Healthcare (Oct 2022)
AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine
- Viktoria Palm,
- Tobias Norajitra,
- Oyunbileg von Stackelberg,
- Claus P. Heussel,
- Stephan Skornitzke,
- Oliver Weinheimer,
- Taisiya Kopytova,
- Andre Klein,
- Silvia D. Almeida,
- Michael Baumgartner,
- Dimitrios Bounias,
- Jonas Scherer,
- Klaus Kades,
- Hanno Gao,
- Paul Jäger,
- Marco Nolden,
- Elizabeth Tong,
- Kira Eckl,
- Johanna Nattenmüller,
- Tobias Nonnenmacher,
- Omar Naas,
- Julia Reuter,
- Arved Bischoff,
- Jonas Kroschke,
- Fabian Rengier,
- Kai Schlamp,
- Manuel Debic,
- Hans-Ulrich Kauczor,
- Klaus Maier-Hein,
- Mark O. Wielpütz
Affiliations
- Viktoria Palm
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Tobias Norajitra
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Oyunbileg von Stackelberg
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Claus P. Heussel
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Stephan Skornitzke
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Oliver Weinheimer
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Taisiya Kopytova
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Andre Klein
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Silvia D. Almeida
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Michael Baumgartner
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Dimitrios Bounias
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Jonas Scherer
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Klaus Kades
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Hanno Gao
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Paul Jäger
- Interactive Machine Learning Research Group, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Marco Nolden
- Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany
- Elizabeth Tong
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Kira Eckl
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Johanna Nattenmüller
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Tobias Nonnenmacher
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Omar Naas
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Julia Reuter
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Arved Bischoff
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Jonas Kroschke
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Fabian Rengier
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Kai Schlamp
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Manuel Debic
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- Klaus Maier-Hein
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany
- Mark O. Wielpütz
- Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
- DOI
- https://doi.org/10.3390/healthcare10112166
- Journal volume & issue
-
Vol. 10,
no. 11
p. 2166
Abstract
Automated image analysis plays an increasing role in radiology in detecting and quantifying image features outside of the perception of human eyes. Common AI-based approaches address a single medical problem, although patients often present with multiple interacting, frequently subclinical medical conditions. A holistic imaging diagnostics tool based on artificial intelligence (AI) has the potential of providing an overview of multi-system comorbidities within a single workflow. An interdisciplinary, multicentric team of medical experts and computer scientists designed a pipeline, comprising AI-based tools for the automated detection, quantification and characterization of the most common pulmonary, metabolic, cardiovascular and musculoskeletal comorbidities in chest computed tomography (CT). To provide a comprehensive evaluation of each patient, a multidimensional workflow was established with algorithms operating synchronously on a decentralized Joined Imaging Platform (JIP). The results of each patient are transferred to a dedicated database and summarized as a structured report with reference to available reference values and annotated sample images of detected pathologies. Hence, this tool allows for the comprehensive, large-scale analysis of imaging-biomarkers of comorbidities in chest CT, first in science and then in clinical routine. Moreover, this tool accommodates the quantitative analysis and classification of each pathology, providing integral diagnostic and prognostic value, and subsequently leading to improved preventive patient care and further possibilities for future studies.
Keywords
- artificial intelligence
- comorbidities
- machine learning
- computer assisted image analysis
- medical image processing
- medical computing