TY - JOUR
T1 - Quantitative Imaging Metrics for the Assessment of Pulmonary Pathophysiology An Official American Thoracic Society and Fleischner Society Joint Workshop Report
AU - American Thoracic Society and the Fleischner Society
AU - Hsia, Connie C.W.
AU - Hopkins, Susan R.
AU - Bates, Jason H.T.
AU - Driehuys, Bastiaan
AU - Fain, Sean B.
AU - Goldin, Jonathan G.
AU - Hoffman, Eric A.
AU - Hogg, James C.
AU - Levin, David L.
AU - Lynch, David A.
AU - Ochs, Matthias
AU - Parraga, Grace
AU - Prisk, G. Kim
AU - Smith, Benjamin M.
AU - Tawhai, Merryn
AU - Vidal Melo, Marcos F.
AU - Woods, Jason C.
N1 - Publisher Copyright:
Copyright © 2023 by the American Thoracic Society.
PY - 2023/2
Y1 - 2023/2
N2 - 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.
AB - 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.
KW - computed tomography
KW - lung mechanics
KW - magnetic resonance imaging
KW - positron emission tomography
KW - ventilation-perfusion-diffusion
UR - http://www.scopus.com/inward/record.url?scp=85147318210&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85147318210&partnerID=8YFLogxK
U2 - 10.1513/ANNALSATS.202211-915ST
DO - 10.1513/ANNALSATS.202211-915ST
M3 - Article
C2 - 36723475
AN - SCOPUS:85147318210
SN - 2325-6621
VL - 20
SP - 161
EP - 195
JO - Annals of the American Thoracic Society
JF - Annals of the American Thoracic Society
IS - 2
ER -