Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

Human cancers exhibit strong phenotypic differences that can be visualized noninvasively by medical imaging. Radiomics refers to the comprehensive quantification of tumour phenotypes by applying a large number of quantitative image features. Here we present a radiomic analysis of 440 features quantifying tumour image intensity, shape and texture, which are extracted from computed tomography data of 1,019 patients with lung or head-and-neck cancer. We find that a large number of radiomic features have prognostic power in independent data sets of lung and head-and-neck cancer patients, many of which were not identified as significant before. Radiogenomics analysis reveals that a prognostic radiomic signature, capturing intratumour heterogeneity, is associated with underlying gene-expression patterns. These data suggest that radiomics identifies a general prognostic phenotype existing in both lung and head-and-neck cancer. This may have a clinical impact as imaging is routinely used in clinical practice, providing an unprecedented opportunity to improve decision-support in cancer treatment at low cost

The diagnostic value of narrow-band imaging for early and invasive lung cancer: a meta-analysis

This study aimed to compare the ability of narrow-band imaging to detect early and invasive lung cancer with that of conventional pathological analysis and white-light bronchoscopy. We searched the PubMed, EMBASE, Sinomed, and China National Knowledge Infrastructure databases for relevant studies. Meta-disc software was used to perform data analysis, meta-regression analysis, sensitivity analysis, and heterogeneity testing, and STATA software was used to determine if publication bias was present, as well as to calculate the relative risks for the sensitivity and specificity of narrow-band imaging vs those of white-light bronchoscopy for the detection of early and invasive lung cancer. A random-effects model was used to assess the diagnostic efficacy of the above modalities in cases in which a high degree of between-study heterogeneity was noted with respect to their diagnostic efficacies. The database search identified six studies including 578 patients. The pooled sensitivity and specificity of narrow-band imaging were 86% (95% confidence interval: 83-88%) and 81% (95% confidence interval: 77-84%), respectively, and the pooled sensitivity and specificity of white-light bronchoscopy were 70% (95% confidence interval: 66-74%) and 66% (95% confidence interval: 62-70%), respectively. The pooled relative risks for the sensitivity and specificity of narrow-band imaging vs the sensitivity and specificity of white-light bronchoscopy for the detection of early and invasive lung cancer were 1.33 (95% confidence interval: 1.07-1.67) and 1.09 (95% confidence interval: 0.84-1.42), respectively, and sensitivity analysis showed that narrow-band imaging exhibited good diagnostic efficacy with respect to detecting early and invasive lung cancer and that the results of the study were stable. Narrow-band imaging was superior to white light bronchoscopy with respect to detecting early and invasive lung cancer; however, the specificities of the two modalities did not differ significantly

PM2.5 Exposure in the Respiratory System Induces Distinct Inflammatory Signaling in the Lung and the Liver of Mice

Fine particulate matter 2.5 (PM2.5) is a harmful air pollutant currently threatening public health. Although many studies have been performed on the general negative effects of PM2.5 in mice and humans, the migration patterns of various immune cells in response to PM2.5 exposure remain unclear. In this study, we aimed to investigate the immune cell migratory response in the lung and the liver of intratracheally PM2.5-inoculated mice. To investigate the migration trajectory of immune cells in the lung and the liver tissues of mice, we employed microscopic tools including two-photon intravital imaging, histological analysis, and transmission electron microscopy. Our data from two-photon intravital imaging showed that there was no significant difference in the number of infiltrated neutrophils in the lung and the liver of PM2.5-treated mice, compared to the nontreated condition. However, from the histological analysis and the transmission electron microscopy after vascular perfusion to remove intravascular leukocytes, we observed that some leukocytes were frequently observed in the lung and the liver of PM2.5-treated mice. Interestingly, quantification of leukocyte population using flow cytometry showed significant increase of neutrophils and macrophages in the lung, but not much in the liver, 24 h post-PM2.5 treatment. These data imply that two-photon intravital imaging of the lung and the liver actually visualized neutrophils, which were adherent to the luminal side of the vasculature. We then conducted mRNA microarray analysis to further observe how PM2.5 affects gene expression patterns in the lung and the liver. PM2.5 treatment changed the mRNA expression associated with the IL-17 signaling pathway in the lung and changed the mRNA expression associated with metabolic pathways in the liver. In summary, these results suggest that the immune response in the lung is distinctly regulated from that in the liver under acute PM2.5-induced inflammation and that these organs consequently are regulated via distinct signaling pathways.ope

Radiomics for Response and Outcome Assessment for Non-Small Cell Lung Cancer.

