Seminars in nuclear medicine最新文献

Stress radionuclide myocardial perfusion imaging (MPI) has been well-established as a useful modality for assessing the status of the coronary circulation in post-coronary artery bypass graft (CABG) patients. CABG by itself escalates progression of atherosclerosis or thrombosis in bypassed native coronary arteries. In most cases MPI will be employed in post-CABG patients who are experiencing symptoms. The major clinical question is whether there is myocardial ischemia, and if so, what is the extent and severity, and are there high-risk markers that would encourage diagnostic coronary and graft angiography. Recent important advances in MPI, including introduction of routine attenuation correction, CZT instrumentation, PET MPI, and PET quantitative blood flow have further enhanced the value of MPI for this population. The purpose of this review is to provide information on these advances relevant to the post-CABG patient, to describe common image findings, and to explore the diagnostic and prognostic significance of different findings in this unique population.

[¹⁸F]FDG PET/CT is a powerful imaging modality of high performance in multiple myeloma (MM) and is considered the appropriate method for assessing treatment response in this disease. On the other hand, due to the heterogeneous and sometimes complex patterns of bone marrow infiltration in MM, the interpretation of PET/CT can be particularly challenging, hampering interobserver reproducibility and limiting the diagnostic and prognostic ability of the modality. Although many approaches have been developed to address the issue of standardization, none can yet be considered a standard method for interpretation or objective quantification of PET/CT. Therefore, advanced diagnostic quantification approaches are needed to support and potentially guide the management of MM. In recent years, radiomics has emerged as an innovative method for high-throughput mining of image-derived features for clinical decision making, which may be particularly helpful in oncology. In addition, machine learning and deep learning, both subfields of artificial intelligence (AI) closely related to the radiomics process, have been increasingly applied to automated image analysis, offering new possibilities for a standardized evaluation of imaging modalities such as CT, PET/CT and MRI in oncology. In line with this, the initial but steadily growing literature on the application of radiomics and AI-based methods in the field of [¹⁸F]FDG PET/CT in MM has already yielded encouraging results, offering a potentially reliable tool towards optimization and standardization of interpretation in this disease. The main results of these studies are presented in this review.

Artificial intelligence (AI) has rapidly reshaped the global practice of nuclear medicine. Through this shift, the integration of AI into nuclear medicine education, clinical practice, and research has a significant impact on workforce diversity. While AI in nuclear medicine has the potential to be a powerful tool to improve clinical, research and educational practice, and to enhance patient care, careful examination of the impact of each AI tool needs to be undertaken with respect to the impact on, among other factors, diversity in the nuclear medicine workforce. Some AI tools can be used to specifically drive inclusivity and diversity of the workforce by supporting women and underrepresented minorities. Other tools, however, have the potential to negatively impact minority groups, leading to a widening of the diversity gap. This manuscript explores how various AI solutions have the potential to both negatively and positively affect diversity in the nuclear medicine workforce.