 69.6 %, 95 % CI: 59.6-78.1 %), positive predictive value (100 %, 95 % CI: 96.1-100 % versus 74.3 %, 95 % CI: 65.5-81.7 %) and negative predictive value (56.3 %, 95 % CI: 48.8-63.6 % versus 39.4 %, 95 % CI: 32.3-47.0 %).

CONCLUSION

Fluorescence-guided biopsy can serve as an important adjunct to WLB for the differential diagnosis of lung cancer in patients with bronchial mucosal lesions.

Electromagnetic Navigational Bronchoscopy Learning Curve Regarding Pneumothorax Rate and Diagnostic Yield

Electromagnetic navigational bronchoscopy (ENB) has emerged as an innovative technique for diagnosing peripheral and central nodules, offering an improved diagnostic yield compared to conventional bronchoscopy with fewer complications. That being said, pneumothorax remains a frequent complication. This retrospective study conducted at Castle Hill Hospital, UK, analysed ENB procedures over four years to assess the diagnostic yield and pneumothorax rates, exploring learning curves and procedural improvements specifically focusing on the diagnostic yield and pneumothorax rate as markers of change. A total of 246 patients underwent 358 peripheral lung biopsies, revealing an overall diagnostic yield of 61.3%. The diagnostic yield increased from 58.2% in 2020-2021 to 66.0% in 2022-2023 while the pneumothorax rate decreased significantly from 9.8% to 3.4% (p = 0.021*). The majority of pneumothorax cases occurred following upper lobe procedures. The study depicts the importance of procedural experience in improving outcomes, suggesting a learning curve effect. Additionally, it emphasizes the potential for technological advancements, such as robotic assistance, to mitigate operator-dependent variability and improve reproducibility in ENB procedures. These findings contribute to optimizing diagnostic pathways for lung lesions and improving patient safety in ENB interventions.

Understanding the Landscape of Bronchoscopy in Lung Cancer: Insights From Lesion Location, Gender, and Diagnostic Efficacy

INTRODUCTION

Lung cancer constitutes a critical global health concern. According to the International Agency for Research on Cancer's (IARC) GLOBOCAN 2020 estimates, lung cancer is the leading cause of death in cancer patients. In areas where tuberculosis is prevalent, misdiagnosis and mistreatment frequently result from overlap, creating significant difficulties that delay diagnosis and treatment. Amid this complication, bronchoscopic techniques emerge as critical diagnostic tools, though their efficacy varies between studies.

METHOD

Our retrospective study, conducted from July 2021 to December 2022 at the Department of Respiratory Medicine, Ganesh Shankar Vidyarthi Memorial Medical College, Kanpur, examined 156 participants with malignancies. Our focus encompassed diverse lesions within the bronchial landscape, revealing intriguing findings.

RESULTS

Bronchoscopic examinations unravelled prevalent abnormalities: 52 (33.3%) manifested as intraluminal growth, 48 (31.6%) as mucosal irregularities, and a less frequent (16, 10.3%) as an intraluminal bulge. Transbronchial needle aspiration stood out with a 10/11 (91%) positivity rate, biopsy came in second at 38/46 (83%), and bronchoalveolar lavage showed a 44/152 (29%) positivity rate. It was interesting to see how the lesions were spread out among the different types of histology. For example, squamous cell carcinoma showed 17/37 (46%) intraluminal growth, while adenocarcinoma showed 22/60 (36.7%) intraluminal growth and 4/60 (6.7%) intraluminal bulge. Moreover, a significant absence of abnormalities was observed in various lesions, underlining the intricacies of characterising bronchial lesions.

CONCLUSION

Our study shows that direct tissue sampling is better and that new bronchoscopic technologies are important for diagnosing lesions that were hard to get to in the past. However, limitations in patient selection biases and the single-centre focus caution against generalised interpretations. Our research illuminates the pivotal role of bronchoscopic methods in diagnosing lung lesions, emphasising the necessity for continued advancements to enhance diagnostic accuracy and treatment efficacy in lung cancer subtypes.

Artificial Intelligence Improves Novices' Bronchoscopy Performance: A Randomized Controlled Trial in a Simulated Setting

BACKGROUND

Navigating through the bronchial tree and visualizing all bronchial segments is the initial step toward learning flexible bronchoscopy. A novel bronchial segment identification system based on artificial intelligence (AI) has been developed to help guide trainees toward more effective training.

RESEARCH QUESTION

Does feedback from an AI-based automatic bronchial segment identification system improve novice bronchoscopists' end-of-training performance?

STUDY DESIGN AND METHODS

The study was conducted as a randomized controlled trial in a standardized simulated setting. Novices without former bronchoscopy experience practiced on a mannequin. The feedback group (n = 10) received feedback from the AI, and the control group (n = 10) trained according to written instructions. Each participant decided when to end training and proceed to performing a full bronchoscopy without any aids.

RESULTS

The feedback group performed significantly better on all three outcome measures (median difference, P value): diagnostic completeness (3.5 segments, P < .001), structured progress (13.5 correct progressions, P < .001), and procedure time (-214 seconds, P = .002).

INTERPRETATION

Training guided by this novel AI makes novices perform more complete, more systematic, and faster bronchoscopies. Future studies should examine its use in a clinical setting and its effects on more advanced learners.

Subsecond lung cancer detection within a heterogeneous background of normal and benign tissue using single-point Raman spectroscopy

Significance

Lung cancer is the most frequently diagnosed cancer overall and the deadliest cancer in North America. Early diagnosis through current bronchoscopy techniques is limited by poor diagnostic yield and low specificity, especially for lesions located in peripheral pulmonary locations. Even with the emergence of robotic-assisted platforms, bronchoscopy diagnostic yields remain below 80%.

