AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine

doi:10.3390/healthcare10112166

. 2022 Oct 29;10(11):2166.

doi: 10.3390/healthcare10112166.

AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine

Viktoria Palm^{1

2

3}, Tobias Norajitra^{2

4

5}, Oyunbileg von Stackelberg^{1

2

3}, Claus P Heussel^{1

2

3}, Stephan Skornitzke^{1

2

3}, Oliver Weinheimer^{1

2

3}, Taisiya Kopytova⁴, Andre Klein^{4

6}, Silvia D Almeida^{2

4

6}, Michael Baumgartner⁴, Dimitrios Bounias^{4

6}, Jonas Scherer^{4

6}, Klaus Kades⁴, Hanno Gao⁴, Paul Jäger⁷, Marco Nolden^{4

5}, Elizabeth Tong^{1

3}, Kira Eckl^{1

3}, Johanna Nattenmüller^{1

2

3

8}, Tobias Nonnenmacher^{1

2

3}, Omar Naas^{1

2

3}, Julia Reuter^{1

2

3}, Arved Bischoff^{1

2

3}, Jonas Kroschke^{1

2

3}, Fabian Rengier^{1

2

3}, Kai Schlamp^{1

2

3}, Manuel Debic^{1

2

3}, Hans-Ulrich Kauczor^{1

2

3}, Klaus Maier-Hein^{2

4

5}, Mark O Wielpütz^{1

2

3}

Affiliations

¹ Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany.
² Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany.
³ Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany.
⁴ Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany.
⁵ Pattern Analysis and Learning Group, Department of Radiation Oncology, University Hospital of Heidelberg, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany.
⁶ Medical Faculty, University of Heidelberg, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany.
⁷ Interactive Machine Learning Research Group, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany.
⁸ Department of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine Freiburg, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, Germany.

PMID: 36360507
PMCID: PMC9690402
DOI: 10.3390/healthcare10112166

AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine

Viktoria Palm et al. Healthcare (Basel). 2022.

. 2022 Oct 29;10(11):2166.

doi: 10.3390/healthcare10112166.

Authors

Affiliations

¹ Department of Diagnostic and Interventional Radiology, Subdivision of Pulmonary Imaging, University Hospital of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany.
² Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120 Heidelberg, Germany.
³ Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at the University Hospital of Heidelberg, Röntgenstr. 1, 69126 Heidelberg, Germany.
⁴ Division of Medical Imaging Computing, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany.
⁵ Pattern Analysis and Learning Group, Department of Radiation Oncology, University Hospital of Heidelberg, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany.
⁶ Medical Faculty, University of Heidelberg, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany.
⁷ Interactive Machine Learning Research Group, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 223, 69120 Heidelberg, Germany.
⁸ Department of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine Freiburg, University of Freiburg, Hugstetter Str. 55, 79106 Freiburg, Germany.

PMID: 36360507
PMCID: PMC9690402
DOI: 10.3390/healthcare10112166

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: CT imaging postprocessing; artificial intelligence; comorbidities; computer assisted image analysis; machine learning; medical computing; medical image processing; preventive medicine; radiomics.

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Conflict of interest statement

Stephan Skornitzke and Viktoria Palm have ownership interests in investment funds containing stock of healthcare companies. Fabian Rengier is, at the time of submission, employee of Bayer Vital GmbH, Germany, but the work presented herein dates to his previous employment at Heidelberg University Hospital. Otherwise, the authors of this manuscript declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

**Figure 1**
Flowchart of planned software integrations with: (a) Technical workflow and (b) Algorithm workflow.

**Figure 2**
Example no. 1 ‘TAVI patient’—Summary of organ segmentations and pathological findings from left to right and top to bottom: pulmonary nodule of the right upper lobe, coronary and aortic calcifications, visceral, subcutaneous and intramuscular adipose tissue, and vertebral segmentations for assessment of BMD.

