The aim of this review is to describe how various AI-supported applications are used in head and neck cancer radiotherapy treatment planning, and the impact on dose management in regards to target volume and nearby organs at risk (OARs). Literature searches were conducted in databases and publisher portals Pubmed, Science Direct, CINAHL, Ovid, and ProQuest to peer reviewed studies published between 2015 and 2021. Out of 464 potential ones, ten articles covering the topic were selected. The benefit of using deep learning-based methods to automatically segment OARs is that it makes the process more efficient producing clinically acceptable OAR doses. In some cases automated treatment planning systems can outperform traditional systems in dose prediction. Based on the selected articles, in general AI-based systems produced time savings. Also, AI-based solutions perform at the same level or better than traditional planning systems considering auto-segmentation, treatment planning and dose prediction. However, their clinical implementation into routine standard of care should be carefully validated IMPLICATIONS TO PRACTICE: AI has a primary benefit in reducing treatment planning time and improving plan quality allowing dose reduction to the OARs thereby enhancing patients' quality of life. It has a secondary benefit of reducing radiation therapists' time spent annotating thereby saving their time for e.g. patient encounters.

Peripheral artery disease (PAD) is a common and debilitating condition characterized by the narrowing of the limb arteries, primarily due to atherosclerosis. Non-invasive multi-modality imaging approaches using computed tomography (CT), magnetic resonance imaging (MRI), and nuclear imaging have emerged as valuable tools for assessing PAD atheromatous plaques and vessel walls. This review provides an overview of these different imaging techniques, their advantages, limitations, and recent advancements. In addition, this review highlights the importance of molecular markers, including those related to inflammation, endothelial dysfunction, and oxidative stress, in PAD pathophysiology. The potential of integrating molecular and imaging markers for an improved understanding of PAD is also discussed. Despite the promise of this integrative approach, there remain several challenges, including technical limitations in imaging modalities and the need for novel molecular marker discovery and validation. Addressing these challenges and embracing future directions in the field will be essential for maximizing the potential of molecular and imaging markers for improving PAD patient outcomes.

Background: Diabetic peripheral arterial disease (PAD) involves complex pathophysiology, including accelerated atherosclerosis and impaired microvascular blood flow. However, the interplay between femoral arterial inflammation, atheroma plaque formation, arterial blood flow and microvascular perfusion remains unclear. This study investigated these relationships using multimodality imaging techniques. Methods: Nine patients with diabetes and PAD and 10 healthy controls were enrolled. Participants underwent hybrid 18F-fluorodeoxyglucose PET/MRI to assess arterial inflammation and microvascular perfusion, duplex ultrasound to evaluate plaque burden and ankle–brachial index and toe–brachial index measurements to determine arterial blood flow. Microvascular perfusion was assessed using blood oxygen level-dependent and intravoxel incoherent motion MRI techniques. Results: Compared with healthy controls, PAD participants exhibited impaired microvascular perfusion, evidenced by prolonged time-to-peak, attenuated maximum T2* and reduced perfusion fraction and pseudo-diffusivity (p<0.05 for all) on blood oxygen level-dependent and intravoxel incoherent motion MRI. 18F-Fluorodeoxyglucose PET/MRI revealed a negative correlation between the maximum target-to-background ratio and toe–brachial index (ρ=−0.57; p<0.05). Although microvascular perfusion was correlated with arterial blood flow, no association was found between arterial inflammation and microvascular perfusion. Conclusions: Multimodality imaging demonstrated an interplay between arterial inflammation, atheroma plaque formation, reduced arterial blood flow and impaired microvascular perfusion in participants with diabetes and PAD. These findings provide valuable insights into the pathophysiology of diabetic PAD and support the potential for personalised disease management and treatment discovery.