Periodic Reporting for period 1 - IMAGE-IN (Imaging infections: integrated, multiscale visualization of infections and host response)
Berichtszeitraum: 2020-01-01 bis 2021-12-31
Infectious diseases are among major causes of death worldwide. As we all could experience during the Covid-19 pandemic, the course of an infection is highly variable and differs greatly between individuals. In order to treat patients efficiently and successfully, powerful diagnostic methods and a profound understanding of disease pathogenesis is crucial. Many molecular imaging approaches are currently being developed and implemented on the researchers’ level and hold great potential to enable precision medicine for infectious diseases. High-resolution imaging methods become a key driver for crucial transformation of medicine and healthcare. The potential of “big data” for the improvement of health is enormous. The successful realization of the complex objectives requires not only insights into the medical problem and into the physics of the different available imaging modalities, but also a deep understanding of handling large imaging data. Therefore, the IMAGE-IN training program bridges the gap between the clinical view on the multiple facets of infection, the complex imaging technology and the statistical algorithms and software solutions, through the creation of a stable link between the disciplines and the assurance of vivid exchange between the involved sectors. The aim of IMAGE-IN is to provide the trainee scientists in the network the tools to start and consolidate their careers in the field of spectroscopy and imaging for the application to the medical need, in particular infections. IMAGE-IN is a European Industrial Doctorate program to train Early Stage Researchers in exciting, high-potential, interdisciplinary, and multi-sectoral topics, as well as to educate the next generation of researchers who can actively advance imaging technology for medical applications. They gain full insight into the medical need, the spectroscopic techniques and the skills to handle and analyze large, multidimensional data. A substantial part of the training scheme will be dedicated to on-field experience in the private sector, with direct feedback from the medical end-user. It will also be dedicated to the training of transferable skills, with the objective of spurring business concepts and entrepreneurship skills in the fellows and of encouraging technology transfer from the research institutes to the industry, in order to boost distributed health care systems and related industry in Europe. The 5 ESRs acquire skills necessary to explore new application areas of biomedical imaging and to put forward new imaging and image analysis methods. They will also bring out data handling algorithms to target better diagnostics and establish imaging technologies to follow new treatment strategies of infections.
“IMAGE-IN - Imaging infections: integrated, multiscale visualization of infections and host response” has started on the 1st of January 2020. Beneficiaries and partner organisations identified experiments to be carried out as a starting point for the scientific collaboration. Scientific results that have been achieved include:
- A new and automated identification algorithm for the rapid identification of multidrug resistant Escherichia coli using specific Raman marker bands (J. Biophoton. 2020, 13:e202000149. DOI: 10.1002/jbio.202000149).
- Correlation of crystal violet biofilm test results of Staphylococcus aureus clinical isolates with Raman spectroscopic read-out. J. Raman Spectrosc. 2021, 1. https://doi.org/10.1002/jrs.6237
- A label-free visualization method to quantitatively follow intracellular pathogenesis in a cell-culture infection model. Exemplarily, the spectroscopic imaging algorithm was verified using Coxiella burnetii, the pathogen leading to Q fever in humans (submitted for publication).
- Improvements in lymphocytes detection using deep learning with a preprocessing stage IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), 2021, pp. 178 -182 (ESR Rodrigo Guerrero).
- Improving the Visualization and Dicomization process for the Stacked Whole Slide Imaging, IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021, pp. 1-8 (ESR Yubraj Gupta).
- Software tools and platforms in Digital Pathology: review for clinicians and computer scientists, submitted for publication (ESR Rodrigo Guerrero).
Furthermore, imaging data on different scales, ranging from whole animal imaging (MRI, X-ray) to high resolution electron microscopy data and spanning label-free imaging methods as well as methods utilizing specific labels have been generated during the project and are provided to the consortium for development of new algorithms and a deeper understanding of infections.
