PMI - RTF VII: Institute of Medical Engineering

PMI - RTF VII: Multiscale imaging / Small animal PET/CT

This project is part of the DFG Exzellenzcluster Precision Medicine in Chronic Inflammation (PMI). The goal of RTF VII is to investigate new approaches for a better and more accurate imaging using positron emission tomography (PET), magnetic resonance imaging (MRI), and advanced optical imaging with lasers. The new imaging systems are aimed to support the study of inflammatory diseases.

Focus of the research project is the development of a reconstruction strategy to process two raw data sets of the same object from different modalities in one reconstruction formulation and therefore facilitate mutual assistance of both imaging techniques. This should enhance the results with respect to contrast, object boundaries and noise statistics.

Grants

The project is financially supported by the German Research Foundation (DFG) under grant agreement no. 390884018

Cooperations

Exzellenzcluster Precision Medicine in Chronic Inflammation (PMI)

Publications

[ 2024 ]
[ 2023 ]
[ 2022 ]

2024[ to top ]

Seeger, S., Vo, H., Elmoujarkach, E., Schmidt, C. and Rafecas, M.: EP-0704 The MERMAID Project : Pioneering PET Imaging for Small Aquatics Animals, European Journal of Nuclear Medicine and Molecular Imaging, EANM’24 Abstract Book Congress Oct 19-23, 2024, 2024, DOI: 10.1007/s00259-024-06838-z.
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@article{seeger2024ep0704, author = {Seeger, Steven and Vo, Hong and Elmoujarkach, Ezzat and Schmidt, Christian and Rafecas, Magdalena}, journal = {European Journal of Nuclear Medicine and Molecular Imaging}, keywords = {SeegerSteven}, title = {EP-0704 The MERMAID Project : Pioneering PET Imaging for Small Aquatics Animals}, volume = {EANM’24 Abstract Book Congress Oct 19-23, 2024}, year = 2024 }
Seeger, S., Elmoujarkach, E., Schmidt, F., Nachimuthu, G., Schmidt, C., Mannheim, J. and Rafecas, M.: EP-0693 Fabrication of Zirconium-89 solid phantoms for PET using 3D Printing, European Journal of Nuclear Medicine and Molecular Imaging, 2024, DOI: 10.1007/s00259-024-06838-z.
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@article{seeger2024ep0693, author = {Seeger, Steven and Elmoujarkach, Ezzat and Schmidt, Fabian and Nachimuthu, Gowthaam and Schmidt, Christian and Mannheim, Julia and Rafecas, Magdalena}, journal = {European Journal of Nuclear Medicine and Molecular Imaging}, keywords = {MERMAID}, title = {EP-0693 Fabrication of Zirconium-89 solid phantoms for PET using 3D Printing}, year = 2024 }
Elmoujarkach, E. A., Pommranz, C., Cabello, J., Schmidt, F. P. and Rafecas, M.: Impact of Re-framing High-Dose Scans for the Training of Neural Networks for Denoising Low-Dose PET, 1–2, 2024, DOI: 10.1109/NSS/MIC/RTSD57108.2024.10657465.
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@inproceedings{10657465, abstract = {In PET, patient radiation exposure is mainly determined by the administered amount of radiotracer and its metabolism. By lowering the activity, the radiation dose is minimized at the cost of increased statistical fluctuations in the data; the latter increases the image noise level. Many artificial intelligence (AI) approaches have been proposed for image denoising of low-dose PET scans. Supervised AI algorithms require the use of labeled datasets, with the high-dose PET image as the target and the low-dose image as the input. This approach assumes that the performance of the PET systems is the same in the two activity regimes. However, the contribution of random coincidences, pile-up and dead-time effects depend on event rates. This study focuses on comparing two approaches to generating the training pair and their impact on the performance of a 3D U-Net using Monte Carlo simulations. The package GATE, v.9.1, was used to simulate a standard BMI XCAT phantom and a Biograph Vision Quadra PET/CT. Digital twins of 5-min 18F-FDG-PET scans for an activity of 3 MBq/kg were obtained to simulate two low-dose scenarios: injected low-dose, and injected high-dose re-framed to low-dose. The results showed that both methods of generating low-dose datasets yield comparable results without degradation in image quality. However, differences were observed in the random fraction for the high-dose dataset, i.e., the texture of the data noise changed. This study shows that using high-dose data is suitable for training of AI-based denoising algorithms on image space; nevertheless, denoising algorithms working on the projection space might overestimate the noise level within the data. Future work will include other activity concentrations and scan durations, incorporating motion, and the use of other radioisotopes.}, author = {Elmoujarkach, E. A. and Pommranz, C. and Cabello, J. and Schmidt, F. P. and Rafecas, M.}, booktitle = {2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD)}, keywords = {KI-INSPIRE}, month = 10, pages = {1-2}, title = {Impact of Re-framing High-Dose Scans for the Training of Neural Networks for Denoising Low-Dose PET}, year = 2024 }
Seeger, S., Elmoujarkach, E., Vo, H., Schmidt, C. and Rafecas, M.: Feasibility of Zirconium-89 Imaging with MERMAID, a small-fish PET scanner prototype, 1–2, 2024, DOI: 10.1109/NSS/MIC/RTSD57108.2024.10656767.