Aim

The aim of this study was to determine whether in situ single-point fingerprint (800 to 1700    cm - 1 ) Raman spectroscopy coupled with machine learning could detect lung cancer within an otherwise heterogenous background composed of normal tissue and tissue associated with benign conditions, including emphysema and bronchiolitis.

Approach

A Raman spectroscopy probe was used to measure the spectral fingerprint of normal, benign, and cancer lung tissue in 10 patients. Each interrogated specimen was characterized by histology to determine cancer type, i.e., small cell carcinoma or non-small cell carcinoma (adenocarcinoma and squamous cell carcinoma). Biomolecular information was extracted from the fingerprint spectra to identify biomolecular features that can be used for cancer detection.

Results

Supervised machine learning models were trained using leave-one-patient-out cross-validation, showing lung cancer could be detected with a sensitivity of 94% and a specificity of 80%.

Conclusions

This proof of concept demonstrates fingerprint Raman spectroscopy is a promising tool for the detection of lung cancer during diagnostic procedures and can capture biomolecular changes associated with the presence of cancer among a complex heterogeneous background within less than 1 s.

Evaluation and Exploration of Machine Learning and Convolutional Neural Network Classifiers in Detection of Lung Cancer from Microarray Gene-A Paradigm Shift

Microarray gene expression-based detection and classification of medical conditions have been prominent in research studies over the past few decades. However, extracting relevant data from the high-volume microarray gene expression with inherent nonlinearity and inseparable noise components raises significant challenges during data classification and disease detection. The dataset used for the research is the Lung Harvard 2 Dataset (LH2) which consists of 150 Adenocarcinoma subjects and 31 Mesothelioma subjects. The paper proposes a two-level strategy involving feature extraction and selection methods before the classification step. The feature extraction step utilizes Short Term Fourier Transform (STFT), and the feature selection step employs Particle Swarm Optimization (PSO) and Harmonic Search (HS) metaheuristic methods. The classifiers employed are Nonlinear Regression, Gaussian Mixture Model, Softmax Discriminant, Naive Bayes, SVM (Linear), SVM (Polynomial), and SVM (RBF). The two-level extracted relevant features are compared with raw data classification results, including Convolutional Neural Network (CNN) methodology. Among the methods, STFT with PSO feature selection and SVM (RBF) classifier produced the highest accuracy of 94.47%.

Lung cancer registry and monitoring: Feasibility study and application (fars lung cancer registry project)

Background

Lung cancer (LC) is the second most common and deadliest cancer in the world. Despite the control of the progressive course of LC in developed countries, studies indicate an increase in the incidence of the disease in developing countries. We designed a stepwise approach-based surveillance system for registering LC in our region (fars lung cancer registry "FaLCaRe" Project).

Materials and Methods

A questionnaire was designed and agreed upon by the steering committee using the Delphi method. Variables in nine fields were divided into three groups based on their importance: core, expanded core, and optional. The web-based data bank software was designed. The informative site about LC and team services was designed and launched for professional and community (www.falcare.org) educational purposes.

Results

545 variables in nine fields were designed (20 core variables). Primary data of 39 LC patients (24 men and 15 women) with a mean age of 62 years were analyzed. Twenty-six patients had a history of smoking. Moreover, 39% and 26% of patients had a history of hookah smoking and opium use, respectively. Adenocarcinoma was the most prevalent pathologic findings in cases. More than 80% of patients were diagnosed in stages 3 and 4 of cancer.

Conclusion

FaLCaRe Project with the capabilities seen in it can be used as a model for national LC registration. With continuous valid data registry about LC, it is possible to make decisions at the national level for control and management its consequences while drawing the natural history of the LC.

A Novel Robotic Bronchoscope System for Navigation and Biopsy of Pulmonary Lesions

Transbronchial biopsy sampling, as a minimally invasive method with relatively low risk, has been proved to be a promising treatment in the field of respiratory surgery. Although several robotic bronchoscopes have been developed, it remains a great challenge to balance size and flexibility, while integrating multisensors to realize navigation during complex airway networks. This paper proposes a novel robotic bronchoscope system composed by end effector with relatively small size, relevant actuation unit, and navigation system with path planning and surgical guidance capability. The main part of the end effector is machined by bidirectional groove on a nickel-titanium tube, which can realize bending, rotation, and translation 3 degrees of freedom. A prototype of the proposed robotic bronchoscope system is designed and fabricated, and its performance is tested through several experiments to verify the stiffness, flexibility, and navigation performance. The results show that the proposed system is with good environment adaptiveness, and it can become a promising biopsy method through natural cavity of the human body.

The value of narrow-band imaging bronchoscopy in diagnosing central lung cancer

Aims

This research aimed to study the value of narrow-band imaging(NBI) in the diagnosis of central lung cancer.

Materials and methods

This study included 916 patients with clinical suspected of central lung cancer or follow-up of patients after curative lung cancer surgery. All of the patients were examined by Olympus Evis Lucera electronic bronchoscope system, any sites that were abnormal when viewed by white-light bronchoscopy (WLB) or NBI were biopsied, four to six biopsies were taken at each site of the abnormal region visualized as lesions, we record the endoscopic features of NBI and compared with histopathology results, to evaluate the diagnostic value of NBI for central lung cancer and the relationship between vascular patterns of NBI and histological types of lung cancer, and try to establish a multinomial logistic regression model for predicting the histological types of lung cancer. The biopsy specimens were examined by CD34 antibody through immunohistochemistry (IHC) method, CD34 marked microvessel density(MVD), compared the number of microvessels between benign and malignant diseases and the number between different histological types of lung cancer, to verify the results of NBI.

