Comparison of CT-derived ventilation maps with deposition patterns of inhaled microspheres in rats

Quantitative Imaging Metrics for the Assessment of Pulmonary Pathophysiology: An Official American Thoracic Society and Fleischner Society Joint Workshop Report

Multiple thoracic imaging modalities have been developed to link structure to function in the diagnosis and monitoring of lung disease. Volumetric computed tomography (CT) renders three-dimensional maps of lung structures and may be combined with positron emission tomography (PET) to obtain dynamic physiological data. Magnetic resonance imaging (MRI) using ultrashort-echo time (UTE) sequences has improved signal detection from lung parenchyma; contrast agents are used to deduce airway function, ventilation-perfusion-diffusion, and mechanics. Proton MRI can measure regional ventilation-perfusion ratio. Quantitative imaging (QI)-derived endpoints have been developed to identify structure-function phenotypes, including air-blood-tissue volume partition, bronchovascular remodeling, emphysema, fibrosis, and textural patterns indicating architectural alteration. Coregistered landmarks on paired images obtained at different lung volumes are used to infer airway caliber, air trapping, gas and blood transport, compliance, and deformation. This document summarizes fundamental "good practice" stereological principles in QI study design and analysis; evaluates technical capabilities and limitations of common imaging modalities; and assesses major QI endpoints regarding underlying assumptions and limitations, ability to detect and stratify heterogeneous, overlapping pathophysiology, and monitor disease progression and therapeutic response, correlated with and complementary to, functional indices. The goal is to promote unbiased quantification and interpretation of in vivo imaging data, compare metrics obtained using different QI modalities to ensure accurate and reproducible metric derivation, and avoid misrepresentation of inferred physiological processes. The role of imaging-based computational modeling in advancing these goals is emphasized. Fundamental principles outlined herein are critical for all forms of QI irrespective of acquisition modality or disease entity.

Advancing New Approach Methodologies (NAMs) for Tobacco Harm Reduction: Synopsis from the 2021 CORESTA SSPT-NAMs Symposium

New approach methodologies (NAMs) are emerging chemical safety assessment tools consisting of in vitro and in silico (computational) methodologies intended to reduce, refine, or replace (3R) various in vivo animal testing methods traditionally used for risk assessment. Significant progress has been made toward the adoption of NAMs for human health and environmental toxicity assessment. However, additional efforts are needed to expand their development and their use in regulatory decision making. A virtual symposium was held during the 2021 Cooperation Centre for Scientific Research Relative to Tobacco (CORESTA) Smoke Science and Product Technology (SSPT) conference (titled "Advancing New Alternative Methods for Tobacco Harm Reduction"), with the goals of introducing the concepts and potential application of NAMs in the evaluation of potentially reduced-risk (PRR) tobacco products. At the symposium, experts from regulatory agencies, research organizations, and NGOs shared insights on the status of available tools, strengths, limitations, and opportunities in the application of NAMs using case examples from safety assessments of chemicals and tobacco products. Following seven presentations providing background and application of NAMs, a discussion was held where the presenters and audience discussed the outlook for extending the NAMs toxicological applications for tobacco products. The symposium, endorsed by the CORESTA In Vitro Tox Subgroup, Biomarker Subgroup, and NextG Tox Task Force, illustrated common ground and interest in science-based engagement across the scientific community and stakeholders in support of tobacco regulatory science. Highlights of the symposium are summarized in this paper.