Routine follow-up visits and radiographic imaging are required for outcome evaluation and tumor recurrence monitoring. Yet more personalized surveillance is required in order to sufficiently address the nature of heterogeneity in nonsmall cell lung cancer and possible recurrences upon completion of treatment. Radiomics, an emerging noninvasive technology using medical imaging analysis and data mining methodology, has been adopted to the area of cancer diagnostics in recent years. Its potential application in response assessment for cancer treatment has also drawn considerable attention. Radiomics seeks to extract a large amount of valuable information from patients' medical images (both pretreatment and follow-up images) and quantitatively correlate image features with diagnostic and therapeutic outcomes. Radiomics relies on computers to identify and analyze vast amounts of quantitative image features that were previously overlooked, unmanageable, or failed to be identified (and recorded) by human eyes. The research area has been focusing on the predictive accuracy of pretreatment features for outcome and response and the early discovery of signs of tumor response, recurrence, distant metastasis, radiation-induced lung injury, death, and other outcomes, respectively. This review summarized the application of radiomics in response assessments in radiotherapy and chemotherapy for non-small cell lung cancer, including image acquisition/reconstruction, region of interest definition/segmentation, feature extraction, and feature selection and classification. The literature search for references of this article includes PubMed peer-reviewed publications over the last 10 years on the topics of radiomics, textural features, radiotherapy, chemotherapy, lung cancer, and response assessment. Summary tables of radiomics in response assessment and treatment outcome prediction in radiation oncology have been developed based on the comprehensive review of the literature

Spatial and temporal changes in extracellular elastin and laminin distribution during lung alveolar development

Lung alveolarization requires precise coordination of cell growth with extracellular matrix (ECM) synthesis and deposition. The role of extracellular matrices in alveogenesis is not fully understood, because prior knowledge is largely extrapolated from two-dimensional structural analysis. Herein, we studied temporospatial changes of two important ECM proteins, laminin and elastin that are tightly associated with alveolar capillary growth and lung elastic recoil respectively, during both mouse and human lung alveolarization. By combining protein immunofluorescence staining with two- and three-dimensional imaging, we found that the laminin network was simplified along with the thinning of septal walls during alveogenesis, and more tightly associated with alveolar endothelial cells in matured lung. In contrast, elastin fibers were initially localized to the saccular openings of nascent alveoli, forming a ring-like structure. Then, throughout alveolar growth, the number of such alveolar mouth ring-like structures increased, while the relative ring size decreased. These rings were interconnected via additional elastin fibers. The apparent patches and dots of elastin at the tips of alveolar septae found in two-dimensional images were cross sections of elastin ring fibers in the three-dimension. Thus, the previous concept that deposition of elastin at alveolar tips drives septal inward growth may potentially be conceptually challenged by our data

An automated system for lung nodule detection in low-dose computed tomography

A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 Italian project. One of the main goals of this project is to build a distributed database of lung CT scans in order to enable automated image analysis through a data and cpu GRID infrastructure. The basic modules of our lung-CAD system, a dot-enhancement filter for nodule candidate selection and a neural classifier for false-positive finding reduction, are described. The system was designed and tested for both internal and sub-pleural nodules. The results obtained on the collected database of low-dose thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.Comment: 9 pages, 9 figures; Proceedings of the SPIE Medical Imaging Conference, 17-22 February 2007, San Diego, California, USA, Vol. 6514, 65143

Mass spectrometry imaging of levofloxacin distribution in TB-infected pulmonary lesions by MALDI-MSI and continuous liquid microjunction surface sampling

