MRI and CT lung biomarkers: Towards an in vivo understanding of lung biomechanics

Use of Quantitative CT Imaging to Identify Bronchial Thermoplasty Responders

BACKGROUND

Bronchial thermoplasty (BT) is a treatment for patients with poorly controlled, severe asthma. However, predictors of treatment response to BT are defined poorly.

RESEARCH QUESTION

Do baseline radiographic and clinical characteristics exist that predict response to BT?

STUDY DESIGN AND METHODS

We conducted a longitudinal prospective cohort study of participants with severe asthma receiving BT across eight academic medical centers. Participants received three separate BT treatments and were monitored at 3-month intervals for 1 year after BT. Similar to prior studies, a positive response to BT was defined as either improvement in Asthma Control Test results of ≥ 3 or Asthma Quality of Life Questionnaire of ≥ 0.5. Regression analyses were used to evaluate the association between pretreatment clinical and quantitative CT scan measures with subsequent BT response.

RESULTS

From 2006 through 2017, 88 participants received BT, with 70 participants (79.5%) identified as responders by Asthma Control Test or Asthma Quality of Life Questionnaire criteria. Responders were less likely to undergo an asthma-related ICU admission in the prior year (3% vs 25%; P = .01). On baseline quantitative CT imaging, BT responders showed less air trapping percentage (OR, 0.90; 95% CI, 0.82-0.99; P = .03), a greater Jacobian determinant (OR, 1.49; 95% CI, 1.05-2.11), greater SD of the Jacobian determinant (OR, 1.84; 95% CI, 1.04-3.26), and greater anisotropic deformation index (OR, 3.06; 95% CI, 1.06-8.86).

INTERPRETATION

To our knowledge, this is the largest study to evaluate baseline quantitative CT imaging and clinical characteristics associated with BT response. Our results show that preservation of normal lung expansion, indicated by less air trapping, a greater magnitude of isotropic expansion, and greater within-lung spatial variation on quantitative CT imaging, were predictors of future BT response.

TRIAL REGISTRY

ClinicalTrials.gov; No.: NCT01185275; URL: www.

CLINICALTRIALS

gov.

Biomarkers: Promising and valuable tools towards diagnosis, prognosis and treatment of Covid-19 and other diseases

The use of biomarkers as early warning systems in the evaluation of disease risk has increased markedly in the last decade. Biomarkers are indicators of typical biological processes, pathogenic processes, or pharmacological reactions to therapy. The application and identification of biomarkers in the medical and clinical fields have an enormous impact on society. In this review, we discuss the history, various definitions, classifications, characteristics, and discovery of biomarkers. Furthermore, the potential application of biomarkers in the diagnosis, prognosis, and treatment of various diseases over the last decade are reviewed. The present review aims to inspire readers to explore new avenues in biomarker research and development.

Lung function measurements in preclinical research: What has been done and where is it headed?

Due to the close interaction of lung morphology and functions, repeatable measurements of pulmonary function during longitudinal studies on lung pathophysiology and treatment efficacy have been a great area of interest for lung researchers. Spirometry, as a simple and quick procedure that depends on the maximal inspiration of the patient, is the most common lung function test in clinics that measures lung volumes against time. Similarly, in the preclinical area, plethysmography techniques offer lung functional parameters related to lung volumes. In the past few decades, many innovative techniques have been introduced for in vivo lung function measurements, while each one of these techniques has their own advantages and disadvantages. Before each experiment, depending on the sensitivity of the required pulmonary functional parameters, it should be decided whether an invasive or non-invasive approach is desired. On one hand, invasive techniques offer sensitive and specific readouts related to lung mechanics in anesthetized and tracheotomized animals at endpoints. On the other hand, non-invasive techniques allow repeatable lung function measurements in conscious, free-breathing animals with readouts related to the lung volumes. The biggest disadvantage of these standard techniques for lung function measurements is considering the lung as a single unit and providing only global readouts. However, recent advances in lung imaging modalities such as x-ray computed tomography and magnetic resonance imaging opened new doors toward obtaining both anatomical and functional information from the same scan session, without the requirement for any extra pulmonary functional measurements, in more regional and non-invasive manners. Consequently, a new field of study called pulmonary functional imaging was born which focuses on introducing new techniques for regional quantification of lung function non-invasively using imaging-based techniques. This narrative review provides first an overview of both invasive and non-invasive conventional methods for lung function measurements, mostly focused on small animals for preclinical research, including discussions about their advantages and disadvantages. Then, we focus on those newly developed, non-invasive, imaging-based techniques that can provide either global or regional lung functional readouts at multiple time-points.