Secondments from the ESRs between industry and academia have been successfully completed. The IMAGE-IN training programme is built around three pilars (original research, training courses, and mentoring) to assure full width of education while at the same time achieving individual support, training and development of each ESR according to the specific skills of the young researchers.
- A new and automated identification algorithm for the rapid identification of multidrug resistant Escherichia coli using specific Raman marker bands (J. Biophoton. 2020, 13:e202000149. DOI: 10.1002/jbio.202000149).
- Correlation of crystal violet biofilm test results of Staphylococcus aureus clinical isolates with Raman spectroscopic read-out. J. Raman Spectrosc. 2021, 1. https://doi.org/10.1002/jrs.6237
- A label-free visualization method to quantitatively follow intracellular pathogenesis in a cell-culture infection model. Exemplarily, the spectroscopic imaging algorithm was verified using Coxiella burnetii, the pathogen leading to Q fever in humans (submitted for publication).
- Improvements in lymphocytes detection using deep learning with a preprocessing stage IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), 2021, pp. 178 -182 (ESR Rodrigo Guerrero).
- Improving the Visualization and Dicomization process for the Stacked Whole Slide Imaging, IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021, pp. 1-8 (ESR Yubraj Gupta).
- Software tools and platforms in Digital Pathology: review for clinicians and computer scientists, submitted for publication (ESR Rodrigo Guerrero).
Furthermore, imaging data on different scales, ranging from whole animal imaging (MRI, X-ray) to high resolution electron microscopy data and spanning label-free imaging methods as well as methods utilizing specific labels have been generated during the project and are provided to the consortium for development of new algorithms and a deeper understanding of infections.
Secondments from the ESRs between industry and academia have been successfully completed. The IMAGE-IN training programme is built around three pilars (original research, training courses, and mentoring) to assure full width of education while at the same time achieving individual support, training and development of each ESR according to the specific skills of the young researchers.
IMAGE-IN is to provide new career perspectives to young researchers through their exposure to the interdisciplinary research field with strong involvement of the non-academic sector and guidance from the medical need. The five ESRs from the IMAGE-IN research and training network are being trained in an emerging field of research which is currently expanding under the medical need by advancing spectroscopic techniques and data analysis algorithms and methods. Imaging techniques enable rapid visualization and monitoring of molecular processes in a non-invasive manner and promise unparalleled opportunities for the field of infectious diseases (diagnosis and monitoring of treatment responses). Those new methods could overcome severe limitations of current tools, and thus generate a broad impact on both basic research and patient care. Beyond diagnosis and monitoring disease, these technologies could also provide a uniform cross-species platform for animal studies, allowing unique insights into understanding disease pathogenesis, and expedite bench-to-bedside translation of new therapeutics. Translation of the newly developed tools for clinical applications and for enabling personalized medicine for infectious diseases is very likely as molecular imaging is readily available for humans. The IMAGE-IN training network will fill the gap between imaging technology and difficulties when analyzing and merging huge spectral data to provide meaningful insights from the life science perspective and medical need. Thus, the graduates from this integrated trans-disciplinary educational program can fill the current lack of trained scientific personnel who is capable of creating the link between the multiple facets of infection and the interpretation and handling of large imaging data.
The IMAGE-IN team is highly committed to rapid, effective internal and external dissemination of project results and knowledge. All partners are using their broad experience in dissemination and outreach activities related to previous projects on national and international scales to maximize the impact of the research and training results of IMAGE-IN. The research and training network IMAGE-IN are generating results which are of high interest to the scientific communities, but due to its impact on medical diagnosis also to the general society and industry.
The IMAGE-IN team is highly committed to rapid, effective internal and external dissemination of project results and knowledge. All partners are using their broad experience in dissemination and outreach activities related to previous projects on national and international scales to maximize the impact of the research and training results of IMAGE-IN. The research and training network IMAGE-IN are generating results which are of high interest to the scientific communities, but due to its impact on medical diagnosis also to the general society and industry.