Solitary pulmonary nodule imaging approaches and the role of optical fibre-based technologies

Peripheral pulmonary lesion: novel approaches in endoscopic guidance systems and a state-of-the-art review

Diagnosis of peripheral pulmonary lesion (PPL) is the most challenging field in bronchoscopy and interventional pulmonology, which concerns early lung cancer diagnosis. Despite novel techniques and new approaches to the periphery of the lung, almost 25% of PPLs remain undiagnosed. Bronchoscopy with guide systems, virtual and/or electromagnetic navigation, robotic bronchoscopy, and transparenchymal nodule approaches tend to provide a higher percentage of reaching the lesion, but the diagnostic yield rarely exceeds 75%, regardless of the instruments used. Further studies are needed to evaluate what the main constraints of this discrepancy are and if a combined use of these techniques and instruments can provide an increased diagnostic yield.

Utility of Raman Spectroscopy in Pulmonary Medicine

The Raman effect, or as per its original description, "modified scattering", is an observation that the number of scattered light waves shifts after photons make nonelastic contact with a molecule. This effect allows Raman spectroscopy to be very useful in various fields. Although it is well known that Raman spectroscopy could be very beneficial in medicine as a diagnostic tool, there are not many applications of Raman spectroscopy in pulmonary medicine. Mostly tumor tissue, sputum and saliva have been used as material for analysis in respiratory medicine. Raman spectroscopy has shown promising results in malignancy recognition and even tumor staging. Saliva is a biological fluid that could be used as a reliable biomarker of the physiological state of the human body, and is easily acquired. Saliva analysis using Raman spectroscopy has the potential to be a relatively inexpensive and quick tool that could be used for diagnostic, screening and phenotyping purposes. Chronic obstructive pulmonary disease (COPD) is a growing cause of disability and death, and its phenotyping using saliva analysis via Raman spectroscopy has a great potential to be a dependable tool to, among other things, help reduce hospitalizations and disease burden. Although existing methods are effective and generally available, Raman spectroscopy has the benefit of being quick and noninvasive, potentially reducing healthcare costs and workload.

Fluorescent covalent organic frameworks - promising bioimaging materials

Fluorescent covalent organic frameworks (COFs) have emerged as promising candidates for imaging living cells due to their unique properties and adjustable fluorescence. In this mini-review, we provide an overview of recent advancements in fluorescent COFs for bioimaging applications. We discuss the strategies used to design COFs with desirable properties such as high photostability, excellent biocompatibility, and pH sensitivity. Additionally, we explore the various ways in which fluorescent COFs are utilized in bioimaging, including cellular imaging, targeting specific organelles, and tracking biomolecules. We delve into their applications in sensing intracellular pH, reactive oxygen species (ROS), and specific biomarkers. Furthermore, we examine how functionalization techniques enhance the targeting and imaging capabilities of fluorescent COFs. Finally, we discuss the challenges and prospects in the field of fluorescent COFs for bioimaging in living cells, urging further research in this exciting area.

Applications of machine learning in time-domain fluorescence lifetime imaging: a review

Many medical imaging modalities have benefited from recent advances in Machine Learning (ML), specifically in deep learning, such as neural networks. Computers can be trained to investigate and enhance medical imaging methods without using valuable human resources. In recent years, Fluorescence Lifetime Imaging (FLIm) has received increasing attention from the ML community. FLIm goes beyond conventional spectral imaging, providing additional lifetime information, and could lead to optical histopathology supporting real-time diagnostics. However, most current studies do not use the full potential of machine/deep learning models. As a developing image modality, FLIm data are not easily obtainable, which, coupled with an absence of standardisation, is pushing back the research to develop models which could advance automated diagnosis and help promote FLIm. In this paper, we describe recent developments that improve FLIm image quality, specifically time-domain systems, and we summarise sensing, signal-to-noise analysis and the advances in registration and low-level tracking. We review the two main applications of ML for FLIm: lifetime estimation and image analysis through classification and segmentation. We suggest a course of action to improve the quality of ML studies applied to FLIm. Our final goal is to promote FLIm and attract more ML practitioners to explore the potential of lifetime imaging.

The role of confocal laser endomicroscopy in pulmonary medicine

Accurate diagnosis and subsequent therapeutic options in pulmonary diseases mainly rely on imaging methods and histological assessment. However, imaging examinations are hampered by the limited spatial resolution of images and most procedures that are related to histological assessment are invasive with associated complications. As a result, a high-resolution imaging technology - confocal laser endomicroscopy (CLE), which is at the forefront and enables real-time microscopic visualisation of the morphologies and architectures of tissues or cells - has been developed to resolve the clinical dilemma pertaining to current techniques. The current evidence has shown that CLE has the potential to facilitate advanced diagnostic capabilities, to monitor and to aid the tailored treatment regime for patients with pulmonary diseases, as well as to expand the horizon for unravelling the mechanism and therapeutic targets of pulmonary diseases. In the future, if CLE can be combined with artificial intelligence, early, rapid and accurate diagnosis will be achieved through identifying the images automatically. As promising as this technique may be, further investigations are required before it can enter routine clinical practice.