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@inproceedings{10656767, author = {Seeger, Steven and Elmoujarkach, Ezzat and Vo, Hong and Schmidt, Christian and Rafecas, Magdalena}, booktitle = {2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD)}, keywords = {SeegerSteven}, pages = {1-2}, title = {Feasibility of Zirconium-89 Imaging with MERMAID, a small-fish PET scanner prototype}, year = 2024 }
Lan, W., Vo, H. P., Pommranz, C., Elmoujarkach, E., Cabello, J., Birge, N., Schleyer, P., Rafecas, M., Lafougère, C. and Schmidt, F.: A Simulation Framework to Establish Ground Truth for Motion Correction in Total-Body PET: Initial Evaluation for Complex Respiratory Motion, 1–2, 2024, DOI: 10.1109/NSS/MIC/RTSD57108.2024.10656116.
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@inproceedings{10656116, abstract = {The enhanced sensitivity of total-body PET/CT scanners substantially decreases noise, however the full potential for spatio-temporal resolution is still hampered by artefacts and quantification degradation due to patient motion. To compensate for this, a variety of different motion correction methods were developed, but lack a motion free reference. To this end, our group developed a framework enabling Monte Carlo simulations of patient-like phantoms with motion modelling that accurately resembles event processing and image reconstruction of the Biograph Vision Quadra total-body PET/CT scanner. Simulations were performed with the XCAT phantom to mimic a clinical 5 min $\left[{ }^{18} \mathrm{ F}-\mathrm{FDG}\right]$ scan, with modelling of breathing motion with various breathing frequency/amplitude. To evaluate the impact of motion correction, an elastic motion deblurring approach, OncoFreeze AI, was used. Image quality, quantification of 5-20 mm lesions in lung and liver, and lesion line profiles were compared for a static (no motion) reference and for modelled motion with and without correction. Motion induced blurring in the images and could be compensated by the motion correction. The respiratory curve could be recovered by OncoFreeze AI with high precision (difference $\mathrm{Hz} \pm 0.5 \%$ over all motion segments). The motion correction helped to increase the recovery of the static activity concentration, e.g. for a 10 mm lung lesion: $9.4 \mathrm{kBq} / \mathrm{ml}$ (static no motion), $7 \mathrm{kBq} / \mathrm{ml}$ (motion) and $8.3 \mathrm{kBq} / \mathrm{ml}$ (motion corrected) and recovery of the lesion size 8.0 mm FWHM (static no motion) to 13.4 mm (motion) and 8.6 mm (motion corrected). This work underlines the need for motion correction and confirms the suitability of our framework to provide ground truth information on patient motion for total-body PET scans. Future work will extend this initial evaluation to more motion correction methods and a larger, more diverse data set with different scan durations, activities, and lesions.}, author = {Lan, W. and Vo, H. P. and Pommranz, C. and Elmoujarkach, E. and Cabello, J. and Birge, N. and Schleyer, P. and Rafecas, M. and Lafougère, C. and Schmidt, F.}, booktitle = {2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD)}, keywords = {nuci}, month = 10, pages = {1-2}, title = {A Simulation Framework to Establish Ground Truth for Motion Correction in Total-Body PET: Initial Evaluation for Complex Respiratory Motion}, year = 2024 }
Vo, H., Pommranz, C., Schmidt, F. P. and Rafecas, M.: Towards Enhancing Auxiliary Lymph Node Detection Using a Breast Insert with a Whole-Body PET/MRI Scanner, 1–2, 2024, DOI: 10.1109/NSS/MIC/RTSD57108.2024.10657626.
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@inproceedings{10657626, abstract = {In general, breast PET inserts are designed to improve the detection capability for small lesions and early metastases. Expanding on prior research, the insert our group is developing aims to enhance the spatial resolution of axillary lymph nodes beyond the insert’s field-of-view (FOV) via the combination with a clinical whole-body (WB) PET scanner. To explore this potential, Monte Carlo simulations were conducted using Na-22 point sources positioned outside of the insert’s FOV to mimic real lymph node locations. A dedicated reconstruction was developed to accommodate different types of coincidences in this hybrid setup, and the system model was partially validated using a phantom of uniformly distributed activity. Results indicate that, while the WB-PET’s spatial resolution may degrade due to insert attenuation, the combination of conventional WB-PET coincidences and mixed coincidences from both systems enhances spatial resolution in terms of full-width at half-maximum in x-direction, and also helps to mitigate the negative effects of the insert in y-direction. Future steps include a comprehensive assessment of image quality, refinement of the reconstruction algorithm to include the solid angle effect, and evaluation of image performance with realistic phantoms.}, author = {Vo, H.P. and Pommranz, C. and Schmidt, F. P. and Rafecas, M.}, booktitle = {2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD)}, keywords = {nuci}, month = 10, pages = {1-2}, title = {Towards Enhancing Auxiliary Lymph Node Detection Using a Breast Insert with a Whole-Body PET/MRI Scanner}, year = 2024 }

