Objectives – To assess midbrain atrophy through morphometric (linear, surface and volumetric) measurements in patients with clinically diagnosed progressive supranuclear palsy (PSP) and to establish the most accurate measure to be implemented in routine magnetic resonance (MR) protocol in distinguishing PSP from healthy subjects and MSA‐p (multiple system atrophy, parkinsonian form) patients. Materials and methods – We studied 15 patients with the diagnosis of probable PSP, seven patients with the diagnosis of probable MSA‐p and 14 age‐matched healthy volunteers. MR protocol includes a sagittal SE T1‐weighted sequence for cross‐sectional area and linear brainstem measurements and a 3D‐FSPGR sequence for brainstem volume measurements. Results – A highly significant difference in the antero‐posterior midbrain diameter, area and volume in PSP compared with control subjects was found. Only a measurement of the midbrain area and pons area enabled one to distinguish between PSP and MSA‐p. Receiver operating characteristic analysis revealed that the midbrain area has the highest diagnostic accuracy in distinguishing between PSP and other conditions, with a sensitivity of 100% and specificity of 90.5%. The addition of the midbrain area/pons area ratio (A_ms/A_pn ratio) measurement improves the specificity in distinguishing between PSP and MSA. Conclusions – Morphological indexes indicate midbrain atrophy in PSP patients The combination of the A_ms and A_ms/A_pn ratio measurements allows to discriminate between PSP and other conditions.

Artificial intelligence (AI) has seen dramatic growth over the past decade, evolving from a niche super specialty computer application into a powerful tool which has revolutionized many areas of our professional and daily lives, and the potential of which seems to be still largely untapped. The field of medicine and medical imaging, as one of its various specialties, has gained considerable benefit from AI, including improved diagnostic accuracy and the possibility of predicting individual patient outcomes and options of more personalized treatment. It should be noted that this process can actively support the ongoing development of advanced, highly specific treatment strategies (e.g., target therapies for cancer patients) while enabling faster workflow and more efficient use of healthcare resources. The potential advantages of AI over conventional methods have made it attractive for physicians and other healthcare stakeholders, raising much interest in both the research and the industry communities. However, the fast development of AI has unveiled its potential for disrupting the work of healthcare professionals, spawning concerns among radiologists that, in the future, AI may outperform them, thus damaging their reputations or putting their jobs at risk. Furthermore, this development has raised relevant psychological, ethical, and medico-legal issues which need to be addressed for AI to be considered fully capable of patient management. The aim of this review is to provide a brief, hopefully exhaustive, overview of the state of the art of AI systems regarding medical imaging, with a special focus on how AI and the entire healthcare environment should be prepared to accomplish the goal of a more advanced human-centered world.

Objectives To evaluate radiation protection basic knowledge and dose assessment for radiological procedures among Italian radiographers Methods A validated questionnaire was distributed to 780 participants with balanced demographic characteristics and geographic distribution. Results Only 12.1 % of participants attended radiation protection courses on a regular basis. Despite 90 % of radiographers stating to have sufficient awareness of radiation protection issues, most of them underestimated the radiation dose of almost all radiological procedures. About 5 % and 4 % of the participants, respectively, claimed that pelvis magnetic resonance imaging and abdominal ultrasound exposed patients to radiation. On the contrary, 7.0 % of the radiographers stated that mammography does not use ionising radiation. About half of participants believed that radiation-induced cancer is not dependent on age or gender and were not able to differentiate between deterministic and stochastic effects. Young radiographers (with less than 3 years of experience) showed a higher level of knowledge compared with the more experienced radiographers. Conclusions There is a substantial need for radiographers to improve their awareness of radiation protection issues and their knowledge of radiological procedures. Specific actions such as regular training courses for both undergraduate and postgraduate students as well as for working radiographers must be considered in order to assure patient safety during radiological examinations. Main messages • Radiographers should improve their knowledge on radiation protection issues. • Only 12.1 % of participants attended radiation protection courses on a regular basis. • Specific actions must be considered in order to increase knowledge and awareness.