Integrative diagnostics: the time is now-a report from the International Society for Strategic Studies in Radiology

Myositis and Its Mimics: Guideline Updates, MRI Characteristics, and New Horizons

Myositis is defined as inflammation within skeletal muscle and is a subcategory of myopathy, which is more broadly defined as any disorder affecting skeletal muscle. Myositis may be encountered as a component of autoimmune and connective tissue diseases, where it is described as idiopathic inflammatory myopathy (IIM). Myositis can also be caused by infections as well as toxins and drugs, including newer classes of medications. MRI plays an important role in the diagnosis and evaluation of patients with suspected myositis, but many entities may have imaging features similar to those of myositis and can be considered myositis mimics. These include muscular dystrophies, denervation, deep venous thrombosis, diabetic myonecrosis, muscle injury, heterotopic ossification, and even neoplasms. In patients with suspected myositis, definitive diagnosis may require integrated analysis of imaging findings with clinical, laboratory, and pathology data. The objectives of this article are to review the fundamental features of myositis, including recent updates in terminology and consensus guidelines for IIMs; the most important MRI differential diagnostic considerations for myositis (i.e., myositis mimics); and new horizons, including the potential importance of artificial intelligence and multimodal integrated diagnostics in the evaluation of patients with muscle disorders.

Advancing value-based laboratory medicine

Following the COVID-19 pandemic, the concepts of value-based medicine (VBM) and value-based laboratory medicine (VBLM) are receiving increasing interest to improve the quality, sustainability and safety of healthcare. Laboratory medicine is well positioned to support the transition to value-based healthcare as it helps to improve clinical outcomes and healthcare sustainability by reducing the time to diagnosis, improving diagnostic accuracy, providing effective guidance for tailored therapies and monitoring, and supporting screening and wellness care. However, the perception of the value of laboratory medicine is still limited, to the extent that it has been defined a "profession without a face", often lacking visibility to patients and the public. In addition, in recent decades, clinical laboratories have sought to improve the ration between outcomes and costs by increasing efficiency and reducing the cost per test rather than improving clinical outcomes. The aim of this paper is to propose a 10-point manifesto for implementing value-based laboratory medicine in clinical practice.

Swiss digital pathology recommendations: results from a Delphi process conducted by the Swiss Digital Pathology Consortium of the Swiss Society of Pathology

Integration of digital pathology (DP) into clinical diagnostic workflows is increasingly receiving attention as new hardware and software become available. To facilitate the adoption of DP, the Swiss Digital Pathology Consortium (SDiPath) organized a Delphi process to produce a series of recommendations for DP integration within Swiss clinical environments. This process saw the creation of 4 working groups, focusing on the various components of a DP system (1) scanners, quality assurance and validation of scans, (2) integration of Whole Slide Image (WSI)-scanners and DP systems into the Pathology Laboratory Information System, (3) digital workflow-compliance with general quality guidelines, and (4) image analysis (IA)/artificial intelligence (AI), with topic experts for each recruited for discussion and statement generation. The work product of the Delphi process is 83 consensus statements presented here, forming the basis for "SDiPath Recommendations for Digital Pathology". They represent an up-to-date resource for national and international hospitals, researchers, device manufacturers, algorithm developers, and all supporting fields, with the intent of providing expectations and best practices to help ensure safe and efficient DP usage.

Photodynamic Therapy for Eye, Ear, Laryngeal Area, and Nasal and Oral Cavity Diseases: A Review

Photodynamic therapy (PDT) has emerged as a promising modality for the treatment of various diseases. This non-invasive approach utilizes photosensitizing agents and light to selectively target and destroy abnormal cells, providing a valuable alternative to traditional treatments. Research studies have explored the application of PDT in different areas of the head. Research is focusing on a growing number of new developments and treatments for cancer. One of these methods is PDT. Photodynamic therapy is now a revolutionary, progressive method of cancer therapy. A very important feature of PDT is that cells cannot become immune to singlet oxygen. With this therapy, patients can avoid lengthy and costly surgeries. PDT therapy is referred to as a safe and highly selective therapy. These studies collectively highlight the potential of PDT as a valuable therapeutic option in treating the head area. As research in this field progresses, PDT may become increasingly integrated into the clinical management of these conditions, offering a balance between effectiveness and minimal invasiveness.

How to prepare for a bright future of radiology in Europe

Because artificial intelligence (AI)-powered algorithms allow automated image analysis in a growing number of diagnostic scenarios, some healthcare stakeholders have raised doubts about the future of the entire radiologic profession. Their view disregards not only the role of radiologists in the diagnostic service chain beyond reporting, but also the many multidisciplinary and patient-related consulting tasks for which radiologists are solicited. The time commitment for these non-reporting tasks is considerable but difficult to quantify and often impossible to fulfil considering the current mismatch between workload and workforce in many countries. Nonetheless, multidisciplinary, and patient-centred consulting activities could move up on radiologists' agendas as soon as AI-based tools can save time in daily routine. Although there are many reasons why AI will assist and not replace radiologists as imaging experts in the future, it is important to position the next generation of European radiologists in view of this expected trend. To ensure radiologists' personal professional recognition and fulfilment in multidisciplinary environments, the focus of training should go beyond diagnostic reporting, concentrating on clinical backgrounds, specific communication skills with referrers and patients, and integration of imaging findings with those of other disciplines. Close collaboration between the European Society of Radiology (ESR) and European national radiologic societies can help to achieve these goals. Although each adequate treatment begins with a correct diagnosis, many health politicians see radiologic procedures mainly as a cost factor. Radiologic research should, therefore, increasingly investigate the imaging impact on treatment and outcome rather than focusing mainly on technical improvements and diagnostic accuracy alone.Critical relevance statement Strategies are presented to prepare for a successful future of the radiologic profession in Europe, if AI-powered tools can alleviate the current reporting overload: engaging in multidisciplinary activities (clinical and integrative diagnostics), enhancing the value and recognition of radiologists' role through clinical expertise, focusing radiological research on the impact on diagnosis and outcome, and promoting patient-centred radiology by enhancing communication skills.Key points • AI-powered tools will not replace radiologists but hold promise to reduce the current reporting burden, enabling them to reinvest liberated time in multidisciplinary clinical and patient-related tasks.• The skills and resources for these tasks should be considered when recruiting and teaching the next generation of radiologists, when organising departments and planning staffing.• Communication skills will play an increasing role in both multidisciplinary activities and patient-centred radiology.• The value and importance of a correct and integrative diagnosis and the cost of an incorrect imaging diagnosis should be emphasised when discussing with non-medical stakeholders in healthcare.• The radiologic community in Europe should start now to prepare for a bright future of the profession for the benefit of patients and medical colleagues alike.

Multimodal analysis and the oncology patient: Creating a hospital system for integrated diagnostics and discovery

We propose that an information technology and computational framework that would unify access to hospital digital information silos, and enable integration of this information using machine learning methods, would bring a new paradigm to patient management and research. This is the core principle of Integrated Diagnostics (ID): the amalgamation of multiple analytical modalities, with evolved information technology, applied to a defined patient cohort, and resulting in a synergistic effect in the clinical value of the individual diagnostic tools. This has the potential to transform the practice of personalized oncology at a time at which it is very much needed. In this article we present different models from the literature that contribute to the vision of ID and we provide published exemplars of ID tools. We briefly describe ongoing efforts within a universal healthcare system to create national clinical datasets. Following this, we argue the case to create "hospital units" to leverage this multi-modal analysis, data integration and holistic clinical decision-making. Finally, we describe the joint model created in our institutions.