Computed tomography-identified phenotypes of small airway obstructions in chronic obstructive pulmonary disease

ABSTRACT

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease characteristic of small airway inflammation, obstruction, and emphysema. It is well known that spirometry alone cannot differentiate each separate component. Computed tomography (CT) is widely used to determine the extent of emphysema and small airway involvement in COPD. Compared with the pulmonary function test, small airway CT phenotypes can accurately reflect disease severity in patients with COPD, which is conducive to improving the prognosis of this disease. CT measurement of central airway morphology has been applied in clinical, epidemiologic, and genetic investigations as an inference of the presence and severity of small airway disease. This review will focus on presenting the current knowledge and methodologies in chest CT that aid in identifying discrete COPD phenotypes.

Quantitative CT metrics are associated with longitudinal lung function decline and future asthma exacerbations: Results from SARP-3

BACKGROUND

Currently, there is limited knowledge regarding which imaging assessments of asthma are associated with accelerated longitudinal decline in lung function.

OBJECTIVES

We aimed to assess whether quantitative computed tomography (qCT) metrics are associated with longitudinal decline in lung function and morbidity in asthma.

METHODS

We analyzed 205 qCT scans of adult patients with asthma and calculated baseline markers of airway remodeling, lung density, and pointwise regional change in lung volume (Jacobian measures) for each participant. Using multivariable regression models, we then assessed the association of qCT measurements with the outcomes of future change in lung function, future exacerbation rate, and changes in validated measurements of morbidity.

RESULTS

Greater baseline wall area percent (β = -0.15 [95% CI = -0.26 to -0.05]; P < .01), hyperinflation percent (β = -0.25 [95% CI = -0.41 to -0.09]; P < .01), and Jacobian gradient measurements (cranial-caudal β = 10.64 [95% CI = 3.79-17.49]; P < .01; posterior-anterior β = -9.14, [95% CI = -15.49 to -2.78]; P < .01) were associated with more severe future lung function decline. Additionally, greater wall area percent (rate ratio = 1.06 [95% CI = 1.01-1.10]; P = .02) and air trapping percent (rate ratio =1.01 [95% CI = 1.00-1.02]; P = .03), as well as lower decline in the Jacobian determinant mean (rate ratio = 0.58 [95% CI = 0.41-0.82]; P < .01) and Jacobian determinant standard deviation (rate ratio = 0.52 [95% CI = 0.32-0.85]; P = .01), were associated with a greater rate of future exacerbations. However, imaging metrics were not associated with clinically meaningful changes in scores on validated asthma morbidity questionnaires.

CONCLUSIONS

Baseline qCT measures of more severe airway remodeling, more small airway disease and hyperinflation, and less pointwise regional change in lung volumes were associated with future lung function decline and asthma exacerbations.

Imaging Biomarkers in Animal Models of Drug-Induced Lung Injury: A Systematic Review

For drug-induced interstitial lung disease (DIILD) translational imaging biomarkers are needed to improve detection and management of lung injury and drug-toxicity. Literature was reviewed on animal models in which in vivo imaging was used to detect and assess lung lesions that resembled pathological changes found in DIILD, such as inflammation and fibrosis. A systematic search was carried out using three databases with key words “Animal models”, “Imaging”, “Lung disease”, and “Drugs”. A total of 5749 articles were found, and, based on inclusion criteria, 284 papers were selected for final data extraction, resulting in 182 out of the 284 papers, based on eligibility. Twelve different animal species occurred and nine various imaging modalities were used, with two-thirds of the studies being longitudinal. The inducing agents and exposure (dose and duration) differed from non-physiological to clinically relevant doses. The majority of studies reported other biomarkers and/or histological confirmation of the imaging results. Summary of radiotracers and examples of imaging biomarkers were summarized, and the types of animal models and the most used imaging modalities and applications are discussed in this review. Pathologies resembling DIILD, such as inflammation and fibrosis, were described in many papers, but only a few explicitly addressed drug-induced toxicity experiments.