**Figure 3**
Example no. 2 ‘COPD patient’—Summary of organ segmentations and pathological findings from left to right and top to bottom: COPD, coronary and aortic calcifications, visceral, subcutaneous and intramuscular adipose tissue, and vertebral segmentations for assessment of BMD.

See this image and copyright information in PMC

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[1] Khan M.S., Samman Tahhan A., Vaduganathan M., Greene S.J., Alrohaibani A., Anker S.D., Vardeny O., Fonarow G.C., Butler J. Trends in Prevalence of Comorbidities in Heart Failure Clinical Trials. Eur. J. Heart Fail. 2020;22:1032–1042. doi: 10.1002/ejhf.1818. - DOI - PMC - PubMed

[2] Khan M.S., Samman Tahhan A., Vaduganathan M., Greene S.J., Alrohaibani A., Anker S.D., Vardeny O., Fonarow G.C., Butler J. Trends in Prevalence of Comorbidities in Heart Failure Clinical Trials. Eur. J. Heart Fail. 2020;22:1032–1042. doi: 10.1002/ejhf.1818. - DOI - PMC - PubMed

[3] Kopf S., Groener J.B., Kender Z., Fleming T., Brune M., Riedinger C., Volk N., Herpel E., Pesta D., Szendrödi J., et al. Breathlessness and Restrictive Lung Disease: An Important Diabetes-Related Feature in Patients with Type 2 Diabetes. Respir. Int. Rev. Thorac. Dis. 2018;96:29–40. doi: 10.1159/000488909. - DOI - PubMed

[4] Kopf S., Groener J.B., Kender Z., Fleming T., Brune M., Riedinger C., Volk N., Herpel E., Pesta D., Szendrödi J., et al. Breathlessness and Restrictive Lung Disease: An Important Diabetes-Related Feature in Patients with Type 2 Diabetes. Respir. Int. Rev. Thorac. Dis. 2018;96:29–40. doi: 10.1159/000488909. - DOI - PubMed

[5] Yumuk V., Tsigos C., Fried M., Schindler K., Busetto L., Micic D., Toplak H. Obesity Management Task Force of the European Association for the Study of Obesity European Guidelines for Obesity Management in Adults. Obes. Facts. 2015;8:402–424. doi: 10.1159/000442721. - DOI - PMC - PubMed

[6] Yumuk V., Tsigos C., Fried M., Schindler K., Busetto L., Micic D., Toplak H. Obesity Management Task Force of the European Association for the Study of Obesity European Guidelines for Obesity Management in Adults. Obes. Facts. 2015;8:402–424. doi: 10.1159/000442721. - DOI - PMC - PubMed

[7] Hoffmann U., Massaro J.M., Fox C.S., Manders E., O’Donnell C.J. Defining Normal Distributions of Coronary Artery Calcium in Women and Men (from the Framingham Heart Study) Am. J. Cardiol. 2008;102:1136–1141.e1. doi: 10.1016/j.amjcard.2008.06.038. - DOI - PMC - PubMed

[8] Hoffmann U., Massaro J.M., Fox C.S., Manders E., O’Donnell C.J. Defining Normal Distributions of Coronary Artery Calcium in Women and Men (from the Framingham Heart Study) Am. J. Cardiol. 2008;102:1136–1141.e1. doi: 10.1016/j.amjcard.2008.06.038. - DOI - PMC - PubMed

[9] Atsou K., Chouaid C., Hejblum G. Variability of the Chronic Obstructive Pulmonary Disease Key Epidemiological Data in Europe: Systematic Review. BMC Med. 2011;9:7. doi: 10.1186/1741-7015-9-7. - DOI - PMC - PubMed

[10] Atsou K., Chouaid C., Hejblum G. Variability of the Chronic Obstructive Pulmonary Disease Key Epidemiological Data in Europe: Systematic Review. BMC Med. 2011;9:7. doi: 10.1186/1741-7015-9-7. - DOI - PMC - PubMed

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AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine

Affiliations

AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

Similar articles

Cited by

References

Grants and funding

LinkOut - more resources

Full Text Sources