TY - JOUR
T1 - LungVis 1.0
T2 - an automatic AI-powered 3D imaging ecosystem unveils spatial profiling of nanoparticle delivery and acinar migration of lung macrophages
AU - Yang, Lin
AU - Liu, Qiongliang
AU - Kumar, Pramod
AU - Sengupta, Arunima
AU - Farnoud, Ali
AU - Shen, Ruolin
AU - Trofimova, Darya
AU - Ziegler, Sebastian
AU - Davoudi, Neda
AU - Doryab, Ali
AU - Yildirim, Ali Önder
AU - Diefenbacher, Markus E.
AU - Schiller, Herbert B.
AU - Razansky, Daniel
AU - Piraud, Marie
AU - Burgstaller, Gerald
AU - Kreyling, Wolfgang G.
AU - Isensee, Fabian
AU - Rehberg, Markus
AU - Stoeger, Tobias
AU - Schmid, Otmar
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/12
Y1 - 2024/12
N2 - Targeted (nano-)drug delivery is essential for treating respiratory diseases, which are often confined to distinct lung regions. However, spatio-temporal profiling of drugs or nanoparticles (NPs) and their interactions with lung macrophages remains unresolved. Here, we present LungVis 1.0, an AI-powered imaging ecosystem that integrates light sheet fluorescence microscopy with deep learning-based image analysis pipelines to map NP deposition and dosage holistically and quantitatively across bronchial and alveolar (acinar) regions in murine lungs for widely-used bulk-liquid and aerosol-based delivery methods. We demonstrate that bulk-liquid delivery results in patchy NP distribution with elevated bronchial doses, whereas aerosols achieve uniform deposition reaching distal alveoli. Furthermore, we reveal that lung tissue-resident macrophages (TRMs) are dynamic, actively patrolling and redistributing NPs within alveoli, contesting the conventional paradigm of TRMs as static entities. LungVis 1.0 provides an advanced framework for exploring pulmonary delivery dynamics and deepening insights into TRM-mediated lung immunity.
AB - Targeted (nano-)drug delivery is essential for treating respiratory diseases, which are often confined to distinct lung regions. However, spatio-temporal profiling of drugs or nanoparticles (NPs) and their interactions with lung macrophages remains unresolved. Here, we present LungVis 1.0, an AI-powered imaging ecosystem that integrates light sheet fluorescence microscopy with deep learning-based image analysis pipelines to map NP deposition and dosage holistically and quantitatively across bronchial and alveolar (acinar) regions in murine lungs for widely-used bulk-liquid and aerosol-based delivery methods. We demonstrate that bulk-liquid delivery results in patchy NP distribution with elevated bronchial doses, whereas aerosols achieve uniform deposition reaching distal alveoli. Furthermore, we reveal that lung tissue-resident macrophages (TRMs) are dynamic, actively patrolling and redistributing NPs within alveoli, contesting the conventional paradigm of TRMs as static entities. LungVis 1.0 provides an advanced framework for exploring pulmonary delivery dynamics and deepening insights into TRM-mediated lung immunity.
UR - http://www.scopus.com/inward/record.url?scp=85210528194&partnerID=8YFLogxK
U2 - 10.1038/s41467-024-54267-1
DO - 10.1038/s41467-024-54267-1
M3 - Article
AN - SCOPUS:85210528194
SN - 2041-1723
VL - 15
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 10138
ER -