Effect of MDI Actuation Timing on Inhalation Dosimetry in a Human Respiratory Tract Model

Accurate knowledge of the delivery of locally acting drug products, such as metered-dose inhaler (MDI) formulations, to large and small airways is essential to develop reliable in vitro/in vivo correlations (IVIVCs). However, challenges exist in modeling MDI delivery, due to the highly transient multiscale spray formation, the large variability in actuation–inhalation coordination, and the complex lung networks. The objective of this study was to develop/validate a computational MDI-releasing-delivery model and to evaluate the device actuation effects on the dose distribution with the newly developed model. An integrated MDI–mouth–lung (G9) geometry was developed. An albuterol MDI with the chlorofluorocarbon propellant was simulated with polydisperse aerosol size distribution measured by laser light scatter and aerosol discharge velocity derived from measurements taken while using a phase Doppler anemometry. The highly transient, multiscale airflow and droplet dynamics were simulated by using large eddy simulation (LES) and Lagrangian tracking with sufficiently fine computation mesh. A high-speed camera imaging of the MDI plume formation was conducted and compared with LES predictions. The aerosol discharge velocity at the MDI orifice was reversely determined to be 40 m/s based on the phase Doppler anemometry (PDA) measurements at two different locations from the mouthpiece. The LES-predicted instantaneous vortex structures and corresponding spray clouds resembled each other. There are three phases of the MDI plume evolution (discharging, dispersion, and dispensing), each with distinct features regardless of the actuation time. Good agreement was achieved between the predicted and measured doses in both the device, mouth–throat, and lung. Concerning the device–patient coordination, delayed MDI actuation increased drug deposition in the mouth and reduced drug delivery to the lung. Firing MDI before inhalation was found to increase drug loss in the device; however, it also reduced mouth–throat loss and increased lung doses in both the central and peripheral regions.

Ventilation/Perfusion Relationships and Gas Exchange: Measurement Approaches

Ventilation-perfusion ( V ˙ A / Q ˙ ) matching, the regional matching of the flow of fresh gas to flow of deoxygenated capillary blood, is the most important mechanism affecting the efficiency of pulmonary gas exchange. This article discusses the measurement of V ˙ A / Q ˙ matching with three broad classes of techniques: (i) those based in gas exchange, such as the multiple inert gas elimination technique (MIGET); (ii) those derived from imaging techniques such as single-photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic resonance imaging (MRI), computed tomography (CT), and electrical impedance tomography (EIT); and (iii) fluorescent and radiolabeled microspheres. The focus is on the physiological basis of these techniques that provide quantitative information for research purposes rather than qualitative measurements that are used clinically. The fundamental equations of pulmonary gas exchange are first reviewed to lay the foundation for the gas exchange techniques and some of the imaging applications. The physiological considerations for each of the techniques along with advantages and disadvantages are briefly discussed. © 2020 American Physiological Society. Compr Physiol 10:1155-1205, 2020.

The VAMPIRE challenge: A multi-institutional validation study of CT ventilation imaging

PURPOSE

CT ventilation imaging (CTVI) is being used to achieve functional avoidance lung cancer radiation therapy in three clinical trials (NCT02528942, NCT02308709, NCT02843568). To address the need for common CTVI validation tools, we have built the Ventilation And Medical Pulmonary Image Registration Evaluation (VAMPIRE) Dataset, and present the results of the first VAMPIRE Challenge to compare relative ventilation distributions between different CTVI algorithms and other established ventilation imaging modalities.

METHODS

The VAMPIRE Dataset includes 50 pairs of 4DCT scans and corresponding clinical or experimental ventilation scans, referred to as reference ventilation images (RefVIs). The dataset includes 25 humans imaged with Galligas 4DPET/CT, 21 humans imaged with DTPA-SPECT, and 4 sheep imaged with Xenon-CT. For the VAMPIRE Challenge, 16 subjects were allocated to a training group (with RefVI provided) and 34 subjects were allocated to a validation group (with RefVI blinded). Seven research groups downloaded the Challenge dataset and uploaded CTVIs based on deformable image registration (DIR) between the 4DCT inhale/exhale phases. Participants used DIR methods broadly classified into B-splines, Free-form, Diffeomorphisms, or Biomechanical modeling, with CT ventilation metrics based on the DIR evaluation of volume change, Hounsfield Unit change, or various hybrid approaches. All CTVIs were evaluated against the corresponding RefVI using the voxel-wise Spearman coefficient r S , and Dice similarity coefficients evaluated for low function lung ( DSC low ) and high function lung ( DSC high ).