2023[ to top ]

Seeger, S., Vo, H., Florack, C., Werner, J., Schmidt, C. and Rafecas, M.: First Images from MERMAID, a Small Aquatic Animal PET Scanner Prototype, 1–1, 2023, DOI: 10.1109/NSSMICRTSD49126.2023.10338697.
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@inproceedings{seeger2023first, author = {Seeger, S. and Vo, H.P. and Florack, C. and Werner, J. and Schmidt, C. and Rafecas, M.}, booktitle = {2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)}, keywords = {MERMAID}, pages = {1-1}, title = {First Images from MERMAID, a Small Aquatic Animal PET Scanner Prototype}, year = 2023 }
Vo, H., Seeger, S., Werner, J. and Rafecas, M.: Towards Full-body Small Aquatic Animal PET: a Simulation Study of MERMAID-v2, 1–1, 2023, DOI: 10.1109/NSSMICRTSD49126.2023.10338525.
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@inproceedings{vo2023towards, author = {Vo, H.P. and Seeger, S. and Werner, J. and Rafecas, M.}, booktitle = {2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)}, keywords = {SeegerSteven}, pages = {1-1}, title = {Towards Full-body Small Aquatic Animal PET: a Simulation Study of MERMAID-v2}, year = 2023 }
Elmoujarkach, E., Seeger, S., Schmidt, C., Mannheim, J. G., Schmidt, F. P. and Rafecas, M.: First 3D printed radioactive 89Zr phantoms for Positron Emission Tomography, Transactions on Additive Manufacturing Meets Medicine, Vol. 5 No. S1 (2023): Trans. AMMM Supplement, 2023, DOI: 10.18416/AMMM.2023.2309833.
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@article{https://doi.org/10.18416/ammm.2023.2309833, author = {Elmoujarkach, Ezzat and Seeger, Steven and Schmidt, Christian and Mannheim, Julia G. and Schmidt, Fabian P. and Rafecas, Magdalena}, journal = {Transactions on Additive Manufacturing Meets Medicine}, keywords = {KI-INSPIRE}, pages = {Vol. 5 No. S1 (2023): Trans. AMMM Supplement}, publisher = {Transactions on Additive Manufacturing Meets Medicine}, title = {First 3D printed radioactive 89Zr phantoms for Positron Emission Tomography}, year = 2023 }

