Optimizing human pulmonary perfusion measurement using an in silico model of arterial spin labeling magnetic resonance imaging

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.

Construction of a hybrid lung model by combining a real geometry of the upper airways and an idealized geometry of the lower airways

BACKGROUND AND OBJECTIVE

Health care costs represent a substantial an increasing percentage of global expenditures. One key component is treatment of respiratory diseases, which account for one in twelve deaths in Europe. Computational simulations of lung airflow have potential to provide considerable cost reduction and improved outcomes. Such simulations require accurate in silico modeling of the lung airway. The geometry of the lung is extremely complex and for this reason very simple morphologies have primarily been used to date. The objective of this work is to develop an effective methodology for the creation of hybrid pulmonary geometries combining patient-specific models obtained from CT images and idealized pulmonary models, for the purpose of carrying out experimental and numerical studies on aerosol/particle transport and deposition in inhaled drug delivery.

METHODS

For the construction of the hybrid numerical model, lung images obtained from computed tomography were exported to the DICOM format to be treated with a commercial software to build the patient-specific part of the model. At the distal terminus of each airway of this portion of the model, an idealization of a single airway path is connected, extending to the sixteenth generation. Because these two parts have different endings, it is necessary to create an intermediate solid to link them together. Physically realistic treatment of truncated airway boundaries in the model was accomplished by mapping of the flow velocity distribution from corresponding conducting airway segments.

RESULTS

The model was verified using two sets of simulations, steady inspiration/expiration and transient simulation of forced spirometry. The results showed that the hybrid model is capable of providing a realistic description of air flow dynamics in the lung while substantially reducing computational costs relative to models of the full airway tree.

CONCLUSIONS

The model development outlined here represents an important step toward computational simulation of lung dynamics for patient-specific applications. Further research work may consist of investigating specific diseases, such as chronic bronchitis and pulmonary emphysema, as well as the study of the deposition of pollutants or drugs in the airways.