Swiss Nuclear Doctors

Exploring the "Rosary Sign" in Nuclear Medicine Thrilled to announce the publication of our latest contribution to Diagnostics: "Rosary Sign at Somatostatin Receptor PET in a Case of Recurrent Meningioma." This case highlights a novel imaging pattern that enhances diagnostic precision for recurrent meningiomas and addresses the potential role of PRRT as a therapeutic option. A sincere thank you to the team for their cooperation in creating this interesting image. Link in the first comment. #NuclearMedicine #Diagnostic #Meningioma #PETimaging

🔬✨ Exploring Total-Body PET/CT: Insights from Stanford’s Cancer Seminar Series ✨🔬 We’re thrilled to feature a remarkable talk delivered by Dr. Lorenzo nardo Chief of Nuclear Medicine at UC Davis Health, as part of the prestigious Stanford University Cancer Seminar Series. This presentation underscores the transformative potential of Total-Body PET/CT and showcases collaborative research between Inselspital Bern (Insel Gruppe) and UC Davis, utilizing Long-Axial Field-of-View (LAFOV) systems. 🌍🤝 🔹 Why This Talk Matters: • Clinical Innovation: Dr. Nardo highlights how Total-Body PET/CT can revolutionize oncological imaging, diagnostics, and therapy planning. • Collaborative Research: Findings from LAFOV systems at Bern and Davis illustrate the power of cross-institutional teamwork in advancing nuclear medicine. • Global Expertise: This partnership demonstrates the importance of international collaboration in driving innovation for improved patient care. 🎥 Don’t miss this insightful talk! Watch it here: https://lnkd.in/eh4DRDDC 🔗 Catch up on past seminars: https://lnkd.in/eTxvpmbm 🗓️ Register for upcoming events: https://lnkd.in/eZCqX_vu 👏 A heartfelt thank you to Stanford University School of Medicine for organizing such outstanding conferences and fostering meaningful dialogue in the global nuclear medicine and cancer research communities. 🙏 Special thanks to Dr. Clemens Mingels, MD from Inselspital Bern for bringing this fantastic talk to our attention! #NuclearMedicine #TotalBodyPET #MedicalImaging #CancerResearch #LAFOV #StanfordCancerSeminars #UCDavis #GlobalCollaboration

🔬✨ The Role of PET-CT in Diagnosing Infections in Cardiac Devices and Prosthetic Valves ✨🔬 We’re excited to share a new preprint by Tardu Özkartal and a dedicated team from the Istituto Cardiocentro Ticino - EOC Ente Ospedaliero Cantonale and the USI Università della Svizzera italiana Published in Heart Rhythm, this study investigates the potential of 18F-FDG PET/CT to enhance diagnostic accuracy in patients with bloodstream infections (BSI) and cardiac implantable electronic devices (CIEDs) or prosthetic heart valves. 🫀📊 🔹 Study Insights and Methodology: Cohort: This study included 27 patients with BSI who underwent PET-CT, divided into two groups: patients with CIEDs only and those with CIEDs + prosthetic valves. Challenges in Diagnosis: Differentiating between device infections and valve endocarditis is critical for determining appropriate treatment strategies. PET-CT Evaluation: PET-CT was performed after a median of 16 days post-BSI diagnosis to identify infection sources, complemented by other diagnostic tools like echocardiography. 🔹 Key Findings: Device vs. Valve Infections: In patients with prosthetic valves, BSIs were more often associated with valve endocarditis (77%) than with CIED infection. Conversely, in CIED-only patients, device infections were significantly more common (57%). Non-Cardiac Infections: PET-CT identified non-cardiac infections in 10 cases, mostly in the CIED-only group. Clinical Implications: PET-CT helped avoid unnecessary device extractions in many cases and guided antibiotic-only treatments successfully in 70% of valve endocarditis cases. 🔹 Future Directions: This study underscores the value of PET-CT in guiding personalized care for complex cases of bloodstream infections. The authors highlight the need for larger, prospective studies to refine clinical recommendations further. 👏 Congratulations to Dr. Özkartal, Dr. Ceriani, and the team for advancing the diagnostic capabilities of nuclear imaging in cardiology! 🔗 Read the preprint: https://lnkd.in/e6_Tfys2 #NuclearMedicine #Cardiology #PETCT #MedicalImaging #InfectionManagement #ProstheticValves #PersonalizedMedicine

