Machine Learning analysis of human pulmonary extracellular matrix architecture identifies disease-specific remodeling patterns

Background: Normal organ function is critically dependent on an intact three-dimensional architecture. Structural abnormalities induced by pathological situations instruct cells to behave abnormally and promoting disease progression oftentimes leading to organ failure. Current approaches do not allow for high-resolution (HR) threedimensional (3D) visualisation and analysis of human organ structure. Method(s): Here, we develop a method to perfuse human tissue segments to remove cells and study the 3D structural scaffold, which could be applied to any organ. Our approach enables HR-3D imaging of organ architecture, which we apply to study healthy and diseased human lung, specifically emphysema, usual interstitial pneumonia, pulmonary sarcoidosis, and COVID-19. Result(s): Our imaging reveals major structural abnormalities previously unseen by existing methodologies. Furthermore, we identify disease-specific patterns of structural remodelling using machine learning, including the altered spatial relationship between extracellular matrix (ECM) proteins collagen type IV, elastin and fibrillar collagen present across all diseases. Conclusion(s): Given the importance of organ structure on function, our approach opens the possibility to understand human physiology in a new way, which may assist in future disease diagnosis and explain the detrimental pulmonary effects of the diseases studied here.

A V/Q SPECT/CT Study on Whether Persistent Reduction in Lung Diffusion Capacity after COVID-19 is Related to Restrictive or Vascular Lung Disease?

Aim/Introduction: Many patients have reduced pulmonary diffusion capacity (DLco) after COVID-19. We assessed whether this is due to a post-COVID restrictive lung disease and/or pulmonary vascular disease. Material(s) and Method(s): In total 67 patients diagnosed with COVID-19 at our hospital in 2020 were included across three severity groups: 12 mild - not admitted to hospital, 40 moderate - admitted to hospital without intensive care unit (ICU) admission, and 15 severe - with ICU admission. At 5-months followup after SARS-CoV-2 diagnosis, lung function (spirometry, body plethysmography, DLco), high-resolution CT of the lungs (HRCT), and ventilation/perfusion (V/Q) SPECT/CT were conducted. Result(s): DLco was reduced in 42% of the patients (mild 17%, moderate 40% and severe 71%);both prevalence and degree depended on clinical severity group and was usually part of a restrictive pattern with reduced TLC. Reduced DLco was associated with ground-glass opacification and pulmonary fibrosis found on HRCT and matched V/Q SPECT defects, but not with mismatched perfusion defects on V/Q SPECT/CT. Conclusion(s): The severity-dependent decline in DLco observed 5 months after COVID-19 is related to restrictive lung disease but not to pulmonary vascular disease.