The role of dual-energy computed tomography (DECT) in emergency radiology: a visual guide to advanced diagnostics.

Dual-energy computed tomography (DECT) has become an essential tool in emergency radiology, significantly enhancing diagnostic capabilities for a variety of acute conditions. By utilising two distinct X-ray energy spectra, DECT differentiates materials based on their attenuation properties, providing detailed insights into tissue composition and pathology. In emergency settings, DECT is used in thoracic imaging for the detection of pulmonary embolism, in abdominal imaging to enhance the diagnosis and characterisation of conditions such as pancreatitis, appendicitis, gastrointestinal bleeding, and bowel ischaemia and in the genitourinary system for identifying kidney stones, pyelonephritis, and urinary bleeding.

Multimodal Imaging of Osteosarcoma: From First Diagnosis to Radiomics.

Osteosarcoma is a primary malignant bone tumor characterized by the production of an osteoid matrix. Although histology remains the definitive diagnostic standard, imaging plays a crucial role in diagnosis, therapeutic planning, and follow-up. Conventional radiography serves as the initial checkpoint for detecting this pathology, which often presents diagnostic challenges due to vague and nonspecific symptoms, especially in its early stages.

Ultrasound-Guided Vacuum-Assisted Excision (VAE) in Breast Lesion Management: An Experimental Comparative Study of Two Different VAE Devices Across Various Aspiration Levels and Window Sizes.

: Vacuum-assisted excision (VAE) is a minimally invasive technique for breast tumor treatment, offering precision, comfort, and quick recovery. It is widely used for benign breast lesions and is playing an increasingly important role in the therapeutic management of non-surgical patients or patients who refuse surgery. Optimal outcomes require an understanding of device features to tailor treatment to each lesion.

Dynamic Digital Radiography (DDR) in the Diagnosis of a Diaphragm Dysfunction.

Dynamic digital radiography (DDR) is a recent imaging technique that allows for real-time visualization of thoracic and pulmonary movement in synchronization with the breathing cycle, providing useful clinical information. A 46-year-old male, a former smoker, was evaluated for unexplained dyspnea and reduced exercise tolerance. His medical history included a SARS-CoV-2 infection in 2021.

Decoding Radiomics: A Step-by-Step Guide to Machine Learning Workflow in Hand-Crafted and Deep Learning Radiomics Studies.

Although radiomics research has experienced rapid growth in recent years, with numerous studies dedicated to the automated extraction of diagnostic and prognostic information from various imaging modalities, such as CT, PET, and MRI, only a small fraction of these findings has successfully transitioned into clinical practice. This gap is primarily due to the significant methodological challenges involved in radiomics research, which emphasize the need for a rigorous evaluation of study quality. While many technical aspects may lie outside the expertise of most radiologists, having a foundational knowledge is essential for evaluating the quality of radiomics workflows and contributing, together with data scientists, to the development of models with a real-world clinical impact.