Publications by authors named "S R Pistorius"

Purpose: To evaluate the clinical and imaging outcome of aneurysmal bone cysts (ABCs) in children using percutaneous cryoablation as the sole treatment.

Materials And Methods: This retrospective study included 7 children with a mean age of 8.7 years (range, 3.

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Transforming growth factor-β (TGF-β) plays a complex role in lung cancer pathophysiology, initially acting as a tumor suppressor by inhibiting early-stage tumor growth. However, its role evolves in the advanced stages of the disease, where it contributes to tumor progression not by directly promoting cell proliferation but by enhancing epithelial-mesenchymal transition (EMT) and creating a conducive tumor microenvironment. While EMT is typically associated with enhanced migratory and invasive capabilities rather than proliferation per se, TGF-β's influence on this process facilitates the complex dynamics of tumor metastasis.

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Background: Research into artificial intelligence (AI)-based fracture detection in children is scarce and has disregarded the detection of indirect fracture signs and dislocations.

Objective: To assess the diagnostic accuracy of an existing AI-tool for the detection of fractures, indirect fracture signs, and dislocations.

Materials And Methods: An AI software, BoneView (Gleamer, Paris, France), was assessed for diagnostic accuracy of fracture detection using paediatric radiology consensus diagnoses as reference.

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Deep Inspiration Breath Hold (DIBH) is a respiratory-gating technique adopted in radiation therapy to lower cardiac irradiation. When performing DIBH treatments, it is important to have a monitoring system to ensure the patient's breath hold level is stable and reproducible at each fraction. In this retrospective study, we developed a system capable of monitoring DIBH breast treatments by utilizing cine EPID images taken during treatment.

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This review evaluates the methods used for image quality analysis and tumour detection in experimental breast microwave sensing (BMS), a developing technology being investigated for breast cancer detection. This article examines the methods used for image quality analysis and the estimated diagnostic performance of BMS for image-based and machine-learning tumour detection approaches. The majority of image analysis performed in BMS has been qualitative and existing quantitative image quality metrics aim to describe image contrast-other aspects of image quality have not been addressed.

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