Machine learning in defining computed tomography-derived fractional flow reserve

Gender Medicine in Clinical Radiology Practice

Gender Medicine is rapidly emerging as a branch of medicine that studies how many diseases common to men and women differ in terms of prevention, clinical manifestations, diagnostic-therapeutic approach, prognosis, and psychological and social impact. Nowadays, the presentation and identification of many pathological conditions pose unique diagnostic challenges. However, women have always been paradoxically underestimated in epidemiological studies, drug trials, as well as clinical trials, so many clinical conditions affecting the female population are often underestimated and/or delayed and may result in inadequate clinical management. Knowing and valuing these differences in healthcare, thus taking into account individual variability, will make it possible to ensure that each individual receives the best care through the personalization of therapies, the guarantee of diagnostic-therapeutic pathways declined according to gender, as well as through the promotion of gender-specific prevention initiatives. This article aims to assess potential gender differences in clinical-radiological practice extracted from the literature and their impact on health and healthcare. Indeed, in this context, radiomics and radiogenomics are rapidly emerging as new frontiers of imaging in precision medicine. The development of clinical practice support tools supported by artificial intelligence allows through quantitative analysis to characterize tissues noninvasively with the ultimate goal of extracting directly from images indications of disease aggressiveness, prognosis, and therapeutic response. The integration of quantitative data with gene expression and patient clinical data, with the help of structured reporting as well, will in the near future give rise to decision support models for clinical practice that will hopefully improve diagnostic accuracy and prognostic power as well as ensure a more advanced level of precision medicine.

The year 2021 in the European Heart Journal—Cardiovascular Imaging: Part I

The European Heart Journal—Cardiovascular Imaging was introduced in 2012 and has during these 10 years become one of the leading multimodality cardiovascular imaging journals. The journal is currently ranked as Number 19 among all cardiovascular journals. It has an impressive impact factor of 9.130 and our journal is well established as one of the top cardiovascular journals. The most important studies published in our Journal in 2021 will be highlighted in two reports. Part I of the review will focus on studies about myocardial function and risk prediction, myocardial ischaemia, and emerging techniques in cardiovascular imaging, while Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease.

Beyond Coronary CT Angiography: CT Fractional Flow Reserve and Perfusion

심장 전산화단층촬영은 비약적인 기술발전과 다양한 연구 결과를 바탕으로 심혈관위험 계층화와 치료 결정을 위한 관상동맥 질환의 진단과 예후 평가성능이 입증되었다. 전산화단층촬영 관상동맥조영술은 폐쇄성 관상동맥 질환에 대한 음성 예측도가 높아서 침습적 혈관조영술의 빈도를 줄일 수 있는 관상동맥 질환 관련 검사의 관문으로 부상했지만, 진단특이도가 상대적으로 낮다. 하지만 심장 전산화단층촬영을 이용한 분획혈류예비력과 심근관류를 분석하여 관상동맥 질환의 혈역학적 유의성을 확인하는 기능적 평가를 통해 그 한계를 극복할 수 있다. 최근에는 이를 보다 객관적이고 재현 가능하도록 인공지능을 접목하는 연구들이 활발히 진행되고 있다. 본 종설에서는 심장 전산화단층촬영의 기능적 영상화 기법들에 대해 알아보고자 한다.