Protein-Functionalized and Intrinsically Radiolabeled [188Re]ReOx Nanoparticles: Breakthrough Application in Multimodal Synergistic Cancer Therapy Cancer remains one of the leading causes of death globally, despite significant progress in medical science over the past few decades. However, early detection and treatment methods still face significan...

Breakthrough Applications of Generative Artificial Intelligence in Nuclear Medicine: Exploring the Potential of Synthetic Bone Scintigraphy Images and Their Application in Deep Learning Background and Research Questions In recent years, the rapid development of Artificial Intelligence (AI) has revolutionized medical imaging analysis. For instance, ...

Development of a Molecular Probe for Tumor-Associated Protein Mesothelin Based on PET Imaging Technology Research Background In recent years, mesothelin (MSLN) has become a key focus in cancer research and diagnostics. Mesothelin is a membrane-bound glycoprotein highly expressed on the surface of various malignancies, including ovarian, pancreatic,...

In-depth Analysis of PSMA PET/CT-based Multimodal Deep Learning Model for Predicting Lymph Node Metastases in Prostate Cancer Patients Background Prostate cancer (PCA) is one of the most common malignant tumors in men and a leading cause of cancer-related deaths. In clinically localized prostate cancer patients, extended pelvic lymph node dissectio...

Multimodal Neuroimaging Study on Cognitive Impairment in Parkinson’s Disease Parkinson’s Disease (PD) is a common neurodegenerative disorder mainly characterized by motor impairments. However, cognitive impairment (CI), one of the non-motor symptoms, significantly affects patients’ quality of life. According to extensive epidemiological studies, ap...

Breakthrough in Nuclear Medicine and Molecular Imaging: European Study Reveals Application of One-Day Dual-Tracer PET/CT Imaging in Neuroendocrine Tumors In the field of nuclear medicine, neuroendocrine neoplasms (NENs), known for their heterogeneity and complexity, have consistently been a focal point of research. A team from Tübingen, Germany, ha...

A Transformer Model Integrating PET Imaging and Clinical Data: A Multicenter Digital Biopsy Study for Predicting Pathological Grading and Prognosis of Follicular Lymphoma Academic Background Follicular Lymphoma (FL) is the most common indolent Non-Hodgkin Lymphoma in Western countries, accounting for approximately 30% of newly diagnosed cases. Acco...

Revealing Gene Expression Patterns Associated with Synaptic Density Network Dysfunction in Temporal Lobe Epilepsy Background Temporal Lobe Epilepsy (TLE) is the most common form of focal epilepsy, and its pathological features and mechanisms have long drawn extensive attention in the field of neuroscience. This disorder involves not only a single b...

Background In recent years, significant progress has been made in the field of cancer diagnosis and treatment, particularly in technologies based on molecular imaging and targeted radiotherapy. Among these, Fibroblast Activation Protein (FAP), a biomarker highly expressed in the tumor microenvironment, has garnered widespread attention. FAP is prim...

Application of Explainable Machine Learning in Amino Acid PET Imaging for Glioma Diagnosis Academic Background Gliomas are among the most common malignant tumors of the central nervous system, with their diagnosis and treatment strategies typically relying on histopathological analysis. However, histopathology has limitations such as being highly i...