Pulmonary Ventilation Maps Generated with Free-breathing Proton MRI and a Deep Convolutional Neural Network

Background Hyperpolarized noble gas MRI helps measure lung ventilation, but clinical translation remains limited. Free-breathing proton MRI may help quantify lung function using existing MRI systems without contrast material and may assist in providing information about ventilation not visible to the eye or easily extracted with segmentation methods. Purpose To explore the use of deep convolutional neural networks (DCNNs) to generate synthetic MRI ventilation scans from free-breathing MRI (deep learning [DL] ventilation MRI)-derived specific ventilation maps as a surrogate of noble gas MRI and to validate this approach across a wide range of lung diseases. Materials and Methods In this secondary analysis of prospective trials, 114 paired noble gas MRI and two-dimensional free-breathing MRI scans were obtained in healthy volunteers with no history of chronic or acute respiratory disease and in study participants with a range of different obstructive lung diseases, including asthma, bronchiectasis, chronic obstructive pulmonary disease, and non-small-cell lung cancer between September 2013 and April 2018 (ClinicalTrials.gov identifiers: NCT03169673, NCT02351141, NCT02263794, NCT02282202, NCT02279329, and NCT02002052). A U-Net-based DCNN model was trained to map free-breathing proton MRI to hyperpolarized helium 3 (³He) MRI ventilation and validated using a sixfold validation. During training, the DCNN ventilation maps were compared with noble gas MRI scans using the Pearson correlation coefficient (r) and mean absolute error. DCNN ventilation images were segmented for ventilation and ventilation defects and were compared with noble gas MRI scans using the Dice similarity coefficient (DSC). Relationships were evaluated with the Spearman correlation coefficient (r_S). Results One hundred fourteen study participants (mean age, 56 years ± 15 [standard deviation]; 66 women) were evaluated. As compared with ³He MRI, DCNN model ventilation maps had a mean r value of 0.87 ± 0.08. The mean DSC for DL ventilation MRI and ³He MRI ventilation was 0.91 ± 0.07. The ventilation defect percentage for DL ventilation MRI was highly correlated with ³He MRI ventilation defect percentage (r_S = 0.83, P < .001, mean bias = -2.0% ± 5). Both DL ventilation MRI (r_S = -0.51, P < .001) and ³He MRI (r_S = -0.61, P < .001) ventilation defect percentage were correlated with the forced expiratory volume in 1 second. The DCNN model required approximately 2 hours for training and approximately 1 second to generate a ventilation map. Conclusion In participants with diverse pulmonary pathologic findings, deep convolutional neural networks generated ventilation maps from free-breathing proton MRI trained with a hyperpolarized noble-gas MRI ventilation map data set. The maps showed correlation with noble gas MRI ventilation and pulmonary function measurements. © RSNA, 2020 See also the editorial by Vogel-Claussen in this issue.

Longitudinal Imaging Using PET/CT with Collagen-I PET-Tracer and MRI for Assessment of Fibrotic and Inflammatory Lesions in a Rat Lung Injury Model

Non-invasive imaging biomarkers (IBs) are warranted to enable improved diagnostics and follow-up monitoring of interstitial lung disease (ILD) including drug-induced ILD (DIILD). Of special interest are IB, which can characterize and differentiate acute inflammation from fibrosis. The aim of the present study was to evaluate a PET-tracer specific for Collagen-I, combined with multi-echo MRI, in a rat model of DIILD. Rats were challenged intratracheally with bleomycin, and subsequently followed by MRI and PET/CT for four weeks. PET imaging demonstrated a significantly increased uptake of the collagen tracer in the lungs of challenged rats compared to controls. This was confirmed by MRI characterization of the lesions as edema or fibrotic tissue. The uptake of tracer did not show complete spatial overlap with the lesions identified by MRI. Instead, the tracer signal appeared at the borderline between lesion and healthy tissue. Histological tissue staining, fibrosis scoring, lysyl oxidase activity measurements, and gene expression markers all confirmed establishing fibrosis over time. In conclusion, the novel PET tracer for Collagen-I combined with multi-echo MRI, were successfully able to monitor fibrotic changes in bleomycin-induced lung injury. The translational approach of using non-invasive imaging techniques show potential also from a clinical perspective.