Imaging plays an increasing role for the diagnosis and for monitoring of pulmonary diseases. This results from cross-sectional imaging's capability for regional differentiation of structural alterations of airways, lung tissue and vasculature, which cannot be captured by pulmonary function testing alone. Further, a plethora of functional and quantitative imaging techniques mainly based on computed tomography (CT) and magnetic resonance imaging (MRI) have emerged, delivering information on local pulmonary function composed of ventilation, perfusion and diffusion, ultimately determining gas exchange. Most important functional techniques such as Gadolinium-based contrast-enhanced perfusion MRI and hyperpolarized gas ventilation MRI, have been introduced into routine patient care as well as implemented as endpoints in clinical trials, whereas other modalities such as non-contrast lung ventilation and perfusion MRI are on the edge of clinical validation.
Quantitative and fucntional lung imaging is transforming patient-centered individualized care in pulmonary medicine. Yet, technique-driven development, availability aspects and limited acceptance by clinicians are hampering its broad dissemination. Now that different modalities employing either radiation based on CT or radiation-free MRI-base techniques have made profound technical advance, future studies should be directed at validation, clinical implementation and decision support in the disease-specific context to bring these technical advances into patient care.
This research topic aims to collect state-of-the-art original research on functional and quantitative lung imaging techniques. There should be a focus on applications directed at specific clinical questions in the context of patient care, clinical trials, therapeutic monitoring, method implementation or clinical validation. Feasibility studies on novel or modified techniques and novel post-processing strategies including the application of machine learning are most welcome as well. Further, this special issue would like to attract work with a holistic approach towards assessing pulmonary and extra-pulmonary comorbidities of pulmonary diseases, such as metabolic imaging, bone mineral density assessment, or manifestations of atherosclerosis associated with lung disease. Studies on reducing the environmental footprint in the context of imaging the lungs are encouraged for submission as well.
Imaging plays an increasing role for the diagnosis and for monitoring of pulmonary diseases. This results from cross-sectional imaging's capability for regional differentiation of structural alterations of airways, lung tissue and vasculature, which cannot be captured by pulmonary function testing alone. Further, a plethora of functional and quantitative imaging techniques mainly based on computed tomography (CT) and magnetic resonance imaging (MRI) have emerged, delivering information on local pulmonary function composed of ventilation, perfusion and diffusion, ultimately determining gas exchange. Most important functional techniques such as Gadolinium-based contrast-enhanced perfusion MRI and hyperpolarized gas ventilation MRI, have been introduced into routine patient care as well as implemented as endpoints in clinical trials, whereas other modalities such as non-contrast lung ventilation and perfusion MRI are on the edge of clinical validation.
Quantitative and fucntional lung imaging is transforming patient-centered individualized care in pulmonary medicine. Yet, technique-driven development, availability aspects and limited acceptance by clinicians are hampering its broad dissemination. Now that different modalities employing either radiation based on CT or radiation-free MRI-base techniques have made profound technical advance, future studies should be directed at validation, clinical implementation and decision support in the disease-specific context to bring these technical advances into patient care.
This research topic aims to collect state-of-the-art original research on functional and quantitative lung imaging techniques. There should be a focus on applications directed at specific clinical questions in the context of patient care, clinical trials, therapeutic monitoring, method implementation or clinical validation. Feasibility studies on novel or modified techniques and novel post-processing strategies including the application of machine learning are most welcome as well. Further, this special issue would like to attract work with a holistic approach towards assessing pulmonary and extra-pulmonary comorbidities of pulmonary diseases, such as metabolic imaging, bone mineral density assessment, or manifestations of atherosclerosis associated with lung disease. Studies on reducing the environmental footprint in the context of imaging the lungs are encouraged for submission as well.