RESULTS

A total of 37 unique combinations of DIR method and CT ventilation metric were either submitted by participants directly or derived from participant-submitted DIR motion fields using the in-house software, VESPIR. The r S and DSC results reveal a high degree of inter-algorithm and intersubject variability among the validation subjects, with algorithm rankings changing by up to ten positions depending on the choice of evaluation metric. The algorithm with the highest overall cross-modality correlations used a biomechanical model-based DIR with a hybrid ventilation metric, achieving a median (range) of 0.49 (0.27-0.73) for r S , 0.52 (0.36-0.67) for DSC low , and 0.45 (0.28-0.62) for DSC high . All other algorithms exhibited at least one negative r S value, and/or one DSC value less than 0.5.

CONCLUSIONS

The VAMPIRE Challenge results demonstrate that the cross-modality correlation between CTVIs and the RefVIs varies not only with the choice of CTVI algorithm but also with the choice of RefVI modality, imaging subject, and the evaluation metric used to compare relative ventilation distributions. This variability may arise from the fact that each of the different CTVI algorithms and RefVI modalities provides a distinct physiologic measurement. Ultimately this variability, coupled with the lack of a "gold standard," highlights the ongoing importance of further validation studies before CTVI can be widely translated from academic centers to the clinic. It is hoped that the information gleaned from the VAMPIRE Challenge can help inform future validation efforts.

Design and development of a nonrigid phantom for the quantitative evaluation of DIR-based mapping of simulated pulmonary ventilation

PURPOSE

The validation of deformable image registration (DIR)-based pulmonary ventilation mapping is time consuming and prone to inaccuracies and is also affected by deformation parameters. In this study, we developed a nonrigid phantom as a quality assurance (QA) tool that simulates ventilation to evaluate DIR-based images quantitatively.

METHODS

The phantom consists of an acrylic cylinder filled with polyurethane foam designed to simulate pulmonic alveoli. A polyurethane membrane is attached to the inferior end of the phantom to simulate the diaphragm. In addition, tracheobronchial-tree-shaped polyurethane tubes are inserted through the foam and converge outside the phantom to simulate the trachea. Solid polyurethane is also used to model arteries, which closely follow the model airways. Two three-dimensional (3D) CT scans were performed during exhalation and inhalation phases using xenon (Xe) gas as the inhaled contrast agent. The exhalation 3D-CT image is deformed to an inhalation 3D-CT image using our in-house program based on the NiftyReg open-source package. The target registration error (TRE) between the two images was calculated for 16 landmarks located in the simulated lung volume. The DIR-based ventilation image was generated using Jacobian determinant (JD) metrics. Subsequently, differences in the Hounsfield unit (HU) values between the two images were measured. The correlation coefficient between the JD and HU differences was calculated. In addition, three 4D-CT scans are performed to evaluate the reproducibility of the phantom motion and Xe gas distribution.

RESULTS

The phantom exhibited a variety of displacements for each landmark (range: 1-20 mm). The reproducibility analysis indicated that the location differences were <1 mm for all landmarks, and the HU variation in the Xe gas distribution was close to zero. The mean TRE in the evaluation of spatial accuracy according to the DIR software was 1.47 ± 0.71 mm (maximum: 2.6 mm). The relationship between the JD and HU differences had a large correlation (R = -0.71) for the DIR software.

CONCLUSION

The phantom implemented new features, namely, deformation and simulated ventilation. To assess the accuracy of the DIR-based mapping of the simulated pulmonary ventilation, the phantom allows for simulation of Xe gas wash-in and wash-out. The phantom may be an effective QA tool, because the DIR algorithm can be quickly changed and its accuracy evaluated with a high degree of precision.