A multi-modal mass spectrometry imaging (MSI) and profiling approach has been applied to assess the partitioning of the anti-TB fluoroquinolone levofloxacin into pulmonary lesions. Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) and a commercial liquid microjunction surface sampling technology (LMJ-SSP), or flowprobe, have been used to both spatially profile and image drug distributions in lung tissue sections from TB-infected rabbits following oral administration of a single human-equivalent dose., Levofloxacin levels were highest at 6 h post-dose in normal lung, cellular granuloma, and necrotic caseum compartments. The drug accumulated in the cellular granuloma regions with lower amounts partitioning into central caseous compartments. Flowprobe imaging at 630 μm (limited by the probe tip diameter) enabled visualization of drug distribution into lesion compartments, including limited differentiation of relative drug abundance in cellular versus caseous regions of the lesions., MALDI-MSI analysis at 75 μm provided more detailed drug distribution, which clearly accumulated in the cellular region immediately surrounding the central caseum core. Imaging and profiling data acquired by flowprobe and MALDI-MSI were validated by quantitative LC/MS/MS analysis of lung and granuloma homogenates taken from the same animals., The results of the investigation show flowprobe imaging and sampling as a rapid and sensitive alternative to MALDI-MSI for profiling drug distributions into tissues when spatial resolution of data below the threshold of the probe diameter is not required

Application of a high-content screening assay utilising primary human lung fibroblasts to identify antifibrotic drugs for rapid repurposing in COVID-19 patients

Lung imaging and autopsy reports among COVID-19 patients show elevated lung scarring (fibrosis). Early data from COVID-19 patients as well as previous studies from severe acute respiratory syndrome, Middle East respiratory syndrome, and other respiratory disorders show that the extent of lung fibrosis is associated with a higher mortality, prolonged ventilator dependence, and poorer long-term health prognosis. Current treatments to halt or reverse lung fibrosis are limited; thus, the rapid development of effective antifibrotic therapies is a major global medical need that will continue far beyond the current COVID-19 pandemic. Reproducible fibrosis screening assays with high signal-to-noise ratios and disease-relevant readouts such as extracellular matrix (ECM) deposition (the hallmark of fibrosis) are integral to any antifibrotic therapeutic development. Therefore, we have established an automated high-throughput and high-content primary screening assay measuring transforming growth factor-β (TGFβ)-induced ECM deposition from primary human lung fibroblasts in a 384-well format. This assay combines longitudinal live cell imaging with multiparametric high-content analysis of ECM deposition. Using this assay, we have screened a library of 2743 small molecules representing approved drugs and late-stage clinical candidates. Confirmed hits were subsequently profiled through a suite of secondary lung fibroblast phenotypic screening assays quantifying cell differentiation, proliferation, migration, and apoptosis. In silico target prediction and pathway network analysis were applied to the confirmed hits. We anticipate this suite of assays and data analysis tools will aid the identification of new treatments to mitigate against lung fibrosis associated with COVID-19 and other fibrotic diseases

Clinical translation of [18F]ICMT-11 for measuring chemotherapy-induced caspase 3/7 activation in breast and lung cancer

Background: Effective anticancer therapy is thought to involve induction of tumour cell death through apoptosis and/or necrosis. [18F]ICMT-11, an isatin sulfonamide caspase-3/7-specific radiotracer, has been developed for PET imaging and shown to have favourable dosimetry, safety, and biodistribution. We report the translation of [18F]ICMT-11 PET to measure chemotherapy-induced caspase-3/7 activation in breast and lung cancer patients receiving first-line therapy. Results: Breast tumour SUVmax of [18F]ICMT-11 was low at baseline and unchanged following therapy. Measurement of M30/M60 cytokeratin-18 cleavage products showed that therapy was predominantly not apoptosis in nature. While increases in caspase-3 staining on breast histology were seen, post-treatment caspase-3 positivity values were only approximately 1%; this low level of caspase-3 could have limited sensitive detection by [18F]ICMT-11-PET. Fourteen out of 15 breast cancer patients responded to first–line chemotherapy (complete or partial response); one patient had stable disease. Four patients showed increases in regions of high tumour [18F]ICMT-11 intensity on voxel-wise analysis of tumour data (classed as PADS); response was not exclusive to patients with this phenotype. In patients with lung cancer, multi-parametric [18F]ICMT-11 PET and MRI (diffusion-weighted- and dynamic contrast enhanced-MRI) showed that PET changes were concordant with cell death in the absence of significant perfusion changes. Conclusion: This study highlights the potential use of [18F]ICMT-11 PET as a promising candidate for non-invasive imaging of caspase3/7 activation, and the difficulties encountered in assessing early-treatment responses. We summarize that tumour response could occur in the absence of predominant chemotherapy-induced caspase-3/7 activation measured non-invasively across entire tumour lesions in patients with breast and lung cancer