First Positronium Imaging Using 44Sc With the J-PET Scanner: a Case Study on the NEMA-Image Quality Phantom
Manish Das, Sushil Sharma, Ermias Yitayew Beyene, Aleksander Bilewicz, Jarosław Choiński, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Kavya Valsan Eliyan, Jakub Hajduga, Sharareh Jalali, Krzysztof Kacprzak, Tevfik Kaplanoglu, Łukasz Kapłon, Kamila Kasperska, Aleksander Khreptak, Grzegorz Korcyl, Tomasz Kozik, Karol Kubat, Deepak Kumar, Anoop Kunimmal Venadan, Edward Lisowski, Filip Lisowski, Justyna Medrala Sowa, Simbarashe Moyo, Wiktor Mryka, Szymon Niedźwiecki, Piyush Pandey, Szymon Parzych, Alessio Porcelli, Bartłomiej Rachwał, Elena Perez del Rio, Martin Rädler, Axel Rominger, Kuangyu Shi, Magdalena Skurzok, Anna Stolarz, Tomasz Szumlak, Pooja Tanty, Keyvan Tayefi Ardebili, Satyam Tiwari, Rafał Walczak, Ewa Ł. Stępień, Paweł Moskal
abstract
Positronium Lifetime Imaging (PLI), an emerging extension of conventional positron emission tomography (PET) imaging, offers a novel window for probing the submolecular properties of biological tissues by imaging the mean lifetime of the positronium atom. Currently, the method is under rapid development in terms of reconstruction and detection systems. Recently, the first in vivo PLI of the human brain was performed using the J-PET scanner utilizing the 68Ga isotope. However, this isotope has limitations due to its comparatively low prompt gamma yields, which is crucial for positronium lifetime measurement. Among alternative radionuclides, 44Sc stands out as a promising isotope for PLI, characterized by a clinically suitable half-life (4.04 hours) emitting 1157 keV prompt gamma in 100% cases after the emission of the positron. This study reports the first experimental demonstration of PLI with 44Sc, carried out on a NEMA-Image Quality (IQ) phantom using the Modular J-PET tomograph?the first plastic scintillators-based PET scanner.
muPPET: Investigating the Muon Puzzle with J-PET Detectors
A. Porcelli, K. Valsan Eliyan, G. Moskal, N. Nasrin Protiti, D. L. Sirghi, E. Yitayew Beyene, N. Chug, C. Curceanu, E. Czerwiński, M. Das, M. Gorgol, J. Hajduga, S. Jalali, B. Jasińska, K. Kacprzak, T. Kaplanoglu, Ł. Kapłon, K. Kasperska, A. Khreptak, G. Korcyl, T. Kozik, D. Kumar, K. Kubat, E. Lisowski, F. Lisowski, J. Mędrala-Sowa, W. Mryka, S. Moyo, S. Niedźwiecki, S. Parzych, P. Pandey, E. Perez del Rio, B. Rachwał, M. Rädler, S. Sharma, M. Skurzok, E. Ł. Stępień, T. Szumlak, P. Tanty, K. Tayefi Ardebili, S. Tiwari, and P. Moskal
abstract
The muPPET [muon Probe with J-PET] project aims to investigate the Muon
Puzzle seen in cosmic ray air showers. This puzzle arises from the observation of a significantly
larger number of muons on Earth's surface than that predicted by the current
theoretical models. The investigated hypothesis is based on recently observed asymmetries
in the parameters for the strong interaction cross-section and trajectory of an outgoing particle
due to projectile-target polarization. The measurements require detailed information
about muons at the ground level, including their track and charge distributions. To achieve
this, the two PET scanners developed at the Jagiellonian University in Krakow (Poland),
the J-PET detectors, will be employed, taking advantage of their well-known resolution
and convenient location for detecting muons that reach long depths in the atmosphere.
One station will be used as a muon tracker, while the second will reconstruct the core of
the air shower. In parallel, the existing hadronic interaction models will be modified and
fine-tuned based on the experimental results. In this work, we present the conceptualization
and preliminary designs of muPPET.
Medical imaging data analysis using 3D deep learning models towards improving the individual treatment plans
K. Kalecińska, T. Fiutowski, P. Jurgielewicz, D. Kabat, B. Rachwał, Ł. Kapłon, M. Kopeć, S. Koperny, D. Kulig, J. Moroń, G. Moskal, A. Ruciński, P. Wiącek, B. Mindur, T. Szumlak
abstract
This work is a part of a research project aiming at delivering the next generation active medical phantom, Dose-3D, with high spatial granulation for quasi-real time measurement of the volumetric radiotherapeutic dose deposited during photon therapy. The preliminary results, discussed here, pertain to the intelligent medical data augmentation using Generative Adversarial Networks (GANs) technique implemented inside MONAI framework. However, in the scope of the project, we perform a broad search for the most efficient and advanced Deep Learning (DL) models to create tools for 3D Computed Tomography (CT) images segmentation and cancer diagnosis improvement that will be an integral part of the custom designed software platform for processing data collected with Dose-3D phantom. Apart from the innovative detection system the software itself may prove to be disruptive in the context of the currently available tools by offering open-source high quality toolkit for wide use in everyday clinical applications.
Simulation studies of a brain PET insert for the total body J-PET tomograph
Simulation studies of a brain PET insert for the total body J-PET tomograph M. Rädler, E. Y. Beyene, A. Bilewicz, J. Choiński, N. Chug, C. Curceanu, E. Czerwiński, M. Das, J. Hajduga, S. Jalali, T. Kaplanoglu, Ł. Kapłon, A. Khreptak, G. Korcyl, K. Kubat, D. Kumar, A. Kunimmal Venadan, E. Lisowski, F. Lisowski, J. Mędrala-Sowa, S. Moyo, W. Mryka, S. Niedźwiecki, P. Pandey, S. Parzych, A. Porcelli, B. Rachwał, E. P. d. Río, S. Sharma, M. Skurzok, A. Stolarz, T. Szumlak, S. Tiwari, P. Tanty, K. Tayefi Ardebili, K. Valsan Eliyan, R. Walczak, E. Ł. Stępień, P. Moskal
IEEE NSS MIC RTSD in Yokohama