Results

NBI provided high sensitivity (91.7%), specificity (84.9%), positive predictive value (97.6%), negative predictive value (61.5%), and agreement rate (90.7%). The predominant vascular patterns in the well-defined histological types of lung cancer were dotted blood vessels (121 patients), tortuous blood vessels (248 patients), and abrupt-ending blood vessels (227 patients). Logistic regression analysis of the results showed that smoking status of the patient, combined with vascular patterns under NBI, and age partly affect the histological types of lung cancer.

Conclusions

NBI is highly accurate for the diagnosis of central lung cancer.

Estimation of the median effective dose and the 95% effective dose of alfentanil required to inhibit the bronchoscopy reaction during painless bronchoscopy with i-gel supraglottic airway device: an Up-and-Down Sequential Allocation Trial

Background

In practice, the optimal dose of alfentanil that should be used when painless bronchoscopy is performed is unknown. The purpose of this study was to investigate the effective dose of alfentanil in suppressing bronchoscopy responses to painless bronchoscopy with an i-gel supraglottic airway device.

Methods

Patients aged 18-70 years, with American Society of Anesthesiologists (ASA) physical status I-II, who planned to undergo painless bronchoscopy were recruited for this study. Alfentanil was administered intravenously 2 minutes before propofol administration. The response to bronchoscopy was measured, including oxygen saturation (SPO₂) and changes in respiratory rhythm. The median effective dose of alfentanil (ED₅₀) required to alleviate responses to the bronchoscopy was calculated using Dixon's up-and-down method in the female and male groups. Probit analysis was used to generate a dose-response curve in each group.

Results

A total of 48 patients were recruited for the study including 25 females and 23 males. The ED₅₀ of alfentanil for suppressing responses to painless bronchoscopy in females and males was 13.68±4.75 and 17.96±3.45 µg/kg, respectively. The difference was not statistically significant between the two groups (P=0.078). Probit analysis showed the ED₅₀ of alfentanil in female bronchoscopy was 12.4 µg/kg [95% confidence interval (CI): 4.5 to 17 µg/kg]. In men, the ED₅₀ of alfentanil was 16.4 µg/kg (95% CI: 12.1 to 20.1 µg/kg). According to the probit analysis, the 95% effective dose (ED₉₅) of alfentanil was 22.4 µg/kg (95% CI: 17.5 to 67.3 µg/kg) in female bronchoscopy. In men, the ED₉₅ of alfentanil was 23.3 µg/kg (95% CI: 19.8 to 46.2 µg/kg).

Conclusions

Our data suggest that there were no obvious differences between men and women in the effective dose of alfentanil in painless bronchoscopy.

Diagnosis of lung cancer by flexible fiberoptic bronchoscopy: a descriptive study

Flexible fiberoptic bronchoscopy (FFB) remains the most important minimally invasive method for the diagnosis of lung cancer (LC). We performed a retrospective study to assess the main endoscopic findings of malignant lung tumors in the large airways in a cohort of Romanian patients. The group consisted of 32 (84.21%) men and six (15.78%) women, with an average age of 64.63±6.07 years. The bronchoscopic examination allowed the detection and biopsy of 36 malignant lung tumors, and in two other cases, due to malignant atelectasis, the patients were sent to a Department of Thoracic Surgery, to perform the biopsy following the surgery. Histopathological (HP) examination revealed the presence of squamous cell carcinoma (SCC) in 19 (50%) patients, adenocarcinoma (ADC) in 11 (28.94%) patients and small cell lung cancer (SCLC) in eight (21.05%) patients. The macroscopic and microscopic analysis of the lung tumors showed that infiltrative forms were found in most cases (58.33%), followed by exophytic (mass) endobronchial lesions (22.22%) and mixed forms (19.44%). If most infiltrative forms were SCC (66.66%), the exophytic and mixed lesions were most frequently ADC (50% and 57.14%). The tumor lesions caused both malignant bronchial stenosis (57.89%) and malignant atelectasis (42.1%). The main mechanisms involved in bronchial malignant obstruction were endoluminal (50%), mixed (31.57%) and extraluminal (18.42%) mechanisms. In conclusion, FFB remains the main method of diagnosing LC in the large airways. The most common macroscopic appearance of lung tumors revealed by bronchoscopy was the infiltrative appearance. In half of our patients, the malignant bronchial obstruction was achieved by endoluminal mechanism. The most common pathological form found in our patients was the SCC, as described in half of the investigated patients.

Fluorescent paper strip immunoassay with carbon nanodots@silica for determination of human serum amyloid A1

A fluorescent paper strip immunoassay in conjunction with carbon nanodots@silica (CND@SiO₂) as a label was developed for the quantitative measurements of human serum amyloid A1 (hSAA1) in serum at clinically significant concentrations for lung cancer diagnosis. Monodispersed CND@SiO₂ was prepared by cohydrolysis between silane-crosslinked carbon nanodots and silica precursors via the Ströber method and further attached covalently to anti-hSAA1 (14F8) monoclonal antibody [anti-hSAA1(14F8)] specific to the hSAA1 target. The hSAA1 concentrations were then determined by quantifying the blue fluorescence intensity upon 365 nm excitation of the captured hSAA1 with anti-hSAA1(14F8)-CND@SiO₂ conjugates in the test line on a paper strip where anti-hSAA1 (10G1) monoclonal antibody was physisorbed. The developed fluorescent paper strip with CND@SiO₂ can detect hSAA1 at concentrations ranging from 0.1 to 5 nM (R² = 0.995), with a limit of detection of  0.258 nM in 10 mM phosphate buffer pH 7.4 containing human serum albumin. The performance of  recovery (90.98-109.17%) and repeatability (coefficients of variation < 8.46%) obtained was also acceptable for quantitative determinations. The platform was employed for direct determination of hSAA1 concentrations in undiluted serum samples from lung cancer patients (relative standard deviation (RSD) < 7.46%) and healthy humans (RSD < 3.96%). The results were compared with those obtained using a commercially available enzyme-linked immunosorbent assay alongside liquid chromatography with tandem mass spectrometry measurements.

