Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR)

Abstract: Observer-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions

U-survival for prognostic prediction of disease progression and mortality of patients with COVID-19

The rapid increase of patients with coronavirus disease 2019 (COVID-19) has introduced major challenges to healthcare services worldwide. Therefore, fast and accurate clinical assessment of COVID-19 progression and mortality is vital for the management of COVID-19 patients. We developed an automated image-based survival prediction model, called U-survival, which combines deep learning of chest CT images with the established survival analysis methodology of an elastic-net Cox survival model. In an evaluation of 383 COVID-19 positive patients from two hospitals, the prognostic bootstrap prediction performance of U-survival was significantly higher (P < 0.0001) than those of existing laboratory and image-based reference predictors both for COVID-19 progression (maximum concordance index: 91.6% [95% confidence interval 91.5, 91.7]) and for mortality (88.7% [88.6, 88.9]), and the separation between the Kaplan–Meier survival curves of patients stratified into low- and high-risk groups was largest for U-survival (P < 3 × 10–14). The results indicate that U-survival can be used to provide automated and objective prognostic predictions for the management of COVID-19 patients

Musculoskeletal Diseases 2021-2024

This open access book focuses on imaging of the musculoskeletal diseases. Over the last few years, there have been considerable advances in this area, driven by clinical as well as technological developments. The authors are all internationally renowned experts in their field. They are also excellent teachers, and provide didactically outstanding chapters. The book is disease-oriented and covers all relevant imaging modalities, with particular emphasis on magnetic resonance imaging. Important aspects of pediatric imaging are also included. IDKD books are completely re-written every four years. As a result, they offer a comprehensive review of the state of the art in imaging. The book is clearly structured with learning objectives, abstracts, subheadings, tables and take-home points, supported by design elements to help readers easily navigate through the text. As an IDKD book, it is particularly valuable for general radiologists, radiology residents, and interventional radiologists who want to update their diagnostic knowledge, and for clinicians interested in imaging as it relates to their specialty

Musculoskeletal Diseases 2021-2024

This open access book focuses on imaging of the musculoskeletal diseases. Over the last few years, there have been considerable advances in this area, driven by clinical as well as technological developments. The authors are all internationally renowned experts in their field. They are also excellent teachers, and provide didactically outstanding chapters. The book is disease-oriented and covers all relevant imaging modalities, with particular emphasis on magnetic resonance imaging. Important aspects of pediatric imaging are also included. IDKD books are completely re-written every four years. As a result, they offer a comprehensive review of the state of the art in imaging. The book is clearly structured with learning objectives, abstracts, subheadings, tables and take-home points, supported by design elements to help readers easily navigate through the text. As an IDKD book, it is particularly valuable for general radiologists, radiology residents, and interventional radiologists who want to update their diagnostic knowledge, and for clinicians interested in imaging as it relates to their specialty

Age-Related Macular Degeneration and Diabetic Retinopathy

This reprint includes contributions from leaders in the field of personalized medicine in ophthalmology. The contributions are diverse and cover pre-clinical and clinical topics. We hope you enjoy reading the articles