Nuklearmedizin-nuclear Medicine最新文献

The cumulative activity map estimation are essential tools for patient specific dosimetry with high accuracy, which is estimated using biokinetic models instead of patient dynamic data or the number of static PET scans, owing to economical and time-consuming points of view. In the era of deep learning applications in medicine, the pix-to-pix (p2 p) GAN neural networks play a significant role in image translation between imaging modalities. In this pilot study, we extended the p2 p GAN networks to generate PET images of patients at different times according to a 60 min scan time after the injection of F-18 FDG. In this regard, the study was conducted in two sections: phantom and patient studies. In the phantom study section, the SSIM, PSNR, and MSE metric results of the generated images varied from 0.98-0.99, 31-34 and 1-2 respectively and the fine-tuned Resnet-50 network classified the different timing images with high performance. In the patient study, these values varied from 0.88-0.93, 36-41 and 1.7-2.2, respectively and the classification network classified the generated images in the true group with high accuracy. The results of phantom studies showed high values of evaluation metrics owing to ideal image quality conditions. However, in the patient study, promising results were achieved which showed that the image quality and training data number affected the network performance. This study aims to assess the feasibility of p2 p GAN network application for different timing image generation.

Aim: In various medical societies, dedicated young talent sections provide an important basis for promoting young members. However, the German Society of Nuclear Medicine (DGN) had not yet implemented such a section. Therefore, the aim of this work was to assess the opinion of nuclear medicine professionals in Germany on establishing a young talent section within the DGN ("Young DGN").

Methods: An initiative group of young DGN members developed a survey questionnaire comprising 18 questions. The questionnaire was initially sent as a PDF to the members of the DGN University Committee (Hochschulausschuss) by e-mail on 10/12/2021. As an online survey, the questionnaire was then emailed at four additional time points between 12/23/2021 and 3/18/2022 via the DGN eBrief and on 2/23/2022 to the members of the mailing list of the Berufsverband Deutscher Nuklearmediziner (BDN).

Results: The survey closed on 3/31/2022 with 111 responses (n=104 online surveys, n=7 PDFs). The median age of participants was 32.5 years (range, 20-80). 86% of participants indicated that they were interested in a Young DGN section, of which 67% were willing to participate. 79% indicated that nuclear medicine was an exciting field for them. 96% expressed interest in additional education offers and 60% in the establishment of a mentoring program. 75% believed that Young DGN would improve the visibility of the specialty.

Conclusion: The survey results indicate strong support for the establishment of a young talent section within the DGN among nuclear medicine professionals in Germany. A large proportion of those who participated in the survey would envision active involvement. There was a particular consensus on the desire to expand the range of education and training activities.

More prevalent in women than men, Antisynthetase Syndrome is a rare and poorly defined autoimmune disease associated with interstitial lung disease, polymyositis, and dermatomyositis. In addition to various diagnostic tools, imaging modalities are needed in certain situations. A 42-year-old woman with Anti-Jo-1-positive Antisynthetase Syndrome presented with thoracic muscular pain. She underwent whole-body Fluorodeoxyglucose positron emission tomography/computed tomography (F18-FDG PET/CT) to evaluate the total extent of the muscles affected. Depicting symptomatic symmetric myositis of the intercostal muscles, F18-FDG PET/CT additionally revealed unusually extensive fasciitis of the lower extremities.