🔬✨ Advocating for Whole-Body Staging in High-Grade Meningiomas: An Open Letter ✨🔬 We’re excited to highlight a compelling open letter from Dr. Ekin Ermiş and colleagues at Bern University Hospital (Insel Gruppe) recently published in the Journal of Nuclear Medicine. This commentary calls for a reevaluation of current practices, proposing the routine use of [68Ga]Ga-DOTATOC PET/CT for whole-body staging in high-grade meningiomas. 🧠📊 🔹 The Case for Change: Current Limitations: Despite their aggressive nature, high-grade meningiomas are typically considered localized, with limited emphasis on identifying extracranial metastases. Clinical Insights: The authors present compelling examples where whole-body [68Ga]Ga-DOTATOC PET/CT identified metastatic disease (e.g., spine, lungs) that had a direct impact on patient management. 🔹 Why It Matters: Management Implications: Accurate staging can guide more personalized treatment strategies, such as radiotherapy for spinal metastases or systemic therapy using [177Lu]Lu-DOTATOC. Future Directions: With advancements in PET/CT technology, the authors advocate for systematic whole-body staging for metastatic risk stratification in high-grade meningiomas. This thought-provoking piece challenges conventional approaches, urging clinicians and researchers to adopt a broader perspective on staging and management of aggressive meningiomas. 👏 Congratulations to Dr. Ermiş, Dr. Nicolas Bachmann, Dr. Katharina Lutz and Dr. Thomas Pykafor sparking this important conversation in the nuclear medicine and oncology communities! 🔗 Read the open letter: https://lnkd.in/e-Ys98D9

Funny way to illustrate distribution of unspecific bone uptakes (UBU) in PSMA imaging in this new paper 🤪 👏 https://lnkd.in/dBk-7-Z6

🔬✨DAT PET-to-SPECT Translation with CycleGAN ✨🔬 We’re excited to share a groundbreaking international study led by Leonor Lopes Lopes, Dr. Kuangyu Shi, and collaborators from Insel Gruppe and Fudan University, Shanghai, recently published in the European Journal of Nuclear Medicine and Molecular Imaging. This work introduces a CycleGAN-based AI approach to translate dopaminergic PET images to SPECT, paving the way for multicenter studies and advancing Parkinson’s disease (PD) diagnostics globally. 🧠🤖 🔹 Study Insights and Methodology: • Challenge: PET imaging ([11C]CFT) and SPECT ([123I]FP-CIT) are widely used for diagnosing Parkinson’s disease and atypical parkinsonian syndromes (APS). However, the difference in imaging modalities complicates data comparison and AI model training across centers. • Solution: A CycleGAN model was developed to synthesize SPECT images from PET data, using unpaired datasets from Huashan Hospital in Shanghai and PPMI. This innovative approach ensures modality compatibility without requiring paired imaging data. • Validation: The synthetic SPECT images were assessed for visual fidelity, semi-quantitative accuracy, and AI-based classification performance. 🔹 Key Findings: • High Visual and Statistical Accuracy: Synthetic SPECT images closely mirrored real SPECT images based on Fréchet Inception Distance (FID) and expert visual evaluation. • AI Classification Success: Models trained on synthetic SPECT achieved 97.2% sensitivity and 90.0% specificity for diagnosing Parkinson’s disease from real SPECT images. • Clinical Potential: This cross-modality synthesis preserves disease-specific features, such as striatal binding loss, supporting studies that integrate PET and SPECT for Parkinsonian disorders. 👏 Congratulations to Leonor Lopes, Dr. Kuangyu Shi, and the Swiss-Chinese research team for their innovative contribution to global nuclear medicine and AI-driven diagnostics! 🔗 Read the full study: https://lnkd.in/evPJ52nh 📂 Explore the GitHub Repository: https://lnkd.in/eRfrmJXB #NuclearMedicine #AI #ParkinsonsDisease #MedicalImaging #DeepLearning #PET #SPECT #CycleGAN #SwissResearch #GlobalCollaboration

🔬✨ Refining Quantification in Bone SPECT/CT Imaging ✨🔬 We’re thrilled to share an innovative study published in EJNMMI Research, supervised by Prof. Burger Irene from University Hospital Zurich, and led by Tiberiu Damian with a multidisciplinary team from Kantonsspital Baden AG. This research explores whether a new normalization approach can improve the accuracy of [99mTc]Tc-HDP bone SPECT/CT quantification compared to the traditional body weight-based SUV approach. 🧠📊 🔹 Study Insights and Methodology: • Challenge: Standard SUV calculations in SPECT/CT often lead to inaccuracies, particularly in obese patients, due to their dependence on body weight (BW). • Approach: This retrospective study analyzed SPECT/CT data from 119 patients, using bone density (Hounsfield Units), weight, and age to develop a more robust normalization formula. • Advanced Modeling: A mixed-effects model incorporated multiple patient-specific factors to refine quantification and reduce variability in tracer uptake values. 🔹 Key Findings: • Improved Normalization: The new formula, accounting for weight, bone density, and age, significantly reduced interindividual variability compared to the BW-based SUV method. • Clinical Implications: This enhanced accuracy could improve the diagnostic and therapeutic application of quantitative bone SPECT/CT, especially in orthopedics and oncology. • Limitations: Despite improvements, strong patient-specific factors suggest the need for individualized approaches rather than a generalized formula. 👏 Congratulations to Prof. Burger, Damian Tiberiu, and the entire team for their contribution to advancing quantitative imaging! 🔗 Read the full study: https://lnkd.in/ert9_Nea #NuclearMedicine #BoneImaging #SPECTCT #QuantitativeImaging #MedicalResearch #PersonalizedMedicine