2022[ to top ]

Elmoujarkach, E., Seeger, S., Schareck, C., De Graaf, L., Barkhausen, J. and Rafecas, M.: Characterization of Using Infused PLA for 3DPrinted Radiation Shielding, Current Directions in Biomedical Engineering, 8(2), 2022, DOI: https://doi.org/10.1515/cdbme-2022-1147.
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@article{elmoujarkach2022characterization, author = {Elmoujarkach, Ezzat and Seeger, Steven and Schareck, Constantin and De Graaf, Leoni and Barkhausen, Jörg and Rafecas, Magdalena}, journal = {Current Directions in Biomedical Engineering}, keywords = {nuci}, number = 2, title = {Characterization of Using Infused PLA for 3DPrinted Radiation Shielding}, volume = 8, year = 2022 }
Seeger, S., Vo, H. P., Bolke, A. and Rafecas, M.: Characterisation of the Upgraded MERMAID Prototype, a PET/CT Device for Small Aquatic Animals, 1–2, 2022, DOI: 10.1109/NSS/MIC44845.2022.10399085.
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@inproceedings{10399085, author = {Seeger, Steven and Vo, Hong Phuc and Bolke, Andreas and Rafecas, Magdalena}, booktitle = {2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)}, keywords = {MERMAID}, pages = {1-2}, title = {Characterisation of the Upgraded MERMAID Prototype, a PET/CT Device for Small Aquatic Animals}, year = 2022 }
Zvolsky, M. L., Schaar, M., Seeger, S. S., Rakers, S. and Rafecas, M.: Development of a digital zebrafish phantom and its application to dedicated small-fish PET, Physics in Medicine & Biology, 67(17), 175005, 2022, DOI: 10.1088/1361-6560/ac71ee.
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@article{zvolsky2022development, author = {Zvolsky, Milan Lukas and Schaar, Moritz and Seeger, Steven Sebastian and Rakers, Sebastian and Rafecas, Magdalena}, journal = {Physics in Medicine \& Biology}, keywords = {nuci}, number = 17, pages = 175005, title = {Development of a digital zebrafish phantom and its application to dedicated small-fish {PET}}, volume = 67, year = 2022 }
Seeger, S., Elmoujarkach, E., Möller, N., Schmidt, C. and Rafecas, M.: 3D printed radioactive phantoms for Positron Emission Tomography, ID 640, 2022, DOI: 10.18416/AMMM.2022.2209640.
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@inproceedings{https://doi.org/10.18416/ammm.2022.2209640, author = {Seeger, Steven and Elmoujarkach, Ezzat and Möller, Nadine and Schmidt, Christian and Rafecas, Magdalena}, journal = {Transactions on Additive Manufacturing Meets Medicine}, keywords = {nuci}, number = {S1 (Supplement)}, pages = {ID 640}, publisher = {Transactions on Additive Manufacturing Meets Medicine}, title = {3D printed radioactive phantoms for Positron Emission Tomography}, volume = 4, year = 2022 }