Fluorescence Guided Surgery

Fluorescence guided surgery (FGS) is an imaging technique that allows the surgeon to visualise different structures and types of tissue during a surgical procedure that may not be as visible under white light conditions. Due to the many potential advantages of fluorescence guided surgery compared to more traditional clinical imaging techniques such as its higher contrast and sensitivity, less subjective use, and ease of instrument operation, the research interest in fluorescence guided surgery continues to grow over various key aspects such as fluorescent probe development and surgical system development as well as its potential clinical applications. This review looks to summarise some of the emerging opportunities and developments that have already been made in fluorescence guided surgery in recent years while highlighting its advantages as well as limitations that need to be overcome in order to utilise the full potential of fluorescence within the surgical environment.

A Soft Robot for Peripheral Lung Cancer Diagnosis and Therapy

Lung cancer is one of the deadliest forms of cancers and is often diagnosed by performing biopsies with the use of a bronchoscope. However, this diagnostic procedure is limited in ability to explore deep into the periphery of the lung where cancer can remain undetected. In this study, we present design, modeling, fabrication, and testing of a one degree of freedom soft robot with integrated diagnostic and interventional capabilities as well as vision sensing. The robot can be deployed through the working channel of commercial bronchoscopes or used as a stand-alone system as it integrates a micro camera to provide vision sensing and controls to the periphery of the lung. The small diameter (2.4 mm) of the device allows navigation in branches deeper in the lung, where current devices have limited reachability. We have performed mechanical characterizations of the robotic platform, including blocked force, maximum bending angle, maximum angular velocity, and workspace, and assessed its performance in in vitro and ex vivo experiments. We have developed a computer vision algorithm, and validated it in in vitro conditions, to autonomously align the robot to a selected branch of the lung and aid the clinician (by means of a graphical user interface) during navigation tasks and to perform robot-assisted stabilization in front of a lesion, with automated tracking and alignment.

Provision of essential bronchoscopy during COVID-19 pandemic

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Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images-The ACDC@LungHP Challenge 2019

Accurate segmentation of lung cancer in pathology slides is a critical step in improving patient care. We proposed the ACDC@LungHP (Automatic Cancer Detection and Classification in Whole-slide Lung Histopathology) challenge for evaluating different computer-aided diagnosis (CADs) methods on the automatic diagnosis of lung cancer. The ACDC@LungHP 2019 focused on segmentation (pixel-wise detection) of cancer tissue in whole slide imaging (WSI), using an annotated dataset of 150 training images and 50 test images from 200 patients. This paper reviews this challenge and summarizes the top 10 submitted methods for lung cancer segmentation. All methods were evaluated using metrics using the precision, accuracy, sensitivity, specificity, and DICE coefficient (DC). The DC ranged from 0.7354 ±0.1149 to 0.8372 ±0.0858. The DC of the best method was close to the inter-observer agreement (0.8398 ±0.0890). All methods were based on deep learning and categorized into two groups: multi-model method and single model method. In general, multi-model methods were significantly better (p 0.01) than single model methods, with mean DC of 0.7966 and 0.7544, respectively. Deep learning based methods could potentially help pathologists find suspicious regions for further analysis of lung cancer in WSI.

Excitation-scanning hyperspectral video endoscopy: enhancing the light at the end of the tunnel

Colorectal cancer is the 3^rd leading cancer for incidence and mortality rates. Positive treatment outcomes have been associated with early detection; however, early stage lesions have limited contrast to surrounding mucosa. A potential technology to enhance early stagise detection is hyperspectral imaging (HSI). While HSI technologies have been previously utilized to detect colorectal cancer ex vivo or post-operation, they have been difficult to employ in real-time endoscopy scenarios. Here, we describe an LED-based multifurcated light guide and spectral light source that can provide illumination for spectral imaging at frame rates necessary for video-rate endoscopy. We also present an updated light source optical ray-tracing model that resulted in further optimization and provided a ∼10X light transmission increase compared to the initial prototype. Future work will iterate simulation and benchtop testing of the hyperspectral endoscopic system to achieve the goal of video-rate spectral endoscopy.

Diagnostic value of radial endobronchial ultrasonographic features in predominant solid peripheral pulmonary lesions

Background

Transbronchial lung biopsy (TBLB) of peripheral pulmonary lesions (PPLs) is usually performed for a definite diagnosis. Radial probe endobronchial ultrasonography is often acknowledged as a good guidance method for TBLB as it can help physicians confirm the lesions’ position. It is also a non-invasive imaging diagnostic method. This clinical study was designed to evaluate the ability of radial endobronchial ultrasonography (R-EBUS) to differentiate benign from malignant predominant solid PPLs based on imaging features.

Methods

Patients with predominant solid PPLs were enrolled in this study retrospectively. TBLB was performed using R-EBUS with or without other guidance techniques. One typical sonographic image and one video of each lesion were recorded for analysis. Six radial probe endobronchial ultrasonographic image features (size, shape, echogenicity, margin, blood vessel, and linear-discrete air bronchogram) were studied by ultrasonography specialists and physicians who were blinded to the final diagnosis. The sum score model of the combined predictive factors indicated the best diagnostic accuracies for predicting malignant PPLs. The model group results were used to establish the diagnostic standard for a verification group.