🔬✨ Enhancing Visual Assessments in Amyloid PET Imaging with Quantification ✨🔬 We’re excited to share key insights from the AMYPAD Diagnostic and Patient Management Study, a pan-European clinical trial that highlights the value of quantification in supporting visual assessment of challenging amyloid PET scans. Led by Lyduine Collij and an international team of experts, including Prof. Valentina GARIBOTTO and Prof. Giovanni Frisoni from Geneva University Hospitals, this study was recently published in the Journal of Nuclear Medicine. 🧠📊 🔹 Study Insights and Methodology: Cohort: The study analyzed 741 participants across the Alzheimer’s disease spectrum, including subjective cognitive decline, mild cognitive impairment (MCI), and dementia, with enriched sampling of challenging cases. Innovative Quantification: The research employed the AmyPype pipeline to calculate Centiloid metrics and regional z-scores from PET images, providing standardized amyloid burden assessments. Visual Assessment: Certified independent readers evaluated scans, with confidence ratings captured before and after quantitative results were disclosed. 🔹 Key Findings: Improved Reader Confidence: Quantification significantly boosted reader confidence (mean score: 4.0 → 4.34) and agreement (Fleiss' kappa: 0.65 → 0.74). Support in Challenging Cases: Quantitative results were deemed supportive in 70% of visual assessments, especially for scans in the “gray zone” (Centiloids 10–30). Clinical Relevance: With the advent of anti-amyloid therapies using Centiloid thresholds for eligibility, quantification ensures higher diagnostic certainty, aiding treatment decisions and improving patient outcomes. 👏 Congratulations to Lyduine Collij, Prof. Garibotto, Prof. Frisoni, and the entire AMYPAD team for this critical advancement in molecular imaging and Alzheimer’s research! 🔗 Read the study: https://lnkd.in/epgwYMgR

Gero-Theranostics: Pioneering the Future of Aging and Precision Medicine! What if aging didn’t have to mean a decline in health? The latest E Patient dives into Gero-Theranostics—a revolutionary field blending #nuclearmedicine, #theranostics, and #geroscience to tackle age-related diseases with unprecedented precision! Authored by THE leading experts Dr. Jean-Luc C. Urbain, Dr. John Prior, Dr. Andrew Ross, and Dr. Francois Lamoureux, this article uncovers how advanced diagnostics and targeted therapies are helping manage conditions like cardiovascular disease, cancer, and neurodegenerative disorders—paving the way for healthier, longer lives. #WhyThisMatters: • Theranostics in Action: The fusion of therapy and diagnostics to tailor treatments down to the cellular level. • Breakthrough Aging Research: Using nuclear medicine to understand and potentially slow down age-related diseases. • Precision Medicine Impact: Empowering clinicians with the tools to enhance patient outcomes through highly targeted therapies. Whether you’re a healthcare professional, researcher, or simply curious about the future of #aging, this piece is a must-read! Dive into how Gero-#Theranostics is transforming medical care for aging populations worldwide. Help #spreadtheword! Like, follow, and share to bring this innovative field to more eyes. #GeroTheranostics #LongevityScience #NuclearMedicine #PrecisionMedicine #EPatient #Theranostics #FutureOfHealth #ShareToInspire

🔬✨ CT-Less Organ Segmentation in PET: A Deep Learning Preprint ✨🔬 We’re excited to share a preprint led by Yazdan Salimi from Geneva University Hospital, under supervision from Prof. Habib Zaidi, and Dr. Ismini Mainta, proposing a groundbreaking approach to multi-organ segmentation in PET imaging without the need for CT. 🧠📊 🔹 Study Overview: Traditional segmentation in PET imaging relies heavily on CT, but CT-PET alignment issues and PET-only workflows can limit its effectiveness. This study introduces a CT-independent deep learning model using PET emission data alone, addressing these challenges head-on. Models and Data: Advanced nnU-Net models were trained and tested on a dataset of over 2,000 PET/CT images, focusing on 18F-FDG and 68Ga-PSMA tracers. Innovation: By eliminating CT reliance, this pipeline enables consistent, accurate organ segmentation, even in PET-only environments. 🚀 🔹 Key Findings: High Accuracy: Achieved Dice coefficients of 0.81–0.82 for 18F-FDG and 0.77–0.79 for 68Ga-PSMA, with strong performance in organs like the brain and lungs. Versatility: Supports applications in dosimetry, kinetic modeling, and radiomics, expanding the utility of PET imaging in clinical and research settings. GitHub Access: The authors have made their repository publicly available for exploration and feedback — try it out here: 🔗 https://lnkd.in/ejhkigVx 👏 We wish this preprint success in finding a peer-reviewed journal for publication and invite the community to explore and engage with this exciting new approach! 🔗 Read the preprint: https://lnkd.in/eC9HkqNg #NuclearMedicine #DeepLearning #PETImaging #MedicalImaging #ArtificialIntelligence #OrganSegmentation #SwissResearch #OpenScience