Nuclear medicine has acquired a crucial role in the management of patients with neuroendocrine neoplasms (NENs) by improving the accuracy of diagnosis and staging as well as their risk stratification and personalized therapies, including radioligand therapies (RLT). Artificial intelligence (AI) and radiomics can enable physicians to further improve the overall efficiency and accuracy of the use of these tools in both diagnostic and therapeutic settings by improving the prediction of the tumor grade, differential diagnosis from other malignancies, assessment of tumor behavior and aggressiveness, and prediction of treatment response. This systematic review aims to describe the state-of-the-art AI and radiomics applications in the molecular imaging of NENs.
View Article and Find Full Text PDFPurpose: Different methods are available to identify haematopoietically active bone marrow (ActBM). However, their use can be challenging for radiotherapy routine treatments, since they require specific equipment and dedicated time. A machine learning (ML) approach, based on radiomic features as inputs to three different classifiers, was applied to computed tomography (CT) images to identify haematopoietically active bone marrow in anal cancer patients.
View Article and Find Full Text PDFRadiotherapy accelerators have undergone continuous technological developments. We investigated the differences between Radixactâ„¢ and VMAT treatment plans. Sixty patients were included in this study.
View Article and Find Full Text PDFThis work deals with the durability of a wood impregnated with alumina (AlO) particles. The samples were impregnated at three different AlO weight fractions (c.a.
View Article and Find Full Text PDFIntroduction: Catheter ablation (CA) is the current standard of care for patients suffering drug-refractory monomorphic ventricular tachycardias (MMVTs). Yet, despite significant technological improvements, recurrences remain common, leading to increased morbidity and mortality. Stereotactic arrhythmia radioablation (STAR) is increasingly being adopted to overcome the limitations of conventional CA, but its safety and efficacy are still under evaluation.
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