Results

A total of 303 patients were enrolled in the model group from July 2018 to July 2019 at the Shanghai Chest Hospital (214 with malignant and 89 with benign lesions). The mean lesion long axis on computed tomographic images was 34.39±13.79 mm. There were significant statistical differences between benign and malignant lesions in the long axis, short axis, shape, margin, blood vessel, and linear-discrete air bronchogram assessed by radial endobronchial ultrasound. Long axis, lobulation, distinct but not sharp margin, absence of blood vessel, and absence of linear-discrete air bronchogram were good predictive factors of malignant lesions. A sum score model value of 79.54% of these combined factors indicated the best diagnostic accuracy for predicting malignant lesions. Eighty-seven patients were enrolled in the verification group from August to October 2019. The sum score model showed a diagnostic accuracy of 82.76%.

Conclusions

Radial endobronchial ultrasonographic features can differentiate malignant from benign lesions and thus have potential diagnosis value in predominant solid PPLs.

Using structured progress to measure competence in flexible bronchoscopy

Background

Flexible bronchoscopy is a core invasive procedure in pulmonary medicine and training in the procedure is mandatory. Diagnostic completeness and procedure time have been identified as useful measures of competence. No outcome measures have been developed regarding navigational path in bronchoscopy to assess whether the bronchial segments have been identified in an arbitrary or structured order. We investigated whether a new outcome measure for structured progression could be used to assess competency in flexible bronchoscopy.

Methods

The study was designed as a prospective comparative study. Twelve novices, eleven intermediates, and ten expert bronchoscopy operators completed three full bronchoscopies in a simulated setting on a phantom. The following outcome measures were collected through a checklist evaluation by a trained rater: Diagnostic Completeness as amount of visualized bronchial segments, Structured Progress between the bronchial segments in ascending order, and average intersegmental time (AIT).

Results

The ability to follow a structured ascending path through the bronchial tree correlated with a higher amount of identified bronchial segments (Pearson’s correlation, r=0.62, P<0.001) and a lower AIT (Pearson’s correlation, r=−0.52, P<0.001).

Conclusions

Operators should advance through the bronchial tree in a structured ascending order to ensure systematic progress with the highest level of diagnostic yield and the lowest procedure time. Structured progression is a useful measure to evaluate competency in flexible bronchoscopy.

Outcomes of patients with a non-diagnostic initial bronchoscopy for suspected thoracic malignancy

Lung cancer is 1 of the leading causes of cancer-related deaths and bronchoscopy is an essential tool for the diagnosis. The diagnostic yield varies based on the characteristics of the lesion and bronchoscopic techniques employed. There is limited data regarding outcomes of patients suspected of thoracic malignancies with a non-diagnostic initial bronchoscopy. The goal of the study was to evaluate the outcomes of patients with a non-diagnostic bronchoscopy for suspected thoracic malignancies and to evaluate variables predictive of a diagnostic bronchoscopy.Retrospective analysis of adult patients at BronxCare Hospital Center who underwent bronchoscopy for suspected thoracic malignancy. The study period was January 2012 to February 2019. Exclusion criteria included patients who underwent only inspection bronchoscopy or bronchoalveolar lavage as the diagnostic yield for malignancy with these techniques is low. All other bronchoscopic procedures were included that is, endobronchial biopsies, transbronchial biopsies, and endobronchial ultrasound guided-transbronchial needle aspiration. Bronchoscopy was considered diagnostic when a specific histopathological diagnosis was established.311 patients underwent bronchoscopy to rule out malignancy. A diagnosis was obtained in 153 (49.2%) patients, 81 (52.9%) had primary lung cancer and 14 (9.15%) other malignancies. 158 (50.8%) patients had initial non-diagnostic bronchoscopy; 86 (54.43%) were lost to follow up. Of the remaining 72 (45.57%) patients, radiological resolution or stability was observed in 51 (70.8%) patients. Primary lung cancer was found in 13 (18.05%) patients and other malignancies in 5 (6.94%). Predictive of a diagnostic bronchoscopy was the performance of endobronchial biopsies and endobronchial ultrasound guided-transbronchial needle aspiration.This study highlights some of the barriers to the timely diagnosis of thoracic malignancies. Following patients with a non-diagnostic procedure as well as all those patients with diagnosed malignancies it of the utmost importance. In patients available for follow up, close to 25% of additional cases with treatable malignancy could be identified and patients diagnosed with cancer could receive timely treatment.

Identification of the intersegmental plane during thoracoscopic segmentectomy: state of the art

During thoracoscopic segmentectomy, where direct palpation of the tumour is not always possible, achieving adequate margins from the cancer is of crucial importance. It is thus mandatory to accurately identify the intersegmental plane (ISP). Indeed, inadequate determination and division of the ISP can lead to unsatisfactory oncological results. Our systematic review focused on the effectiveness of the different techniques for identifying the ISP, highlighting the fact that a 1-size-fits-all method is not feasible. Based on the published evidence, 6 main methods were reported, each with its pros and cons: inflation-deflation technique, selective resected segmental inflation, systemic injection of indocyanine green, injection of endobronchial dye, 3-dimensional simulation using multidetector computed tomography and virtual-assisted lung mapping. In conclusion, ISP demarcation is mandatory to achieve a high rate of success of thoracoscopic segmentectomy, and it is very helpful in surgical planning, especially when preoperative multidetector computed tomography and 3-dimensional reconstructions are routinely performed.

The top 100 most cited articles on bronchoscopy: a bibliometric analysis

Background

Bronchoscopy is applied broadly in the diagnosis and treatment of pulmonary diseases. Over the past few decades, an increasing number of studies about bronchoscopy have been published. However, little is known about their qualities and characteristics.

Methods

All of the databases in Web of Science (including the Web of Science Core Collection, BIOSIS Citation Index, KCI-Korean Journal Database, MEDLINE, Russian Science Citation Index, and SciELO Citation Index) were utilized to identify articles published from 1990 to 2020. The top 100 most cited articles about bronchoscopy were selected for degree centrality analysis and analyses regarding publication time, total citation number, the citation density, time-related flux, first author, published journal, geographic origin, and research theme.