Mid-Infrared Imaging Characterization to Differentiate Lung Cancer Subtypes

Introduction: Lung cancer is the most common malignancy worldwide. Squamous cell carcinoma (SQ) and adenocarcinoma (LUAD) are the two most frequent histological subtypes. Small cell carcinoma (SCLC) subtype has the worst prognosis. Differential diagnosis is essential for proper oncological treatment. Life science associated mid- and near-infrared based microscopic techniques have been developed exponentially, especially in the past decade. Vibrational spectroscopy is a potential non-destructive approach to investigate malignancies.

Aims: Our goal was to differentiate lung cancer subtypes by their label-free mid-infrared spectra using supervised multivariate analyses.

Material and Methods: Formalin-fixed paraffin-embedded (FFPE) samples were selected from the archives. Three subtypes were selected for each group: 10-10 cases SQ, LUAD and SCLC. 2 μm thick sections were cut and laid on aluminium coated glass slides. Transflection optical setup was applied on Perkin-Elmer infrared microscope. 250 × 600 μm areas were imaged and the so-called mid-infrared fingerprint region (1800-648cm⁻¹) was further analysed with linear discriminant analysis (LDA) and support vector machine (SVM) methods.

Results: Both “patient-based” and “pixel-based” approaches were examined. Patient-based analysis by using 3 LDA models and 2 SVM models resulted in different separations. The higher the cut-off value the lower is the accuracy. The linear C-support vector classification (C-SVC) SVM resulted in the best (100%) accuracy for the three subtypes using a 50% cut-off value. The pixel-based analysis gave, similarly, the linear C-SVC SVM model to be the most efficient in the statistical indicators (SQ sensitivity 81.65%, LUAD sensitivity 82.89% and SCLC sensitivity 88.89%). The spectra cut-off, the kernel function and the algorithm function influence the accuracy.

Conclusion: Mid-Infrared imaging could be used to differentiate FFPE lung cancer subtypes. Supervised multivariate tools are promising to accurately separate lung tumor subtypes. The long-term perspective is to develop a spectroscopy-based diagnostic tool, revolutionizing medical differential diagnostics, especially cancer identification.

Targeted detection of cancer cells during biopsy allows real-time diagnosis of pulmonary nodules

Background

The diagnostic yield of biopsies of solitary pulmonary nodules (SPNs) is low, particularly in sub-solid lesions. We developed a method (NIR-nCLE) to achieve cellular level cancer detection during biopsy by integrating (i) near-infrared (NIR) imaging using a cancer-targeted tracer (pafolacianine), and (ii) a flexible NIR confocal laser endomicroscopy (CLE) system that can fit within a biopsy needle. Our goal was to assess the diagnostic accuracy of NIR-nCLE ex vivo in SPNs.

Methods

Twenty patients with SPNs were preoperatively infused with pafolacianine. Following resection, specimens were inspected to identify the lesion of interest. NIR-nCLE imaging followed by tissue biopsy was performed within the lesion and in normal lung tissue. All imaging sequences (n = 115) were scored by 5 blinded raters on the presence of fluorescent cancer cells and compared to diagnoses by a thoracic pathologist.

Results

Most lesions (n = 15, 71%) were adenocarcinoma-spectrum malignancies, including 7 ground glass opacities (33%). Mean fluorescence intensity (MFI) by NIR-nCLE for tumor biopsy was 20.6 arbitrary units (A.U.) and mean MFI for normal lung was 6.4 A.U. (p < 0.001). Receiver operating characteristic analysis yielded a high area under the curve for MFI (AUC = 0.951). Blinded raters scored the NIR-nCLE sequences on the presence of fluorescent cancer cells with sensitivity and specificity of 98% and 97%, respectively. Overall diagnostic accuracy was 97%. The inter-observer agreement of the five raters was excellent (κ = 0.95).

Conclusions

NIR-nCLE allows sensitive and specific detection of cancer cells in SPNs. This technology has far-reaching implications for diagnostic needle biopsies and intraprocedural decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-022-05868-9.

