Evaluation of large language models performance against humans for summarizing MRI knee radiology reports: A feasibility study.

Objectives: This study addresses the critical need for accurate summarization in radiology by comparing various Large Language Model (LLM)-based approaches for automatic summary generation. With the increasing volume of patient information, accurately and concisely conveying radiological findings becomes crucial for effective clinical decision-making. Minor inaccuracies in summaries can lead to significant consequences, highlighting the need for reliable automated summarization tools.

How to do and evaluate DWI and DCE-MRI sequences for diabetic foot assessment.

MRI evaluation of the diabetic foot is still a challenge not only from an interpretative but also from a technical point of view. The incorporation of advanced sequences such as diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI into standard protocols for diabetic foot assessment could aid radiologists in differentiating between neuropathic osteoarthropathy (Charcot's foot) and osteomyelitis. This distinction is crucial as both conditions can coexist in diabetic patients, and they require markedly different clinical management and have distinct prognoses.

Surface primary bone tumors: Systematic approach and differential diagnosis.

Surface primary bone tumors may appear similar to their intramedullary counterpart, but because they are rare, they may pose diagnostic challenges when showing different characteristics compared to their intramedullary counterpart. It is important for radiologists to recognize the imaging findings for various uncommon surface primary bone tumors, which may help to reduce the differential diagnosis or to lead to a specific diagnosis. Radiography is typically used for first-line imaging.