Results

The selected articles were published mainly in the 2000s and 1990s. Citations per article ranged from 731 to 196. The leading country was the USA, followed by the United Kingdom. The most frequently studied themes were bronchoalveolar lavage (BAL) fluid and biopsy. The degree centrality analysis connoted that “BAL, inflammation, diagnosis” had a high degree of centrality in the 1990s, while “diagnosis, BAL, biopsy, prospective” took centre stage in the 2000s.

Conclusions

The time, area, and theme distribution of the 100 most cited articles on bronchoscopy have been thoroughly analyzed. It is noticeable that researches based on BAL and endobronchial or transbronchial biopsies currently plays a major role.

Enhanced Cellular Uptake and Gene Silencing Activity of Survivin-siRNA via Ultrasound-Mediated Nanobubbles in Lung Cancer Cells

PURPOSE

Paclitaxel is a first-line drug for the therapy of lung cancer, however, drug resistance is a serious limiting factor, related to overexpression of anti-apoptotic proteins like survivin. To overcome this phenomenon, developing novel ultrasound responsive nanobubbles - nanosized drug delivery system- for the delivery of paclitaxel and siRNA in order to silence survivin expression in the presence of ultrasound was aimed.

METHODS

Paclitaxel-carrying nanobubble formulation was obtained by modifying the multistep method. Then, the complex formation of the nanobubbles - paclitaxel formulation with survivin-siRNA, was examined in terms of particle size, polydispersity index, zeta potential, and morphology. Furthermore, siRNA binding and protecting ability, cytotoxicity, cellular uptake, gene silencing, and induction of apoptosis studies were investigated in terms of lung cancer cells.

RESULTS

Developed nanobubbles have particle sizes of 218.9-369.6 nm, zeta potentials of 27-34 mV, were able to protect siRNA from degradation and delivered siRNA into the lung cancer cells. Survivin expression was significantly lower compared with the control groups and enhanced apoptosis was induced by the co-delivery of survivin-siRNA and paclitaxel. Furthermore, significantly higher effects were obtained in the presence of ultrasound induction.

CONCLUSION

The ultrasound responsive nanobubble system carrying paclitaxel and survivin-siRNA is a promising and effective approach against lung cancer cells.

[Current Status and Development of Interventional Techniques for Pulmonary Diseases]

Bronchoscope is the core part of the interventional diagnosis and treatment technology for lung diseases, which has experienced more than 100 years of development history. It has gradually formed a diagnosis and treatment model of pulmonary diseases with cooperation of multi-clinical disciplines, deep integration of interventional minimally invasive techniques, and cross-integration of diversified diagnosis and treatment concepts. This article aimed to review the current status and development of interventional diagnosis and treatment techniques for lung diseases, and introduces the characteristics of the interventional treatment of our center.

Versatile role of curcumin and its derivatives in lung cancer therapy

Lung cancer is a main cause of death all over the world with a high incidence rate. Metastasis into neighboring and distant tissues as well as resistance of cancer cells to chemotherapy demand novel strategies in lung cancer therapy. Curcumin is a naturally occurring nutraceutical compound derived from Curcuma longa (turmeric) that has great pharmacological effects, such as anti-inflammatory, neuroprotective, and antidiabetic. The excellent antitumor activity of curcumin has led to its extensive application in the treatment of various cancers. In the present review, we describe the antitumor activity of curcumin against lung cancer. Curcumin affects different molecular pathways such as vascular endothelial growth factors, nuclear factor-κB (NF-κB), mammalian target of rapamycin, PI3/Akt, microRNAs, and long noncoding RNAs in treatment of lung cancer. Curcumin also can induce autophagy, apoptosis, and cell cycle arrest to reduce the viability and proliferation of lung cancer cells. Notably, curcumin supplementation sensitizes cancer cells to chemotherapy and enhances chemotherapy-mediated apoptosis. Curcumin can elevate the efficacy of radiotherapy in lung cancer therapy by targeting various signaling pathways, such as epidermal growth factor receptor and NF-κB. Curcumin-loaded nanocarriers enhance the bioavailability, cellular uptake, and antitumor activity of curcumin. The aforementioned effects are comprehensively discussed in the current review to further direct studies for applying curcumin in lung cancer therapy.

Applications and strategies in nanodiagnosis and nanotherapy in lung cancer

Lung cancer is the second most common cancer and the leading cause of death in both men and women in the world. Lung cancer is heterogeneous in nature and diagnosis is often at an advanced stage as it develops silently in the lung and is frequently associated with high mortality rates. Despite the advances made in understanding the biology of lung cancer, progress in early diagnosis, cancer therapy modalities and considering the mechanisms of drug resistance, the prognosis and outcome still remains low for many patients. Nanotechnology is one of the fastest growing areas of research that can solve many biological problems such as cancer. A growing number of therapies based on using nanoparticles (NPs) have successfully entered the clinic to treat pain, cancer, and infectious diseases. Recent progress in nanotechnology has been encouraging and directed to developing novel nanoparticles that can be one step ahead of the cancer reducing the possibility of multi-drug resistance. Nanomedicine using NPs is continuingly impacting cancer diagnosis and treatment. Chemotherapy is often associated with limited targeting to the tumor, side effects and low solubility that leads to insufficient drug reaching the tumor. Overcoming these drawbacks of chemotherapy by equipping NPs with theranostic capability which is leading to the development of novel strategies. This review provides a synopsis of current progress in theranostic applications for lung cancer diagnosis and therapy using NPs including liposome, polymeric NPs, quantum dots, gold NPs, dendrimers, carbon nanotubes and magnetic NPs.