Contemporary Concise Review 2021: Pulmonary nodules from detection to intervention

The US Preventive Task Force (USPSTF) has updated screening criteria by expanding age range and reducing smoking history required for eligibility; the International Lung Screen Trial (ILST) data have shown that PLCOM2012 performs better for eligibility than USPSTF criteria. Screening adherence is low (4%-6% of potential eligible candidates in the United States) and depends upon multiple system and patient/candidate-related factors. Smoking cessation in lung cancer improves survival (past prospective trial data, updated meta-analysis data); smoking cessation is an essential component of lung cancer screening. Circulating biomarkers are emerging to optimize screening and early diagnosis. COVID-19 continues to affect lung cancer treatment and screening through delays and disruptions; specific operational challenges need to be met. Over 70% of suspected malignant lesions develop in the periphery of the lungs. Bronchoscopic navigational techniques have been steadily improving to allow greater accuracy with target lesion approximation and therefore diagnostic yield. Fibre-based imaging techniques provide real-time microscopic tumour visualization, with potential diagnostic benefits. With significant advances in peripheral lung cancer localization, bronchoscopically delivered ablative therapies are an emerging field in limited stage primary and oligometastatic disease. In advanced stage lung cancer, small-volume samples acquired through bronchoscopic techniques yield material of sufficient quantity and quality to support clinically relevant biomarker assessment.

Targeted detection of cancer at the cellular level during biopsy by near-infrared confocal laser endomicroscopy

Suspicious nodules detected by radiography are often investigated by biopsy, but the diagnostic yield of biopsies of small nodules is poor. Here we report a method-NIR-nCLE-to detect cancer at the cellular level in real-time during biopsy. This technology integrates a cancer-targeted near-infrared (NIR) tracer with a needle-based confocal laser endomicroscopy (nCLE) system modified to detect NIR signal. We develop and test NIR-nCLE in preclinical models of pulmonary nodule biopsy including human specimens. We find that the technology has the resolution to identify a single cancer cell among normal fibroblast cells when co-cultured at a ratio of 1:1000, and can detect cancer cells in human tumors less than 2 cm in diameter. The NIR-nCLE technology rapidly delivers images that permit accurate discrimination between tumor and normal tissue by non-experts. This proof-of-concept study analyzes pulmonary nodules as a test case, but the results may be generalizable to other malignancies.

Fibroblast Activation Protein Specific Optical Imaging in Non-Small Cell Lung Cancer

Fibroblast activation protein (FAP) is a cell surface propyl-specific serine protease involved in the regulation of extracellular matrix. Whilst expressed at low levels in healthy tissue, upregulation of FAP on fibroblasts can be found in several solid organ malignancies, including non-small cell lung cancer, and chronic inflammatory conditions such as pulmonary fibrosis and rheumatoid arthritis. Their full role remains unclear, but FAP expressing cancer associated fibroblasts (CAFs) have been found to relate to a poor prognosis with worse survival rates in breast, colorectal, pancreatic, and non-small cell lung cancer (NSCLC). Optical imaging using a FAP specific chemical probe, when combined with clinically compatible imaging systems, can provide a readout of FAP activity which could allow disease monitoring, prognostication and potentially stratify therapy. However, to derive a specific signal for FAP any sequence must retain specificity over closely related endopeptidases, such as prolyl endopeptidase (PREP), and be resistant to degradation in areas of active inflammation. We describe the iterative development of a FAP optical reporter sequence which retains FAP specificity, confers resistance to degradation in the presence of activated neutrophil proteases and demonstrates clinical tractability ex vivo in NSCLC samples with an imaging platform.

Advanced bronchoscopic techniques for the diagnosis and treatment of peripheral lung cancer

Lung cancer is the leading cause of cancer related deaths worldwide. As a result of the increasing use of chest CT scans and lung cancer screening initiatives, there is a rapidly increasing need for lung lesion analysis and - in case of confirmed cancer - treatment. A desirable future concept is the one-stop outpatient bronchoscopic approach including navigation to the tumor, malignancy confirmation and immediate treatment. Several novel bronchoscopic diagnostic and treatment concepts are currently under evaluation contributing to this concept. As the majority of suspected malignant lung lesions develop in the periphery of the lungs, improved bronchoscopic navigation to the target lesion is of key importance. Fortunately, the field of interventional pulmonology is evolving rapidly and several advanced bronchoscopic navigation techniques are clinically available, allowing an increasingly accurate tissue diagnosis of peripheral lung lesions. Additionally, multiple bronchoscopic treatment modalities are currently under investigation. This review will provide a concise overview of advanced bronchoscopic techniques to diagnose and treat peripheral lung cancer by describing their working mechanisms, strengths and weaknesses, identifying knowledge gaps and indicating future developments. The desired one-step concept of bronchoscopic 'diagnose and treat' peripheral lung cancer is on the horizon.

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.