Artificial intelligence (AI) in medical imaging is a potentially disruptive technology. An understanding of the principles and application of radiomics, artificial neural networks, machine learning, and deep learning is an essential foundation to weave design solutions that accommodate ethical and regulatory requirements, and to craft AIbased algorithms that enhance outcomes, quality, and efficiency. Moreover, a more holistic perspective of applications, opportunities, and challenges from a programmatic perspective contributes to ethical and sustainable implementation of AI solutions.

The COVID-19 crisis has caused a number of significant challenges to the higher education sector. Universities worldwide have been forced to rapidly transition to online delivery, working at home, and disruption to research while concurrently facing the longer-term impacts in institution financial reform. Here, the impact of COVID-19 on academic staff in the medical radiation science (MRS) teaching team at Charles Sturt University are explored. While COVID-19 imposes potentially the greatest challenge many of us will experience in our personal and professional lifetimes, it also affords the opportunity to objectively re-evaluate and, where appropriate, re-design learning and teaching in higher education. Technology has allowed rapid assimilation to online learning environments with additional benefits that allow flexible, mobile, agile, sustainable, culturally safe and equitable learning focussed educational environments in the post-COVID-19 “new normal”.

Objective:This review aims to arm readers with a deep understanding of pharmacokinetics of digoxin.Data Sources:Pharmacology and pharmacokinetic references texts, and peer reviewed medical journal manuscripts indexed on Medline included based on currency, accuracy and appropriateness.Results:Physiologic changes and disease associated with aging have an impact on pharmacokinetics and pharmacodynamics of medications. Altered drug response and increased adverse reactions are common amongst the elderly. The narrow therapeutic index of digoxin and pharmacokinetic changes associated with aging increases the risk of toxicity. In the aging population, a number of factors combine to increase the risk, severity and likelihood of hospitalisation or death due to adverse drug effects: changes to absorption, distribution, metabolism and excretion,increased susceptibility to drug sensitivity,co-existing pathology,polypharmacy.Conclusion:A thorough understanding of digoxin pharmacokinetics in the older person is essential for improved therapeutic outcomes, improved compliance, reduced morbidity and improved quality of life.

Complete the test online no later than December 2022. Your online test will be scored immediately. You may make 3 attempts to pass the test and must answer 80% of the questions correctly to receive 1.0 CEH (Continuing Education Hour) credit. SNMMI members will have their CEH credit added to their VOICE transcript automatically; nonmembers will be able to print out a CE certificate upon successfully completing the test. The online test is free to SNMMI members; nonmembers must pay $15.00 by credit card when logging onto the website to take the test. The emergence of artificial intelligence (AI) in nuclear medicine and radiology has been accompanied by AI commentators and experts predicting that AI would make radiologists, in particular, extinct. More realistic perspectives suggest significant changes will occur in medical practice. There is no escaping the disruptive technology associated with AI, neural networks, and deep learning, the most significant perhaps since the early days of Roentgen, Becquerel, and Curie. AI is an omen, but it need not be foreshadowing a negative event; rather, it is heralding great opportunity. The key to sustainability lies not in resisting AI but in having a deep understanding and exploiting the capabilities of AI in nuclear medicine while mastering those capabilities unique to the human resources.

There is an emerging need for greater understanding of pharmacology principles among technical staff. Indeed, the responsibility of dose preparation and administration, under any level of supervision, demands a foundational understanding of pharmacology. This is true for radiopharmaceuticals, contrast media, and pharmaceutical interventions or adjunctive medications. Regulation around the same might suggest a need to embed pharmacology theory in undergraduate education programs, and there is a need to disseminate that same foundational understanding to practicing clinicians. Moreover, pharmacology foundations can provide a key understanding of the principles that underpin quantitative techniques (e.g., pharmacokinetics). This article is the first in a series that aims to enhance the understanding of pharmacologic principles relevant to nuclear medicine. This article will deal with the introductory concepts, terminology, and principles that underpin the concepts to be discussed in the remainder of the series. The second article will build on the pharmacodynamic principles examined in this article with a treatment of pharmacokinetics. Article 3 will outline pharmacology relevant to pharmaceutical interventions and adjunctive medications used in general nuclear medicine, article 4 will cover pharmacology relevant to pharmaceutical interventions and adjunctive medications used in nuclear cardiology, and article 5 will discuss the pharmacology related to contrast media associated with CT and MRI. The final article (6) in the series will examine the pharmacology of drugs associated with the crash cart/emergency trolley.

Pharmacology principles provide a key understanding that underpins the clinical and research roles of nuclear medicine practitioners. This article is the second in a series of articles that aims to enhance the understanding of pharmacologic principles relevant to nuclear medicine. This article will build on the introductory concepts, terminology, and principles of pharmacodynamics explored in the first article in the series. Specifically, this article will focus on the basic principles associated with pharmacokinetics. Article 3 will outline pharmacology relevant to pharmaceutical interventions and adjunctive medications used in general nuclear medicine; article 4, pharmacology relevant to pharmaceutical interventions and adjunctive medications used in nuclear cardiology; article 5, pharmacology relevant to contrast media associated with CT and MRI; and article 6, drugs in the emergency cart.

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Artificial intelligence (AI) in nuclear medicine and radiology represents a significant disruptive technology. Although there has been much debate about the impact of AI on the careers of radiologists, the opportunities in nuclear medicine enhance the capability of the physician and at the same time have an impact on the responsibilities of physicists and technologists. This transformative technology requires insight into the principles and opportunities for seamless assimilation into practice without the associated displacement of human resources. This article introduces the current clinical applications of machine learning and deep learning.