Optical simulations for determining efficacy of new light source designs for excitation-scanning high-speed hyperspectral imaging systems

Positive outcomes for colorectal cancer treatment have been linked to early detection. The difficulty in detecting early lesions is the limited contrast with surrounding mucosa and minimal definitive markers to distinguish between hyperplastic and carcinoma lesions. Colorectal cancer is the 3rd leading cancer for incidence and mortality rates which is potentially linked to missed early lesions which allow for increased growth and metastatic potential. One potential technology for early-stage lesion detection is hyperspectral imaging. Traditionally, hyperspectral imaging uses reflectance spectroscopic data to provide a component analysis, per pixel, of an image in fields such as remote sensing, agriculture, food processing and archaeology. This work aims to acquire higher signal-to-noise fluorescence spectroscopic data, harnessing the autofluorescence of tissue, adding a hyperspectral contrast to colorectal cancer detection while maintaining spatial resolution at video-rate speeds. We have previously designed a multi-furcated LED-based spectral light source to prove this concept. Our results demonstrated that the technique is feasible, but the initial prototype has a high light transmission loss (~98%) minimizing spatial resolution and slowing video acquisition. Here, we present updated results in developing an optical ray-tracing model of light source geometries to maximize irradiance throughput for excitation-scanning hyperspectral imaging. Results show combining solid light guide branches have a compounding light loss effect, however, there is potential to minimize light loss through the use of optical claddings. This simulation data will provide the necessary metrics to verify and validate future physical optical components within the hyperspectral endoscopic system for detecting colorectal cancer.

Prognostic and therapeutic significance of circulating tumor cells in patients with lung cancer

BACKGROUND

Lung cancer is the second most common cancer and the main cause of cancer-related mortality worldwide. In spite of various efforts that have been made to facilitate the early diagnosis of lung cancer, most patients are diagnosed when the disease is already in stage IV, which is generally associated with the occurrence of distant metastases and a poor survival. Moreover, a large proportion of these patients will relapse after treatment, heralding the need for the stratification of lung cancer patients in addition to identifying those who are at a higher risk of relapse and, thus, require alternative and/or additional therapies. Recently, circulating tumor cells (CTCs) have been considered as valuable markers for the early diagnosis, prognosis and risk stratification of cancer patients, and they have been found to be able to predict the survival of patients with various types of cancer, including lung cancer. Additionally, the characterization of CTCs has recently provided fascinating insights into the heterogeneity of tumors, which may be instrumental for the development of novel targeted therapies.

CONCLUSIONS

Here we review our current understanding of the significance of CTCs in lung cancer metastasis. We also discuss prominent studies reporting the utility of enumeration and characterization of CTCs in lung cancer patients as prognostic and pharmacodynamic biomarkers for those who are at a higher risk of metastasis and drug resistance.

Role of bronchoscopy in management of central squamous cell lung carcinoma in situ

Squamous cell carcinoma in situ (SCIS) is the pre-invasive stage of squamous cell carcinoma. Early detection and management of SCIS can prevent further progression. Although surgery and external beam radiation therapy are treatment options for SCIS, smaller lesions can be easily managed by bronchoscopic modalities like photodynamic therapy (PDT), cryotherapy, mechanical debulking with biopsy forceps, electrocautery and argon plasma coagulation (APC). Endobronchial brachytherapy (EBBT) and lasers may be judiciously utilized in selected cases. Although, previous studies of treatment modalities may have inadvertently included cases of invasive carcinomas, the advent of new technologies like radial probe endobronchial ultrasound (RP-EBUS) and optical coherence tomography (OCT) can help accurately determine the of depth of invasion. Superficial extent can also be better demarcated with techniques like auto-fluorescence bronchoscopy and narrow band imaging (NBI). New drugs for PDT with deeper penetration and less phototoxicity are being developed. These advances hopefully will allow us to perform superior clinical trials in future and improve our understanding of diagnosis and management of SCIS.

Advances in Interventional Pulmonology

Much has changed since the last review of interventional pulmonology (IP) published in this Clinics series. The rate of development of new techniques and their complexities require IP physicians to be constantly maintaining and updating their skill set. International agreed training pathways help ensure that the interventionalists of the present and future have the required knowledge of anatomy, manual dexterity, and clinical judgment to keep up with the continuing advances that are constantly expanding IP's diagnostic and therapeutic boundaries. IP remains one of the most desirable subspecialities in pulmonology, and the technologic advances make the future an exciting one.

Lung Cancer Screening, Towards a Multidimensional Approach: Why and How?

Early-stage treatment improves prognosis of lung cancer and two large randomized controlled trials have shown that early detection with low-dose computed tomography (LDCT) reduces mortality. Despite this, lung cancer screening (LCS) remains challenging. In the context of a global shortage of radiologists, the high rate of false-positive LDCT results in overloading of existing lung cancer clinics and multidisciplinary teams. Thus, to provide patients with earlier access to life-saving surgical interventions, there is an urgent need to improve LDCT-based LCS and especially to reduce the false-positive rate that plagues the current detection technology. In this context, LCS can be improved in three ways: (1) by refining selection criteria (risk factor assessment), (2) by using Computer Aided Diagnosis (CAD) to make it easier to interpret chest CTs, and (3) by using biological blood signatures for early cancer detection, to both spot the optimal target population and help classify lung nodules. These three main ways of improving LCS are discussed in this review.

