Quantitative imaging and medical physics team
Making every photon count.
QIMP “Quantitative Imaging and Medical Physics” was founded in 2013. The group is associated with a full professorship for “Physics of Medical Imaging – Hybrid Imaging” at the Med Uni Vienna.
The group comprises of a variety of academic and non-academic experts who are united by the intent to provide scientific support to improving healthcare for patients. We are engaged in applied research that helps to clinically anchor the concept of personalized medicine through the use of multi-modal imaging methods.
Research Area
Research Topics
Hybrid Imaging Technology | Data Analytics | AI and quantum computing
Team members
Principal Investigator
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| Thomas Beyer |
Postdocs
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| Barbara Geist Nuclear Medicine | Ivo Rausch | Lalith Kumar Shyiam Sundar |
PhD students
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| July Alejandra Gonzalez Valladares | Marko Grahovac Nuclear Medicine | David Iommi | Hunor Kertesz |
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| Denis Krajnc | Laszlo Papp | Clemens Spielvogel Nuclear Medicine |
Master students
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| Sarit Alaev | Nicole Jurjew |
Technical staff
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| Peter M. Schaffarich |
Alumni
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Projects
- Improving Clinical PET imaging for non-optimal positron emitters (2018)
Supported by Siemens Healthineers (SMS) - Low-count-high-quality reconstructions for PET and SPECT (2017)
Supported by Austrian Science Fund (FWF) - Innovative Training Network towards raising and supporting the next generation of creative and entrepreneurial cross-specialty imaging expert (2017)
EU Project 764458 “HYBRID” (H2020-MSCA-ITN-2017) - Personalized diagnosis of non-lesional epilepsy using simultaneous PET/MR (2016)
Supported by Austrian Science Fund (FWF) - [18F]FDG and [18F]NaF-PET Imaging of Vulnerable Plaque (2016)
Supported by Siemens Healthineers (SMS) - Quantification of bone lesions in combined PET/MR and Dual-time point imaging of lesions with PET/MR (2014)
Supported by Siemens Healthcare (SMS) - Multi-centre PET/CT: Quality control, FDG-guidelines and quantification (2013)
Supported by the Austrian Society of Nuclear Medicine (OGN)
Publications
Selected peer-reviewed publications
- Papp, L. et. al., 2018. Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis Front. Phys. June
- Valladares, A. et. 2019. Clinically Valuable Quality Control for PET/MRI Systems: Consensus Recommendation From the HYBRID Consortium, Frontiers in Physics, 2019, 7, 136
- Rausch, I. et. al., 2019. Performance evaluation of the Vereos PET/CT system according to NEMA NU2-2012 standard. J Nucl Med 60(4): 561-567
- Shiyam Sundar, L. K. et. al., 2019 The promise of fully-integrated PET/MR imaging: Non-invasive clinical quantification of cerebral glucose metabolism. J Nucl Med, 61 no. 2 276-284
- Beyer T et al., 2020. What scans we will read: Imaging instrumentation trends in clinical oncology, Cancer Imaging,
Completed Theses
- Shiyam Sundar, Lalith Kumar, Personalized neuroimaging for improved assessment of non-lesional epilepsy based on fully-integrated PET/MRI imaging, PhD thesis, Medical university of Vienna, 2019.
- Rausch, Ivo, Advanced quantification for fully-integrated PET/MRI : implementing MRI-based attenuation correction in clinical routine, PhD thesis, Medical university of Vienna, 2017
- Lassen, Martin Lyngby, PET Quantification in PET/CT and PET/MR, PhD thesis, Medical university of Vienna, 2017
Highlights
This guidance document on consensus recommendations on mandatory quality control processes for integrating dual-modality PET/MRI into clinical practice and research was put together by Alejandra Valladares, MSc as part of her engagement in the MSCA ITN “HYBRID” project (2017-21).
“Images are data, and data is knowledge.” This comprehensive introduction of the concept of holomics as the next frontier in clinically relevant data sciences was published by Laszlo Papp and colleagues in open access.
“Full quantification of metabolic rates of glucose (CMRGlc) is made possible with a fully automated pipeline built on integrated PET/MR data.” This high-level publication was one of the results of the thesis work of Lalith Shiyam Sundar who defended his PhD in 2019.