Peripheral tumour targeting using open-source virtual bronchoscopy with electromagnetic tracking: a multi-user pre-clinical study

Objectives: The goal was to demonstrate the utility of open-source tracking and visualisation tools in the targeting of lung cancer.Material and methods: The study demonstrates the first deployment of the Anser electromagnetic (EM) tracking system with the CustusX image-guided interventional research platform to navigate using an endobronchial catheter to injected tumour targets. Live animal investigations validated the deployment and targeting of peripheral tumour models using an innovative tumour marking routine.Results: Novel tumour model deployment was successfully achieved at all eight target sites across two live animal investigations without pneumothorax. Virtual bronchoscopy with tracking successfully guided the tracked catheter to 2-12 mm from the target tumour site. Deployment of a novel marker was achieved at all eight sites providing a reliable measure of targeting accuracy. Targeting accuracy within 10 mm was achieved in 7/8 sites and in all cases, the virtual target distance at marker deployment was within the range subsequently measured with x-ray.Conclusions: Endobronchial targeting of peripheral airway targets is feasible using existing open-source technology. Notwithstanding the shortcomings of current commercial platforms, technological improvements in EM tracking and registration accuracy fostered by open-source technology may provide the impetus for widespread clinical uptake of electromagnetic navigation in bronchoscopy.

The clinical usefulness of optical coherence tomography during cancer interventions

INTRODUCTION

Tumor detection and visualization plays a key role in the clinical workflow of a patient with suspected cancer, both in the diagnosis and treatment. Several optical imaging techniques have been evaluated for guidance during oncological interventions. Optical coherence tomography (OCT) is a technique which has been widely evaluated during the past decades. This review aims to determine the clinical usefulness of OCT during cancer interventions focussing on qualitative features, quantitative features and the diagnostic value of OCT.

METHODS

A systematic literature search was performed for articles published before May 2018 using OCT in the field of surgical oncology. Based on these articles, an overview of the clinical usefulness of OCT was provided per tumor type.

RESULTS

A total of 785 articles were revealed by our search, of which a total of 136 original articles were available for analysis, which formed the basis of this review. OCT is currently utilised for both preoperative diagnosis and intraoperative detection of skin, oral, lung, breast, hepatobiliary, gastrointestinal, urological, and gynaecological malignancies. It showed promising results in tumor detection on a microscopic level, especially using higher resolution imaging techniques, such as high-definition OCT and full-field OCT.

CONCLUSION

In the near future, OCT could be used as an additional tool during bronchoscopic or endoscopic interventions and could also be implemented in margin assessment during (laparoscopic) cancer surgery if a laparoscopic or handheld OCT device will be further developed to make routine clinical use possible.

In-vivo Raman spectroscopy: from basics to applications

For more than two decades, Raman spectroscopy has found widespread use in biological and medical applications. The instrumentation and the statistical evaluation procedures have matured, enabling the lengthy transition from ex-vivo demonstration to in-vivo examinations. This transition goes hand-in-hand with many technological developments and tightly bound requirements for a successful implementation in a clinical environment, which are often difficult to assess for novice scientists in the field. This review outlines the required instrumentation and instrumentation parameters, designs, and developments of fiber optic probes for the in-vivo applications in a clinical setting. It aims at providing an overview of contemporary technology and clinical trials and attempts to identify future developments necessary to bring the emerging technology to the clinical end users. A comprehensive overview of in-vivo applications of fiber optic Raman probes to characterize different tissue and disease types is also given.

Enhanced recovery after thoracic surgery: patient information and care-plans

Many studies have confirmed that the implementation of enhanced recovery after surgery (ERAS) protocols has the advantages of reducing the potential complications after thoracic surgery and the length of hospital stay. The ERAS program involves a multidisciplinary team, aimed at integrating evidence-based knowledge into clinical practice in order to reduce the patient's stress response to the surgical procedure and improve the response to stress, guaranteeing a combination of better outcomes and cost savings. All this would not be possible without the improvement of minimally invasive surgical techniques, progression of anesthesia, pain control, and careful patient preparation. In this setting, a preoperative personal counselling may play a key role to reduce stress, fear or anxiety and improve the morbidity of patients, enabling them to achieve functional and psychological compensatory mechanisms more quickly. Preoperative patient counselling, performed using verbal, written or multimedia materials, is crucial in order to achieve the goal of the ERAS project: making the patient a potentially active participant and the main character of his recovery, able to positively impact himself throughout the surgical and healing process. This report is aimed at evaluating patient information and care-plans in thoracic surgery, reviewing the available evidence on ERAS pathways, and demonstrating our ideal program as discussed and shared among the Italian Thoracic Surgery Units accredited in the video-assisted thoracic surgery (VATS) group.

The technique of endoscopic airway tumor treatment

More than half of primary lung cancers are not resectable at diagnosis and 40% of deaths may be secondary to loco-regional disease. Many of these patients suffer from symptoms related to airways obstruction. Indications for therapeutic endoscopic treatment are palliation of dyspnea and other obstructive symptoms in advanced cancerous lesions and cure of early lung cancer. Bronchoscopic management is also indicated for all those patients suffering from benign or minimally invasive neoplasm who are not suitable for surgery due to their clinical conditions. Clinicians should select cases, evaluating tumor features (size, location) and patient characteristics (age, lung function impairment) to choose the most appropriate endoscopic technique. Laser therapy, electrocautery, cryotherapy and stenting are well-described techniques for the palliation of symptoms due to airway involvement and local treatment of endobronchial lesions. Newer technologies, with an established role in clinical practice, are endobronchial ultrasound (EBUS), autofluorescence bronchoscopy (AFB), and narrow band imaging (NBI). Other techniques, such as endobronchial intra-tumoral chemotherapy (EITC), EBUS-guided-transbronchial needle injection or bronchoscopy-guided radiofrequency ablation (RFA), are in development for the use within the airways. These endobronchial interventions are important adjuncts in the multimodality management of lung cancer and should become standard considerations in the management of patients with advanced lung cancer, benign or otherwise not approachable central airway lesions. We aimed at revising several endobronchial treatment modalities that can augment standard antitumor therapies for advanced lung cancer, including rigid and flexible bronchoscopy, laser therapy, endobronchial prosthesis, and photodynamic therapy (PDT).